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Higher dietary protein, alone or in combination with physical activity (PA), may slow the loss of age-related muscle strength in older adults. We investigated the longitudinal relationship between protein intake and grip strength, and the interaction between protein intake and PA, using four longitudinal ageing cohorts. Individual participant data from 5584 older adults (52 % women; median: 75 years, IQR: 71·6, 79·0) followed for up to 8·5 years (mean: 4·9 years, SD: 2·3) from the Health ABC, NuAge, LASA and Newcastle 85+ cohorts were pooled. Baseline protein intake was assessed with food frequency questionnaires and 24-h recalls and categorized into < 0·8, 0·8–<1·0, 1·0–<1·2 and ≥ 1·2 g/kg adjusted body weight (aBW)/d. The prospective association between protein intake, its interaction with PA, and grip strength (sex- and cohort-specific) was determined using joint models (hierarchical linear mixed effects and a link function for Cox proportional hazards models). Grip strength declined on average by 0·018 SD (95 % CI: –0·026, –0·006) every year. No associations were found between protein intake, measured at baseline, and grip strength, measured prospectively, or rate of decline of grip strength in models adjusted for sociodemographic, anthropometric, lifestyle and health variables (e.g., protein intake ≥ 1·2 v· < 0·8 g/kg aBW/d: β = –0·003, 95 % CI: –0·014, 0·005 SD per year). There also was no evidence of an interaction between protein intake and PA. We failed to find evidence in this study to support the hypothesis that higher protein intake, alone or in combination with higher PA, slowed the rate of grip strength decline in older adults.
Older adults are often underrepresented in clinical research, even though older adults are major consumers of novel therapies. We present major themes and recommendations from the 2021 "Inclusion of Older Adults in Clinical Research" Workshop, convened by the Clinical and Translational Science Award (CTSA) Inclusion of Older Adults as a Model for Special Populations Workgroup and the Research Centers Collaborative Network (RCCN). The goal of this workshop was to develop strategies to assist the research community in increasing the inclusion of older adults in clinical research. Major identified barriers include historical lack of federal guidelines, ageist biases and stereotypes, and lack of recruitment and retention techniques or infrastructure focused on older adults. Three key recommendations emerged: 1) engaging with the policymaking process to further promote inclusion; 2) using the CTSA Workgroup Presentation Materials Library and other resources to overcome ageism, and 3) building institutional capacity to support age inclusion.
The role that vitamin D plays in pulmonary function remains uncertain. Epidemiological studies reported mixed findings for serum 25-hydroxyvitamin D (25(OH)D)–pulmonary function association. We conducted the largest cross-sectional meta-analysis of the 25(OH)D–pulmonary function association to date, based on nine European ancestry (EA) cohorts (n 22 838) and five African ancestry (AA) cohorts (n 4290) in the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium. Data were analysed using linear models by cohort and ancestry. Effect modification by smoking status (current/former/never) was tested. Results were combined using fixed-effects meta-analysis. Mean serum 25(OH)D was 68 (sd 29) nmol/l for EA and 49 (sd 21) nmol/l for AA. For each 1 nmol/l higher 25(OH)D, forced expiratory volume in the 1st second (FEV1) was higher by 1·1 ml in EA (95 % CI 0·9, 1·3; P<0·0001) and 1·8 ml (95 % CI 1·1, 2·5; P<0·0001) in AA (Prace difference=0·06), and forced vital capacity (FVC) was higher by 1·3 ml in EA (95 % CI 1·0, 1·6; P<0·0001) and 1·5 ml (95 % CI 0·8, 2·3; P=0·0001) in AA (Prace difference=0·56). Among EA, the 25(OH)D–FVC association was stronger in smokers: per 1 nmol/l higher 25(OH)D, FVC was higher by 1·7 ml (95 % CI 1·1, 2·3) for current smokers and 1·7 ml (95 % CI 1·2, 2·1) for former smokers, compared with 0·8 ml (95 % CI 0·4, 1·2) for never smokers. In summary, the 25(OH)D associations with FEV1 and FVC were positive in both ancestries. In EA, a stronger association was observed for smokers compared with never smokers, which supports the importance of vitamin D in vulnerable populations.
Since its inception, the Society for Healthcare Epidemiology of America (SHEA) has promoted research into prevention of adverse events in hospitals. In 1995, SHEA made this mission concrete by initiating a collaborative research project with the Joint Commission on the Accreditation of Health Care Organization (now known as the Joint Commission). In the early 1990s, the Joint Commission was implementing its “Agenda for Change” and associated Indicator Monitoring System. At the time, there were numerous competing measurement systems that used different definitions, all aimed at measuring the quality of patient care, and many had indicators measuring the incidence of hospital-acquired infections. Some of these indicators used administrative data, such as International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) codes, to measure adverse events.
