Diagnostic Value of Clinical Features to Distinguish Enteric Fever From Other Febrile Illnesses in Bangladesh, Nepal, and Pakistan
Bibliographic record
Abstract
BACKGROUND: Enteric fever, a bacterial infection caused by Salmonella enterica serotypes Typhi and Paratyphi A, frequently presents as a nonlocalizing febrile illness that is difficult to distinguish from other infectious causes of fever. Blood culture is not widely available in endemic settings and, even when available, results can take up to 5 days. We evaluated the diagnostic performance of clinical features, including both reported symptoms and clinical signs, of enteric fever among patients participating in the Surveillance for Enteric Fever in Asia Project (SEAP), a 3-year surveillance study in Bangladesh, Nepal, and Pakistan. METHODS: Outpatients presenting with ≥3 consecutive days of reported fever and inpatients with clinically suspected enteric fever from all 6 SEAP study hospitals were eligible to participate. We evaluated the diagnostic performance of select clinical features against blood culture results among outpatients using mixed-effect regression models with a random effect for study site hospital. We also compared the clinical features of S. Typhi to S. Paratyphi A among both outpatients and inpatients. RESULTS: We enrolled 20 899 outpatients, of whom 2116 (10.1%) had positive blood cultures for S. Typhi and 297 (1.4%) had positive cultures for S. Paratyphi A. The sensitivity of absence of cough was the highest among all evaluated features, at 65.5% (95% confidence interval [CI], 55.0-74.7), followed by measured fever at presentation at 59.0% (95% CI, 51.6-65.9) and being unable to complete normal activities for 3 or more days at 51.0% (95% CI, 23.8-77.6). A combined case definition of 3 or more consecutive days of reported fever and 1 or more of the following (a) either the absence of cough, (b) fever at presentation, or (c) 3 or more consecutive days of being unable to conduct usual activity--yielded a sensitivity of 94.6% (95% CI, 93.4-95.5) and specificity of 13.6% (95% CI, 9.8-17.5). CONCLUSIONS: Clinical features do not accurately distinguish blood culture-confirmed enteric fever from other febrile syndromes. Rapid, affordable, and accurate diagnostics are urgently needed, particularly in settings with limited or no blood culture capacity.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".