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Background: No comprehensive assessment of the quality of medications used in older outpatients has been conducted in Thailand. This study aimed to ascertain the prevalence of and factors contributing to older outpatients' use of potentially inappropriate medications (PIMs)., Methods: This cross-sectional study retrospectively assessed the prescriptions of older (≥60 years) outpatients at a secondary-care hospital. For PIM identification, the 2019 American Geriatric Society (AGS) Beers criteria were applied, considering all five PIM categories: PIM category I (medications that are potentially inappropriate in most older adults), II (disease-/syndrome-exacerbating drugs), III (medications that should be used with caution), IV (clinically important drug-drug interactions), and V (medications that should be avoided or have their dosage reduced based on renal function)., Results: This study included 22,099 patients (mean age, 68.86±7.64 years). Nearly three-fourths of patients were prescribed PIMs, with 68.90%, 7.68%, 44.23%, 15.66%, and 3.05%, respectively, receiving category I-V medications. The positive factors associated with PIM use included female sex (odds ratio [OR]=1.08; 95% confidence interval [CI], 1.01-1.16), age ≥75 years (OR=1.10; 95% CI, 1.01-1.21), polypharmacy (OR=10.21; 95% CI, 9.31-11.21), ≥3 diagnostic categories (OR=2.31; 95% CI, 2.14-2.50), and ≥3 chronic morbidities (OR=1.46; 95% CI, 1.26-1.68). The negative factor associated with PIM use was a comorbidity score of ≥1 (OR=0.78; 95% CI, 0.71-0.86)., Conclusion: PIM use among older outpatients remains highly prevalent in clinical practice. The results of this study identified polypharmacy as the strongest factor affecting PIM use.

Objective: To study the prevalence of potentially inappropriate medications for patients with heart failure (PIMHF) use and to identify factors associated with PIMHF use in Thai older HF patients., Methods: This cross-sectional analytical survey included data on older (≥ 60 years) HF patients obtained from the electronic medical record databases of secondary- and tertiary-care hospitals. The medication profiles of patients were assessed to examine whether they were prescribed any PIMHF after an HF diagnosis. For PIMHF detection, the HF-specific criteria, including 2014 St Vincent criteria, 2019 Beers criteria, and 2021 Thailand criteria were applied. The prevalence of PIMHF use was expressed as percentages. The associated factors were identified using a binary logistic regression analysis, expressed as the adjusted odds ratio (aOR) and 95% confidence interval (95% CI)., Results: A total of 2,639 patients were included in the study. Thirty-two PIMHF were found to have been prescribed to these patients. The prevalence of PIMHF use identified by the ST Vincent criteria, the Beers criteria, the Thailand criteria, and the three combined criteria was 23.76%, 19.67%, 21.18%, and 25.16%, respectively. The factors associated with PIMHF use were secondary-care hospital (aOR = 1.54, 95% CI: 1.26-1.87), HF with preserved ejection fraction (HFpEF) (aOR = 1.81, 95% CI: 1.38-2.38), hypertension (HTN) (aOR = 1.24, 95% CI: 1.02-1.51), diabetes mellitus (DM) (aOR = 1.39, 95% CI: 1.10-1.75), chronic pulmonary diseases (CPD) (aOR = 2.09, 95% CI: 1.56-2.80), and connective tissue diseases (CTD) (aOR = 5.10, 95% CI: 2.20-11.83)., Conclusions: PIMHF are commonly used in Thai older HF patients. The factors associated with PIMHF use identified in this study include secondary-care hospital, HFpEF, HTN, DM, CPD, and CTD., (© 2022 JGC All rights reserved; www.jgc301.com.)

Background: Thailand have developed a list of potentially inappropriate medications for patients with heart failure (PIMHF). However, its association with clinical outcomes has not been evaluated in real-world clinical practice., Objective: To examine the association between the prescription of any PIMHF and hospitalization from heart failure (HF)., Methods: A 1:1 matched case-control study was conducted. Data on HF patients visiting the study hospitals during 2017-2019 were obtained from the electronic medical record database. Patients with a history of first hospitalization due to HF and those with a history of outpatient department visits or non-HF hospitalization were defined as cases and controls, respectively. The association of hospitalization from HF with the prescription of any PIMHF was expressed as the adjusted odds ratio (aOR) and 95% confidence interval (95%CI), calculated using a conditional logistic regression (CLR) model., Results: After matching, 1,603 pairs of case and control were generated for the analysis. In total, 21 of 47 PIMHF were found to have been prescribed. Compared with the reference group of patients not prescribed any of the 21 PIMHF, those who had been prescribed a PIMHF had an aOR of 1.47 [95%CI 1.02:2.13]. NSAIDs/COX-2 inhibitors, oral short-acting beta-2 agonists, medications that promote fluid overload, and medications that elevate blood pressure were the four medication classes associated with the increased risk of hospitalization from HF (aOR = 2.64, [95%CI 1.30:5.38], aOR = 4.87, [95%CI 1.17:20.29], aOR = 1.50, [95%CI 1.01:2.22], and aOR = 2.51, [95%CI 1.26:4.99], respectively)., Conclusions: The prescription of any of the 21 PIMHF found to have been prescribed in this study may increase the risk of hospitalization from HF. The Thai PIMHF list may be used in pharmacy practice as an assessment tool for the appropriate use of medication in HF patients., (Copyright: © Pharmacy Practice.)

