Effectiveness, reach, uptake and feasibility of digital health interventions for adults with venous thromboembolism: protocol of a systematic review and meta-analysis
Bibliographic record
Abstract
INTRODUCTION: Prevention of recurrence after an episode of venous thromboembolism (VTE), and also the post-thrombotic syndrome (PTS), is still a recognised challenge. In this meta-analysis, we will summarise existing evidence to compare intelligent system follow-up and routine follow-up for patients with VTE. METHODS AND ANALYSIS: Relevant randomised controlled trials (RCTs) and cohort studies will be included from the following databases: MEDLINE/PubMed, Web of Science and the Cochrane Library. The last search time will be 31 March 2024. Two reviewers will independently identify RCTs and cohort studies according to eligibility and exclusion criteria. The risk of bias of included cohort studies will be assessed with the Newcastle-Ottawa Scale, Methodological Index of Non-Randomised Studies, and the risk of bias of RCTs will be assessed with and Cochrane Collaboration's tool. The primary outcomes include overall survival rate and PTS incidence rate. The Grades of Recommendations, Assessment, Development and Evaluation tool will be used to assess the level of evidence for outcome from RCTs. RevMan V.5.4 software will be used to pool outcomes. ETHICS AND DISSEMINATION: Ethical approval was obtained from Shanghai Ninth People's Hospital, Shanghai JiaoTong University School of Medicine Science Research Ethics Committee (SH9H-2023-T466-1). The findings will be disseminated to the public through conference presentations and publication in peer-reviewed scientific journals. PROSPERO REGISTRATION NUMBER: CRD42023410644.
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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 | 0.077 | 0.088 |
| Meta-epidemiology (narrow) | 0.006 | 0.005 |
| Meta-epidemiology (broad) | 0.021 | 0.037 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.039 | 0.005 |
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".