Hematology Case Study: CBC with >80% Blasts

The patient is a 67 year old male who first visited his dentist at the end of December complaining of pain in the jaw that he had been experiencing since early Dec. He had put off making an appointment because he didn’t want to have to go to the doctor with COVID precautions, but the pain was now radiating to his teeth, so he made a dentist appointment. The dentist found no evidence of abscess or other infection but ‘adjusted his bite’. The patient was advised to take over the counter NSAIDs as needed or pain but no prescriptions was needed. Three weeks later the patient visited an urgent care because he had no improvement of the jaw pain. At this time he relayed symptoms of cough, fever, chills, night sweats and chronic fatigue. Patient history included an active lifestyle with vigorous aerobic exercise several times a week, but the he stated that he had been feeling too fatigued to exercise for over a month. On exam the patient was found to be tachycardic with bilateral tonsillar lymphadenopathy and oropharyngeal exudate. The patient was tested for COVID, influenza and Group A Strep. The COVID-19 was negative, as was the influenza A and B, but the Group A Strep was positive. The patient was sent home with a prescription for antibiotics.

One week later, the patient called his PCP because he still had cough, fever and chills and now was experiencing shortness of breath. The office directed the patient to go to the ER but the patient was reluctant to go to the hospital and stated he would rather be seen at the office. On review of the patients chart, the PCP agreed to see him in the office because he had had a negative COVID test in the past week. Two days later the doctor examined the patient in his office and still suspected COVID-19. He ordered a PCR COVID-19 test along with CBC/differential and erythrocyte sedimentation rate (ESR). We received a routine CBC on the patient. Results are shown below.

The patient had no previous hematology or oncology history and no previous CBC received at our lab. The critical WBC was called to the physician. Based on the WBC and flags on the auto differential, a slide was made and sent to our CellaVision (CV). On opening the slide in CV, we immediately called our pathologist for a pathology review. A rare neutrophil was seen on the peripheral smear, with immature appearing monocytes, few lymphocytes and many blasts.

Image 1. Images from CellaVision.

The pathologist reviewed the slide and the sample was sent for flow cytology studies and FISH. The pathologist’s comment ”Numerous blasts (>60%) consistent with Acute Myeloid Leukemia(AML). Specimen to be submitted for flow cytometry. Hematology consult recommended” was added to the report.

Image 2. Image from CellaVision. Predominately blasts with one neutrophil seen in field of unremarkable RBCs.
Image 3. Image from CellaVision.

The myeloid/lymphoid disorders and acute leukemia analysis by flow cytometry reported myeloblasts positive for CD117,CD33, and CD13. Final interpretation was Acute Myeloid leukemia (non-M3 type).

AML is the most common form of leukemia found in adults. AML was traditionally classified into subtypes M0 through M7, based on the cell line and maturity of the cells. This was determined by how the cells looked under the microscope after a series of special staining techniques, but did not take into account prognosis. It is now known that the subtype of AML is important in helping to determine a patient’s prognosis. In 2016 World Health Organization (WHO) updated the classification system to better address prognostic factors. They divided AML into several broad groups, including AML with certain chromosomal translocations, AML related to previous cancer or cancer therapy, AML with involvement of more than one cell type, and other AML that don’t fall into the first three groups.2 Once a case has been placed in one of these broad groups, the AML can be further classified as poor risk, intermediate risk and better risk based on other test results. Better risk is associated with better response to treatments and longer survival.3 The European LeukemiaNET (ELN) first recommended integrating molecular and cytogenic data into classification to create such a risk classification system for AML in 2010 (ELN-2010). In 2017, this was again revised (ELN-2017) to further improve risk stratification. The ELN-2017 can be used to more accurately predict prognosis in newly diagnosed AML.1

What this means is that AML is now classified by abnormal cell type as well as by the cytogenetic, or chromosome, changes found in the leukemia cells. Certain chromosomal changes can be matched with the morphology of the abnormal cells. These chromosomal changes can help doctors determine the best treatment options for patients because these changes can predict how well treatment will work.

Examples of risk classification include the knowledge that some chromosome rearrangements actually offer a better prognosis. For example, a translocation between chromosomes 15 and 17 [t(15;17)] is associated with acute promyelocytic leukemia (APL or M3). APL is treated differently than other subtypes and has the best prognosis of all the AML subtypes. Other favorable chromosomal changes include [t(8;21)] and [inversion (16) or translocation t(16;16)]. Examples of intermediate risk prognosis are ones associated with normal chromosomes and [t(9;11)]. Poor prognosis is associated with findings such as deletions or extra copies of certain chromosomes or complex changes in many chromosomes.3

The patient was diagnosed with AML, non M3 type. AML prognosis is based on CBC results, markers on the leukemia cells (flow cytometry), chromosome (cytogenic) abnormalities found and gene mutations (molecular abnormalities). In this patient the FISH studies did not demonstrate any chromosome rearrangements, which alone would place him in an intermediate risk group. In addition, our patient was over age 60 and had a WBC over 100,000/mm3 which have both been linked to worse outcomes.

Here’s one more photo for your enjoyment! It’s not often that we see so many blasts in a patient with no previous history. As a side note, I was contemplating titling this blog “Fatigue and Shortness of Breath in the Time of COVID.” I can’t help but wonder if this patient would have been diagnosed 6-8 weeks earlier if this was another year and he had been seen when he first experienced symptoms. This year, emergency rooms and physicians have reported a decrease in numbers of patients being seen for chest pain, ketoacidosis, shortness of breath, strokes and other serious conditions. Many patients are reluctant or afraid of sitting in crowded waiting rooms, fearful they will catch COVID. And many doctors are only offering virtual visits or have reduced the number of patients being seen so it is harder to get appointments. This patient expressed his reluctance to seek medical help because of fears of COVID. He did not want to go out in public and waited almost a month for symptoms to go away on their own before first being seen. After going to the walk in center, he called his PCP a week later and was still averse to going to the ER as suggested by the doctor. Then he waited another 2 days for an office appointment. The doctor still suspected COVID, but fortunately for the patient, ordered a CBC. The flow cytometry and FISH studies were available the following day. The patient was referred for hematology consult but has not been seen again at our hospital.

Image 4. More images from CellaVision.

References

  1. Boddu, P.C., Kadia, T.M., Garcia‐Manero, G., Cortes, J., Alfayez, M., Borthakur, G., Konopleva, M., Jabbour, E.J., Daver, N.G., DiNardo, C.D., Naqvi, K., Yilmaz, M., Short, N.J., Pierce, S., Kantarjian, H.M. and Ravandi, F. (2019), Validation of the 2017 European LeukemiaNet classification for acute myeloid leukemia with NPM1 and FLT3‐internal tandem duplication genotypes. Cancer, 125: 1091-1100. https://doi.org/10.1002/cncr.31885
  2. Mandel, Ananya. Acute Myeloid Leukemia Classification. Medical Life Sciences. https://www.news-medical.net/health/Acute-Myeloid-Leukemia-Classification.aspx
  3. Ari VanderWalde, MD, MPH, MA, FACP; Chief Editor: Karl S Roth, MD. Genetics of Acute Myeloid Leukemia. Medscape. Updated: Dec 17, 2018 
Socha-small

-Becky Socha, MS, MLS(ASCP)CMBBCM graduated from Merrimack College in N. Andover, Massachusetts with a BS in Medical Technology and completed her MS in Clinical Laboratory Sciences at the University of Massachusetts, Lowell. She has worked as a Medical Technologist for over 40 years and has taught as an adjunct faculty member at Merrimack College, UMass Lowell and Stevenson University for over 20 years.  She has worked in all areas of the clinical laboratory, but has a special interest in Hematology and Blood Banking. She currently works at Mercy Medical Center in Baltimore, Md. When she’s not busy being a mad scientist, she can be found outside riding her bicycle.

