Risk factors for urinary tract infection in elderly patients with type 2 diabetes: A protocol for systematic review and meta-analysis
Bibliographic record
Abstract
INTRODUCTION: Type 2 diabetes mellitus (T2DM) is a frequent chronic condition among the elderly, which increasing their susceptibility to infection. Urinary tract infection (UTI) is one of the most prevalent infections among older people with T2DM. However, the association between geriatric T2DM and the risk of UTI has not been thoroughly researched and is still contentious. Consequently, this protocol describes a systematic review to pinpoint the primary risk factors for UTI among elderly T2DM. Our goal is to improve recommendations for the creation of targeted treatment interventions by examining risk factors for UTI in elderly individuals with T2DM. METHODS AND ANALYSIS: We will search 4 English literature databases (PubMed, Embase, Web of Science, and Cochrane Library) and 3 major Chinese databases (CNKI, WanFang, and VIP) from the establishment of the database to June 20, 2024. Systematic evaluation and meta-analysis will be conducted on cohort and case-control studies exploring the occurrence and risk determinants of UTI in individuals diagnosed with T2DM. The main focus will be on identifying the risk factors for UTI in elderly diabetic patients. Two researchers will independently review articles, collect data, and evaluate the quality and potential bias of study inclusion. We will use RevMan V.5.4 software to analyze the data. The quality of the included studies will be assessed using the Newcastle-Ottawa scale. In addition, the GRADE (Grade of Recommendations, Assessment, Development, Evaluation) method will be used to examine the quality of evidence for each exposure and outcome of interest. DISCUSSION: This study aims to illuminate the various risk factors associated with UTI in older patients diagnosed with T2DM. By this thorough investigation, we hope to provide a more comprehensive reference for medical professionals and researchers, thereby supporting the implementation of effective preventive strategies against UTI and improving overall nursing outcomes for this specific patient population. TRAIL REGISTRATION: PROSPERO (CRD42024559129).
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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 | 0.061 | 0.100 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.021 | 0.029 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.044 | 0.003 |
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".