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Prevalence of clinically manifested drug interactions in hospitalized patients: A systematic review and meta-analysis.

ABSTRACT: AIMS:This review aims to determine the prevalence of clinically manifested drug-drug interactions (DDIs) in hospitalized patients. METHODS:PubMed, Scopus, Embase, Web of Science, and Lilacs databases were used to identify articles published before June 2019 that met specific inclusion criteria. The search strategy was developed using both controlled and uncontrolled vocabulary related to the following domains: "drug interactions," "clinically relevant," and "hospital." In this review, we discuss original observational studies that detected DDIs in the hospital setting, studies that provided enough data to allow us to calculate the prevalence of clinically manifested DDIs, and studies that described the drugs prescribed or provided DDI adverse reaction reports, published in either English, Portuguese, or Spanish. RESULTS:From the initial 5,999 articles identified, 10 met the inclusion criteria. The pooled prevalence of clinically manifested DDIs was 9.2% (CI 95% 4.0-19.7). The mean number of medications per patient reported in six studies ranged from 4.0 to 9.0, with an overall average of 5.47 ± 1.77 drugs per patient. The quality of the included studies was moderate. The main methods used to identify clinically manifested DDIs were evaluating medical records and ward visits (n = 7). Micromedex® (27.7%) and Lexi-Comp® (27.7%) online reference databases were commonly used to detect DDIs and none of the studies evaluated used more than one database for this purpose. CONCLUSIONS:This systematic review showed that, despite the significant prevalence of potential DDIs reported in the literature, less than one in ten patients were exposed to a clinically manifested drug interaction. The use of causality tools to identify clinically manifested DDIs as well as clinical adoption of DDI lists based on actual adverse outcomes that can be identified through the implementation of real DDI notification systems is recommended to reduce the incidence of alert fatigue, enhance decision-making for DDI prevention or resolution, and, consequently, contribute to patient safety.

SUBMITTER: Gonzaga de Andrade Santos TN

PROVIDER: S-EPMC7329110 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Prevalence of clinically manifested drug interactions in hospitalized patients: A systematic review and meta-analysis.

Gonzaga de Andrade Santos Tâmara Natasha TN Mendonça da Cruz Macieira Givalda G Cardoso Sodré Alves Bárbara Manuella BM Onozato Thelma T Cunha Cardoso Geovanna G Ferreira Nascimento Mônica Thaís MT Saquete Martins-Filho Paulo Ricardo PR Pereira de Lyra Divaldo D Oliveira Filho Alfredo Dias de AD

PloS one 20200701 7

<h4>Aims</h4>This review aims to determine the prevalence of clinically manifested drug-drug interactions (DDIs) in hospitalized patients.<h4>Methods</h4>PubMed, Scopus, Embase, Web of Science, and Lilacs databases were used to identify articles published before June 2019 that met specific inclusion criteria. The search strategy was developed using both controlled and uncontrolled vocabulary related to the following domains: "drug interactions," "clinically relevant," and "hospital." In this rev ...[more]

PMID: 32609783

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Project description:Drug-drug interactions (DDIs) can lead to medication-related harm, and the older population is at greatest risk. We conducted a systematic review and meta-analysis to estimate DDI prevalence and identify common DDIs in older community-dwelling adults. PubMed and EMBASE were searched for observational studies published between 01/01/2010 and 10/05/2021 reporting DDI prevalence in community-dwelling individuals aged ≥ 65 years. Nursing home and inpatient hospital studies were excluded. Study quality was assessed using the Joanna Briggs Institute critical appraisal tool. Meta-analysis was performed using a random-effects model with logit transformation. Heterogeneity was evaluated using Cochran's Q and I2. DDI prevalence and 95% confidence intervals (CIs) are presented. All analyses were performed in R (version 4.1.2). There were 5144 unique articles identified. Thirty-three studies involving 17,011,291 community-dwelling individuals aged ≥ 65 years met inclusion criteria. Thirty-one studies reported DDI prevalence at the study-participant level, estimates ranged from 0.8% to 90.6%. The pooled DDI prevalence was 28.8% (95% CI 19.3-40.7), with significant heterogeneity (p < 0.10; I2 = 100%; tau2 = 2.13) largely explained by the different DDI identification methods. Therefore, 26 studies were qualitatively synthesised and seven studies were eligible for separate meta-analyses. In a meta-analysis of three studies (N = 1122) using Micromedex®, pooled DDI prevalence was 57.8% (95% CI 52.2-63.2; I2 = 69.6%, p < 0.01). In a meta-analysis of two studies (N = 809,113) using Lexi-Interact®, pooled DDI prevalence was 30.3% (95% CI 30.2-30.4; I2 = 6.8%). In a meta-analysis of two studies (N = 947) using the 2015 American Geriatrics Society Beers criteria®, pooled DDI prevalence was 16.6% (95% CI 5.6-40.2; I2 = 97.5%, p < 0.01). Common DDIs frequently involved cardiovascular drugs, including ACE inhibitor-potassium-sparing diuretic; amiodarone-digoxin; and amiodarone-warfarin. DDIs are prevalent among older community-dwelling individuals; however, the methodology used to estimate these events varies considerably. A standardised methodology is needed to allow meaningful measurement and comparison of DDI prevalence.