Eye Spy 2.0

Now that you’ve seen some malignant ocular entities (both primary and metastatic), I’d like to share some (in my eyes) curveballs. Working in a cancer center, I see more cancer than I do benign processes. You can say I’m fine tuned to identifying malignant cells, and I find it difficult to rest assured that what I’m diagnosing truly is benign. When you find one malignant cell in a pleural fluid, changing the patient’s diagnosis from Stage II to Stage IV, that primed search for atypia is always on. With that said, not every specimen screened at a cancer center is malignant. We rule out malignancy and confirm benign processes as well. As for benign ocular FNAs, well… you have to be as certain calling benign as you do malignant because the process of acquiring an additional sample to confirm your diagnosis is just as involved and unpleasant as the first biopsy.

Here, I present six non-malignant eye FNA cytopreparations that had me searching for atypia longer than I expected.


Case 1. A 72 year old female with a history of breast carcinoma; She presented with a choroidal nevus, OD in 2014. The oncologist noted a slight increase in base and thickness six years after the initial evaluation. The clinical diagnosis is a choroidal nevus, rule out low-grade melanoma.

Images 1-2: Eye, Right, Choroid, Fine Needle Aspiration. Pap-stain.

Final Diagnosis: No malignant cells identified. A few benign-appearing melanocytes, consistent with nevus.

Note: Material is scant cellular and consists mainly of scattered retinal pigment epithelial cells and sensory cells. There are a few benign-appearing spindle-shaped cells with bland nuclei, consistent with nevus. However, the paucity of the sample precludes a definitive diagnosis. Recommend clinical correlation to exclude sampling error.


Case 2. A 21 month old male with a history of an iris stromal cyst, OS. Lesion is status post-FNA (twice), had regrowth, and aspirated for the third time. Previous FNAs showed no malignant cells.

Images 3-4: Eye, Left, Choroid, Fine Needle Aspiration. Pap-stain.

Final Diagnosis: No malignant cells identified. Rare pigment-laden macrophages, a few lymphocytes, and benign surface epithelial cells present. (Consistent with stromal cyst).


Case 3. A 65 year old female with a history of nevus, OD. Ocular oncology followed up and noted an increase in thickness from 2.76 to 3.00 mm. In light of family history of cutaneous melanoma, treatment is suggested. Clinical diagnosis: ciliary body melanoma.

Images 5-6: Eye, Right, Choroid, Fine Needle Aspiration. Pap-stain.

Final Diagnosis: Scant mildly atypical amelanotic spindle cells, consistent with nevus.

Note: Diagnostic material is very scant. There are a few benign-appearing single spindle cells and one cluster of cohesive spindle cells with no pigment. Prominent nucleoli are not seen. While the cytologic features in the context of clinical presentation is consistent with nevus, the paucity of the sample precludes a definitive diagnosis. There is no diagnostic evidence of malignant melanoma in this sample. Recommend clinical correlation to exclude sampling error.


Case 4. A 9 year old female with a history of retinoblastoma, OD; status post IAC (intra-arterial chemotherapy) x5, IVit melphalan x 4, and plaque radiotherapy. She recently developed vitreous hemorrhage (OD). Since the hemorrhage is obscuring the retinal view, vitrectomy is planned.

Image 7: Eye, Right, Vitreous, Fine Needle Aspiration. Pap-stain.

Final Diagnosis: No malignant cells identified. Lymphocytes and histiocytes present.


Case 5. An 11 year old female with vitreal retinoblastomas, OU; status post CRD therapy x6; plaque I-125, EBRT, proton beam; IVit Metphalan x2, and PPV (pars plana vitrectomy), OS. She now presents with dense vitreous hemorrhage blocking view since 2019.

Images 8-9: Eye, Left, Vitreous, Fine Needle Aspiration. Pap-stain.

Final Diagnosis: No malignant cells identified. Proteinaceous material and scattered small lymphocytes present.


Case 6. A 52 year old female with no cancer history. In 2019, she presented with pain, floaters, decreased visual acuity, and photophobia, OS. She was treated with antibiotic drops and steroids. In 2020, she was noted to have panuveitis with yellow iris nodules. FNA showed necrotic cells inadequate for diagnosis, as well as a negative culture and PCR for HSV, toxoplasmosis, CMV, and VZV. Clinical diagnosis: suspicious for iris lymphoma, OS.

Images 10-11: Eye, Left, Anterior Chamber, Fine Needle Aspiration. Pap-stain.

Final Diagnosis: Mixed inflammatory cells, favor an inflammatory process.

Note: There are neutrophils, lymphocytes, and scattered histiocytes in a background of numerous fragments of an amorphous substance. The cellularity is inadequate for flow cytometric analysis. We performed immunocytochemical stains on cytospin preparations. The lymphocytes are predominantly T-cells showing positive staining for CD45 and CD3 and negative for CD20. There is no diagnostic evidence of malignant lymphoma in this sample. The amorphous substance may represent lens fragments, in which case the possibility of lens-induced uveitis should be considered in the differential diagnosis. Recommend clinical correlation.


As you can tell, benign processes are complicated and require thorough explanations in our pathologic diagnoses, especially when they differ from the clinical impression. The majority of benign ocular FNAs are paucicellular, and we make the most of what we have through optimal preservation and preparation of cellular material. And don’t forget-not everything is cancer. Cyst contents, proteinaceous debris, and inflammatory cells make up a share of cases we see, and it’s okay to diagnosis them as benign. Just keep an eye out.

-Taryn Waraksa, MS, SCT(ASCP)CM, CT(IAC), has worked as a cytotechnologist at Fox Chase Cancer Center, in Philadelphia, Pennsylvania, since earning her master’s degree from Thomas Jefferson University in 2014. She is an ASCP board-certified Specialist in Cytotechnology with an additional certification by the International Academy of Cytology (IAC). She is also a 2020 ASCP 40 Under Forty Honoree.

Breakpoint Breakdown II: Breakpoints at the Bedside

A critical task for clinical microbiologists is interpreting antimicrobial susceptibility testing (AST) results for microorganisms recovered from patient specimens. But what happens to that information after it is passed along to the clinical team, and how does it influence patient care at the bedside? In our previous blog, we discussed details concerning how breakpoints are established and identified them as an indispensable component of appropriate and effective antimicrobial prescribing. Here we will discuss the more practical application of breakpoints to guide patient care. To aid in the discussion, I’ve once again recruited two infectious diseases (ID) pharmacists from the UT Southwestern Medical Center to provide their valuable prospective on the use of AST results both at the bedside and to optimize antimicrobial stewardship initiatives.

