Hospitalisation and mortality outcomes of patients with comorbid COPD and heart failure: a systematic review protocol
Bibliographic record
Abstract
INTRODUCTION: Chronic obstructive pulmonary disease (COPD) and heart failure (HF) often coexist in patients. Many studies have explored the short-term and long-term outcomes of patients with comorbid COPD and HF; however, there have been discrepancies in their findings. METHODS AND ANALYSIS: In this systematic review, MEDLINE and Embase will be searched using a prespecified search strategy. Randomised controlled trials and studies conducted in the general population that employ analytical or descriptive (longitudinal or case-control) study designs that report odds ratios (ORs), hazard ratios (HRs), or risk ratios (RRs) of mortality or hospitalisation, comparing patients with comorbid COPD and HF with patients with just COPD, will be selected. Screening by title and abstract, then full-text screening will be conducted by two reviewers. The Population, Exposure, Comparator, Outcomes, Study (PECOS) characteristics framework will be used to systemise the data extraction from selected studies. Study quality will be assessed using an adapted version of the Newcastle-Ottawa risk of bias tool. Data extraction and the risk of bias will also be conducted by two reviewers. Given sufficient homogeneity of selected studies, a meta-analysis will be conducted. Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) criteria will be used to assess the quality of cumulative evidence. DISSEMINATION: With this review, we hope to improve the understanding of clinical outcomes of patients with comorbid COPD and HF. We intend to publish the results of our review in a peer-reviewed journal and to present our findings at national and international meetings and conferences. PROSPERO REGISTRATION NUMBER: CRD42018089534.
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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 | 0.070 | 0.061 |
| Meta-epidemiology (narrow) | 0.006 | 0.006 |
| Meta-epidemiology (broad) | 0.018 | 0.016 |
| Bibliometrics | 0.013 | 0.014 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.076 | 0.010 |
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".