Leptospirosis as a risk factor for chronic kidney disease: A systematic review of observational studies
Bibliographic record
Abstract
BACKGROUND: Leptospirosis is a worldwide prevalent zoonosis and chronic kidney disease (CKD) is a leading global disease burden. Because of pathophysiological changes in the kidney, it has been suggested that these conditions may be associated. However, the extent of this interaction has not been synthetized. We aimed to systematically review and critically appraise the evidence on the association between leptospirosis and CKD. METHODOLOGY/PRINCIPAL FINDINGS: Observational studies with a control group were selected. Leptospirosis, confirmed with laboratory methods, and CKD also based on a laboratory assessment, were the exposures and outcomes of interest. The search was conducted in EMBASE, MEDLINE, Global Health, Scopus and Web of Science. Studies selected for qualitative synthesis were assessed for risk of bias following the Newcastle-Ottawa Scale. 5,981 reports were screened, and 2 (n = 3,534) were included for qualitative synthesis. The studies were conducted in Taiwan and Nicaragua; these reported cross-sectional and longitudinal estimates. In the general population, the mean estimated glomerular filtration rate (eGFR) was lower (p<0.001) in people testing positive for antileptospira antibodies (eGFR = 98.3) than in negative controls (eGFR = 100.8). Among sugarcane applicants with high creatinine, those who were seropositive had lower eGFR (mean difference: -10.08). In a prospective analysis, people with high antileptospira antibodies titer at baseline and follow-up, had worse eGFR (p<0.05). CONCLUSION: Although the available evidence suggests there may be a positive association between leptospirosis and CKD, whereby leptospirosis could be a risk factor for CKD, it is still premature to draw conclusions. There is an urgent need for research on this association.
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 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 | 0.000 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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; both teacher heads agree on what is shown here.
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".