Applying Breakpoints in Clinical Care

In the most simplistic terms, the reporting of isolate’s categorical susceptibility (susceptible, intermediate, and resistant) provides guidance concerning which antimicrobials will likely be effective to treat an infection.1 Many microbiology laboratories, however, report additional AST information including minimal inhibitory concentrations (MICs) and phenotypic information concerning resistance mechanisms (e.g. production of Extended Spectrum Beta-Lactamases (ESBLs) or inducible-clindamycin resistance)2. This more detailed information is often utilized by ID specialists to help guide and optimize beside management.

Unfortunately, several misapplications of AST data can be encountered in clinical care (Image 1). One common error is simply selecting the antimicrobial with the lowest MIC for treatment. This runs contrary to the idea that each antimicrobial has an individualized breakpoint for a given pathogen or pathogen group. Therefore, a low MIC for antimicrobial “A” may be at or near the breakpoint, but higher MIC for antimicrobial “B” may be a dilution or more lower than the breakpoint. Another common misconception is that if the isolate is reported susceptible to a given antimicrobial, that antimicrobial is the optimal choice for the patient, and will work 100% of the time! Very little in medicine is 100%, and this holds true for antimicrobials. Even if the optimal agent is selected based on AST data, there is no guarantee it will be effective in the patient. Many factors influence the effectiveness of antimicrobials including patient characteristics (e.g., immune system, kidney function), drug characteristics (i.e., pharmacokinetics [PK]/pharmacodynamics[PD]), and bug characteristics (e.g., underlying resistance present despite reporting as susceptible or potential for inducible resistance).2 This illustrates why clinicians may prefer to have all available information to further aid in optimization of antimicrobial therapy beyond the information provided by categorical reporting.

But why is an MIC needed – isn’t just knowing something is susceptible or resistant enough? In particular, more granular information such as the actual MIC for a given bug-drug combination may aid in more intricate decisions surrounding the choice of agent and dose. One argument for routine reporting of MIC values is the ability to better discern how near the breakpoint the particular MIC is for a given drug. The standard MIC reporting error is plus or minus one doubling dilution. When this is factored in, it may provide additional context as to how near or over the isolates phenotype is to assigned breakpoint.2 Clinicians may further couple this with their understanding of PK/PD to determine the optimal agent based on antimicrobial properties and microbial characteristics.

A counter argument is that the MIC values are prone to variation depending on testing modality and may not represent truly what occurs in actual humans (see Mouton JW et al. for more detailed discussion).3 As mentioned above, some argue that MIC reporting leads to misinterpretations of AST by a provider’s tendency to pick the lowest number, and thus prefer categorical reporting for simplification. Provider education and selective or cascade reporting are two strategies that may help clinicians select the optimal agent, but also have inherent limitations. All this taken into consideration, we feel the benefit of antimicrobial optimization supports reporting the MIC.

Applying Breakpoints at the Bedside

Breakpoints and MIC data are utilized at the bedside to avoid utilization of suboptimal agents due to issues with the drug and bug. For example, underlying resistance patterns may not be overtly apparent to clinicians. Depending on an institution’s reporting criteria, an E. coli isolate may be reported as susceptible to piperacillin/tazobactam despite being identified as an ESBL producer. In this instance, piperacillin/tazobactam may be suboptimal for certain infections based on available outcomes data, with some supposition that reported MIC values may be responsible for improper drug selection and treatment failures.4 Therefore, clinicians may favor alternative agents for infections despite documented susceptibility. This example also illustrates that certain resistance patterns (e.g., ceftriaxone resistance as surrogate for possible ESBL production) may help alert clinicians to underlying resistance, steering them clear of potential suboptimal agents reported as susceptible.

ID pharmacists often utilize MIC values to determine the optimal agent and dose for a given patient based on a working knowledge of breakpoint relationships and PK/PD. This may be taken a step further in the setting of an infection with a multidrug resistant organism which exhibit MICs in the intermediate or susceptible dose-dependent range. For certain drug-bug combinations with elevated MICs, it may be possible for the ID pharmacist to devise an optimized and personalized therapeutic regimen that will likely overcome the elevated MIC, either as monotherapy or utilizing potential synergistic combinations of different antibiotics.

The application of dose-dependent breakpoints, as seen with daptomycin for Enterococcus faecium, help illustrate the importance of understanding and applying dosing concepts in the context of established clinical breakpoints.1 This allows the clinician to not only optimize dosing, but also understand that an MIC at or near the breakpoint may warrant combination therapy in the setting of a serious infection. A lack of understanding of the relationship between breakpoints and dosing could potentially lead to an inadvertent assumption that lower FDA-approved doses would be reasonable despite the breakpoint being based on higher dosing strategies. These are just a small sampling of the clinical applications utilized on a daily basis to optimize a particular patient’s antimicrobial therapy.

A more global application of breakpoints occurs within antimicrobial stewardship programs. Antimicrobial stewardship focuses on the appropriate and optimal use of antimicrobials. To aid in this goal, AST reporting is key to developing clinical guidance on treating a variety of infections. Most notably, the optimization of empiric antimicrobial choices is aided by local or institutional susceptibility patterns. The cumulative antibiogram is pivotal to establishing optimal empiric antimicrobial choices across the spectrum of infectious diseases.5 Importantly, breakpoints are revised when new or additional clinical information becomes available, further illustrating the need to understand how a given institution implements and applies them. There is always the potential that from one year to the next susceptibilities may drop substantially due to implementation of new breakpoints, not necessarily an increased incidence of pathogens with a certain resistance pattern.6 In addition, the ability to adopt CLSI breakpoints often lags well beyond the release of the updated breakpoints, necessitating clinicians to be cognizant of changes and carefully assess categorical reporting as it may be discordant with the most up-to-date breakpoints.1,6 This topic will be the focus of our next blog.

More specific application of AST data can be made for either site (e.g., blood, urine, etc.), infection type (e.g., community-acquired pneumonia), or organism-specific MIC distributions. A recent trend in national guideline recommendations centers on ascertaining local susceptibility and pathogen distribution to provide optimal antimicrobial choices for certain infections (e.g., pneumonia).7 In addition, focused review of individual pathogen MIC distributions provide another level of detail that helps better define upfront institutional antimicrobial dosing strategies to optimize PK/PD parameters. In conclusion, the reporting of AST data remains a cornerstone for the effective management of infections. Information collected by laboratory technicians provides invaluable information to clinicians. This information helps optimize the selection and dosing of antimicrobial agents at the bedside, which in turn improves the clinical management of patients and infection-related outcomes.

Image 1: Clinical scenario outlining the application of MIC and breakpoint data at the bedside.

References

  1. Clinical and Laboratory Standards Institute. Development of In Vitro Susceptibility Testing Criteria and Quality Control Parameters, 5th Edition (M23).
  2. Giuliano C, Patel CR, and Kale-Pradhan PB. A Guide to Bacterial Culture Identification and Results Interpretation. P&T. 2019 April 44(4):192-200.
  3. Mouton JW, Muller AE, Canton R, et al. MIC-based dose adjustment: facts and fables. J Antimicrob Chemother 2018; 73:567-68.
  4. Pogue JM and Heil EL. Laces out Dan! The role of tazobactam based combinations for invasive ESBL infections in a post-MERINO world. E Expert Opin Pharmacother.2019 Dec;20(17):2053-57.
  5. Clinical and Laboratory Standards Institute. Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data; Approved Guideline, 4th Edition (M39-A4).
  6. Humphries RM, Abbott A, Hindler JA. Understanding and Addressing CLSI Breakpoint Revisions: a Primer for Clinical Laboratories. J Clin Microbiol. 2019 May 24;57(6):e00203-19.
  7. Khalil AC, Metersky ML, Klompas M, et al. Management of Adults with Hospital-acquired and Ventilator-associated Pneumonia: 2016 Clinical Practice Guidelines by the Infectious Diseases Society of America and the American Thoracic Society. Clin Infect Dis. 2016 Sep 1;63(5):e61-e111.

