English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

BACKGROUND  Hypertension remains a global health problem. Since, there is a significant positive correlation between antihypertensive medication adherence and blood pressure control, it is therefore of great importance to elucidate the determinants of adherence to antihypertensive medications among hypertensive patients.    METHODS  Hereby, we retrospectively analyzed the medical records of a hypertensive cohort recruited from a community hospital in Beijing, China, to investigate the factors affecting adherence to antihypertensive medications using decision trees. In addition, all data were assigned into a training set (75%) and testing set (25%) by the random number seed method to build and validate a compliance predictive model. We identified that how many times patients became nonadherent to antihypertensive medications in the year before the first prescription, types of antihypertensive drugs used in the year before the first prescription, body weight, smoking history, total number of hospital visits in the past year, total number of days of medication use in the year before enrollment, age, total number of outpatient follow-ups in the year after the first prescription, and concurrent diabetes greatly affected the compliance to antihypertensive medications.    RESULTS  The compliance predictive model we built showed a 0.78 sensitivity and 0.69 specificity for the prediction of the compliance to antihypertensive medications, with an area under the representative operating characteristics curve of 0.810.    CONCLUSIONS  Our data provide new insights into the improvements of the compliance to antihypertensive medications, which is beneficial for the management of hypertension, and the compliance predictive model may be used in community-based hypertension management.

A Clinical Prediction Model of Medication Adherence in Hypertensive Patients in a Chinese Community Hospital in Beijing