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rehabilitation affect outcome?, Arch Phys Med Rehabil, 56, 375",{},{"id":24,"text":454,"url":24,"identifiers":455},"Katz S., 1968, Comprehensive out patient care in rheumatoid arthritis: A controlled study, JAMA, 206, 1249, 10.1001\u002Fjama.1968.03150060023004",{"doi":456},"10.1001\u002Fjama.1968.03150060023004",{"id":24,"text":458,"url":24,"identifiers":459},"Katz S., 1972, Effects of Continued Care: A Study of Chronic Illness in the Home",{},{"id":24,"text":461,"url":24,"identifiers":462},"Papsidero J., 1979, Chance for Change",{},{"id":24,"text":464,"url":24,"identifiers":465},"10.1093\u002Fgeronj\u002F35.2.256",{"doi":464},{"id":24,"text":467,"url":24,"identifiers":468},"10.1097\u002F00005650-198006000-00001",{"doi":467},{"id":24,"text":470,"url":24,"identifiers":471},"10.1097\u002F00005792-196605000-00003",{"doi":470},{"id":24,"text":473,"url":24,"identifiers":474},"Katz S., 1967, Long‐term course of 147 patients with fracture of the hip, Surg Gynecol Obstet, 124, 1219",{},false,{"id":477,"createTime":478,"updateTime":478,"relativeEntities":479,"slug":480,"properties":481,"entityType":137,"verifyStatus":138,"verifyTime":478,"verifyNote":139,"syncStatus":23,"languages":495,"translateLanguages":24,"viewCount":25,"primaryUrl":496,"fullTextUrl":24,"authors":497,"publicationType":163,"publisherRelationship":570,"citationCount":610,"citationInfo":611,"publishDate":624,"publishYear":625,"citationAnalyzeStatus":23,"lastCitationAnalyze":24,"indexDatabases":24,"openAccess":24,"references":626,"isForceReanalyzing":475},"5343dcc0-4a23-4768-adb2-e89845f61b3f","2024-09-19T23:57:17.143+00:00",[],"Assessing-Risk-for-the-Onset-of-Functional-Dependence-Among-Older-Adults-The-Role-of-Physical-Performance",{"mag":482,"keywords":484,"openalex":485,"abstract":487,"title":489,"pm":491,"doi":493},{"VOID":483},"2083633493",{},{"VOID":486},"W2083633493",{"EN":488},"\u003Cjats:p>\u003Cjats:bold>BACKGROUND\u003C\u002Fjats:bold>: Approximately 10% of nondisabled, community‐dwelling adults aged 75 years and older lose independence in basic activities of daily living (ADLs) each year. The purpose of this study was to evaluate whether simple tests of physical performance could identify older adults, independent in their basic ADLs, who were at increased risk for the onset of functional dependence.\u003C\u002Fjats:p>\u003Cjats:p>\u003Cjats:bold>METHODS\u003C\u002Fjats:bold>: Among a representative cohort of 1103 community‐dwelling adults aged 72 years and older, we evaluated the 664 subjects who were cognitively intact and independent in their basic ADLs at the baseline interview. All cohort members had undergone a comprehensive assessment, including a battery of qualitative and timed performance tests. The main outcome event was the onset of functional dependence, defined as a new disability in one or more of the seven basic ADLs at the 1‐year follow‐up.\u003C\u002Fjats:p>\u003Cjats:p>\u003Cjats:bold>RESULTS\u003C\u002Fjats:bold>: Functional dependence developed in 53 (9%) of the 563 subjects who had complete data at the 1‐year follow‐up. Eight of the 12 qualitative tests and all six of the timed tests were significantly associated (\u003Cjats:italic>P\u003C\u002Fjats:italic> < .05) with the onset of functional dependence. Both qualitative and timed performance tests demarcated subjects into groups at low and high risk for functional dependence. Four timed tests—chair stands, rapid gait, 360° turn, and bending over—showed a threshold phenomenon, where the rate of new dependence increased slowly with worsening performance until a critical point (or threshold) was reached, and the rate of dependence increased substantially. For timed chair stands, for example, the rates of functional dependence within quarters of worsening performance were 5.3%, 6.3%, 6.7%, and 16%. The risk of functional dependence was markedly elevated (30%‐50%) for subjects who were unable to perform the timed tests.