-James Sanders, PharmD, PhD, is an infectious diseases pharmacy specialist and assistant professor at the University of Texas Southwestern Medical Center in Dallas, Texas. His academic and research interests are focused on multi-drug resistant Gram-negative bacteria, surgical site infections and HIV pharmacotherapy.

-Marguerite Monogue, PharmD is an infectious diseases pharmacy specialist and assistant professor at the University of Texas Southwestern Medical Center in Dallas, Texas. She is interested in antimicrobial pharmacokinetics/pharmacodynamics and multi-drug resistant Gram-negative bacteria.

-Andrew Clark, PhD, D(ABMM) is an Assistant Professor at UT Southwestern Medical Center in the Department of Pathology, and Associate Director of the Clements University Hospital microbiology laboratory. He completed a CPEP-accredited postdoctoral fellowship in Medical and Public Health Microbiology at National Institutes of Health, and is interested in antimicrobial susceptibility and anaerobe pathophysiology.

AI vs. Crystallography: Predicting Pathogenic Variants?

Some very exciting news was recently announced about Artificial Intelligence impacting protein structure prediction. But like many of us, you probably thought, “Oh that’s nice.” Followed by either, “But that’s unlikely to impact lab medicine” or “I have no idea how they did that.”  Today I will help turn around those last two thoughts for you!

The big news was that a U.K. company specializing in artificial intelligence, DeepMind (owned by Google-of course), won the CASP14 competition. CASP14 is the 14th edition of the biannual bake-off competition where teams use bioinformatic approaches to predict protein structures. The organizers then judge how well predictions match experimentally derived structures using a score called: GDT. This score reflects the distance of where something is vs. where it should be. Each of the ~150 protein sequences are scored on this basis and given a final percent identity score (0-100%).

Figure 1. The Z-score is just the difference of a sample’s value with respect to the population mean, divided by the standard deviation. The groups that are markedly better than the average will have larger Z-scores.

Since the competition started in 1997, the winners have scored ~50% on average. That is until 2 years ago when AlphaFold, the AI created by DeepMind, won with a top score of 55%. Their paper was published open access (Ref: https://www.nature.com/articles/s41586-019-1923-7) and used similar techniques applied by others where proteins were progressively folded by a computer until the lowest energy state is revealed.

Figure 2. Improvements in the media accuracy of predictions in the free modelling category for the best team in each CASP. Measured as best-of-5 GDT.
GDT: Global Distance Test (0-100); the percentage of amino acid residues within a threshold distance from the correct position. GDT of around 90 is considered competitive with results obtained from experimental methods.

The programs driving this folding may consider amino acid charge, size, and polarity, genetic conservation (Ref), or similarity to other protein domains. However, the innovation here was that DeepMind used artificial intelligence to examine sequence information with a convolutional neural network to identify structural constraints that are used to predict accurate protein folding.




Figure 3. Sequence of events from Dataà Deep neural network (Artificial intelligence)àPredictions à protein folding process. (Figure 2 of this reference: https://www.nature.com/articles/s41586-019-1923-7/figures/2).

This results in one of those famous algorithms you’ve heard about. However, these algorithms are more complex than a simple linear regression and it is nearly impossible to trace how exactly how different levels of importance were assigned to each variable. An important requirement for an accurate A.I. derived algorithm is that it has a large training data set. Fortunately for Deepmind, they were able to train AlphaFold using about 170,000 structures that were determined experimentally using x-ray crystallography, nuclear magnetic resonance spectroscopy, and electron microscopy.

Although we haven’t seen what was changed between AlphaFold and AlphaFold 2, we have learned that AlphaFold 2 vastly outperformed the original in CASP14 with 91% accuracy. When programs are >90% accurate they are considered to be essentially as good as experimentally derived structures. In fact, AlphaFold 2 was able to provide more information than the experiments!  One researcher found that their experimentally derived structure had a different configuration than the one predicted by AlphaFold, so they assumed the prediction by AlphaFold 2 was incorrect. After further analysis, the experimentally derived structure was found to be very similar to the structure predicted by AlphaFold 2. In another case, AlphaFold 2 predicted that an amino acid was in an infrequently found conformation, so they figured AlphaFold 2 made a mistake. After reanalyzing the experimental data, they found that that AlphaFold 2 was correct. It was even suspected that several lower-scoring structures based on NMR data may reflect lower accuracy in the experimental structure instead of a problem with the algorithm.

Figure 4. (Left) Model for the T1064 target (red) superimporsed onto the structure from DeepMind in CASP14 (blue). (Right) Black and green structures are from the runner-ups who made predictions for the same structure (correct in blue). Obtained from CASP14 webpage on Tuesday December 1st, 2020.

Will AI replace experimental crystallography? To answer this question, I turned to a colleague in my basic science lab, Lijing Su, who has been a structural biologist for many years. Like many cases of AI, this is a useful tool, but it doesn’t entirely replace her work because a lot of the structural biology research focuses on how proteins move and change as they do their job. Structural biology has moved beyond structures of single proteins and is now focused on how different proteins interact. There is still a role for crystallographers as AlphaFold cannot perform this role…yet.

All this still begs the question of a laboratorian “Who needs to know protein structure anyways?” We understand that knowing protein structures can help explain function, which has implications with drug development. However, our main role is to provide tests that diagnose disease. A major challenge in molecular pathology is to predict whether a genetic variant causes loss of protein function. Current software has poor performance (PolyPhen2 sensitivity= 45% specificity= 50%) as they mainly measure changes in chemical properties and amino acid site conservation. One potential application of AlphaFold is to examine the effect of genetic variants on protein structure. Pathogenic changes would be predicted to deform portions of the structure impairing activity or provoking degradation through the unfolded protein response.

As the current speed of the program is quite long, this could be difficult to implement immediately, but it is imaginable that this will become quicker. A straightforward way to validate this AI software would use confirmed pathogenic or benign variants from the public database ClinVar. There are over 1,000,000 entries into this database, which would provide a useful training and validation set. It is likely that change in protein structure would be a stronger mechanism of disease for certain types of proteins (ion channels for epilepsy or myosin chains for muscular disorders) and a less strong predictor of pathogenicity for other types of proteins (enzymes for metabolic disorders or signaling proteins where protein-protein interaction is important for function).

This blog entry was written with the very helpful insights and knowledge of Lijing Su, PhD.

References

  1. Senior AW et al. Improved protein structure prediction using potentials from deep learning. Nature. 2020; 577: 706–710.
  2. CASP14 website: https://predictioncenter.org/casp14/
  3. Arnold CN et al. ENU-induced phenovariance in mice: inferences from 587 mutations. BMC Res Notes. 2012; 5: 577.
  4. https://deepmind.com/blog/article/alphafold-a-solution-to-a-50-year-old-grand-challenge-in-biology

-Lijing Su is Assistant Professor in the Center for Genetics of Host Defense at the University of Southwestern Medical Center. She specializes in structural biology and helps determine multi-protein interactions to explain unknown mechanisms of genes important to immunology.

