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Determinants of adherence among patients with hypertension

2024· article· en· W4403822158 on OpenAlexaboutno aff
Katarzyna Lomper, Marta Wleklik, Anna Chudiak, Grzegorz Mazur, I Uchmanowicz

Bibliographic record

VenueEuropean Heart Journal · 2024
Typearticle
Languageen
FieldPsychology
TopicHealth and Well-being Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineInternal medicineIntensive care medicine

Abstract

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Abstract Background Poor adherence to pharmacological treatment among patients with hypertension (HTN) is common. Approximately half of HTN patients do not use their medications as prescribed. Multiple barriers can influence adherence to antihypertensive medications. HTN patients may be characterized by the presence of frailty syndrome (FS) and cognitive impairment (CI). FS and CI may adversely affect the course of the disease and adherence to therapeutic recommendations. Purpose To assess the adherence and its determinants among patients with hypertension. Methods The study included 129 patients diagnosed with hypertension (81 men, 48 women; mean age M±SD=69.98±11.67) hospitalized in the Department of Occupational Diseases and Hypertension. Medical record analysis, the author's sociodemographic questionnaire, the Tilburg Frailty Idicator (TFI) to determine the presence of frailty syndrome, the Montreal Cognitive Assesment (MoCa) questionnaire to assess cognitive function, and the Adherence to Medication Scale (ARMS) to assess adherence were used. Results The majority of respondents were male (62.79%), living in large cities (31.78%), in a relationship (61.24%), with a high school education (68.22%), and retired (67.44%). Analysis of medical records among comorbidities showed diabetes (59.69%) and other cardiovascular diseases (58.91%) to be the most common. Hospitalizations due to hypertension within the past year in the range of 1-2 were reported in 72.09% of the subjects, 3-5 hospitalizations in 17.05%, and more than 5 hospitalizations in 10.85% subjects. The surveyed patients mostly kept self-monitoring diaries (61.24%), measured their blood pressure values 2-3 times a day (58.15%) with an upper arm blood pressure monitor (64.34%). In terms of self-care behaviors, respondents most often indicated following a diet with a restriction of unhealthy fats (52.71%), following a low-sodium diet (44.19%) and being physically active (33.33%). The mean blood pressure values in the study group were M±SD=139.73±16.73 mmHg for SBP and M±SD=81.48±13.25 mmHg for DBP, respectively. On the basis of the TFI, 99.22% of patients showed the presence of FS (M±SD =10.66±2.82), the MoCa questionnaire indicated abnormal values in cognitive function in 79.07% (M±SD =18.16±8.3). The average adherence ARMS score was M±SD 17,6±6,72 pcts. (higher the ARMS score the worse adherence). Univariate analysis as determinants of adherence showed unemployment (b=9.391;p=0.001), smoking (b=6.701;p=0.001), duration of illness (b=-0.153;p=0.003), 3-5 hospitalizations in the past year (b=3.891;p=0.014). Multivariate analysis among determinants of adherence showed unemployment (b=7.556;p=0.022), duration of illness (b=-0.167;p=0.002) and 3-5 hospitalizations (b=5.011;p=0.001). Conclusion Hypertensive patients are characterized by optimal adherence. Despite expectations, cognitive impairment and frailty syndrome did not determine adherence to medications.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
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)0.0030.000

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 head0.046
GPT teacher head0.331
Teacher spread0.285 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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