\u003C\u002Fjats:p>\u003Cjats:p>\u003Cjats:bold>CONCLUSIONS\u003C\u002Fjats:bold>: Several simple tests of physical performance were strongly associated with the onset of functional dependence. 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examine whether preclinical disability in performance of cognitively focused instrumental activity of daily living (C‐\u003Cjats:styled-content style=\"fixed-case\">IADL\u003C\u002Fjats:styled-content>) tasks can discriminate between older adults with normal cognitive function and those with mild cognitive impairment (\u003Cjats:styled-content style=\"fixed-case\">MCI\u003C\u002Fjats:styled-content>) and, secondarily, to determine the two tasks with the strongest psychometric properties and assess their discriminative ability so as to generate diagnosis‐relevant information about cognitive changes associated with \u003Cjats:styled-content style=\"fixed-case\">MCI\u003C\u002Fjats:styled-content> and mild neurocognitive disorder according to \u003Cjats:italic>Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition\u003C\u002Fjats:italic>, criteria.\u003C\u002Fjats:p>\u003C\u002Fjats:sec>\u003Cjats:sec>\u003Cjats:title>Design\u003C\u002Fjats:title>\u003Cjats:p>Secondary analyses of cross‐sectional data from a cohort of individuals diagnosed with normal cognitive function or \u003Cjats:styled-content style=\"fixed-case\">MCI\u003C\u002Fjats:styled-content>.\u003C\u002Fjats:p>\u003C\u002Fjats:sec>\u003Cjats:sec>\u003Cjats:title>Setting\u003C\u002Fjats:title>\u003Cjats:p>\u003Cjats:styled-content style=\"fixed-case\">P\u003C\u002Fjats:styled-content>ittsburgh, \u003Cjats:styled-content style=\"fixed-case\">P\u003C\u002Fjats:styled-content>ennsylvania.\u003C\u002Fjats:p>\u003C\u002Fjats:sec>\u003Cjats:sec>\u003Cjats:title>Participants\u003C\u002Fjats:title>\u003Cjats:p>Older adults with remitted major depression (N = 157).\u003C\u002Fjats:p>\u003C\u002Fjats:sec>\u003Cjats:sec>\u003Cjats:title>Measurements\u003C\u002Fjats:title>\u003Cjats:p>Diagnosis of cognitive status was made at the \u003Cjats:styled-content style=\"fixed-case\">A\u003C\u002Fjats:styled-content>lzheimer's Disease Research Center, University of \u003Cjats:styled-content style=\"fixed-case\">P\u003C\u002Fjats:styled-content>ittsburgh. Performance on eight C‐\u003Cjats:styled-content style=\"fixed-case\">IADL\u003C\u002Fjats:styled-content>s was measured using the criterion‐referenced, observation‐based Performance Assessment of Self‐Care Skills (\u003Cjats:styled-content style=\"fixed-case\">PASS\u003C\u002Fjats:styled-content>).\u003C\u002Fjats:p>\u003C\u002Fjats:sec>\u003Cjats:sec>\u003Cjats:title>Results\u003C\u002Fjats:title>\u003Cjats:p>Ninety‐six older adults with normal cognitive function (mean age 72.5 ± 5.9) and 61 with \u003Cjats:styled-content style=\"fixed-case\">MCI\u003C\u002Fjats:styled-content> (mean age 75.5 ± 6.3) participated. The eight C‐\u003Cjats:styled-content style=\"fixed-case\">IADL\u003C\u002Fjats:styled-content>s demonstrated 81% accuracy in discriminating cognitive status (area under the receiver operating characteristic curve (\u003Cjats:styled-content style=\"fixed-case\">AUC\u003C\u002Fjats:styled-content>) = 0.81, \u003Cjats:italic>P\u003C\u002Fjats:italic> < .001). Two tasks (shopping and checkbook balancing) were the most discriminating (\u003Cjats:styled-content style=\"fixed-case\">AUC\u003C\u002Fjats:styled-content> = 0.80, \u003Cjats:italic>P\u003C\u002Fjats:italic> < .001); they demonstrated similar ability as all eight C‐\u003Cjats:styled-content style=\"fixed-case\">IADL\u003C\u002Fjats:styled-content>s in determining cognitive status. Assessing performance on these two C‐\u003Cjats:styled-content style=\"fixed-case\">IADL\u003C\u002Fjats:styled-content>s takes 10 to 15 minutes.