Statin use and the risk of Parkinson's disease in persons with diabetes: A nested case-control study.

AIMS: Persons with diabetes may have an elevated risk of Parkinson's disease (PD). Statin use could also modify the progression of PD. The aim was to study whether there is an association between statin exposure and risk of PD in persons with diabetes. METHODS: A nationwide, nested case-control study restricted to people with diabetes was performed as part of nationwide register-based Finnish study on PD (FINPARK). Study included 2017 PD cases and their 7934 matched controls without PD. Persons with PD were diagnosed between 1999 and 2015, and statin use (1995-2015) was determined from Prescription Register. In the main analysis, exposure at least 3 years before outcome was considered. Cumulative exposure was categorized into tertiles, and associations were analysed with conditional logistic regression (adjusted with comorbidities and number of antidiabetic drugs). RESULTS: Prevalence of statin use was similar in PD cases and controls, with 54.2% of cases and 54.4% controls exposed before the lag time (adjusted odds ratio [aOR] = 1.03; 95% confidence interval [CI]: 0.92-1.15). Those in the highest cumulative statin exposure tertile had higher risk of PD than statin nonusers (aOR = 1.22; 95% CI: 1.04-1.43), or those in the lowest cumulative statin exposure tertile (aOR = 1.29; 95% CI: 1.07-1.57). CONCLUSION: Our nationwide study that controlled for diabetes duration and used 3-year lag between exposure and outcome to account for reverse causality does not provide support for the hypothesis that statin use decreases the risk of PD.

Use of oral health care services among older home care clients in the context of an intervention study.

BACKGROUND: An increasing number of care-dependent older people living at home need external support to receive regular dental care. OBJECTIVES: To investigate the use of oral health care services among old home care clients who participated in an intervention study focusing on oral self-care and nutrition. MATERIALS AND METHODS: This study employed data from the multidisciplinary Nutrition, Oral Health and Medication (NutOrMed) intervention study with a population-based sample of 245 home care clients (74% female) aged 75 or more divided in intervention (n = 140) and two control groups (n = 105). The data were collected through interviews at baseline and 6-month follow-up. RESULTS: At baseline, 43% of participants reported visits to oral health care within the previous year. At 6-month follow-up, this proportion was 51%. In the intervention group, the corresponding figures were 46% and 53%, and in the controls 39% and 48%. Adjusted regression analyses showed that this change was statistically significant (p = 0.008). In addition, higher education and toothache or other discomfort related to teeth or dentures at baseline were associated with increased use after the 6-month follow-up (OR = 1.1, 95% CI = 1.0-1.2; OR = 3.4, 95% CI = 1.5-7.9) but being edentulous indicated the opposite (OR = 0.2, 95% CI = 0.1-0.4). Belonging to the intervention group was not associated with increased use. CONCLUSIONS: In older adults, any efforts to raise awareness of oral health are of great potential to increase use of services.

Symptomatic and Preventive Medication Use before and after Alzheimer's Disease Diagnosis: A 10-Year Matched Cohort Study.

OBJECTIVE: To investigate longitudinal changes in symptomatic and preventive medication use among community-dwelling people with and without Alzheimer's disease (AD) 5 years pre- and post-AD diagnosis. DESIGN: Retrospective matched cohort study. SETTINGS AND PARTICIPANTS: The sample comprised 58,496 people with a geriatrician/neurologist-verified AD diagnosis matched 1:1 for age, sex, and region to people without AD in Finland. METHODS: Medication dispensing data were obtained from the Finnish Prescription Register. Prevalence of symptomatic and preventive medication use was evaluated every 6 months from 5 years pre- to post-AD diagnosis. Longitudinal changes in medication use between people with and without AD were compared using ordinal logistic regression. RESULTS: During the 5 years pre- and post-diagnosis, there were differences in symptomatic (P < .001) and preventive (P = .006) medication use between people with and without AD. Over the 5 years pre-diagnosis, prevalence of symptomatic and preventive medications increased in both people with and without AD. During the 1 year pre-diagnosis, people with AD had a higher increase in use of ≥3 symptomatic medications (+4.4% vs +2.2%) and ≥3 preventive medications (+6.4% vs +2.9%) compared to people without AD. Over the 5 years post-diagnosis, symptomatic medication use plateaued in both people with and without AD. Meanwhile, people using ≥3 preventive medications decreased (-6.0%) in those with AD, but increased (+6.1%) in those without AD. During the follow-up period, people with AD had a larger absolute percentage increase in prevalence of antipsychotics (+22.7% vs +1.8%) and antidepressants (+19.1% vs +5.0%) than people without AD. During the same period, paracetamol and calcium supplement use increased by 31.1% and 20.4%, respectively, among people with AD. The largest absolute percentage decrease in prevalence of preventive medications over the 5 years post-diagnosis were beta-blockers (-9.8%) and statins (-7.0%) in people with AD. CONCLUSIONS AND IMPLICATIONS: At the point of and following diagnosis, there were population-level changes in medication use among people with AD. Medication assessments during this period appear to coincide with discontinuation of preventive medications whereas minimal changes were observed in symptomatic medication use.

