Leptospirosis in Pregnancy: A Rare Condition Mimicking HELLP Syndrome
Bibliographic record
Abstract
We report a case of leptospirosis in pregnancy. A 37-year-old woman of para 1, normal vaginal delivery (NVD) presented at 33 weeks with 3 days of jaundice and diarrhea and no history of fever, abdominal pain, itch or pale stools. Her pregnancy was uneventful except for gestational diabetes. On examination she had jaundice otherwise unremarkable. Investigations revealed proteinuria, hemolysis, low platelets, raised transaminases and bilirubin. Working diagnosis was of atypical hemolysis, elevated liver enzymes, low platelets (HELLP) syndrome owing to absence of hypertension. She progressed into labour 1 day later after preterm premature rupture of membranes (PPROM), had thick meconium and pathological cardiotocography (CTG). She delivered a baby weighing 1,736 g and normal Apgar scores. Arterial cord pH was 7.275, lactate 3.04, base excess of -8.8 and venous pH was 7.316, lactate 2.93, BE -10.6. Leptospirosis EIA IgM antibody was positive and placenta histology showed focus increased perivillous fibrinoid deposits with acute intervillositis and meconium staining. Baby showed no signs of congenital leptospirosis and was discharged on day 15 of life. Patient’s symptoms resolved within 2 weeks and her biochemistry normalized within 1 month. Owning to unusual presentation and rarity, leptospirosis in pregnancy is often misdiagnosed and underreported. It mimics HELLP syndrome, viral hepatitis, obstetric cholestasis and acute fatty liver of pregnancy. It has severe implications of early miscarriages, stillbirths and neonatal leptospirosis requiring high index of suspicion, need for increased awareness, early diagnosis and treatment. J Med Cases. 2018;9(7):198-200 doi: https://doi.org/10.14740/jmc3073w
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".