\u003C\u002Fjats:p>\u003C\u002Fjats:sec>\u003Cjats:sec>\u003Cjats:title>Conclusion\u003C\u002Fjats:title>\u003Cjats:p>This is the first demonstration of the discriminative ability of preclinical disability to distinguish older adults with \u003Cjats:styled-content style=\"fixed-case\">MCI\u003C\u002Fjats:styled-content> from cognitively normal older adults. These findings highlight potential tasks that, when measured using the observation‐based \u003Cjats:styled-content style=\"fixed-case\">PASS\u003C\u002Fjats:styled-content>, demonstrate greater effort for individuals with \u003Cjats:styled-content style=\"fixed-case\">MCI\u003C\u002Fjats:styled-content>. These tasks may be considered when attempting to diagnose \u003Cjats:styled-content style=\"fixed-case\">MCI\u003C\u002Fjats:styled-content> or mild neurocognitive disorder in clinical practice and research.\u003C\u002Fjats:p>\u003C\u002Fjats:sec>",{"EN":1037},"Can Performance on Daily Activities Discriminate Between Older Adults with Normal Cognitive Function and Those with Mild Cognitive Impairment?",{"VOID":1039},"24890517",{"VOID":1041},"10.1111\u002Fjgs.12878","2024-12-03T23:38:51.024+00:00",[141],"https:\u002F\u002Fagsjournals.onlinelibrary.wiley.com\u002Fdoi\u002F10.1111\u002Fjgs.12878",[1046,1068,1090,1107,1124,1141,1158,1180],{"id":1047,"sortIndex":46,"researcher":24,"roles":1048,"affiliations":1049,"properties":1061},"71425c77-66dc-43dd-b6a4-ec2b6834f0fd",[],[1050],{"id":1051,"sortIndex":25,"affiliation":1052,"properties":24},"7e689e7c-d8ec-42ac-9fed-bdf5b631918f",{"id":1053,"createTime":1054,"updateTime":1055,"relativeEntities":1056,"slug":1057,"properties":1058,"entityType":45,"verifyStatus":23,"verifyTime":24,"verifyNote":24,"syncStatus":23,"languages":24,"translateLanguages":24,"viewCount":25},"2a8dc125-cdf7-446a-9b6c-fc145bd251d2","2024-01-11T07:33:55.572+00:00","2024-12-03T23:38:51.078+00:00",[],"Department-of-Occupational-Therapy-University-of-Pittsburgh-Pittsburgh-Pennsylvania",{"title":1059},{"VI":1060},"Department of Occupational Therapy, University of Pittsburgh, Pittsburgh, Pennsylvania",{"openalex":1062,"orcid":1064,"title":1066},{"VOID":1063},"A5103002897",{"VOID":1065},"https:\u002F\u002Forcid.org\u002F0000-0002-6892-8230",{"EN":1067},"Margo B. 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Chem, 39, 561, 10.1093\u002Fclinchem\u002F39.4.561",{"doi":1314},"10.1093\u002Fclinchem\u002F39.4.561",{"id":24,"text":1316,"url":24,"identifiers":1317},"10.1002\u002F0471722146",{"doi":1316},{"id":24,"text":1319,"url":24,"identifiers":1320},"10.1001\u002Farchneur.60.12.1777",{"doi":1319},{"id":24,"text":1322,"url":24,"identifiers":1323},"10.1136\u002Fjnnp.71.4.441",{"doi":1322},{"id":24,"text":1325,"url":24,"identifiers":1326},"Royall DR, 2013, The default mode network may be the key substrate of depressive symptom‐related cognitive changes, J Alzheimers Dis, 34, 547, 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develop and validate a model estimating the survival time of hospitalized persons aged 80 years and older.