Epidemiological Determinants for Mortality from Neonatal Tetanus in Punjab Province, Pakistan (2020)
Bibliographic record
Abstract
Background Neonatal tetanus (NNT) is a vaccine-preventable disease that occurs at higher incidence in resource-poor countries, presumably because of low maternal immunization rates and unhygienic cord care practices. NNT remains an important cause of infant mortality in rural areas of Punjab Province. Objective This study aims to evaluate and determine the risk factors for mortality in NNT cases and to make recommendations for future strategies. Methods A descriptive study was conducted from July 6 to 14, 2021, at Directorate General Health Office Lahore. The surveillance data set for the year 2020 and clinical notes were reviewed and analyzed. Demographic information, clinical presentation progression, and outcomes were evaluated for all investigated cases, and a comparison analysis was performed between those who survived and those who died. Results Of a total of 176 reported cases, 145 (82.3%) were notified from rural areas of Punjab. The mean age was 9 days, 65 (37%) infants were females, and 111 (63%) were males. The overall mortality was 77 (43.6%), while 31 (17.6%) maternal deliveries were conducted by untrained birth attendants. In addition, 119 (67.6%) women received zero tetanus toxoid (TT) shots in their life. Clinical notes revealed that the group that survived had a significantly greater mean body weight on admission, had later onset of disease, was hospitalized early, and received tetanus immunoglobulin (TIG). The children who could not survive had significantly common clinical features, such as generalized rigidity, fever, and respiratory arrest. Conclusions The increased mortality in rural and tribal areas is suggestive of poor TT immunization coverage. Low literacy, poor socioeconomic status of families, lack of awareness regarding antenatal care, and poor hygienic deliveries conducted by untrained persons remain the main risk factors. Improvement in TT coverage, deployment of trained community midwives, and awareness sessions regarding TT vaccination in hard-to-reach areas are recommended.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".