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Kaplan Webb
Kaplan Webb

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Loss in thermotolerance in antibiotic-resistant Acinetobacter baumannii.

d a timely entry to CR may yield greater improvements in VO2peak among individuals with PAD.
This study assessed the feasibility, tolerability, safety, and potential efficacy of a novel, 6-wk, high-intensity interval training (HIIT) program for patients with intermittent claudication (IC).

Patients referred to a usual-care supervised exercise program were invited to undertake a HIIT program. All recruited patients performed a baseline cardiopulmonary exercise test (CPX) to inform their exercise prescription. HIIT involved 10, 1-min high-intensity cycling intervals interspersed with 1-min recovery intervals, performed 3 d/wk for 6 wk. Outcomes included feasibility, tolerability, safety, walking distance, and quality of life.

A total of 144 patients with IC were referred, 95 met initial eligibility criteria (66%) and 30 (32%) were recruited for HIIT, of which 15 (50%) completed. Of the recruited patients, 90% were on optimal medical therapy and 40% had concomitant cardiac, cerebrovascular, and/or respiratory disease. Patients who completed the program attended 100% of the sessions and one seriousand inclusion/exclusion criteria now seem appropriate for this population, meaning further research to evaluate HIIT in patients with IC is warranted.
We compared the prevalence of participants with and without symptomatic peripheral artery disease (PAD) who met the goals of attaining >7000 and 10 000 steps/d, and we determined whether PAD status was significantly associated with meeting the daily step count goals before and after adjusting for demographic variables, comorbid conditions, and cardiovascular risk factors.

Participants with PAD (n = 396) and without PAD (n = 396) were assessed on their walking for 7 consecutive days with a step activity monitor.

The PAD group took significantly fewer steps/d than the non-PAD control group (6722 ± 3393 vs. 9475 ± 4110 steps/d; P < .001). Only 37.6% and 15.7% of the PAD group attained the goals of walking >7000 and 10 000 steps/d, respectively, whereas 67.9% and 37.4% of the control group attained these goals (P < .001 for each goal). Having PAD was associated with a 62% lower chance of attaining 7000 steps/d than compared with the control group (OR = 0.383; 95% CI, 0.259-0.565; P < .001), and a 55% lower chance of attaining 10 000 steps/d (OR = 0.449; 95% CI, 0.282-0.709; P < .001). Significant covariates (P < .01) included age, current smoking, diabetes, and body mass index.

Participants with symptomatic PAD had a 29% lower daily step count compared with age- and sex-matched controls, and were less likely to attain the 7000 and 10 000 steps/d goals. Additionally, participants who were least likely to meet the 7000 and 10 000 daily step count recommendations included those who were older, currently smoked, had diabetes, and had higher body mass index.
Participants with symptomatic PAD had a 29% lower daily step count compared with age- and sex-matched controls, and were less likely to attain the 7000 and 10 000 steps/d goals. Additionally, participants who were least likely to meet the 7000 and 10 000 daily step count recommendations included those who were older, currently smoked, had diabetes, and had higher body mass index.
Monitoring home exercise using accelerometry in patients with peripheral artery disease (PAD) may provide a tool to improve adherence and titration of the exercise prescription. However, methods for unbiased analysis of accelerometer data are lacking. The aim of the current post hoc analysis was to develop an automated method to analyze accelerometry output collected during home-based exercise.

Data were obtained from 54 patients with PAD enrolled in a clinical trial that included a home-based exercise intervention using diaries and an accelerometer. Peak walking time was assessed on a graded treadmill at baseline and 6 mo. In 35 randomly selected patient data sets, visual inspection of accelerometer output confirmed exercise sessions throughout the 6 mo. An algorithm was developed to detect exercise sessions and then compared with visual inspection of sessions to mitigate the heterogeneity in session intensity across the population. Identified exercise sessions were characterized on the basis of total step count and activity duration. The methodology was then applied to data sets for all 54 patients.

The ability of the algorithm to detect exercise sessions compared with visual inspection of the accelerometer output resulted in a sensitivity of 85% and specificity of 90%. Algorithm-detected exercise sessions (total) and intensity (steps/wk) were correlated with change in peak walking time (r = 0.28; r = 0.43).

An algorithm to assess data from an accelerometer successfully detected home-based exercise sessions. Algorithm-identified exercise sessions were correlated with improvements in performance after 6 mo of training in patients with PAD, supporting the effectiveness of monitored home-based exercise.
An algorithm to assess data from an accelerometer successfully detected home-based exercise sessions. Algorithm-identified exercise sessions were correlated with improvements in performance after 6 mo of training in patients with PAD, supporting the effectiveness of monitored home-based exercise.
Cardiovascular rehabilitation programs (CRPs) are effective in secondary stroke prevention, yet the enrollment rate is suboptimal. find more This study aims to identify demographic and clinical factors and patient-reported reasons for non-enrollment in a center-based outpatient CRP among patients with transient ischemic attack (TIA) or mild stroke.

This mixed-method retrospective chart review was conducted in an outpatient CRP affiliated with a tertiary care hospital in Canada from January 2009 to October 2017. A total of 621 patients with TIA or mild stroke were included. Multiple logistic regression was used to determine the relationship between demographic and clinical predictors with non-enrollment. A thematic analysis of multidisciplinary progress notes was done for the non-enrollment subgroup of patients to understand the patient-reported reasons.

The non-enrollment rate was 42%. Travel distance to CRP (OR = 1.024; 95% CI, 1.010-1.038), age (OR = 1.023; 95% CI, 1.004-1.042), and current smoking status (OR = 1.find more

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