\u003C\u002Fjats:p>\u003Cjats:p>\u003Cjats:bold>DESIGN:\u003C\u002Fjats:bold>A prospective cohort study with mortality follow‐up using the National Death Index.\u003C\u002Fjats:p>\u003Cjats:p>\u003Cjats:bold>SETTING:\u003C\u002Fjats:bold>Four teaching hospitals in the US.\u003C\u002Fjats:p>\u003Cjats:p>\u003Cjats:bold>PARTICIPANTS:\u003C\u002Fjats:bold>Hospitalized patients enrolled between January 1993 and November 1994 in the Hospitalized Elderly Longitudinal Project (HELP). Patients were excluded if their length of hospital stay was 48 hours or less or if admitted electively for planned surgery.\u003C\u002Fjats:p>\u003Cjats:p>\u003Cjats:bold>MEASUREMENTS:\u003C\u002Fjats:bold>A log‐normal model of survival time up to 711 days was developed with the following variables: patient demographics, disease category, nursing home residence, severity of physiologic imbalance, chart documentation of weight loss, current quality of life, exercise capacity, and functional status. We assessed whether model accuracy could be improved by including symptoms of depression or history of recent fall, serum albumin, physician's subjective estimate of prognosis, and physician and patient preferences for general approach to care.\u003C\u002Fjats:p>\u003Cjats:p>\u003Cjats:bold>RESULTS:\u003C\u002Fjats:bold>A total of 1266 patients were enrolled over a 10‐month period, (median age 84.9, 61% female, 68% with one or more dependency), and 505 (40%) died during an average follow‐up of more than 2 years. Important prognostic factors included the Acute Physiology Score of APACHE III collected on the third hospital day, modified Glasgow coma score, major diagnosis (ICU categories together, congestive heart failure, cancer, orthopedic, and all other), age, activities of daily living, exercise capacity, chart documentation of weight loss, and global quality of life. The Somers' Dxy for a model including these factors was 0.48 (equivalent to a receiver‐operator curve (ROC) area of 0.74, suggesting good discrimination). Bootstrap estimation indicated good model validation (corrected Dxy of 0.46, ROC of 0.73). A nomogram based on this log‐normal model is presented to facilitate calculation of median survival time and 10th and 90th percentile of survival time.\u003C\u002Fjats:p>\u003Cjats:p>A count of geriatric syndromes or comorbidities did not add explanatory power to the model, nor did the hospital of patient recruitment, depression, or the patient preferences for general approach to care. The physician's perception of the patient's preferences and the physician's subjective estimate of the patient's prognosis improved the estimate of survival time significantly.\u003C\u002Fjats:p>\u003Cjats:p>\u003Cjats:bold>CONCLUSIONS:\u003C\u002Fjats:bold>Accurate estimation of length of life for older hospitalized persons may be calculated using a limited amount of clinical information available from the medical chart plus a brief interview with the patient or surrogate. The accuracy of this model can be improved by including measures of the physician's perception of the patient's preferences for care and the physician's subjective estimate of prognosis.