| Literature DB >> 35149569 |
Tichawona Chinzowu1, Sandipan Roy2, Prasad S Nishtala3.
Abstract
INTRODUCTION: Older adults (aged 65 years and above) constitute the fastest growing population cohort in the western world. There is increasing evidence that the burden of infections disproportionately affects this cohort of older adults and hence this vulnerable population is frequently exposed to antimicrobials. There is currently no systematic review summarising the evidence for risk of organ injury following antimicrobial exposure among older adults. This protocol will outline how we will conduct a systematic review and meta-analyses to examine the relationship between antimicrobial exposure and organ injury in older adults. METHODS AND ANALYSIS: We will search for PsycINFO, PubMed and EMBASE databases for relevant articles using MeSH terms where applicable. After removing duplicates, articles will be screened for inclusion into or exclusion from the study by two reviewers. Title and abstract screening will be done first, followed by full-text screening. The Newcastle-Ottawa scale will be used to assess the risk of bias for cohort and case control studies, and the Cochrane collaboration's risk of bias tool will be used for randomised control trials. We will explore the potential sources of heterogeneity and bias using funnel and forest plots of the included studies. ETHICS AND DISSEMINATION: During the conduct of the review, ethical principles will be observed to ensure integrity. Any potential conflicts of interests will be declared, all contributors acknowledged and no plagiarised material will be included in the review.The systematic review and meta-analysis will be submitted for publication in a peer-reviewed journal in geriatrics. The findings will also be presented at international conferences in geriatrics or pharmacoepidemiology. The results will be communicated to patient and public engagement networks supported by the NHS Research and Development. PROSPERO REGISTRATION NUMBER: This protocol is registered in the PROSPERO database (registration number CRD42020152621). © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.Entities:
Keywords: epidemiology; geriatric medicine; infectious diseases
Mesh:
Substances:
Year: 2022 PMID: 35149569 PMCID: PMC8845168 DOI: 10.1136/bmjopen-2021-055210
Source DB: PubMed Journal: BMJ Open ISSN: 2044-6055 Impact factor: 2.692
Figure 1Process flow chart for full-text inclusion of studies into the systematic review from studies selected from the title and abstract screening process.
| Type of bias | Type studies | Low/High risk |
| Selection bias | Controlled studies |
Low risk if random sequence generation allocation concealment used |
| observational studies |
Low risk if patients enrolled as consecutively observed based on the pre-existing protocol Low risk if numbers and reasons for exclusions were reported High risk when the association between exposure and outcome is different for study participants compared with non-participants | |
| Performance bias | Controlled studies |
High risk if study personnel were not blinded as to which intervention the elderly patient has received |
| Observational studies |
High risk if there are systematic differences in the treatment of participants | |
| Detection bias | Controlled studies |
High risk if personnel evaluating outcomes were not blinded |
| Observational studies |
High risk if there were systematic differences in outcomes assessment among comparison groups High risk if the measurement of exposure is flawed, for example, recall bias in case–control studies | |
| Reporting bias | Controlled studies |
High risk if reporting of outcomes is not prespecified as of interest to the review |
| Observational studies |
High risk if there are systematic differences between reported and unreported findings | |
| Confounding | Controlled studies |
Low risk if allocation was balanced between groups by for example, matching, stratification, etc |
| Observational studies |
High risk, but can be mitigated using matching by propensity scores, etc High risk if there is a failure to adjust for important confounders in the statistical analysis. |