Nomogram based on clinical features at a single outpatient visit to predict masked hypertension and masked uncontrolled hypertension: A study of diagnostic accuracy

Abstract

Patients with masked hypertension (MH) and masked uncontrolled hypertension (MUCH) are easily overlooked, and both cause target organ damage. We propose a prediction model for MH and MUCH patients based on clinical features at a single outpatient visit. Data collection was planned before the index test and reference standard were after. Thus, we retrospectively collect analyzed 804 subjects who underwent ambulatory blood pressure monitoring (ABPM) at Renmin Hospital of Wuhan University. These patients were divided into normotension/controlled hypertension group (n = 121), MH/MUCH (n = 347), and sustained hypertension (SH)/sustained uncontrolled hypertension group (SUCH) (n = 302) for baseline characteristic analysis. Models were constructed by logistic regression, a nomogram was visualized, and internal validation by bootstrapping. All groups were performed according to the definition proposed by the Chinese Hypertension Association. Compared with normotension/controlled hypertension, patients with MH/MUCH had higher office blood pressure (BP) and were more likely to have poor liver and kidney function, metabolic disorder and myocardial damage. By analysis, [office systolic blood pressure (OSBP)] (P = .004) and [office diastolic blood pressure (ODBP)] (P = .007) were independent predictors of MH and MUCH. By logistic regression backward stepping method, office BP, body mass index (BMI), total cholesterol (Tch), high-density lipoprotein cholesterol (HDL-C), and left ventricular mass index are contained in this model [area under curve (AUC) = 0.755] and its mean absolute error is 0.015. Therefore, the prediction model established by the clinical characteristics or relevant data obtained from a single outpatient clinic can accurately predict MH and MUCH.

Analysis of risk factors and construction of nomograph model for critical condition of patients with hypertension during pregnancy

“…Nomogram model, based on core diagnostic indicators, can be used for risky patient assessment and early disease diagnosis. It has been used effectively for various conditions, including prediction of adverse outcomes in pregnant women and fetuses with pulmonary arterial hypertension [ 19 ], radiomics-based prediction of the risk of preeclampsia in patients with hypertension during pregnancy [ 13 ], screening for new-onset hypertension in rural Chinese population [ 20 ], prediction of occult hypertension and occult uncontrolled hypertension based on clinical characteristics of single outpatient visit [ 21 ], etc. In this study, after integrating the risk factors of the multifactorial analysis results, the constructed visualized nomogram model had an AUC value of more than 0.8 in both internal and external validation, indicating good consistency and discrimination of the nomogram model herein.…”

A nomogram based on the clinical features of a single hospitalization predicts Heart failure and preserves Ejection Fraction with atrial fibrillation: a study of diagnostic accuracy

“…Based on the current de nitions, we retrospectively studied 259 (male/female: 146/113) patients with the clinical diagnosis of symptomatic HFpEF secondary to ischemic or non-ischemic aetiology. There are many de nitions of HFpEF, however, we use consensus statements from both the ACC/AHA/Heart Failure Society of America (HFSA) and the ESC continue to use an ejection fraction ≥ 50% as the threshold to identify HFpEF [13,14].…”

“…The corresponding score is shown by the model that was made of the level of in uence per variable. It is calculated in every patient to determine the patient's disease probability [14]. The model's area under the curve (AUC) value, sensitivity, speci city, and cutoff value were determined through receiver operating characteristic (ROC) analysis.…”