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Record W4392123220 · doi:10.3233/jrs-230004

Assessment of drug utilization and potentially inappropriate medications in hemodialysis patients with end-stage renal dysfunction: A study in a tertiary care hospital in Bahrain

2024· article· en· W4392123220 on OpenAlexaboutno aff
Kannan Sridharan

Bibliographic record

VenueInternational Journal of Risk & Safety in Medicine · 2024
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePolypharmacyRegimenHemodialysisInternal medicineAllopurinolDialysisIntensive care medicineEnd stage renal disease

Abstract

fetched live from OpenAlex

BACKGROUND: Patients undergoing dialysis pose therapeutic challenges in terms of polypharmacy, administration of potentially inappropriate drugs, and drugs with the potential risk of toxicity. OBJECTIVE: This study evaluated the use of drugs, potentially inappropriate medicines (PIM), drugs with risk of Torsades de Pointes (TdP), and the complexity of the prescribed regimen using the medication regimen complexity index scale in patients undergoing hemodialysis. METHODS: A retrospective cohort study was carried out amongst patients receiving hemodialysis. Drugs were classified into one of four classes: (i) drugs used in managing renal complications, (ii) cardiovascular drugs, (iii) anti-diabetic drugs, (iv) drugs for symptomatic management, and (v) others. Drugs were considered as PIM according to the Can-SOLVE CKD working group from a network of Canadian nephrology health professionals. The study adhered to the CredibleMeds classification of drugs with known, possible, and conditional risk of TdP and the complexity of prescribed medicines was evaluated based on the pre-validated medication regimen complexity index scale based on form/route, frequency of dosing, and requirement of special instructions. RESULTS: Sixty-three participants were included in the study (49 males and 14 females) with the median (range) age of 45 (21-66) years. Cardiovascular drugs followed by drugs used for managing renal complications were the most common classes administered. Notably, 12 (19.1%) patients received one of the non-steroidal anti-inflammatory drugs, 21 (33.3%) received a proton pump inhibitor, three (4.8%) received pregabalin, two (3.2%) received opioid drugs, and one (1.6%) was administered celecoxib. Atorvastatin, furosemide, omeprazole, and allopurinol were the most common PIM drugs administered to the study participants followed by others. Drugs used for symptomatic management had significantly more PIM compared to other classes (p < 0.0001). Six (9.5%) patients received drugs with known TdP risk, one with possible TdP risk, and 61 with conditional risk. Median (range) medical regimen complexity index score was 26.5 (2-62.5). CONCLUSION: A huge burden of drug therapy was observed in the hemodialysis patients in terms of higher proportions of PIM, complex medical regimen, and prescription of drugs with risk of TdP. Implementation of clinical decision support tools enhancing rational prescription and identification of drugs with TdP risk, introducing antimicrobial stewardship, and stepwise deprescription of the drugs with the least benefit-risk ratio are warranted.

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)0.001
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 score0.027
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.289
Teacher spread0.283 · 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".

Quick stats

Citations2
Published2024
Admission routes1
Has abstractyes

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