Identifying Common Predictors of Multiple Adverse Outcomes Among Elderly Adults With Type-2 Diabetes

Polypharmacy and Elevated Risk of Severe Adverse Events in Older Adults Based on the Korea Institute of Drug Safety and Risk Management-Korea Adverse Event Reporting System Database

BACKGROUND

Older adults are at a higher risk of severe adverse drug events (ADEs) because of multimorbidity, polypharmacy, and lower physiological function. This study aimed to determine whether polypharmacy, defined as the use of ≥ 5 active drug ingredients, was associated with severe ADEs in this population.

METHODS

We used ADE reports from the Korea Institute of Drug Safety and Risk Management-Korea Adverse Event Reporting System Database, a national spontaneous ADE report system, from 2012 to 2021 to examine and compare the strength of association between polypharmacy and severe ADEs in older adults (≥ 65 years) and younger adults (20-64 years) using disproportionality analysis.

RESULTS

We found a significant association between severe ADEs of cardiac and renal/urinary Medical Dictionary for Regulatory Activities System Organ Classes (MedDRA SOC) with polypharmacy in older adults. Regarding individual-level ADEs included in these MedDRA SOCs, acute cardiac arrest and renal failure were more significantly associated with polypharmacy in older adults compared with younger adults.

CONCLUSION

The addition of new drugs to the regimens of older adults warrants close monitoring of renal and cardiac symptoms.

Polypharmacy and risk of fractures in older adults: A systematic review

BACKGROUND

Fractures have serious health consequences in older adults. While some medications are individually associated with increased risk of falls and fractures, it is not clear if this holds true for the use of many medications (polypharmacy). We aimed to identify what is known about the association between polypharmacy and the risk of fractures in adults aged ≥65 and to examine the methods used to study this association.

METHODS

We conducted a systematic review with narrative synthesis of studies published up to October 2023 in PubMed, Embase, CINAHL, PsychINFO, Cochrane Library, Web of Science, and the grey literature. Two independent reviewers screened titles, abstracts, and full texts, then performed data extraction and quality assessment.

RESULTS

Among the 31 studies included, 11 different definitions of polypharmacy were used and were based on three medication counting methods (concurrent use 15/31, cumulative use over a period 6/31, daily average 3/31, and indeterminate 7/31). Overall, polypharmacy was frequent and associated with higher fracture risk. A dose-response relationship between increasing number of medications and increased risk of fractures was observed. However, only seven studies adjusted for major confounders (age, sex, and chronic disease). The quality of the studies ranged from poor to high.

CONCLUSIONS

Polypharmacy appears to be a relevant modifiable risk factor for fractures in older individuals that can easily be used to identify those at risk. The diversity of medication calculation methods and definitions of polypharmacy highlights the importance of a detailed methodology to understand and compare results.

Real-World Hemoglobin A1c Changes, Prescribing Provider Types, and Medication Dose Among Patients with Type 2 Diabetes Mellitus Initiating Treatment with Oral Semaglutide

INTRODUCTION

Given the lack of real-world data on oral semaglutide use outside clinical trials, the purpose of this study was to describe dose, prescriber specialty, and change in hemoglobin A1c (HbA1c) after 6 months of oral semaglutide treatment for patients with type 2 diabetes mellitus (T2DM).

METHODS

This was a retrospective study among adult patients with T2DM with ≥ 1 claim for oral semaglutide between November 1, 2019`1-June 30, 2020. Patients had continuous health plan enrollment ≥ 12 months prior to (pre-index) and ≥ 6 months following (post-index) the date of the first oral semaglutide claim (index). Dose at initiation and specialty of the prescribing provider were captured. Change in HbA1c between the last post- and pre-index HbA1c measurement was calculated. Patients were stratified by pre-index HbA1c ≥ 9% (poorly controlled) and HbA1c < 9%.

RESULTS

A total of 744 HbA1c < 9% and 268 poorly controlled patients were included in the study. Most patients had an initial oral semaglutide dose of 7 mg (49.3%) or 3 mg (42.9%), prescribed most frequently by a primary care provider (27.8%). Mean HbA1c reduction was 0.8% (p < 0.001). Patients with poorly controlled T2DM had greater HbA1c reductions than patients with HbA1c < 9% (2.0% versus 0.4%, p < 0.001). Patients persistent with oral semaglutide (≥ 90 days continuous treatment) had a mean HbA1c reduction of 0.9% (p < 0.001); persistent patients with poorly controlled T2DM had a mean reduction of 2.5%.

CONCLUSIONS

Patients with T2DM in this study experienced significant reductions in HbA1c within 6 months following initiation of oral semaglutide. Patients with a higher starting HbA1c experienced greater HbA1c reductions. The initial dose of oral semaglutide was higher than prescribing instructions indicated for more than half of the study patients.

