Effect of Intermittent Pneumatic Compression in Addition to Pharmacologic Prophylaxis for Thromboprophylaxis in Hospitalized Adult Patients: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Venous thromboembolic events (VTE) are frequent complications in hospitalized patients and a leading cause of preventable death in hospital. Pharmacologic prophylaxis is a standard of care to prevent VTE in patients at risk, the additional value of intermittent pneumatic compression (IPC) is uncertain. We aimed to evaluate the efficacy of adding IPC to pharmacologic prophylaxis to prevent VTE in hospitalized adults. DATA SOURCES: We searched the Cochrane Central Register of Controlled Trials, Embase, MEDLINE, Cumulative Index to Nursing and Allied Health Literature, ClinicalTrials.gov, and the International Clinical Trials Registry Platform from inception to July 2022. STUDY SELECTION: We included randomized controlled trials comparing the use of IPC in addition to pharmacological thromboprophylaxis to pharmacological thromboprophylaxis alone in hospitalized adults. DATA EXTRACTION: Meta-analyses were performed to calculate risk ratio (RR) of VTE, deep venous thrombosis (DVT), and pulmonary embolism (PE). We assessed the risk of bias using the Cochrane Risk of Bias Tool for Randomized Trials, Version 2 and the quality of evidence using the Grading of Recommendations Assessment, Development and Evaluation approach. DATA SYNTHESIS: We included 17 trials enrolling 8,796 participants. The IPC was mostly applied up to the thigh and pharmacological thromboprophylaxis was primarily low-molecular-weight heparin. Adjunctive IPC was associated with a decreased risk of VTE (15 trials, RR = 0.53; 95% CI [0.35-0.81]) and DVT (14 trials, RR = 0.52; 95% CI [0.33-0.81]) but not PE (seven trials, RR = 0.73; 95% CI [0.32-1.68]). The quality of evidence was graded low, downgraded by risk of bias and inconsistency. Moderate and very low-quality evidence, respectively, suggests that adjunctive IPC is unlikely to change the risk of all-cause mortality or adverse events. Subgroup analyses indicate a more evident apparent benefit in industry-funded trials. CONCLUSIONS: Results indicate low-quality evidence underpinning the additional use of IPC to pharmacological thromboprophylaxis for prevention of VTE and DVT. Further large high-quality randomized trials are warranted to support its use and to identify patient subgroups for whom it could be beneficial.
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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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.042 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".