Predicting Alzheimer's disease from cognitive footprints in mid and late life: How much can register data and machine learning help?

BACKGROUND: Real-world data with decades-long medical records are increasingly available alongside the growing adoption of machine learning in healthcare research. We evaluated the performance of machine learning models in predicting the risk of Alzheimer's disease (AD) using data from the Finnish national registers. METHODS: We conducted a case-control study using data from the Finnish MEDALZ (Medication use and Alzheimer's disease) study. Altogether 56,741 individuals with incident AD diagnosis (age ≥ 65 years at diagnosis and born after 1922) and their 1:1 age-, sex-, and region of residence-matched controls were included. The association of risk factors, evaluated at different age periods (45-54, 55-64, 65+), and AD were assessed with logistic regression. Predictive accuracies of logistic regressions were compared with seven machine learning models (L1-regularized logistic regression, Naive bayes, Decision tree, Random Forest, Multilayer perceptron, XGBoost, and LightGBM). FINDINGS: 63.5 % of cases and controls were females and the mean age was 79.1 (SD = 5.1). The strongest associations with AD were observed for head injuries at age 55-64 (OR, 95 % CI 1.33, 1.19-1.48) and 65+ (1.31, 1.23-1.40), followed by antidepressant use (1.30, 1.22-1.38) at 55-64 and antipsychotic use (1.27, 1.19-1.35) at 65+. The predictive accuracies of all models were low, with the best performance (AUC 0.603) observed in Random Forest for predicting AD onset at age 65-69. INTERPRETATION: Although significant associations were identified between many risk factors and AD, the low predictive accuracies suggest that specialised healthcare diagnosis data is not sufficient for predicting AD and linkage with other data sources is needed.

Prescribing Appropriate Medicines to Older Adults: A Finnish Experience with the Web-Based Meds75+ Database.

The Finnish web-based Meds75+ database supports rational, safe and appropriate prescribing to older adults in primary care. This article describes the content and updating process of Meds75+ and demonstrates its applicability in everyday clinical practice. Meds75+ contains a classification (A-D) and recommendation texts for 450-500 drug substances when used in the treatment of older adults aged 75 years or older. The content of Meds75+ is continually updated. Each assessment of a drug substance begins with a structured collection of available information and research evidence. After that, an interdisciplinary expert panel discusses the classification and recommendation using a consensus method. A rolling 3-year updating cycle guarantees that all drug substances are reviewed regularly. Most drug substances are classified as class A (41%) (suitable, e.g. bisoprolol) or as class C (37%) (suitable with specific precautions, e.g. ibuprofen). One-fifth (20%) of the substances are in class D (avoid use, e.g. diazepam). Most commonly, older adults have purchased substances affecting the alimentary tract and metabolism (17%), the nervous system (16%) and the cardiovascular system (15%). In Finland, the proportion of older adults using class D substances (37%) has not changed between the years 2019 and 2022. Meds75+ has potential to support safer and more effective use of medications for older adults, since it offers up-to-date information on drug substances for healthcare professionals.

Top 10 Signs and Symptoms of Psychotropic Adverse Drug Events to Monitor in Residents of Long-Term Care Facilities.

OBJECTIVES: To produce a consensus list of the top 10 signs and symptoms suggestive of adverse drug events (ADEs) for monitoring in residents of long-term care facilities (LTCFs) who use antipsychotics, benzodiazepines, or antidepressants. DESIGN: A 3-round Delphi study. SETTING AND PARTICIPANTS: Geriatricians, psychiatrists, pharmacologists, general practitioners, pharmacists, nurses, and caregivers from 13 Asia Pacific, European, and North American countries. METHODS: Three survey rounds were completed between April and June 2023. In Round 1, participants indicated their level of agreement on a 9-point Likert scale on whether 41 signs or symptoms identified in a systematic review should be routinely monitored. Participants considered signs and symptoms that reduce quality of life or cause significant harm, are observable or measurable by nurses or care workers, and can be assessed at a single time point. Round 1 statements were included in a list for prioritization in Round 3 if ≥ 70% of participants responded ≥7 on the Likert scale. Statements were excluded if ≤ 30% of participants responded ≥7. In Round 2, participants indicated their level of agreement with statements that did not reach initial consensus, plus amended statements based on Round 1 participant feedback. Round 2 statements were included in Round 3 if ≥ 50% of the participants responded ≥7 on the Likert scale. In Round 3, participants prioritized the signs and symptoms. RESULTS: Forty-four participants (93.6%) completed all 3 rounds. Four of 41 signs and symptoms reached consensus for inclusion after Round 1, and 9 after Round 2. The top 10 signs and symptoms prioritized in Round 3 were recent falls, daytime drowsiness or sleepiness, abnormal movements (eg, shaking or stiffness), confusion or disorientation, balance problems, dizziness, postural hypotension, reduced self-care, restlessness, and dry mouth. CONCLUSIONS AND IMPLICATIONS: The top 10 signs and symptoms provide a basis for proactive monitoring for psychotropic ADEs.