Effectiveness of countermeasure for polypharmacy by multidisciplinary team review in patients with diabetes mellitus

AIMS/INTRODUCTION

Polypharmacy in diabetes patients is related to worse clinical outcomes. The aim of this study was to evaluate the usefulness of our countermeasure for polypharmacy, which combines a pharmacist check followed by a multidisciplinary team review in diabetic patients with polypharmacy.

METHODS

A single-center, retrospective observational study was conducted at Gifu University Hospital. Study participants included diabetic patients taking six or more drugs on admission to the diabetes ward between July 2021 and June 2022. Drugs which were discontinued by the present countermeasure were examined, and the number of drugs being taken by each patient was compared between admission and discharge.

RESULTS

102 of 308 patients were taking six or more drugs on admission. The drugs being taken by these patients were evaluated by pharmacists using a checklist for polypharmacy. Eighty-four drugs which were evaluated as inappropriate or potentially inappropriate medications by pharmacists were discontinued following the multidisciplinary team review. The median and mean number of drugs taken by the 102 patients significantly decreased from 9.0 (IQR: 8-12) and 9.26 ± 2.64 on admission to 9.0 (IQR: 6-10) and 8.42 ± 2.95 on discharge (P = 0.0002). We followed up with these patients after discontinuation of the drugs and confirmed that their clinical status had not deteriorated.

CONCLUSION

The present countermeasure for polypharmacy, which combines a pharmacist check based on a checklist for evaluating polypharmacy followed by a multidisciplinary team review, was useful for reducing the number of inappropriate or potentially inappropriate medications taken by diabetes patients with polypharmacy.

Prevalence and impact of polypharmacy in older patients with type 2 diabetes

BACKGROUND

Polypharmacy is a prevalent condition in older adults, especially those with multiple chronic diseases, and has been largely associated with adverse outcomes, including disability, hospitalizations, and death.

AIMS

This systematic review focused on diabetes and aimed to investigate the prevalence and impact of polypharmacy in older adults affected by such disease.

METHODS

Observational (either cross-sectional or longitudinal) or experimental studies investigating the frequency and impact of polypharmacy in older adults with diabetes were identified from scientific databases and grey literature until August 2021. The prevalence and the 95% Confidence Interval (95% CI) of polypharmacy in older people with diabetes were summarized by a random-effects meta-analysis.

RESULTS

From a total of 1465 records, 9 were selected for the qualitative synthesis, and 8 for the quantitative synthesis. Most studies defined polypharmacy using a cut-off for the minimum number of medications ranging from 4 to 6 drugs/day. The pooled prevalence of polypharmacy in older people with diabetes was 64% (95% CI 45-80%). Considering studies that used the same definition of polypharmacy (i.e. ≥ 5 drugs/day), the pooled prevalence was 50% (95% CI 37-63%). The between-studies heterogeneity was high. Across the selected studies, polypharmacy seemed to negatively influence both diabetes-specific (poor glycemic control and risk of hypoglycemia) and health-related (risk of incident falls, syncope, hospitalization, and death) outcomes.

CONCLUSION

This systematic review confirms the high prevalence of polypharmacy in older people with diabetes and its strong impact on several health-related outcomes, including mortality. These results strengthen the need to improve care strategies for management of these patients.

A dependency-based machine learning approach to the identification of research topics: a case in COVID-19 studies

Purpose

Previous research concerning automatic extraction of research topics mostly used rule-based or topic modeling methods, which were challenged due to the limited rules, the interpretability issue and the heavy dependence on human judgment. This study aims to address these issues with the proposal of a new method that integrates machine learning models with linguistic features for the identification of research topics.

Design/methodology/approach

First, dependency relations were used to extract noun phrases from research article texts. Second, the extracted noun phrases were classified into topics and non-topics via machine learning models and linguistic and bibliometric features. Lastly, a trend analysis was performed to identify hot research topics, i.e. topics with increasing popularity.

Findings

The new method was experimented on a large dataset of COVID-19 research articles and achieved satisfactory results in terms of f-measures, accuracy and AUC values. Hot topics of COVID-19 research were also detected based on the classification results.

Originality/value

This study demonstrates that information retrieval methods can help researchers gain a better understanding of the latest trends in both COVID-19 and other research areas. The findings are significant to both researchers and policymakers.

A Novel Method for Identifying a Parsimonious and Accurate Predictive Model for Multiple Clinical Outcomes

BACKGROUND AND OBJECTIVE

Most methods for developing clinical prognostic models focus on identifying parsimonious and accurate models to predict a single outcome; however, patients and providers often want to predict multiple outcomes simultaneously. As an example, for older adults one is often interested in predicting nursing home admission as well as mortality. We propose and evaluate a novel predictor-selection computing method for multiple outcomes and provide the code for its implementation.