Background: Several medications are likely to be potentially inappropriate medications for patients with heart failure (PIMHF) as they may worsen heart failure (HF). A screening tool inclusive of PIMHF is lacking., Objective: To develop an extensive list of PIMHF for HF patients., Methods: A list of PIMHF was developed using reviews of recent HF guidelines and literature and validated through a survey study of HF experts using a modified Delphi technique. The study participants were Thai HF experts with ≥ 5 years of practice experience in Thailand. To create an initial list of PIMHF, medications likely to be PIMHF were gathered from both HF guidelines and HF-related explicit criteria. A 3-round Delphi survey was conducted for 9 months, from January 1, 2019 to September 30, 2019. In the first round, medication items that ≥ 60% of the participants rated as "not PIMHF" were excluded. The two subsequent rounds were conducted to measure an agreement on PIMHF. To reach consensus, medication items in the PIMHF list had to meet the following pre-determined criteria: convergence (median ≥ 3.5 and interquartile range ≤ 1.5) and stability (marginal changes of medians between round 2 and round 3 < 15%)., Results: Seventeen eligible HF experts, including 10 cardiologists, 3 hospital pharmacists and 4 academic pharmacists, participated in the study. The initial list of PIMHF consisted of 100 medication items. From round 1, 8 medication items were excluded from the initial list. Thus, 92 medication items were considered in the second and the third round, respectively. After 3 surveys, 47 medication items reached the consensus and agreed as PIMHF., Conclusion: This Delphi survey on opinion about PIMHF among an HF expert panel produced a list of 47 medication items as PIMHF which may be used as a screening tool for PIMHF in Thai HF patients., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Background: Several medications may worsen heart failure (HF), and they are considered as potentially inappropriate medications for patients with heart failure (PIMHF). No studies reported the prevalence of PIMHF use and its associated factors in Thai HF patients., Objective: To determine the prevalence of PIMHF use and identify factors associated with PIMHF use., Material and Method: A cross-sectional study was conducted using data on HF patients obtained from the electronic medical databases (EMDs) of two hospitals, including a secondary and a tertiary care hospital. Data collected included demographics, diagnoses and medications prescribed during 2016-2019. The prevalence of PIMHF use identified by the Thailand list of PIMHF was determined. Patient and clinical factors were examined whether they were associated with PIMHF use by calculating the adjusted odds ratio (aOR) and 95% confidence interval (95% CI) using a binary logistic regression analysis., Results: From the EMD, 972 and 2888 eligible HF patients from a secondary and a tertiary care hospital, respectively, were included in this study. The prevalence of PIMHF use was 45.16% and 33.07% at a secondary and a tertiary care hospital, respectively. Factors associated with PIMHF use were HFpEF (aOR = 1.68, 95% CI = 1.39-2.03), diabetes mellitus (DM) (aOR = 1.66, 95% CI = 1.35-2.05), renal failure (RF) (aOR = 1.49, 95% CI = 1.21-1.84), chronic pulmonary diseases (CPD) (aOR = 2.41, 95% CI = 1.74-3.34), connective tissue diseases (CTD) (aOR = 5.21, 95% CI = 2.17-12.49), and cancer (aOR = 2.57, 95% CI = 1.36-4.86)., Conclusion: PIMHF use according to the Thailand list of PIMHF was prevalent in Thai HF patients and associated with HFpEF, DM, RF, CPD, CTD and cancer., (© 2020 John Wiley & Sons Ltd.)

Background: Readmission to hospital after discharge has been recognized as a significant problem in patients with chronic heart failure (CHF). No studies report rate of early readmission (defined as readmission within 30 days after discharge) and its predictors among Thai patients with CHE., Objective: To determine rate and predictors of early readmission among Thai patients with heart failure., Material and Method: From an electronic medical database of a tertiary care hospital in Thailand, we retrieved data of all patients who were hospitalized with a principal diagnosis of CHF between January 1, 2005 and December 31, 2006. Patients were followed whether they were readmitted within 30 days after discharge., Results: Seven hundred eighteen patients were included for analysis. Studied patients were mostly female (57.52%) with mean age of 64.91 +/- 14.14 (SD) years. The median length of hospital stay (LOS) was five days. One hundred one patients (14.07%) had their first readmission from all causes within 30 days after discharge. An exacerbation of CHF was the most common cause. In a multivariate model, only the LOS >5 days predict higher risk of early readmission (adjusted OR = 1.41, 95% CI = 1.05-1.89, p = 0.023). No significant association between discharge medications and early readmission was found in the present study., Conclusion: Early readmission rates appear modest among Thai patients with CHFE The LOS > 5 days was a positive predictor of early readmission while discharge cardiovascular medications were not associated with early readmission.