Medication reviews and deprescribing as a single intervention in falls prevention: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: our aim was to assess the effectiveness of medication review and deprescribing interventions as a single intervention in falls prevention. DESIGN: systematic review and meta-analysis. DATA SOURCES: Medline, Embase, Cochrane CENTRAL, PsycINFO until 28 March 2022. ELIGIBILITY CRITERIA: randomised controlled trials of older participants comparing any medication review or deprescribing intervention with usual care and reporting falls as an outcome. STUDY RECORDS: title/abstract and full-text screening by two reviewers. RISK OF BIAS: Cochrane Collaboration revised tool. DATA SYNTHESIS: results reported separately for different settings and sufficiently comparable studies meta-analysed. RESULTS: forty-nine heterogeneous studies were included. COMMUNITY: meta-analyses of medication reviews resulted in a risk ratio (RR) of 1.05 (95% confidence interval, 0.85-1.29, I2 = 0%, 3 studies(s)) for number of fallers, in an RR = 0.95 (0.70-1.27, I2 = 37%, 3 s) for number of injurious fallers and in a rate ratio (RaR) of 0.89 (0.69-1.14, I2 = 0%, 2 s) for injurious falls. HOSPITAL: meta-analyses assessing medication reviews resulted in an RR = 0.97 (0.74-1.28, I2 = 15%, 2 s) and in an RR = 0.50 (0.07-3.50, I2 = 72% %, 2 s) for number of fallers after and during admission, respectively. LONG-TERM CARE: meta-analyses investigating medication reviews or deprescribing plans resulted in an RR = 0.86 (0.72-1.02, I2 = 0%, 5 s) for number of fallers and in an RaR = 0.93 (0.64-1.35, I2 = 92%, 7 s) for number of falls. CONCLUSIONS: the heterogeneity of the interventions precluded us to estimate the exact effect of medication review and deprescribing as a single intervention. For future studies, more comparability is warranted. These interventions should not be implemented as a stand-alone strategy in falls prevention but included in multimodal strategies due to the multifactorial nature of falls.PROSPERO registration number: CRD42020218231.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".