Association of Drug–Disease Interactions with Mortality or Readmission in Hospitalised Middle-Aged and Older Adults: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Multimorbidity is common in hospitalised adults who are at increased risk of inappropriate prescribing including drug-disease interactions. These interactions occur when a medicine being used to treat one condition exacerbates a concurrent medical condition and may lead to adverse health outcomes. The aim of this review was to examine the association between drug-disease interactions and the risk of mortality and readmission in hospitalised middle-aged and older adults. METHODS: A systematic review was conducted on drug-disease interactions in hospitalised middle-aged (45-64 years) and older adults (≥65 years). The study protocol was prospectively registered with PROSPERO (Registration Number: CRD42022341998). Drug-disease interactions were defined as a medicine being used to treat one condition with the potential to exacerbate a concurrent medical condition or that were inappropriate based on a comorbid medical condition. Both observational and interventional studies were included. The outcomes of interest were mortality and readmissions. The databases searched included MEDLINE, CINAHL, EMBASE, Web of Science, SCOPUS and the Cochrane Library from inception to 12 July, 2022. A meta-analysis was performed to pool risk estimates using the random-effects model. RESULTS: A total of 563 studies were identified and four met the inclusion criteria. All were observational studies in older adults, with no studies identified in middle-aged adults. Most of the studies were at risk of bias because of an inadequate adjustment for covariates and a lack of clarity around individuals lost to follow-up. There were various definitions of drug-disease interactions within these four studies. Two studies assessed drugs that were contraindicated based on renal function, one assessed an individual drug-disease combination, and one was based on the clinical judgement of a pharmacist. There were two studies that showed an association between drug-disease interactions and the outcomes of interest. One reported that the use of diltiazem in patients with heart failure was associated with an increased risk of readmissions. The second reported that the use of medicines contraindicated according to renal function were associated with increased risk of all-cause mortality and a composite of mortality and readmission. Three of the studies (total study population = 5705) were amenable to a meta-analysis, which showed no significant association between drug-disease interactions and readmissions (odds ratio = 1.0, 95% confidence interval 0.80-1.38). CONCLUSIONS: Few studies were identified examining the risk of drug-disease interactions and mortality and readmission in hospitalised adults. Most of the identified studies were at risk of bias. There is no universal accepted definition of drug-disease interactions in the literature. Further studies are needed to develop a standardised and accepted definition of these interactions to guide further research in this area.
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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 | 0.012 | 0.034 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.033 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".