\u003C\u002Fjats:p>",{"EN":1348},"Prediction of Survival for Older Hospitalized Patients: The HELP Survival Model",{"VOID":1350},"10809452",{"VOID":1352},"10.1111\u002Fj.1532-5415.2000.tb03126.x","2024-10-10T23:29:22.708+00:00",[141],"https:\u002F\u002Fagsjournals.onlinelibrary.wiley.com\u002Fdoi\u002F10.1111\u002Fj.1532-5415.2000.tb03126.x",[1357,1379,1401,1423,1440,1472,1491,1506,1527,1542,1559],{"id":1358,"sortIndex":537,"researcher":24,"roles":1359,"affiliations":1360,"properties":1372},"ca5d0747-53ee-4d6c-9d89-55670a8282ff",[],[1361],{"id":1362,"sortIndex":25,"affiliation":1363,"properties":24},"5c4a1c86-c6d8-4e9c-b03b-b581d3716301",{"id":1364,"createTime":1365,"updateTime":1366,"relativeEntities":1367,"slug":1368,"properties":1369,"entityType":45,"verifyStatus":23,"verifyTime":24,"verifyNote":24,"syncStatus":23,"languages":24,"translateLanguages":24,"viewCount":25},"5de628bd-4c0a-486c-bd06-270ac7f6b9ae","2023-11-25T01:49:22.299+00:00","2024-10-10T23:29:22.737+00:00",[],"University-of-Virginia-School-of-Medicine-Charlottesville-Virginia",{"title":1370},{"VI":1371},"University of Virginia, School of Medicine, Charlottesville Virginia",{"openalex":1373,"orcid":1375,"title":1377},{"VOID":1374},"A5042352003",{"VOID":1376},"https:\u002F\u002Forcid.org\u002F0000-0002-8271-5493",{"EN":1378},"Frank E. 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The mortality rate was significantly greater among those taking some form of medication for sleep (\u003Cjats:italic>n\u003C\u002Fjats:italic> = 208) than for those not taking sleep medication (\u003Cjats:italic>n\u003C\u002Fjats:italic> = 812; chi‐square = 4.91, \u003Cjats:italic>df\u003C\u002Fjats:italic> = 1, \u003Cjats:italic>P\u003C\u002Fjats:italic> = 0.027). When sleep medication users were categorized as either “hypnotic users” (ie, users of medication with recognized hypnotic or sedative actions) or “other users” (including analgesics and other over‐the‐counter medicines), only “other users” showed significant excess mortality (chi‐square = 7.27, \u003Cjats:italic>df\u003C\u002Fjats:italic> = 1, \u003Cjats:italic>P\u003C\u002Fjats:italic> = 0.007). Logistic regression showed that “other users” were 2.5 times more likely to die than “non‐users” even when gender, health risk, and usual sleep duration were controlled. There were no significant relationships between mortality and subjective insomnia or reported duration of sleep.\u003C\u002Fjats:p>\u003C\u002Fjats:sec>\u003Cjats:sec>\u003Cjats:title>Conclusions\u003C\u002Fjats:title>\u003Cjats:p>Earlier reported relationships between excess mortality and use of medication for sleep are replicated in this study. Among elderly people, however, this relationship does not derive from the pharmacological characteristics of prescription hypnotics. Rather, it appears that reported self‐medication to promote sleep, using a variety of non‐sedative products, provides an epidemiological “marker” for a group within which levels of morbidity and mortality are particularly high. Excess mortality associated with very short or long sleep duration was not replicated in this study. 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During the 10‐year follow‐up, 1,208 died.\u003C\u002Fjats:p>\u003Cjats:p>\u003Cjats:bold>MEASUREMENTS: \u003C\u002Fjats:bold> Self‐reported health information was used to construct a frailty index (Frailty Index) as a proportion of deficits accumulated in individuals. The main outcome measure was mortality.\u003C\u002Fjats:p>\u003Cjats:p>\u003Cjats:bold>RESULTS: \u003C\u002Fjats:bold> The prevalence of frailty increased with age in men and women (correlation coefficient=0.955–0.994, \u003Cjats:italic>P\u003C\u002Fjats:italic><.001). The Frailty Index estimated that 622 (22.7%, 95% confidence interval (CI)=21.0–24.4%) of the sample was frail. Frailty was more common in women (25.3%, 95% CI=23.2–27.5%) than in men (18.6%, 95% CI=15.9–21.3%). For those aged 85 and older, the Frailty Index identified 39.1% (95% CI=31.3–46.9%) of men as frail, compared with 45.1% (95% CI=39.7–50.5%) of women. 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