Frequency and distribution of eschar in patients with scrub typhus in India: systematic review of literature and meta-analysis
Bibliographic record
Abstract
Introduction: Scrub typhus is a mite-borne tropical febrile illness with high mortality if untreated. The presence of eschar is pathognomonic, but a wide range of frequencies of eschar positivity has been reported in Indian patients. Therefore, this systematic review and meta-analysis aimed to ascertain the frequency (overall and geographic region-wise) and anatomical distribution of eschar in scrub typhus in India. Methodology: We searched articles in two databases using: [(scrub OR typhus OR Orientia) AND (eschar) AND (India)]. The articles were independently screened and critically appraised by two authors. The frequency and distribution of eschar in patients with scrub typhus were pooled using a random-effect model. Results: After the title-abstract and full-text screening, 107 articles (34002 cases of scrub typhus) were finally included. The overall pooled proportion of eschar positivity was 28.5% (95% CI: 24.1 to 32.9%). The pooled eschar positivity varied from ≤12% in Haryana, Rajasthan, Madhya Pradesh, Punjab, and Meghalaya to ≥46% in Tamil Nadu and Tripura. The pooled proportion of eschar positivity in the 'trunk' (39.3%), 'groin' (23.8%), and 'axilla' (16.5%) was higher than in the 'limbs' (9.9%) and 'head' (11.3%). Conclusion: Eschar is reported in less than a third of the patients with scrub typhus in India. Most eschars were in the groin, axilla, and the trunk. There is a need to create awareness amongst physicians of the need for thorough physical examination.
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 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 | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.028 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".