Dataset Information

Development and Validation of a Hypertension Prevalence Estimator Tool For Use in Clinical Settings.

ABSTRACT: Health systems are well positioned to identify and control hypertension among their patients. However, almost one third of US adults with uncontrolled hypertension are currently receiving medical care and are unaware of being hypertensive. This study describes the development and validation of a tool that health systems can use to compare their reported hypertension prevalence with their expected prevalence. Tool users provide the number of patients aged 18 to 85 years treated annually, stratified by sex, age group, race/ethnicity, and comorbidity status. Each stratum is multiplied by stratum-specific national prevalence estimates and the amounts are summed to calculate the number of expected hypertensive patients. The tool's validity was assessed by applying samples from cohorts with known hypertension prevalence; small differences in expected vs actual prevalence were identified (range, -3.3% to 0.6%). This tool provides clinically useful hypertension prevalence estimates that health systems can use to help inform hypertension management quality improvement efforts.

SUBMITTER: Ritchey M

PROVIDER: S-EPMC4935656 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Development and Validation of a Hypertension Prevalence Estimator Tool For Use in Clinical Settings.

Ritchey Matthew M Yuan Keming K Gillespie Cathleen C Zhang Guangyu G Ostchega Yechiam Y

Journal of clinical hypertension (Greenwich, Conn.) 20160105 8

Health systems are well positioned to identify and control hypertension among their patients. However, almost one third of US adults with uncontrolled hypertension are currently receiving medical care and are unaware of being hypertensive. This study describes the development and validation of a tool that health systems can use to compare their reported hypertension prevalence with their expected prevalence. Tool users provide the number of patients aged 18 to 85 years treated annually, stratifi ...[more]

PMID: 26729615

Similar Datasets

Project description:BackgroundAlthough 80% of children with disabilities live in developing countries, there are few culturally appropriate developmental assessment tools available for these settings. Often tools from the West provide misleading findings in different cultural settings, where some items are unfamiliar and reference values are different from those of Western populations.Methods and findingsFollowing preliminary and qualitative studies, we produced a draft developmental assessment tool with 162 items in four domains of development. After face and content validity testing and piloting, we expanded the draft tool to 185 items. We then assessed 1,426 normal rural children aged 0-6 y from rural Malawi and derived age-standardized norms for all items. We examined performance of items using logistic regression and reliability using kappa statistics. We then considered all items at a consensus meeting and removed those performing badly and those that were unnecessary or difficult to administer, leaving 136 items in the final Malawi Developmental Assessment Tool (MDAT). We validated the tool by comparing age-matched normal children with those with malnutrition (120) and neurodisabilities (80). Reliability was good for items remaining with 94%-100% of items scoring kappas >0.4 for interobserver immediate, delayed, and intra-observer testing. We demonstrated significant differences in overall mean scores (and individual domain scores) for children with neurodisabilities (35 versus 99 [p<0.001]) when compared to normal children. Using a pass/fail technique similar to the Denver II, 3% of children with neurodisabilities passed in comparison to 82% of normal children, demonstrating good sensitivity (97%) and specificity (82%). Overall mean scores of children with malnutrition (weight for height <80%) were also significantly different from scores of normal controls (62.5 versus 77.4 [p<0.001]); scores in the separate domains, excluding social development, also differed between malnourished children and controls. In terms of pass/fail, 28% of malnourished children versus 94% of controls passed the test overall.ConclusionsA culturally relevant developmental assessment tool, the MDAT, has been created for use in African settings and shows good reliability, validity, and sensitivity for identification of children with neurodisabilities.