Cross-Regional Data Initiative for the Assessment and Development of Treatment for Neurological and Mental Disorders.

Purpose: To describe and categorize detailed components of databases in the Neurological and Mental Health Global Epidemiology Network (NeuroGEN). Methods: An online 132-item questionnaire was sent to key researchers and data custodians of NeuroGEN in North America, Europe, Asia and Oceania. From the responses, we assessed data characteristics including population coverage, data follow-up, clinical information, validity of diagnoses, medication use and data latency. We also evaluated the possibility of conversion into a common data model (CDM) to implement a federated network approach. Moreover, we used radar charts to visualize the data capacity assessments, based on different perspectives. Results: The results indicated that the 15 databases covered approximately 320 million individuals, included in 7 nationwide claims databases from Australia, Finland, South Korea, Taiwan and the US, 6 population-based electronic health record databases from Hong Kong, Scotland, Taiwan, the Netherlands and the UK, and 2 biomedical databases from Taiwan and the UK. Conclusion: The 15 databases showed good potential for a federated network approach using a common data model. Our study provided publicly accessible information on these databases for those seeking to employ real-world data to facilitate current assessment and future development of treatments for neurological and mental disorders.

Analysis of potential interactions between warfarin and prescriptions in Estonian outpatients aged 50 years or more / Análisis de las interacciones potenciales entre warfarina y medicamentos prescritos en pacientes ambulatorios mayores de 50 años en Estonia

In Estonia, warfarin is widely prescribed by general practitioners to prevent and treat thromboembolic diseases. To date, there has been no systematic analysis of the potential risk of warfarin interactions with other drugs in the outpatient population. Objective: The aim of the study was to analyze the incidence of potential interactions in prescription schemes in Estonia in a cohort of outpatients receiving warfarin treatment. Methods: The retrospective study population included 203,646 outpatients aged 50 years or older of whom 7,175 received warfarin therapy. Patients who had used at least one prescription drug for a minimum period of 7 days concomitantly with warfarin were analyzed. Potential drug interactions were analyzed using Epocrates online, Stockley’s Drug Interactions and domestic drug interaction databases. Results: The average number of drugs used concomitantly with warfarin was 4.8 (SD=1.9) (males: 4.7 SD=2.0, females: 4.9 SD=2.0). No potential interactions in treatment regimens were found in 38% of patients, one potential interaction was observed in 29% and two or more potential interactions were observed in 33% of patients. The mean number of all potential interactions was 1.2 per patient and about the same in men and women. Potential interactions were associated with the number of drugs. Warfarin-related interactions were detected in 57% of patients, and the number of interactions related to warfarin per patient varied from 1 to 5. Most frequent were use of warfarin with NSAIDs (14%), followed by simvastatin (9%) and amiodarone (7%). Conclusion: This study shows that 57% of outpatients in Estonia receiving warfarin have drugs potentially interacting with warfarin in their treatment schemes. Most interactions (14%) with warfarin are associated with the prescription of NSAIDs (AU)

En Estonia, la warfarina es prescrita por médicos generales para tratar enfermedades tromboembólicas. Hasta la fecha, no se ha realizado un análisis sistemático del riesgo de interacciones potenciales de la warfarina con otros medicamentos en la población ambulatoria. Objetivo: El objetivo de este estudio fue analizar la incidencia de interacciones potenciales en los esquemas prescritos en Estonia en una cohorte de pacientes ambulatorios recibiendo warfarina. Métodos: El estudio retrospectivo incluyó 203.646 pacientes ambulatorios de 50 o más años de los que 7.175 recibían tratamiento con warfarina. Se analizó a los pacientes que usaron como mínimo un medicamento de prescripción por un periodo mínimo de 7 días concomitante con warfarina. Las interacciones potenciales fueron analizadas usando Epocrates online, Stockley’s Drug Interactions, y bases de datos locales de interacciones. Resultados: El numero medio de medicamentos usados concomitantemente con warfarina fue de 4,8 (DE=1,9) (hombres 4,7 DE=2,0; mujeres 4,9 DE=2,0). No se encontraron interacciones potenciales en el 38% de los pacientes, se observó una interacción potencial en el 29%, y se encontraron dos o más interacciones potenciales en el 33% de pacientes. El número medio de interacciones potenciales fue de 1,2 por paciente, prácticamente igual en hombres y en mujeres. Las interacciones potenciales estaban asociadas con el número de medicamentos. Se detectaron interacciones relacionadas con la warfarina en el 57% de los pacientes, y el número de interacciones relacionadas con warfarina varió de 1 a 5. Las más frecuentes fueron el uso de warfarina con AINE (14%), seguidas de sinvastatina (9%) y amiodarona (7%). Conclusión: Este estudio muestra que el 57% de los pacientes ambulatorios que reciben warfarina en estonia tienen medicamentos potencialmente interaccionando con la warfarina en sus esquemas terapéuticos. La mayoría de las interacciones (14%) con warfarina estaban asociadas a los AINE (AU)