Project description:BackgroundClostridium difficile is the leading cause of infectious diarrhea that develops in patients after hospitalization during antibiotic administration. It has also become a big issue in community-acquired diarrhea. The emergence of hypervirulent strains of C. difficile poses a major problem in hospital-associated diarrhea outbreaks and it is difficult to treat. The antimicrobial resistance in C. difficile has worsened due to the inappropriate use of broad-spectrum antibiotics including cephalosporins, clindamycin, tetracycline, and fluoroquinolones together with the emergence of hypervirulent strains.ObjectiveTo estimate the pooled prevalence and antimicrobial resistance pattern of C. difficile derived from hospitalized diarrheal patients, a systematic review and meta-analysis was performed.MethodsPreferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline was followed to review published studies conducted. We searched bibliographic databases from PubMed, Scopus, Google Scholar, and Cochrane Library for studies on the prevalence and antimicrobial susceptibility testing on C. difficile. The weighted pooled prevalence and resistance for each antimicrobial agent was calculated using a random-effects model. A funnel plot and Egger's regression test were used to see publication bias.ResultsA total of 15 studies were included. Ten articles for prevalence study and 5 additional studies for antimicrobial susceptibility testing of C. difficile were included. A total of 1967/7852 (25%) C. difficile were isolated from 10 included studies for prevalence study. The overall weighted pooled proportion (WPP) of C. difficile was 30% (95% CI: 10.0-49.0; p<0.001). The analysis showed substantial heterogeneity among studies (Cochran's test = 7038.73, I2 = 99.87%; p<0.001). The weighed pooled antimicrobial resistance (WPR) were: vancomycin 3%(95% CI: 1.0-4.0, p<0.001); metronidazole 5%(95% CI: 3.0-7.0, p<0.001); clindamycin 61%(95% CI: 52.0-69.0, p<0.001); moxifloxacin 42%(95% CI: 29-54, p<0.001); tetracycline 35%(95% CI: 22-49, p<0.001); erythromycin 61%(95% CI: 48-75, p<0.001) and ciprofloxacin 64%(95% CI: 48-80; p< 0.001) using the random effect model.ConclusionsA higher weighted pooled prevalence of C. difficile was observed. It needs a great deal of attention to decrease the prevailing prevalence. The resistance of C. difficile to metronidazole and vancomycin was low compared to other drugs used to treat C. difficile infection. Periodic antimicrobial resistance monitoring is vital for appropriate therapy of C. difficile infection.

Project description:BACKGROUND:Management of co-infections including cryptococcal meningitis, tuberculosis and other opportunistic infections in persons living with HIV can lead to complex polypharmacotherapy and increased susceptibility to drug-drug interactions (DDIs). Here we characterize the frequency and types of potential DDIs (pDDIs) in hospitalized HIV patients presenting with suspected cryptococcal or tuberculous meningitis. METHODS:In a retrospective review of three cryptococcal meningitis trials between 2010 and 2017 in Kampala, Uganda, medications received over hospitalization were documented and pDDI events were assessed. IBM Micromedex DRUGDEX® online drug reference system was used to identify and describe potential interactions as either contraindicated, major, moderate or minor. For antiretroviral DDIs, the Liverpool Drug Interactions Checker from the University of Liverpool was also used to further describe interactions observed. RESULTS:In 1074 patients with suspected meningitis, pDDIs were present in 959 (overall prevalence?=?89.3%) during the analyzed 30?day window. In total, 278 unique interacting drug pairs were identified resulting in 4582 pDDI events. Of all patients included in this study there was a mean frequency of 4.27 pDDIs per patient. Of the 4582 pDDI events, 11.3% contraindicated, 66.4% major, 17.4% moderate and 5% minor pDDIs were observed. Among all pDDIs identified, the most prevalent drugs implicated were fluconazole (58.4%), co-trimoxazole (25.7%), efavirenz (15.6%) and rifampin (10.2%). Twenty-one percent of the contraindicated pDDIs and 27% of the major ones involved an antiretroviral drug. Increased likelihood of QT interval prolongation was the most frequent potential clinical outcome. Dissonance in drug interaction checkers was noted requiring clinicians to consult more than one database in making clinical decisions about drug combinations. CONCLUSIONS:The overall prevalence of pDDIs in this population is high. An understanding of drug combinations likely to result in undesired clinical outcomes, such as QT interval prolongation, is paramount. This is especially important in resource limited settings where availability of therapeutic drug monitoring and laboratory follow-up are inconsistent. Adequate quantification of the increased likelihood of adverse clinical outcomes from multiple drug-drug interactions of the same kind in a single patient is needed to aid clinical decisions in this setting.