METHODS

Our proposed algorithm selected the best subset of common predictors based on the minimum average normalized Bayesian Information Criterion (BIC) across outcomes: the Best Average BIC (baBIC) method. We compared the predictive accuracy (Harrell's C-statistic) and parsimony (number of predictors) of the model obtained using the baBIC method with: 1) a subset of common predictors obtained from the union of optimal models for each outcome (Union method), 2) a subset obtained from the intersection of optimal models for each outcome (Intersection method), and 3) a model with no variable selection (Full method). We used a case-study data from the Health and Retirement Study (HRS) to demonstrate our method and conducted a simulation study to investigate performance.

RESULTS

In the case-study data and simulations, the average Harrell's C-statistics across outcomes of the models obtained with the baBIC and Union methods were comparable. Despite the similar discrimination, the baBIC method produced more parsimonious models than the Union method. In contrast, the models selected with the Intersection method were the most parsimonious, but with worst predictive accuracy, and the opposite was true in the Full method. In the simulations, the baBIC method performed well by identifying many of the predictors selected in the baBIC model of the case-study data most of the time and excluding those not selected in the majority of the simulations.

CONCLUSIONS

Our method identified a common subset of variables to predict multiple clinical outcomes with superior balance between parsimony and predictive accuracy to current methods.

Hospital adverse outcomes of the elderly in a tertiary referral hospital: A prospective cohort study of 9,586 admissions

OBJECTIVE

This study aimed to evaluate the hospital adverse outcomes (HAO) of admitted older adult patients in a large prospective cohort and investigate the demographic, economic, and health-related characteristics at risk of HAO in all older adult patients admitted in the general ward of a tertiary referral hospital.

MATERIALS AND METHODS

We recruited admission episodes of older adult patients aged over 65 years who were admitted at the general ward of Konkuk University Medical Center, which is a tertiary referral hospital, from September 2016 to October 2017. Out of 9,586 admission episodes, 8,263 were included. Modified from the Geriatric Screening for Care-10, six common geriatric health issues, namely, dysphagia, polypharmacy, fecal incontinence, functional mobility, depression, and dementia, were evaluated. Fall, hospital-acquired pressure ulcer (HPU), and mortality were checked daily by experienced nurses during the patients' hospital stay. A logistic regression model was used, and P < 0.05 was the threshold of significance.

RESULTS

The incidence rates of fall and HPU were 1.3 % and 4.0 %, respectively. The hospital mortality was 6.1 %. Older adult patients with dysphagia or dementia upon admission were significantly associated with an increased likelihood of falls. Furthermore, age, ER admission, low income, fecal incontinence, or functional immobility increased the HPU incidence. Meanwhile, age, male, ER admission, fecal incontinence, or functional immobility significantly increased the hospital mortality.

CONCLUSION

All demographic, economic, and health-related characteristics, except for polypharmacy and depression, affect the incidence of HAO. Intervention to vulnerable older adult patients with HAO risk could improve the treatment outcome.

Prevalence of Depressive Symptoms in the Elderly Population Diagnosed with Type 2 Diabetes Mellitus

Introduction: A sharp rise in the population of elderly people, who are more prone to somatic and mental diseases, combined with the high prevalence of type 2 diabetes mellitus and diabetes-associated complications in this age group, have an impact on the prevalence of depressive symptoms. Aim of the work: The work of the study was the evaluation of the prevalence of depressive symptoms in the elderly population diagnosed with type 2 diabetes mellitus. Materials and methods: The pilot study was conducted in 2019 among 200 people diagnosed with type 2 diabetes mellitus, aged 65 years and above, receiving treatment in a specialist diabetes outpatient clinic. The study was based on a questionnaire aimed at collecting basic sociodemographic and clinical data and the complete geriatric depression scale (GDS, by Yesavage) consisting of 30 questions. Results: The study involved 200 patients receiving treatment in a diabetes outpatient clinic. The mean age of the study subjects was 71.4 ± 5.0 years. The vast majority of the subjects (122; 61%) were women, with men accounting for 39% of the study population (78 subjects). A statistically significant difference in the GDS (p < 0.01) was shown for marital status, body mass index (BMI), duration of diabetes, and the number of comorbidities. Patients with results indicative of symptoms of mild and severe depression were found to have higher BMI, longer disease duration, and a greater number of comorbidities. There were no statistically significant differences in the level of HbA1c. Conclusions: In order to verify the presence of depressive symptoms in the group of geriatric patients with diabetes mellitus, an appropriate screening programme must be introduced to identify those at risk and refer them to specialists, so that treatment can be promptly initiated. Screening tests conducted by nurses might help with patient identification.