Bloodstream infection (BSI) rates are used as comparative clinical performance indicators; however, variations in definitions and data-collection approaches make it difficult to compare and interpret rates. To determine the extent to which variation in indicator specifications affected infection rates and hospital performance rankings, we compared absolute rates and relative rankings of hospitals across 5 BSI indicators.
Multicenter observational study. BSI rate specifications varied by data source (clinical data, administrative data, or both), scope (hospital wide or intensive care unit specific), and inclusion/exclusion criteria. As appropriate, hospital-specific infection rates and rankings were calculated by processing data from each site according to 2-5 different specifications.
A total of 28 hospitals participating in the EPIC study.
Hospitals submitted deidentified information about all patients with BSIs from January through September 1999.
Median BSI rates for 2 indicators based on intensive care unit surveillance data ranged from 2.23 to 2.91 BSIs per 1000 central-line days. In contrast, median rates for indicators based on administrative data varied from 0.046 to 7.03 BSIs per 100 patients. Hospital-specific rates and rankings varied substantially as different specifications were applied; the rates of 8 of 10 hospitals were both greater than and less than the mean. Correlations of hospital rankings among indicator pairs were generally low (rs = 0-0.45), except when both indicators were based on intensive care unit surveillance (rs = 0.83).
Although BSI rates seem to be a logical indicator of clinical performance, the use of various indicator specifications can produce remarkably different judgments of absolute and relative performance for a given hospital. Recent national initiatives continue to mix methods for specifying BSI rates; this practice is likely to limit the usefulness of such information for comparing and improving performance.
To describe the conceptual framework and methodology of the Evaluation of Processes and Indicators in Infection Control (EPIC) study and present results of CVC insertion characteristics and organizational practices for preventing BSIs. The goal of the EPIC study was to evaluate relationships among processes of care, organizational characteristics, and the outcome of BSI.
This was a multicenter prospective observational study of variation in hospital practices related to preventing CVC-associated BSIs. Process of care information (eg, barrier use during insertions and experience of the inserting practitioner) was collected for a random sample of approximately 5 CVC insertions per month per hospital during November 1998 to December 1999. Organization demographic and practice information (eg, surveillance activities and staff and ICU nurse staffing levels) was also collected.
Medical, surgical, or medical-surgical ICUs from 55 hospitals (41 U.S. and 14 international sites).
Process information was obtained for 3,320 CVC insertions with an average of 58.2 (± 16.1) insertions per hospital. Fifty-four hospitals provided policy and practice information.
Staff spent an average of 13 hours per week in study ICU surveillance. Most patients received nontunneled, multiple lumen CVCs, of which fewer than 25% were coated with antimicrobial material. Regarding barriers, most clinicians wore masks (81.5%) and gowns (76.8%); 58.1% used large drapes. Few hospitals (18.1%) used an intravenous team to manage ICU CVCs.
Substantial variation exists in CVC insertion practice and BSI prevention activities. Understanding which practices have the greatest impact on BSI rates can help hospitals better target improvement interventions.
Hospital epidemiologists have an opportunity to apply their skills to hospital quality problems other than infection control. Soon, hospitals will be required to collect and report numerous quality indicators, whose results will require epidemiologic interpretation. For those who choose to make the transition into quality management, careful assessment and planning are needed to succeed.
The Project to Monitor Indicators (PMI) will be a collaborative effort between the Society for Healthcare Epidemiology of America (SHEA) and the Joint Commission on Accreditation of Healthcare Organizations (JCAHO). The goal of this collaboration is to create an intellectual infrastructure to support the effective use, development, understanding, and continuous improvement of clinical quality indicators through coordinated study by hospital epidemiologists.
The Joint Commission is in the midst of an extensive effort to develop a set of indicators that reflect the performance of various aspects of clinical practice. These indicators will form the foundation of a national comparative measurement system called the Indicator Measurement System (IMSystem). It is the Joint Commission's plan that hospitals will be required to participate in the IMSystem as part of the accreditation process in the near future.
Why do two physicians faced with similar patients make different decisions about the care their patients should receive? This area of health services research has been energized by recent concerns about rising healthcare costs. In 1982, Wennberg and Gittelsohn described the great variation in surgical procedure rates throughout the northeastern United States during the 1970s. Population rates of hysterectomy and prostatectomy varied fourfold between local service areas; tonsilectomy rates varied sixfold. Differences in patient populations could not explain the variation in rates. The authors concluded that a large portion of the variability was attributable to the personal preferences of the surgeons practicing in the various communities. Similar differences in procedure rates are easy to replicate and are evident at several levels of aggregation. On larger scales, regional and international differences can be documented easily. On a smaller scale, practice variation within individual hospitals is frequently evident.