Back

Laboratory changes associated with medication non-adherence in patients with hypertension over six months of the COVID-19 pandemic

Chang, S.-M.; Chen, Y.-C.; Hsuan, C.-F.; Lu, I.-C.; Chuang, H.-Y.

2022-03-15 public and global health
10.1101/2022.03.15.22272192 medRxiv
Show abstract

The coexistence of multiple diseases is common in the elderly and often accompanied by medication non-adherence. This study investigated the relationship between medication non- adherence and laboratory findings inpatients with hypertension and hypertensive comorbidities (i.e., diabetes and nephropathy) in southern Taiwan during 6 months of the coronavirus disease pandemic. This was a panel study and involved outpatients from three hospitals classified as regional hospitals or above. Questionnaireswere usedto collect information on patient demographics, diet, medication adherence, and laboratory data at the time of recruitment and 6 months after. A total of 140 patients with only hypertension and 98 patients with hypertension and comorbidities were recruited, and the changes inblood pressure andlaboratory data were assessed after 6 months. Analyses performed with generalized estimating equations showed that patients who had not forgotten to take medication had a higher estimated glomerular filtration rate. Moreover, patients who did not change their medication time arbitrarily had lower low- density lipoprotein levels. Furthermore, patients who did not stop or interrupt their medication arbitrarily had lower diastolic blood pressuresand low-density lipoprotein levels. Overall, patients with better medication adherence had better estimated glomerular filtration rates,lower low-density lipoprotein levels, and lower diastolic blood pressures.

Matching journals

The top 1 journal accounts for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.