Project description:BackgroundThe use of obstetric early-warning-systems (EWS) has been recommended to improve timely recognition, management and early referral of women who have or are developing a critical illness. Development of such prediction models should involve a statistical combination of predictor clinical observations into a multivariable model which should be validated. No obstetric EWS has been developed and validated for low resource settings. We report on the development and validation of a simple prediction model for obstetric morbidity and mortality in resource-limited settings.MethodsWe performed a multivariate logistic regression analysis using a retrospective case-control analysis of secondary data with clinical indices predictive of severe maternal outcome (SMO). Cases for design and validation were randomly selected (n = 500) from 4360 women diagnosed with SMO in 42 Nigerian tertiary-hospitals between June 2012 and mid-August 2013. Controls were 1000 obstetric admissions without SMO diagnosis. We used clinical observations collected within 24 h of SMO occurrence for cases, and normal births for controls. We created a combined dataset with two controls per case, split randomly into development (n = 600) and validation (n = 900) datasets. We assessed the model's validity using sensitivity and specificity measures and its overall performance in predicting SMO using receiver operator characteristic (ROC) curves. We then fitted the final developmental model on the validation dataset and assessed its performance. Using the reference range proposed in the United Kingdom Confidential-Enquiry-into-Maternal-and-Child-Health 2007-report, we converted the model into a simple score-based obstetric EWS algorithm.ResultsThe final developmental model comprised abnormal systolic blood pressure-(SBP > 140 mmHg or < 90 mmHg), high diastolic blood pressure-(DBP > 90 mmHg), respiratory rate-(RR > 40/min), temperature-(> 38 °C), pulse rate-(PR > 120/min), caesarean-birth, and the number of previous caesarean-births. The model was 86% (95% CI 81-90) sensitive and 92%- (95% CI 89-94) specific in predicting SMO with area under ROC of 92% (95% CI 90-95%). All parameters were significant in the validation model except DBP. The model maintained good discriminatory power in the validation (n = 900) dataset (AUC 92, 95% CI 88-94%) and had good screening characteristics. Low urine output (300mls/24 h) and conscious level (prolonged unconsciousness-GCS < 8/15) were strong predictors of SMO in the univariate analysis.ConclusionWe developed and validated statistical models that performed well in predicting SMO using data from a low resource settings. Based on these, we proposed a simple score based obstetric EWS algorithm with RR, temperature, systolic BP, pulse rate, consciousness level, urinary output and mode of birth that has a potential for clinical use in low-resource settings..

Project description:BackgroundAs populations are aging, the number of older patients with multiple chronic diseases demanding complex care increases. Although clinical guidelines recommend care to be personalized accounting for life expectancy, there are no tools to estimate life expectancy among multimorbid patients. Our objective was therefore to develop and internally validate a life expectancy estimator specifically for older multimorbid adults.MethodsWe analyzed data from the OPERAM (OPtimising thERapy to prevent avoidable hospital admissions in multimorbid older people) study in Bern, Switzerland. Participants aged 70 years old or more with multimorbidity (3 or more chronic medical conditions) and polypharmacy (use of 5 drugs or more for > 30 days) were included. All-cause mortality was assessed during 3 years of follow-up. We built a 3-year mortality prognostic index and transformed this index into a life expectancy estimator. Mortality risk candidate predictors included demographic variables (age, sex), clinical characteristics (metastatic cancer, number of drugs, body mass index, weight loss), smoking, functional status variables (Barthel-Index, falls, nursing home residence), and hospitalization. We internally validated and optimism corrected the model using bootstrapping techniques. We transformed the mortality prognostic index into a life expectancy estimator using the Gompertz survival function.ResultsEight hundred five participants were included in the analysis. During 3 years of follow-up, 292 participants (36%) died. Age, metastatic cancer, number of drugs, lower body mass index, weight loss, number of hospitalizations, and lower Barthel-Index (functional impairment) were selected as predictors in the final multivariable model. Our model showed moderate discrimination with an optimism-corrected C statistic of 0.70. The optimism-corrected calibration slope was 0.96. The Gompertz-predicted mean life expectancy in our sample was 5.4 years (standard deviation 3.5 years). Categorization into three life expectancy groups led to visually good separation in Kaplan-Meier curves. We also developed a web application that calculates an individual's life expectancy estimation.ConclusionA life expectancy estimator for multimorbid older adults based on an internally validated 3-year mortality risk index was developed. Further validation of the score among various populations of multimorbid patients is needed before its implementation into practice.Trial registrationClinicalTrials.gov NCT02986425. First submitted 21/10/2016. First posted 08/12/2016.

Dataset Information

Development and Validation of a Hypertension Prevalence Estimator Tool For Use in Clinical Settings.

Publications

Development and Validation of a Hypertension Prevalence Estimator Tool For Use in Clinical Settings.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets