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Record W2599453747 · doi:10.1093/pch/21.1.9

Case 1: A newborn with pancytopenia

2016· article· en· W2599453747 on OpenAlexaff
Isabel Cardona, Emanuela Ferretti, Thierry Daboval, Robert J. Klaassen, Yigal Dror

Bibliographic record

VenuePaediatrics & Child Health · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBlood disorders and treatments
Canadian institutionsSickKids FoundationHospital for Sick ChildrenChildren's Hospital of Eastern OntarioMcGill University Health CentreMontreal Children's Hospital
Fundersnot available
KeywordsPancytopeniaMedicinePediatricsPathologyBone marrow

Abstract

fetched live from OpenAlex

An infant was delivered via spontaneous vaginal delivery at 384 weeks’ gestational age. She was born following in vitro fertilization to a 31-year-old primigravida mother known to have hypothyroidism. There was no reported consanguinity between the parents. Maternal toxoplasmosis, other (syphilis, varicella-zoster, parvovirus B19), rubella, cytomegalovirus and herpes infections (TORCH) serology was negative and her blood count was normal. Fetal ultrasound revealed an absent right kidney but otherwise normal anatomy. Integrated prenatal screen was normal. The mother received one prophylactic dose of penicillin G for group B Streptococcus-positive status. At delivery, the infant had normal vital signs and no dysmorphic features; however, she was pale, with a ‘blueberry’ rash (palpable purpura-petechiae) covering her entire body (Figure 1). The first complete blood count performed after birth revealed a hemoglobin level of 52 g/L, platelet count of 3×109/L and a relatively low white blood cell count (6.1×109/L) but normal neutrophil count (1.6×109/L). She immediately received platelet and red blood cell transfusions. Kleihauer-Betke test was negative. Five days later, she developed severe, persistent neutropenia (nadir 0.0×109/L). A fundoscopic examination revealed bilateral retinal hemorrhages. Magnetic resonance imaging of the brain revealed multiple small cortical petechial hemorrhages. Further testing helped clarify the diagnosis. Pancorporal palpable purpura-petechial rash, typical of a ‘blueberry muffin’ rash A search for a known constitutional, toxic and viral etiology, such as toxoplasmosis, cytomegalovirus, rubella, varicella zoster, herpes and parvovirus B19, was negative. The negative Kleihauer-Betke test excluded fetomaternal bleeding. Intrathoracic, retroperitoneal and adrenal masses were not found on radiological examinations (chest x-ray and abdomen ultrasound), excluding neuroblastoma stage IVS. X-rays of the forearms were normal. The parents were both negative for platelet antibodies and there was no platelet antigen incompatibility. To determine the diagnosis, a bone marrow aspirate and biopsy were performed. They revealed active erythropoiesis and granulopoiesis with absent megakaryocytes. Repeat bone marrow examination performed one month later revealed severe hypoplasia of erythroid, myeloid and megakaryocyte lineages, with absence of fibrosis, increased blasts, leukemic or solid tumour infiltrations, or cytological abnormalities consistent with bone marrow failure. A lymphoid leukemic process was ruled out by a negative terminal deoxynucleotidyl transferase. Normal chromosomal fragility testing ruled out Fanconi’s anemia. Genetic testing (c-Mpl) for congenital amegakaryocytic thrombocytopenia was negative. The recognition of bicytopenia (thrombocytopenia and anemia) in a newborn requires careful investigation for an underlying cause and prompt management to prevent severe sequelae and even death, secondary to complications (1). In the present case, severe bicytopenia and, especially, profound thrombocytopenia at birth, initially caused the clinicians to suspect a more common diagnosis such as neonatal alloimmune thrombocytopenia (NAIT) complicated by blood loss. Inherited bone marrow failure syndrome (IBMFS) and NAIT are easily confused early in their presentation. The clinical evolution, such as a lack of improvement in the following weeks after birth and the need for repeated platelet transfusions along with a negative test for anti-platelet antibodies, eliminated NAIT as the cause of the severe thrombocytopenia (2). We were left with a diagnosis of IBMFS; however, the lack of the characteristic short stature, craniofacial abnormalities or pancreatic insufficiency associated with Shwachman-Diamond syndrome, the lack of the classic radial bone aplasia associated with Fanconi anemia or thrombocytopenia-absent radius syndrome, and the absence of liver and renal dysfunction associated with bone marrow cells vacuolization in mitochondrial diseases such as Pearsons syndrome (3), made these diagnoses less likely (Table 1) (4). Aneuploidy, including trisomy 13, 18 and 21, were not considered without pathognomonic dysmorphic features. Given bicytopenia at birth, congenital amegakaryocytic thrombocytopenia – a rare autosomal recessive disorder affecting megakaryocyte production and classically causing isolated neonatal thrombocytopenia progressing late into childhood to bone marrow aplasia (5) – was only considered after the first bone marrow result. A negative result to identify the c-Mpl gene, as well as the repeat bone marrow findings, did not confirm the diagnosis. Differential diagnoses of marrow failure during the first three years of life Diamond-Blackfan anemia Dyskeratosis congenita Fanconi anemia Shwachman-Diamond syndrome Kostmann syndrome Congenital amegakaryocytic thrombocytopenia Diamond-Blackfan anemia Dyskeratosis congenita Fanconi anemia Shwachman-Diamond syndrome Kostmann syndrome Congenital amegakaryocytic thrombocytopenia Differential diagnoses of marrow failure during the first three years of life Diamond-Blackfan anemia Dyskeratosis congenita Fanconi anemia Shwachman-Diamond syndrome Kostmann syndrome Congenital amegakaryocytic thrombocytopenia Diamond-Blackfan anemia Dyskeratosis congenita Fanconi anemia Shwachman-Diamond syndrome Kostmann syndrome Congenital amegakaryocytic thrombocytopenia IBMFS is a diagnosis that includes a collection of heterogeneous genetic disorders usually classified by the predominantly involved cell lineage and the associated extrahematological manifestations (6). Mutations associated with some types of IBMFS are identifiable using genetic testing, enabling patients to be classified into a specific syndrome, which directs prognosis and treatment (7). One-quarter of patients diagnosed with IBMFS are left unclassified (7). Our patient fulfilled the criteria for unclassified IBMFS (UC-IBMFS) because the clinical picture did not fit with any categorized types; she had symptoms present at birth with persistent transfusion-dependent cytopenias, secondary to ineffective hematopoiesis. In the present case, the negative gene testing left us with a diagnosis of UC-IBMFS, which was treated with platelet and red cell transfusions over the first few months of her life. Transfusions are a supportive measure, and the only curative treatment for UC-IBMFS is stem cell transplantation (6), which was successfully performed in our patient using a matched-unrelated donor cord cell transplant when she was three months of age. She has had normal blood counts since her transplantation, with no evidence of acute or chronic graft-versus-host disease. Because the patient has UC-IBMFS, the long-term prognosis is not clear. She will require long-term follow-up to monitor for any late presenting extramedullary manifestations and malignant transformations as well as the small chance for graft failure. The differential diagnosis for ‘blueberry muffin’ rash should include IBMFS. The presence of severe congenital bicytopenia (thrombocytopenia and anemia) at birth should be a clue to consider investigation for IBMFS. IBMFSs are classified according to the cell lineage predominantly involved and associated extrahematological manifestations, and would benefit from rapid genetic testing from a specialized laboratory.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.007
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.001
Science and technology studies0.0030.002
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0110.004
Insufficient payload (model declined to judge)0.0040.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.237
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2016
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