Jeff SoRelle, MD is Assistant Instructor of Pathology at the University of Texas Southwestern Medical Center in Dallas, TX working in the Next Generation Sequencing lab. His clinical research interests include understanding how lab medicine impacts transgender healthcare and improving genetic variant interpretation. Follow him on Twitter @Jeff_SoRelle.

The Laboratory Safety Challenge

In 2014 there was an internet challenge which exploded in popularity. It was the ALS Ice Bucket Challenge in which people would dump cold water on their heads and post the video on social media. The person getting the ice water dumped on them would challenge others to post a video of their dousing and they would in turn donate to the cause of finding a cure for ALS, a progressive neurodegenerative disease. The challenge became a world-wide sensation and raised $115 million for ALS research. But, like many good things, the challenge had a dark side. Many people were injured while attempting the challenge, and at least two deaths were at least indirectly associated with it.

Another challenge has come to social media lately, and this one involves a technical skill in the laboratory. It, too, has a dark side. The blood smear challenge is the latest rage for lab techs who enjoy posting videos on Facebook, Instagram, and other social media platforms. Lab techs show off their skill by making the perfect blood smear. At first it was about who could make a smear with the most perfect beautiful, feathered edge. Then the challenge evolved into people making smears while holding the top slide with one finger or even a pencil. There are those who were quite proud to show off their skill and work.

When watching videos of people in various labs performing this challenge, I cannot help but cringe. Several of these lab techs are not wearing lab coats. Many are not wearing gloves, and I have not seen any perform the challenge while using face protection or goggles. Ignoring the safety regulations about using basic personal protective equipment is apparently the norm. These people post this online without a second thought to a public display of working in the lab without PPE. It speaks volumes about the safety culture in those laboratories, and what it says is not favorable.

The next, less obvious safety issue with the videos is that they are created using cell phones or other personal electronic devices in the laboratory. People are handling devices sometimes with gloves, sometimes without, or they are setting them on lab counters which are likely contaminated. The use of cell phones and other personal electronic devices is a dangerous infection control issue, but it is unfortunately all too common. Even before this latest challenge, lab staff all over the country pose for pictures for social media posts that are taken by cell phones. Despite the fact that known and reported infections have occurred in labs from cell phones (and other items brought home from work), techs continue to use them.  

Other issues with the blood smear challenge may be less obvious. Unless these smears are being used, valuable lab supplies are being wasted. Slides and blood-dispenser cap piercing devices cost money, and many lab supplies manufacturers have run into supply shortages this year because of the pandemic. To have a lab waste money or run into shortages for the sake of this challenge might seem foolhardy to some.

Another safety issue with the challenge is the blatant act of playing around with human, potentially infectious blood to make the smears. Staff use engineering controls, work practice controls and PPE to separate people from the hazards in the laboratory. To place oneself at risk unnecessarily, especially during the COVID-19 pandemic, borders on reckless.

When the COVID-19 pandemic began affecting labs over a year ago, many laboratorians became concerned for their own personal safety. They were unsure about how they might catch this virus and what effects it might for them and their family. These were valid concerns, and some still have fears today. In conversations with lab staff over the past months I reminded them that they work with bloodborne pathogens every day, and many are as potentially dangerous (or more) than the COVID-19 virus. If Standard Precautions are used on the job, workers will be safe from infections from COVID-19 and other pathogens. The same is true today. Laboratorians may be less worried about the coronavirus, but the risk of infection in labs from this and other pathogens is as real as ever. Using engineering controls, PPE, and safe work practices is the only way to ensure lab staff can go home without bringing something dangerous to our families.

Challenges can be fun. I participated in the ALS Ice Bucket Challenge. I came out unscathed, but I was likely just lucky, not safe. The same is true for those posting pictures and videos online from inside laboratories. You might have been working that way for years and nothing has happened. Again, that is just luck, and it will run out. Make sure you and your staff are doing what is right, and what is safe. The real challenge is how to get laboratorians in all labs to work safely and follow basic safety regulations. Can your lab meet that challenge?

Dan Scungio, MT(ASCP), SLS, CQA (ASQ) has over 25 years experience as a certified medical technologist. Today he is the Laboratory Safety Officer for Sentara Healthcare, a system of seven hospitals and over 20 laboratories and draw sites in the Tidewater area of Virginia. He is also known as Dan the Lab Safety Man, a lab safety consultant, educator, and trainer.

The Pathology Value Chain and Global Health, Part 3

In the first two installments of this blog series, we looked at inbound logistics and operations in which we can conclude that competitive advantage may be challenging to achieve. Now we turn to outbound logistics or, in simplest terms, the pathology report.

No document can be more terrifying for a patient than a pending pathology report from a biopsy, as it may contain a benign diagnosis, a malignant diagnosis, or something entirely unexpected. These reports are so important that unsuspected (non-malignant) and malignant diagnoses are included as “critical values” requiring a call and documentation to the clinical team as soon as they are discovered. Pathology reports in HIC are often not immediately available to the patient (unlike other laboratory tests) because the reports are often complex, may contain confusing terms, and may use language that patients inappropriately react to without the guidance of their clinician for meaning in their care. For example, cytology reports may be highly informative to a clinician by simply stating, “No evidence of malignancy” but may be stressful to a patient without guidance because there is not a definitive answer to what a lesion was. Similarly, a colon resection that states, “Invasive adenocarcinoma confined to the mucosa” is good news to the clinician but the first two words (and the internet) may be disturbing for the patient. The important point here is that pathology reports are written for clinicians and not written for patients as an audience. To that end, pathology reports should be highly aligned with the clinical decision-making process, an approach which is naturally aided by standardize or synoptic reporting of cancers using guidelines such as those of the College of American Pathologists, the Royal Colleges of the UK and Australia, and/or the International Collaboration on Cancer Reporting (a consortium of CAP, RCUK, RCA, ASCP, and others). These templates for a given cancer are complex, not easily committed to memory, nuanced, and require a high degree of pathology knowledge to apply correctly from the gross to the final histology findings. Thus, the value in these templates is in use by a pathologist directly, making task-shifting in this area nearly impossible without the aid of tools such as whole slide imaging and artificial intelligence (which still require a pathologist to finalize the report). Like operations, we see that a “standard of care” or a “standardized approach” to reporting cancer reduces the variability or uniqueness that can be achieved with a pathology report, infringing on competitive advantage.

