Global, regional and national incidence and causes of needlestick injuries: a systematic review and meta-analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Needlestick injuries (NSIs) are one of the most serious occupational hazards for healthcare workers (HCWs). Aims: The aim of this study was to evaluate the incidence and causes of NSIs globally. Methods: A systematic review and meta-analysis of data from January 2000 to May 2020 collected from Scopus, PubMed, Embase, Web of Science, and Google Scholar. The Newcastle-Ottawa Scale was used to assess the quality of the included articles. The data obtained were analysed by R version 3/5/0, and 113 articles were retrieved. Results: There were 113 studies with a total of 525 798 HCWs. The incidence of NSIs was 43%. Africa had the highest rate of these injuries of 51%, and the World Health Organization (WHO) African Region had the highest incidence among WHO regions of 52%. Women were more frequently affected by NSIs than men. Hepatitis C virus infection was the disease most commonly transmitted via NSIs (21%). The highest rates of NSIs according to causes, devices, hospital locations, occupations and procedures were for recapping of needles, needles, general wards, nurses and waste disposal, respectively. Conclusion: The incidence of NSIs is gradually decreasing. The findings of this study can contribute to improving the decision-making process for reducing NSIs in HCWs.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it