Burden of COVID-19 pandemic on tuberculosis hospitalisation patterns at a tertiary care hospital in Rajasthan, India: a retrospective analysis
Bibliographic record
Abstract
OBJECTIVE: This study aimed to investigate the burden of the COVID-19 pandemic on tuberculosis (TB) trends, patient demographics, disease types and hospitalisation duration within the Respiratory Medicine Department over three distinct phases: pre-COVID-19, COVID-19 and post-COVID-19. DESIGN: Retrospective analysis using electronic medical records of patients with TB admitted between June 2018 and June 2023 was done to explore the impact of COVID-19 on patients with TB. The study employed a meticulous segmentation into pre-COVID-19, COVID-19 and post-COVID-19 eras. SETTING: National Institute of Medical Science Hospital in Jaipur, Rajasthan, India. PRIMARY AND SECONDARY OUTCOME MEASURES: Primary outcome includes patients admitted to the Respiratory Medicine Department of the hospital and secondary outcome involves the duration of hospital stay. RESULTS: The study encompassed 1845 subjects across the three eras, revealing a reduction in TB incidence during the post-COVID-19 era compared with the pre-COVID-19 period (p<0.01). Substantial demographic shifts were observed, with 5.2% decline in TB incidence among males in the post-COVID-19 era (n=529) compared with the pre-COVID-19 era (n=606). Despite the decrease, overall TB incidence remained significantly higher in males (n=1460) than females (n=385), with consistently elevated rates in rural (65.8%) as compared with the urban areas (34.2%). Extended hospital stays were noted in the post-COVID-19 era compared with the pre-COVID-19 era (p<0.01). CONCLUSION: The study underscores the influence of the COVID-19 pandemic on the TB landscape and hospitalisation dynamics. Notably, patient burden of TB declined during the COVID-19 era, with a decline in the post-COVID-19 era compared with the pre-COVID-19 era. Prolonged hospitalisation in the post-COVID-19 period indicates the need for adaptive healthcare strategies and the formulation of public health policies in a post-pandemic context. These findings contribute to a comprehensive understanding of the evolving TB scenario, emphasising the necessity for tailored healthcare approaches in the aftermath of a global health crisis.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".