Outbound Logistics – This activity covers the distribution of the final product to the consumer. For the maximum value to the patient, a report should be organized to match the treatment plan, available immediately upon completion, and provide an unambiguous answer than can be acted on. Although the first two activities generate the most important information for the patient and do so with “standards of care”, this activity involves communicating the results to the clinical team members who will act on it and, therefore, can open opportunities for competitive advantage. A new diagnosis of cancer is considered a “critical value” and requires a communication with documentation to the clinical team. However, much of pathology’s role in cancer care includes work with existing cancer patients so rapid communication of any result (not just the first cancer diagnosis) can add value. For example, integration of the pathology laboratory information system into the electronic medical record creates immediate results to clinicians. Alert systems including text messages, instant messages, emails, faxes, etc. add value by informing the busy clinician that the result is there. Photographs of the tumor grossly, histologically, or the results of specials studies can be included in printed or digital reports. Pathologists can attend tumor boards or other in-person or virtual meetings to present the results and explain them if there are questions. The more information that is transmitted with clarity to clinicians, the higher value the patient will obtain. The challenge in this activity is that the payment for the laboratory services ends with the diagnostic report and appropriate coding and, thus, laboratories may have to upcharge for their services to add these features. These further communications, which we can see adds value to the patient, does not add value to the laboratory’s revenue model without upcharges. In fact, it likely costs more to have such active communications as it takes pathologists away from the higher volumes which do equate to higher revenue (as we saw in operations). Streamlining these types of communications with electronic systems is key in cost and time savings and is the basis for the laws and regulations, for example, in the USA which require electronic medical records including laboratories. However, as laws, regulations, and guidelines evolved, these electronic communications are becoming standard of care requiring the entire system to increase the costs to have them but eroding the competitive advantage of providing such concierge services. Consider the change COVID-19 has had on communications between patients, clinicians, and the laboratory where a multi-person discussion of a case with images and consensus opinions can be done in a few minutes over a video conference without anyone leaving their office. Has this crisis provided a new way to capture time (and therefore revenue) but still provide concierge services? Or has it (more likely) created a new normal that everyone has to adopt (eroding competitive advantage)?

When we turn to LMICs and observe the activities of the pathology laboratory, communication with clinical teams on the front or back end has been uncommon and traditionally not done. Oncological practices in HIC are filtering down to LMICs including tumor boards, frozen sections (i.e., rapid, in surgery diagnostics), etc. and being instituted with some frequency. These activities improve patient value and outcomes, educate the teams in both directions, and are clearly beneficial to the system. But they take time and effort away from already understaffed systems which detracts from the value of other patients ultimately. However, when we observe these systems, we often find that they lack electronic tools for running the laboratory internally which inhibits tools for reporting externally. Thus, the major needed solution now is that any histology laboratory anywhere in the world should be using an anatomic pathology laboratory information system as it creates internal and external tools for standardized reporting, communication, and management. Furthermore, it creates better opportunities to integrate synoptic (templated) reporting, interdisciplinary team activities, and standardization of requisitions (i.e., upon receipt of samples). Greatly increased value for patients in LMICs can be achieved with electronic APLIS.

Lastly, there are incredible examples of pathologists who make time in their day to meet with patients to discuss their pathology reports. These discussions can only focus on what the reports says and what the words in the report mean, as defined not in context of that patient. Such exchanges can provide patients with helpful questions to ask their clinicians and prepare them to better understand what the clinicians suggests as next steps for treatment. Clearly valuable to the patient, these exchanges are also valued by the pathologists who enjoy the face-to-face interactions with patients that humanize the process. In rare cases (possibly a for-profit situation), these services may generate revenue but under current medical billing rules there is no standard mechanism for the pathologist to be reimbursed. If we have identified this as adding value to the patient in the pathology value chain, should we not try to find ways to build these services into the care model financially? With the ubiquitous use of video conferencing in the COVID-19 era, can this task be of minimal effort to pathologists but still add value for patients?

In our last installment, we will discuss marketing & sales and service, both of which are particularly flawed and fascinating to consider.

References

  1. Porter, M. (1985). The value chain and competitive advantage, Chapter 2 in Competitive Advantage: Creating and Sustaining Superior Performance. Free Press, New York, 33-61.
  2. Histology. Wikipedia. https://en.wikipedia.org/wiki/Histology#:~:text=In%20the%2019th%20century%20histology,by%20Karl%20Meyer%20in%201819.
  3. Thorpe A et al. The healthcare diagnostics value game. KPMG International. Global Strategy Group. https://assets.kpmg/content/dam/kpmg/xx/pdf/2018/07/the-healthcare-diagnostics-value-game.pdf
  4. Digital Pathology Market CAGR, Value Chain Study, PESTEL Analysis and SWOT Study|Omnyx LLC, 3DHISTECH Ltd, Definiens AG. https://www.pharmiweb.com/press-release/2020-06-30/digital-pathology-market-cagr-value-chain-study-pestel-analysis-and-swot-study-omnyx-llc-3dhistec
  5. Friedman B. The Three Key Components of the Diagnostic Value Chain. Lab Soft News. January 2007. https://labsoftnews.typepad.com/lab_soft_news/2007/01/the_three_eleme.html
  6. XIFIN. The Evolution of Diagnostics: Climbing the Value Chain. January 2020. https://www.xifin.com/resources/blog/202001/evolution-diagnostics-climbing-value-chain
  7. Sommer R. Profiting from Diagnostic Laboratories. November 2011. Seeking alpha. https://seekingalpha.com/article/305931-profiting-from-diagnostic-laboratories#:~:text=The%20three%20year%20average%20operating,current%20operating%20margin%20of%2012.9%25.
  8. Cancer Patients Want to Pull Back the Curtain on Pathology. M Health Lab. October 10, 2019. https://labblog.uofmhealth.org/industry-dx/cancer-patients-want-to-pull-back-curtain-on-pathology
  9. Guttman EJ. Pathologists and Patients: Can we talk?. Modern Pathology. May 2003. https://www.nature.com/articles/3880797
  10. Lapedis CJ et al. The Patient-Pathologist Consultation Program: A Mixed-Methods Study of Interest and Motivations in Cancer Patients. Arch Path Lab Med. August 20, 2019. https://meridian.allenpress.com/aplm/article/144/4/490/427452/The-Patient-Pathologist-Consultation-Program-A
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-Dan Milner, MD, MSc, spent 10 years at Harvard where he taught pathology, microbiology, and infectious disease. He began working in Africa in 1997 as a medical student and has built an international reputation as an expert in cerebral malaria. In his current role as Chief Medical officer of ASCP, he leads all PEPFAR activities as well as the Partners for Cancer Diagnosis and Treatment in Africa Initiative.

ASCP Releases Two Evidence-Based Recommendations for COVID-19 Testing

COVID-19 testing can be a bit confusing. Recently, ASCP released two recommendations for COVID-19 testing to help clinicians and laboratories sort through the noise and order the right test at the right time. In addition, ASCP has a plethora of COVID-19 resources, including Town Halls, podcasts, journal articles, and more.

A Trilogy of Food, Fun, and Facts: Musings of a Pathologist-in-Training

Pathology is a perfectly blended specialty filled with food, fun and a whole range of factual morphological descriptions!

As a pathology resident, one of the first things that got me intrigued by the specialty was its strong association with many food epithets. From the almond-shaped ovary,1 to the blueberry muffin baby,2 to the coffee bean nuclei in the thyroid,3 fried egg appearance of mast cells,4 grape-like lesions seen in molar pregnancy5 to the flat cake placenta6 and even to the strawberry cervix!7 The list is endless. I found these descriptions so interesting that I kept asking myself, “why do pathologists have to make associations with food for many normal and pathological disease processes we see around?”

Aside from the fun association with food (which I happen to like a lot), getting to learn and understand the pathology of disease processes, genetic and syndromic associations have been a fascinating, humbling, and altogether nerve-wracking experience for me.

It has been fascinating because I totally enjoy learning about the underlying processes that get some people sick while others stay healthy. At the same time, it has also been humbling, because, then I realize that so many disease processes are genetically determined and so out of our control. Along the same lines, the experience has also been neck-wracking, because of the detail and efficiency that goes into mastering different disease morphologies and preparing a comprehensive pathology report. The ability to tell the difference between two very similar disease entities but with different morphological features can drive one crazy, because, sometimes everything just seems to look the same!

I remember my early days as a resident. The first week in residency training to be precise. Then, I got reintroduced to the microscope, which is the power of the pathologist. Looking into the microscope and feigning to see what the senior residents and attendings were seeing felt like outright torture to me. You know why? It’s because everything under the microscope was either blue or pink.

In my few years of training as a resident, I have come to learn that in order to be successful as a pathologist, one must be adept with every single detail. As Pathologists, we deal with the facts. We do not make things up, and strive to present the facts of every case which ultimately supports our rendered diagnoses.

Unlike when I first started my residency training, I now know that not everything under the microscope is just blue and pink, and even if they are indeed blue and pink, the degree of their “blueness” or “pinkness” varies. And the intensity of the hematoxylin and eosin (H&E)/immunohistochemical stains may sometimes tell disease entities apart from one another. So, sometimes when people ask me what type of doctor I am training to be, I tell them, “I am a doctor of colors,” which of course often leaves them confused!

I also tell people that I am training to be a doctor who works from behind the scenes, to make sure they get treated right all the time. And this realization I believe is what has created the greatest impression for me. Realizing that a patient’s choice of treatment may totally be dependent on the pronouncements I make on their disease process, is something that gets me motivated to keep putting in my best into my training in order to become one of the best in my field. Therefore, even though we operate as doctors from behind the scenes, our professional judgments often go a long way in impacting the welfare and outcomes of patients whom we never get to see, which is one of the aspects of the specialty that I truly love.

So, pathology as a specialty has given me a more robust meaning to life. I have learned to value and appreciate the time I spend with those I love, and to make special moments with them count. It has made me realize that there are certain things about life such as genetic diseases, that I have no control over and therefore should only be concerned with giving my very best all the time. Pathology has also made me more detail oriented, by learning to distinguish benign from malignant processes. It has reinforced for me, the importance of being the best person I can be to both my family, neighbors and my community in general. And I would also add that pathology has further reignited my love for good food. So, let the party begin!!!

References

  1. Ignatavicius DD, Workman ML. Medical-Surgical Nursing: Patient-centered collaborative care. Elsevier Health Sciences; 2015. 1735p.
  2. Mehta V, Balachandran C, Lonikar V. Blueberry muffin baby: a pictoral differential diagnosis. Dermatol Online J. 2008;14(2):8.
  3. Oertli D, Udelsman R. Surgery of the thyroid and parathyroid Glands. Springer Science & Business Media; 2012. p. 620.
  4. Bolognia JL, Jorizzo JL, Rapini RP. Dermatology. Gulf Professional Publishing; p. 1438.
  5. Daftary. 100+Clinical Cases In Obstetrics. Elsevier India; 2006. p. 478.
  6. Power ML, Schulkin J. The Evolution of the Human Placenta. JHU Press; 2012. p. 278.
  7. Swygard H, Seña AC, Hobbs MM, Cohen MS. Trichomoniasis: clinical manifestations, diagnosis and management. Sex Transm Infect. 2004 Apr 1;80(2):91–5.

-Evi Abada, MD, MS is a Resident Physician in anatomic and clinical pathology at the Wayne State University School of Medicine/Detroit Medical Center in Michigan. She earned her Masters of Science in International Health Policy and Management from Brandeis University in Massachusetts, and is a global health advocate. Dr. Abada has been appointed to serve on the ASCP’s Resident’s Council and was named one of ASCP’S 40 under Forty honorees for the year 2020. You can follow her on twitter @EviAbadaMD.

Patients and Patience (Part 2)

Holiday season in well behind us and, while we celebrate and coordinate getting our COVID vaccinations (side note: get yours please), I’d like to revisit a piece from a while back called “Patients and Patience.”

Then I talked about how our professionally shared spirit of camaraderie and patient advocacy go hand-in-hand with the ASCP mission. How, regardless of what role we play in patient care, we continue to give as much as we can to make the lives and hopes of patients everywhere a bit brighter. This year especially, as the pandemic continues to take over all frequencies and channels (including this blog, I’m sorry), I think it’s especially poignant to remember how life can be both grand and fragile. You’ve read my musings on how doctors can be patients too, and how we can all be stretch so thin it can affect our health. When you think the experiences of anyone in healthcare this past year you can’t help but reflect on how burnout and compassion really both know no bounds.

This month, I’m dedicating this piece to one of Loyola’s faculty who sadly and unexpectedly passed away just before the New Year, Dr. Stefan Pambuccian. In a caustic reminder of life’s grand fragility, he was an archetype of what it meant to be an accomplished and respected pathologist, physician, teacher, and friend. While he and other faculty here push all of us resident/trainees or fellows to be better, and research, publish, learn, share, and grow, people like Dr. Pambuccian set the tone with years of experience, an open door, and an uncanny ability to give you a differential diagnosis from only peeking at a slide from across the room at 1x—not a typo.

Image 1. You can barely find any posters on our walls (of which there are many) that don’t in some way bear the name or relate to the work or Dr. Pambuccian here at Loyola. His office and door continue to receive new messages of loss, praise, thanks, and sentiment. Losses like these are never easy, but no one here went through this alone.

While the residents were having a great uplifting secret santa exchange a few days after Christmas, we went around praising our anonymous gift recipients and shared some laughs amidst a new warm holiday memory. The same joy that filled our workroom vanished after everyone had heard the awful news, taking time to process and simply be with each other that afternoon and the weeks that followed. That’s exactly the message I think rings true this time around: in order to care for patients, and ourselves, our friends, and our colleagues, we should always have reserves of patience, compassion, and humanity. While there are great wellness programs, and tips and tricks to avoid burnout, that’s for other blogs; sometimes what one really needs is other people. Peers. Friends. Family. I’m relatively new here in this program, but what I could see that day was an immediate working shift from signing out cases to taking the time to make sure everyone was okay—whatever that meant for them. You can promote wellness all day, but you can’t (ethically) pose any actual testing of resilience. The loss of Dr. Pambuccian not only demonstrated the camaraderie and compassion at Loyola Pathology, but made sure we all learned what it means to be a great pathologist.

Image 2. A fun yet fleeting secret Santa. Despite the mood of this day being changed by the news, happy memories are still just as important. Both the sad and happy parts of this day brought us all closer, and stronger, together.

Like I said, my interactions with him were brief at best but he gave the morning didactic at my very first residency interview here and I learned all about his bottomless sense of humor and wit. Since starting, he was always there running the Thursday unknown sessions, where I felt empowered to participate alongside his openness for learners at all levels. I even remember I was on-call one night with him on service, and after checking in with other residents, I gave him a call to say there was nothing much happening tonight—I barely made it past my hello, before he told me to have  good night because he already checked the surgery schedule and was just waiting on me to call. Thanks. I could never do justice in telling stories about him when compared to literally anyone else in my department. There were countless more stories, and tons of experiences my fellow senior residents and faculty all shared about their working with him. I just feel lucky enough to have known him.

Image 3. I volunteered along with one of our fellows to take new faculty and resident photographs for our new website. My cloud photo storage is full of 3-4 similarly posed faces of everyone I work with…except Dr. Pambuccian. He wanted to make this fun, much like everything else he did.

