RESUMO
PURPOSE: Predictive models allow clinicians to identify higher- and lower-risk patients and make targeted treatment decisions. Microalbuminuria (MA) is a condition whose presence is understood to be an early marker for cardiovascular disease. The aims of this study were to develop a patient data-driven predictive model and a risk-score assessment to improve the identification of MA. METHODS: The 2007-2008 National Health and Nutrition Examination Survey (NHANES) was utilized to create a predictive model. The dataset was split into thirds; one-third was used to develop the model, while the other two-thirds were utilized for internal validation. The 2012-2013 NHANES was used as an external validation database. Multivariate logistic regression was performed to create the model. Performance was evaluated using three criteria: (1) receiver operating characteristic curves; (2) pseudo-R (2) values; and (3) goodness of fit (Hosmer-Lemeshow). The model was then used to develop a risk-score chart. RESULTS: A model was developed using variables for which there was a significant relationship. Variables included were systolic blood pressure, fasting glucose, C-reactive protein, blood urea nitrogen, and alcohol consumption. The model performed well, and no significant differences were observed when utilized in the validation datasets. A risk score was developed, and the probability of developing MA for each score was calculated. CONCLUSION: The predictive model provides new evidence about variables related with MA and may be used by clinicians to identify at-risk patients and to tailor treatment. The risk score developed may allow clinicians to measure a patient's MA risk.
Assuntos
Albuminúria/diagnóstico , Biomarcadores/análise , Modelos Estatísticos , Inquéritos Nutricionais/métodos , Medição de Risco/métodos , Adulto , Albuminúria/sangue , Albuminúria/epidemiologia , Bases de Dados Factuais , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Valor Preditivo dos Testes , Estudos Prospectivos , Curva ROC , Fatores de Risco , Estados Unidos/epidemiologiaRESUMO
BACKGROUND: Patient adherence is often not monitored because existing methods of evaluating adherence are either burdensome or do not accurately predict treatment outcomes. AIM: To examine whether two simple, single-item physician-administered measures of patient adherence to antihypertensive medication are predictive of blood pressure outcomes. DESIGN AND SETTING: Retrospective database analysis of patients with hypertension treated in Belgian primary care. METHOD: Using pooled data from five observational studies, a sample was identified of 9725 patients who were assessed using two single-item physician-administered measures of adherence to antihypertensive medication: the first item of the Basel Assessment of Adherence Scale (BAAS) and the Visual Analogue Scale (VAS). These two assessment tools were administered by GPs during regular appointments with patients. Systolic blood pressure (SBP), diastolic blood pressure (DBP), and combined SBP/DBP were measured at baseline and at 90 days. RESULTS: BAAS-identified adherent patients achieved lower mean SBP and DBP compared with non-adherent patients at 90 days (P<0.001), and had odds ratios of achieving blood pressure control of 0.66 (95% confidence intervals (CI) = 0.61 to 0.73, P<0.001) for SBP, 0.69 (95% CI = 0.62 to 0.76, P<0.001) for DBP, and 0.65 (95% CI = 0.59 to 0.72, P<0.001) for combined SBP/DBP. For VAS-identified adherent patients, the odds ratios of achieving blood pressure control were 0.93 (95% CI = 0.86 to 1.00, P<0.001) for SBP, 0.79 (95% CI = 0.73 to 0.85, P<0.001) for DBP, and 0.91 (95% CI = 0.84 to 0.99, P<0.001) for combined SBP/DBP. CONCLUSIONS: The first item of the BAAS and the VAS are independent predictors of blood pressure control. These methods can be integrated seamlessly into routine clinical practice by allowing GPs to quickly evaluate a patient's adherence and tailor treatment recommendations accordingly.