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Record W3010712810 · doi:10.1186/s12877-020-1430-6

Self-reported medication in community-dwelling older adults in Germany: results from the Berlin Initiative Study

2020· article· en· W3010712810 on OpenAlexaff
Nina Mielke, Dörte Huscher, Antonios Douros, Natalie Ebert, Jens Gaedeke, Markus van der Giet, Martin K. Kuhlmann, Peter Martus, Elke Schäeffner

Bibliographic record

VenueBMC Geriatrics · 2020
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical Practices and Patient Outcomes
Canadian institutionsMcGill UniversityJewish General Hospital
Fundersnot available
KeywordsPolypharmacyMedicineCohortMedical prescriptionGeriatricsDemographicsPopulationCohort studyGerontologyDemographyInternal medicinePsychiatryEnvironmental healthPharmacology

Abstract

fetched live from OpenAlex

BACKGROUND: Older adults have the highest drug utilization due to multimorbidity. Although the number of people over age 70 is expected to double within the next decades, population-based data on their medication patterns are scarce especially in combination with polypharmacy and potentially inappropriate medication (PIM). Our objective was to analyse the frequency of polypharmacy, pattern of prescription (PD) and over-the-counter (OTC) drug usage, and PIMs according to age and gender in a population-based cohort of very old adults in Germany. METHODS: Cross-sectional baseline data of the Berlin Initiative Study, a prospective cohort study of community-dwelling adults aged ≥70 years with a standardized interview including demographics, lifestyle variables, co-morbidities, and medication assessment were analysed. Medication data were coded using the Anatomical Therapeutic Chemical (ATC) classification. Age- and sex-standardized descriptive analysis of polypharmacy (≥5 drugs, PD and OTC vs. PD only and regular and on demand drugs vs regular only), medication frequency and distribution, including PIMs, was performed by age (</≥80) and gender. RESULTS: Of 2069 participants with an average age of 79.5 years, 97% (95%CI [96%;98%]) took at least one drug and on average 6.2 drugs (SD = 3.5) with about 40 to 66% fulfilling the criteria of polypharmacy depending on the definition. Regarding drug type more female participants took a combination of PD and OTC (male: 68%, 95%CI [65%;72%]); female: 78%, 95%CI [76%;80%]). Most frequently used were drugs for cardiovascular diseases (85%, 95%CI [83%;86%]). Medication frequency increased among participants aged ≥80 years, especially for cardiovascular drugs, antithrombotics, psychoanaleptics and dietary supplements. Among the top ten prescription drugs were mainly cardiovascular drugs including lipid-lowering agents (simvastatin), beta-blockers (metoprolol, bisoprolol) and ACE inhibitors (ramipril). The most common OTC drug was acetylsalicylic acid (35%; 95%CI [33%;37%])). Dose-independent PIM were identified for 15% of the participants. CONCLUSIONS: Polypharmacy was excessive in older adults, with not only PD but also OTC drugs contributing to the high point prevalence. The medication patterns reflected the treatment of chronic diseases in this age group. There was even an increase in medication frequency between below and above 80 years especially for drugs of cardiovascular diseases, antithrombotic medication, psychoanaleptics, and dietary supplements.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.092
Threshold uncertainty score0.479

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.173
GPT teacher head0.386
Teacher spread0.212 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations30
Published2020
Admission routes1
Has abstractyes

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