Predictive modelling methods of hospital readmission risks for patients with chronic obstructive pulmonary disease (COPD): a systematic review protocol
Bibliographic record
Abstract
INTRODUCTION: Chronic obstructive pulmonary disease (COPD) is a significant chronic respiratory condition characterised by persistent airway obstruction, leading to substantial morbidity and mortality worldwide. Patients with COPD frequently experience hospital readmissions shortly after discharge, mainly due to acute exacerbations. This review aims to identify and synthesise the reported performance metrics and methodological limitations of different predictive modelling methods for hospital readmissions in COPD patients. METHOD AND ANALYSIS: This protocol adheres to the Preferred Reporting Items for Systematic reviews and Meta-Analysis Protocols (PRISMA-P) guidelines. The review will include studies that develop or validate predictive models for hospital readmissions in COPD patients. A comprehensive search will be conducted across PubMed, Embase, Cochrane Library, IEEE Xplore, Web of Science and Google Scholar using predefined keywords. Eligible studies will include those utilising any predictive modelling method, focusing on unplanned readmissions within specified timeframes (30, 60 or 90 days). Two independent reviewers will screen titles, abstracts and full texts, selecting studies based on predefined inclusion criteria.Data extraction will be conducted based on the CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies (CHARMS), and the methodological quality and risk of bias will be assessed using the Prediction Model Risk Of Bias Assessment Tool (PROBAST).The results will be synthesised narratively. A meta-analysis using a random-effects model will be conducted if at least five external validation studies are available for the same prediction model. ETHICS AND DISSEMINATION: This research is based exclusively on published studies and does not involve the collection of primary data collection from patients. Therefore, ethical approval is not required. Findings will be disseminated through publications in peer-reviewed journals and presentations at national and international conferences. PROSPERO REGISTRATION NUMBER: CRD42024579524.
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 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 | 0.074 | 0.087 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.014 | 0.019 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.084 | 0.011 |
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".