26 research outputs found

    Detection of delirium by nurses among long-term care residents with dementia

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    <p>Abstract</p> <p>Background</p> <p>Delirium is a prevalent problem in long-term care (LTC) facilities where advanced age and cognitive impairment represent two important risk factors for this condition. Delirium is associated with numerous negative outcomes including increased morbidity and mortality. Despite its clinical importance, delirium often goes unrecognized by nurses. Although rates of nurse-detected delirium have been studied among hospitalized older patients, this issue has been largely neglected among demented older residents in LTC settings. The goals of this study were to determine detection rates of delirium and delirium symptoms by nurses among elderly residents with dementia and to identify factors associated with undetected cases of delirium.</p> <p>Methods</p> <p>In this prospective study (N = 156), nurse ratings of delirium were compared to researcher ratings of delirium. This procedure was repeated for 6 delirium symptoms. Sensitivity, specificity, positive and negative predictive values were computed. Logistic regressions were conducted to identify factors associated with delirium that is undetected by nurses.</p> <p>Results</p> <p>Despite a high prevalence of delirium in this cohort (71.5%), nurses were able to detect the delirium in only a minority of cases (13%). Of the 134 residents not identified by nurses as having delirium, only 29.9% of them were correctly classified. Detection rates for the 6 delirium symptoms varied between 39.1% and 58.1%, indicating an overall under-recognition of symptoms of delirium. Only the age of the residents (≥ 85 yrs) was associated with undetected delirium (OR: 4.1; 90% CI: [1.5–11.0]).</p> <p>Conclusion</p> <p>Detection of delirium is a major issue for nurses that clearly needs to be addressed. Strategies to improve recognition of delirium could result in a reduction of adverse outcomes for this very vulnerable population.</p

    3-year cumulative incidence of cardiovascular events according to anti-hypertensive intensity in older adults with hypertension.

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    <p>Legend: The cumulative incidence was estimated using a subdistribution hazards regression model, with the cardiovascular events as the primary outcome and mortality among participants with no primary CV event during follow-up as the competing outcome. Follow-up period was three years. Anti-hypertensive intensity was trichotomized into no anti-hypertensive use, moderate anti-hypertensive intensity, and high anti-hypertensive intensity as defined in the <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0090733#s2" target="_blank">Methods</a>. The variables included in the propensity score are noted in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0090733#pone-0090733-t001" target="_blank">Table 1</a>. The model adjusted for year of study entry, propensity score as a continuous variable, age, gender, prior myocardial infarction, prior stroke, heart failure, diabetes atrial fibrillation, valvular heart disease, renal disease, current smoking status, statin use, difficulty walking, obesity, depression, cognitive impairment, number of non-antihypertensive medications, self-perceived health, blood pressure taken within past six month. Vertical line (Y Axis) represents cumulative incidence probability (%); horizontal line (X Axis) represents time in days from study entry to onset of first cardiovascular event.</p

    Effect of Antihypertensive Medication Intensity on Cardiovascular Events and Mortality in Older Adults with Hypertension.

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    <p>Abbreviations: CV, cardiovascular; HF, heart failure.</p>a<p>Hazard ratios and 95% confidence intervals were estimated for moderate and high antihypertensive intensity group, in reference to the no anti-hypertensive group.</p>b<p>The outcome was occurrence during follow-up of acute coronary syndrome (MI, unstable angina, or cardiac revascularization), stroke, or hospitalization for heart failure. The variables included in the propensity score are noted in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0090733#pone-0090733-t001" target="_blank">Table 1</a>. For the full cohort analyses, the models included year of study entry, age, gender, race, prior myocardial infarction, prior stroke, prior hospitalization for heart failure, diabetes, atrial fibrillation, valvular heart disease, renal disease, statin use, current smoking status, difficulty walking, obesity, depression, cognitive impairment, number of non-antihypertensive medications, self-perceived health, blood pressure taken within past six month) and a continuous variable for propensity score. For the PS-matched cohort analyses, the models included the same 19 covariates with the propensity score matched sets as a clustering factor.</p>c<p>The outcome was death during follow-up among all cohort members. The model adjusted for the same covariates as for the cardiovascular event model.</p>d<p>The outcome was death among the subgroup of participants who experienced a CV event (coronary event, stroke, or hospitalization for heart failure) any time during follow-up. See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0090733#s2" target="_blank">Methods</a> for analytical details. PS-matched analyses not performed due to small sample size.</p

    Frequency of Cardiovascular Events and Mortality in Older Adults with Hypertension According to Anti-hypertensive Medication Intensity.

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    <p>Abbreviations: CV, cardiovascular; MI, myocardial infarction.</p>a<p>The number and percent of participants who experienced at least one CV event during follow-up.</p>b<p>The composite CV outcome included any of coronary event, stroke, and hospitalization for heart failure during follow-up. Participants could experience more than one CV event. A total of 1247 participants (25.1%) experienced 2123 cardiovascular events. A total of 407 participants (8.2%) suffered 466 coronary events while 270 participants (5.4%) experienced 303 strokes. A total of 732 participants (14.8%) had at least one hospitalization for heart failure including 582 (11.7%) with one, 180 (3.6%) with two, and 114 (2.3%) with three or more hospitalizations.</p>c<p>Coronary event included MI, unstable angina, and cardiac revascularization.</p>d<p>The sample size is smaller for heart failure than the other outcomes because the prebaseline and year 1 claims were used to establish a diagnosis of heart failure; follow-up for heart failure was therefore two, rather than three, years.</p>e<p>Deaths among participants who experienced a CV event (any of coronary event, stroke, or hospitalization for heart failure) anytime during follow-up. The denominator is the number of persons who experienced a CV event.</p

    Baseline Characteristics by Antihypertensive Medication Intensity<sup>a</sup>.

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    <p>Abbreviations: BADL, basic activities of daily living; BMI, body mass index; COPD, chronic obstructive pulmonary disease; ESRD, end stage renal disease; IADL, instrumental activities of daily living; MI, myocardial infarction; PVD, peripheral vascular disease; RAS, renin angiotensin system; SD, standard deviation.</p>a<p>Members of the 2004–2007 Medicare Current Beneficiary Survey with hypertension. Anti-hypertensive medication intensity is defined in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0090733#s2" target="_blank">Methods</a>. Data are presented as number (%) unless otherwise indicated.</p>b<p>All variables were included in the propensity model.</p>c<p>The P-values in parentheses are the propensity score adjusted P-values.</p>d<p>d1 and d2 are the standardized differences between the moderate or high anti-hypertensive intensity groups, and the no hypertensive group, respectively; d2 is in parentheses. Standardized differences compare the mean differences between the comparison groups in units of the pooled standard deviations of the comparison groups, with a value of < 0.10 denoting negligible imbalance. See Statistical Analyses for details. In the full cohort before matching), 25 of the 36 PS covariates had d1 and/or d2 greater than 0.10 in contrast to 2 of 36 covariates for the PS-matched subcohort.</p
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