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dc.contributor.authorTchalla, Achille E.en_US
dc.contributor.authorDufour, Alyssa B.en_US
dc.contributor.authorTravison, Thomas G.en_US
dc.contributor.authorHabtemariam, Danielen_US
dc.contributor.authorIloputaife, Ikechukwuen_US
dc.contributor.authorManor, Braden_US
dc.contributor.authorLipsitz, Lewis A.en_US
dc.date.accessioned2014-10-01T14:29:36Z
dc.date.issued2014en_US
dc.identifier.citationTchalla, Achille E., Alyssa B. Dufour, Thomas G. Travison, Daniel Habtemariam, Ikechukwu Iloputaife, Brad Manor, and Lewis A. Lipsitz. 2014. “Patterns, Predictors, and Outcomes of Falls Trajectories in Older Adults: The MOBILIZE Boston Study with 5 Years of Follow-Up.” PLoS ONE 9 (9): e106363. doi:10.1371/journal.pone.0106363. http://dx.doi.org/10.1371/journal.pone.0106363.en
dc.identifier.issn1932-6203en
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:12987416
dc.description.abstractBackground: Falls may occur as unpredictable events or in patterns indicative of potentially modifiable risks and predictive of adverse outcomes. Knowing the patterns, risks, and outcomes of falls trajectories may help clinicians plan appropriate preventive measures. We hypothesized that clinically distinct trajectories of falls progression, baseline predictors and their coincident clinical outcomes could be identified. Methods: We studied 765 community-dwelling participants in the MOBILIZE Boston Study, who were aged 70 and older and followed prospectively for falls over 5 years. Baseline demographic and clinical data were collected by questionnaire and a comprehensive clinic examination. Falls, injuries, and hospitalizations were recorded prospectively on daily calendars. Group-Based Trajectory Modeling (GBTM) was used to identify trajectories. Results: We identified 4 distinct trajectories: No Falls (30.1%), Cluster Falls (46.1%), Increasing Falls (5.8%) and Chronic Recurring Falls (18.0%). Predictors of Cluster Falls were faster gait speed (OR 1.69 (95CI, 1.50–2.56)) and fall in the past year (OR 3.52 (95CI, 2.16–6.34)). Predictors of Increasing Falls were Diabetes Mellitus (OR 4.3 (95CI, 1.4–13.3)) and Cognitive Impairment (OR 2.82 (95CI, 1.34–5.82)). Predictors of Chronic Recurring Falls were multi-morbidity (OR 2.24 (95CI, 1.60–3.16)) and fall in the past year (OR 3.82 (95CI, 2.34–6.23)). Symptoms of depression were predictive of all falls trajectories. In the Chronic Recurring Falls trajectory group the incidence rate of Hospital visits was 121 (95% CI 63–169) per 1,000 person-years; Injurious falls 172 (95% CI 111–237) per 1,000 person-years and Fractures 41 (95% CI 9–78) per 1,000 person-years. Conclusions: Falls may occur in clusters over discrete intervals in time, or as chronically increasing or recurring events that have a relatively greater risk of adverse outcomes. Patients with multiple falls, multimorbidity, and depressive symptoms should be targeted for preventive measures.en
dc.language.isoen_USen
dc.publisherPublic Library of Scienceen
dc.relation.isversionofdoi:10.1371/journal.pone.0106363en
dc.relation.hasversionhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC4153626/pdf/en
dash.licenseLAAen_US
dc.subjectMedicine and Health Sciencesen
dc.subjectClinical Medicineen
dc.subjectGeriatricsen
dc.subjectHealth Careen
dc.subjectPublic and Occupational Healthen
dc.titlePatterns, Predictors, and Outcomes of Falls Trajectories in Older Adults: The MOBILIZE Boston Study with 5 Years of Follow-Upen
dc.typeJournal Articleen_US
dc.description.versionVersion of Recorden
dc.relation.journalPLoS ONEen
dash.depositing.authorTchalla, Achille E.en_US
dc.date.available2014-10-01T14:29:36Z
dc.identifier.doi10.1371/journal.pone.0106363*
dash.contributor.affiliatedTchalla, Achille E.
dash.contributor.affiliatedDufour, Alyssa
dash.contributor.affiliatedLipsitz, Lewis
dash.contributor.affiliatedTravison, Thomas


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