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Record W3020956628 · doi:10.1177/2054358120912652

Prescription Patterns in Dialysis Patients: Differences Between Hemodialysis and Peritoneal Dialysis Patients and Opportunities for Deprescription

2020· article· en· W3020956628 on OpenAlexaffabout
Judith Marin, Laura Beresford, Christine Lo, Alexander Pai, Gabriela Espino-Hernández, Monica Beaulieu

Bibliographic record

VenueCanadian Journal of Kidney Health and Disease · 2020
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsUniversity of British ColumbiaProvidence Health CareSt. Paul's HospitalUniversity of British Columbia Hospital
Fundersnot available
KeywordsMedicineMedical prescriptionPeritoneal dialysisDialysisPolypharmacyHemodialysisInternal medicineKidney diseaseIntensive care medicineRetrospective cohort studyEmergency medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Patients treated with maintenance dialysis are at high risk of polypharmacy given their many comorbidities as well as complications from their disease state and treatment. The prescribing patterns and burden of polypharmacy in patients treated with maintenance dialysis, and specifically the difference between hemodialysis (HD) and peritoneal dialysis (PD) prescribing, are not well characterized. OBJECTIVES: The objectives of this study were to review the prescribing patterns for patients treated with maintenance dialysis, to compare prescribing pattern between HD and PD, and to identify opportunities for deprescription. DESIGN: This is a retrospective cohort study. SETTING: This study was conducted in all dialysis centers in British Columbia, Canada. PATIENTS: Patients who were receiving chronic dialysis (>120 days on the same dialysis modality) between June 3 and October 1, 2015, and registered in the British Columbia (BC) Renal Patient Records and Outcomes Management Information System. MEASUREMENTS: value of <.05 was considered statistically significant. METHODS: Medications were classified by indication: (1) management of renal complications, (2) cardiovascular (CV) medications, (3) diabetes medications, or (4) management of symptoms, and then classified as to whether they were a "potentially inappropriate medication" (PIM) or not. Ethics approval was granted from the University of British Columbia Research and Ethics Board. RESULTS: In total, 3017 patients met inclusion criteria (2243 HD, 774 PD). The mean age was 66.2 ± 14.8 years. The HD group had more patients over 80 years old (22.1% vs 12.5%) and more patients with diabetes and CV disease. The mean number (standard deviation [SD]) of discrete prescribed medications was 17.71 (5.72) overall with more medications in the HD group versus the PD group. The mean number of medications increased with dialysis vintage in both groups. HD patients were on more medications for renal complications and management of symptoms than PD patients. Of the total number of medications prescribed, 5.02 (2.78) were classified as a PIM, with the number of PIMs higher in HD vs PD patients: 5.37 (2.83) versus 4.02 (2.37). LIMITATIONS: In BC, some of the medications are prescribed through standardized protocols and may not be comparable with other Canadian provinces. We report here prescribing patterns, not utilization patterns, as we are not able to ascertain actual consumption of prescribed medication. CONCLUSION: This study reviews and characterizes both the prescription and non-prescription medication prescribed to HD patients and PD patients in BC. Pill burden in both groups is high, as is the prescription of PIMs. Patients receiving maintenance HD receive more overall medications and more PIMs. These results highlight areas of opportunities for future systematic and patient-informed deprescription initiatives in both patient groups.

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)0.000
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 score0.043
Threshold uncertainty score0.630

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.047
GPT teacher head0.258
Teacher spread0.211 · 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

Citations47
Published2020
Admission routes2
Has abstractyes

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Same venueCanadian Journal of Kidney Health and DiseaseSame topicDialysis and Renal Disease ManagementFrench-language works237,207