I find myself in the same position as the last time I talked on this topic: at a new chapter in life to start becoming the doctor I set off on this journey to become many years ago. With the addition of excellent faculty mentors, friends and colleagues, and an ongoing, renewed sense of purpose, I’ll keep you all posted.

To read more about Dr. Pambuccian’s life, his love of art and cats, his numerous publications which will undoubtedly crash your computer, please click this link to Loyola Pathology’s in memoriam.

Thank you for reading and letting me take this aside to say, as I have before, that we deserve the same compassion and patience as we extend to our patients and that the values that inspire us to do our best to improve healthcare at large are the same values that can help us build strong, caring relationships with our families, friends, and colleagues.

Take care of yourselves and those around you. Thanks for reading! See you next time!

(And look into how and where to get your COVID vaccine!)

Constantine E. Kanakis MD, MSc, MLS(ASCP)CM is a first-year resident physician in the Pathology and Laboratory Medicine Department at Loyola University Medical Center in Chicago with interests in hematopathology, transfusion medicine, bioethics, public health, and graphic medicine. He is a certified CAP inspector, holds an ASCP LMU certificate, and xxx. He was named on the 2017 ASCP Forty Under 40 list, The Pathologist magazine’s 2020 Power List and serves on ASCP’s Commission for Continuing Professional Development, Social Media Committee, and Patient Champions Advisory Board. He was featured in several online forums during the peak of the COVID pandemic discussing laboratory-related testing considerations, delivered a TEDx talk called “Unrecognizable Medicine,” and sits on the Auxiliary Board of the American Red Cross in Illinois. Dr. Kanakis is active on social media; follow him at @CEKanakisMD.

Case Study: Newborn with Thrombocytopenia and Bruising

A newborn, healthy, full term, male child, was born with bruising on his left thigh and developed petechiae and purpuric hemorrhages several hours after birth. The baby was moved to the NICU for observation and a CBC was ordered by the NICU provider.

  • WBC, RBC, Hgb, Hct and indicies were normal
  • Platelet count 58 x103/μL
  • Baby exhibited no symptoms of sepsis
  • Smear reviewed with no platelet clumping observed

The mother is a 28 year old, gravida 1, para 1 with normal CBC and platelet count. Her prenatal history was unremarkable. She has no history of immune thrombocytopenia (ITP) and no history of being prescribed drugs known to be associated with drug induced thrombocytopenia

Thrombocytopenia is not an uncommon finding in neonates, particularly in the neonatal intensive care unit (NICU). In preterm infants, the most common causes of thrombocytopenia are complications of pregnancy, including pregnancy-induced hypertension (PIH), intrauterine growth retardation, preeclampsia ,and HELLP syndrome (hemolytic anemia, elevated liver enzymes, low platelet count). Examination of a peripheral smear in these patients will typically reveal neutropenia with densely packed red cells, increased nucleated RBCs and deceased platelet estimate. These placental insufficiency cases typically occur within the first 72 hours of life, platelet counts are >50 x 103/μL, resolve without treatment and require no further investigation. On the other hand, thrombocytopenia in preterm infants that develops after 72 hours is most likely due to sepsis or necrotizing enterocolitis and requires investigation and treatment.2

In an otherwise healthy appearing full term infant, the most common cause of thrombocytopenia in the first 72 hours of life is neonatal alloimmune thrombocytopenia (NAIT). When a platelet count drops below 150 x 103/L in these newborns, it is important to investigate the thrombocytopenia. The first step is to always check a peripheral smear for clumping to rule out spurious thrombocytopenia. With a low platelet count and the absence of spurious thrombocytopenia, NAIT can be suspected. This condition is similar in pathogenesis to hemolytic disease of the fetus and newborn (HDFN), and is caused by an incompatibility in human platelet antigens between mother and baby. In about 80% of cases, the mother is found to be HPA-1b and the father and baby are HPA-1a.1 The mother forms anti-HPA-1a which crosses the placenta and destroys the fetus’ platelets. Most cases of NAIT are asymptomatic, or cause only mild bleeding, and resolve in 1-2 weeks.1

Although many cases of NAIT are mild, it is important to recognize because it can be a life-threatening disorder. With more severe thrombocytopenia, in both premature and full term infants, NAIT can result in intracranial bleeding either before birth or shortly after birth. NAIT can also cause long term neurologic complications. Therefore, when a neonate is suspected to have NAIT, he should be screened for intracranial hemorrhage. Since mothers are most often found to have anti- HPA-1a, and the second most commonly found antibody is anti-HPA-5b, neonates with platelet counts <30 x 103/L should be transfused with antigen matched or HPA-1a and HPA-5b negative, CMV negative, single donor apheresis platelets.

It is important to note that NAIT can occur in a first pregnancy but subsequent pregnancies are usually more severely affected. In confirming NAIT after a first delivery or monitoring a subsequent pregnancy, serological testing should be done on both parents to determine the risk of having an infant born with NAIT. If the father is homozygous for the antigen which the mother lacks, 100% of infants would be at risk. If the father is heterozygous, an infant would have a 50% chance of inheriting the antigen from the father.

NAIT in a first pregnancy is typically unrecognized until after birth. Some groups have advocated for routine prenatal screening for NAIT in all pregnant women, but this is costly and still debated. It is agreed that after an affected first child, subsequent pregnancies should be monitored closely. In at risk pregnancies, weekly antenatal IVIg infusions should be used during pregnancy to help prevent fetal bleeding.3

The mother in this case was tested and found to be HPA-1a negative with anti-HPA-1a. The father was also tested and found to be HPA-1a positive. The infant’s platelet counts began to increase at 7 days, with no further bleeding. The mother was referred to a NAIT specialty team for future pregnancies.

Diagnosis: Neonatal Immune Thrombocytopenia (NAIT)

  • Similar in pathogenesis to hemolytic disease of the fetus and newborn (HDFN)
  • Incompatibility in human platelet antigens between mother and baby.
  • Can affect first born
  • In majority of cases, the mother is HPA-1b and the father and baby are HPA-1a
  • Second most common is anti-HPA-5b

References

  1. http://naitbabies.org/wp-content/uploads/141208_NAIT_Registry_poster.pdf
  2. Subarna Chakravorty and Irene Roberts. How I manage neonatal thrombocytopenia . Blackwell Publishing Ltd, British Journal of Haematology. 2011; 156, 155–162
  3. T.W. de Vos, D. Winkelhorst, M. de Haas, E. Lopriore, D. Oepkes. Epidemiology and management of fetal and neonatal alloimmune thrombocytopenia. Transfusion and Apheresis Science. 2020
  4. Shamudheen Rafiyath, Immune Thrombocytopenia and Pregnancy Treatment & Management Updated: Sept. 2020 https://emedicine.medscape.com/article/208697-treatment

-Becky Socha, MS, MLS(ASCP)CM BB CM graduated from Merrimack College in N. Andover, Massachusetts with a BS in Medical Technology and completed her MS in Clinical Laboratory Sciences at the University of Massachusetts, Lowell. She has worked as a Medical Technologist for over 30 years. She’s worked in all areas of the clinical laboratory, but has a special interest in Hematology and Blood Banking. When she’s not busy being a mad scientist, she can be found outside riding her bicycle.