Project description:Although most patients recover from COVID-19, it has been linked to cardiac, pulmonary, and neurologic complications. Despite not having formal criteria for its diagnosis, COVID-19 associated cardiomyopathy has been observed in several studies through biomarkers and imaging. This study aims to estimate the proportion of COVID-19 patients with cardiac abnormalities and to determine the association between the cardiac abnormalities in COVID-19 patients and disease severity and mortality. Observational studies published from December 1, 2019 to September 30, 2020 were obtained from electronic databases (PubMed, Embase, Cochrane Library, CNKI) and preprint servers (medRxiv, bioRxiv, ChinaXiv). Studies that have data on prevalence were included in the calculation of the pooled prevalence, while studies with comparison group were included in the calculation of the odds ratio. If multiple tests were done in the same study yielding different prevalence values, the largest one was used as the measure of prevalence of that particular study. Metafor using R software package version 4.0.2 was used for the meta-analysis. A total of 400 records were retrieved from database search, with 24 articles included in the final analysis. Pooled prevalence of cardiac abnormalities in 20 studies was calculated to be 0.31 [95% Confidence Intervals (CI) of (0.23; 0.41)], with statistically significant heterogeneity (percentage of variation or I-squared statistic I2 = 97%, p < 0.01). Pooled analysis of 19 studies showed an overall odds ratio (OR) of 6.87 [95%-CI (3.92; 12.05)] for cardiac abnormalities associated with disease severity and mortality, with statistically significant heterogeneity (I2 = 85%, between-study variance or tau-squared statistic τ2 = 1.1485, p < 0.01). Due to the high uncertainty in the pooled prevalence of cardiac abnormalities and the unquantifiable magnitude of risk (although an increased risk is certain) for severity or mortality among COVID-19 patients, much more long-term prognostic studies are needed to check for the long-term complications of COVID-19 and formalize definitive criteria of "COVID-19 associated cardiomyopathy".

Project description:Rationale & objectiveCoronavirus disease 2019 (COVID-19) may be associated with high rates of acute kidney injury (AKI) and kidney replacement therapy (KRT), potentially overwhelming health care resources. Our objective was to determine the pooled prevalence of AKI and KRT among hospitalized patients with COVID-19.Study designSystematic review and meta-analysis.Data sourcesMEDLINE, Embase, the Cochrane Library, and a registry of preprinted studies, published up to October 14, 2020.Study selectionEligible studies reported the prevalence of AKI in hospitalized patients with COVID-19 according to the Kidney Disease: Improving Global Outcomes (KDIGO) definition.Data extraction & synthesisWe extracted data on patient characteristics, the proportion of patients developing AKI and commencing KRT, important clinical outcomes (discharge from hospital, ongoing hospitalization, and death), and risk of bias.Outcomes & measuresWe calculated the pooled prevalence of AKI and receipt of KRT along with 95% CIs using a random-effects model. We performed subgroup analysis based on admission to an intensive care unit (ICU).ResultsOf 2,711 records reviewed, we included 53 published and 1 preprint study in the analysis, which comprised 30,657 hospitalized patients with COVID-19. Data for AKI were available for 30,639 patients (n = 54 studies), and receipt of KRT, for 27,525 patients (n = 48 studies). The pooled prevalence of AKI was 28% (95% CI, 22%-34%; I 2 = 99%), and the pooled prevalence of KRT was 9% (95% CI, 7%-11%; I 2 = 97%). The pooled prevalence of AKI among patients admitted to the ICU was 46% (95% CI, 35%-57%; I 2 = 99%), and 19% of all ICU patients with COVID-19 (95% CI, 15%-22%; I 2 = 88%) commenced KRT.LimitationsThere was significant heterogeneity among the included studies, which remained unaccounted for in subgroup analysis.ConclusionsAKI complicated the course of nearly 1 in 3 patients hospitalized with COVID-19. The risk for AKI was higher in critically ill patients, with a substantial number receiving KRT at rates higher than the general ICU population. Because COVID-19 will be a public health threat for the foreseeable future, these estimates should help guide KRT resource planning.

Dataset Information

Prevalence of clinically manifested drug interactions in hospitalized patients: A systematic review and meta-analysis.

Publications

Prevalence of clinically manifested drug interactions in hospitalized patients: A systematic review and meta-analysis.

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