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Record W7006623723

Trends and Appropriateness of Sodium-glucose Co-transporter 2 Inhibitors Use in Qatar

2023· dissertation· en· W7006623723 on OpenAlexaboutno aff

Bibliographic record

VenueQatar University QSpace (Qatar University) · 2023
Typedissertation
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedical prescriptionContraindicationRetrospective cohort studyDosingFormularyMetforminConfidence intervalDrug Utilization Review
DOInot available

Abstract

fetched live from OpenAlex

Background: Sodium glucose co-transporter 2 inhibitors (SGLT2is) are the most recently approved class of oral antidiabetic drugs (ADDs). The objective of this study was to explore the trends in the use of SGLT2is compared to other oral ADDs, to evaluate the appropriateness of prescribing SGLT2is, and to determine the factors associated with SGLT2is prescribing in Qatar. Methods: This is a two-phase study. Phase 1 was a descriptive, retrospective crosssectional study, where relevant data on all oral ADDs prescriptions from 2016 to 2020 in Hamad Medical Corporation (HMC) were collected. Phase 2 was an analytical, retrospective cross-sectional study, and it included patients newly initiated on SGLT2is and/or other oral ADDs during 2020. Prescriptions of patients newly initiated on SGLT2is (dapagliflozin and empagliflozin) were evaluated for appropriateness based on indication, dosage, and contraindication according to American and the Canadian labelling standards. Multivariable logistic regression analysis was conducted to investigate factors associated with prescribing SGLT2is. Results: SGLT2i prescriptions increased over the years after their introduction to HMC’s formulary in 2017. Consistently, sulfonylurea prescriptions declined between 2017 and 2020. Empagliflozin prescribing showed an increase over dapagliflozin, which decreased by the end of 2018. SGLT2is were prescribed for appropriate indication in 400 (100%) patients studied, while inappropriate dosing was found in 13 (3%) patients. Male gender (odds ratio [OR], 1.692; 95% confidence interval [CI], 1.015 to 2.822; P=0.044), patients with a baseline glycated hemoglobin (HbA1c) >7% (OR, 3.219; 95% CI, 1.838 to 5.637; P<0.001) and atherosclerotic cardiovascular disease (ASCVD) (OR, 2.182; 95% CI, 1.053 to 4.523), patients on metformin (OR, 7.556; 95% CI, 4.460 to 12.802; P<0.001), sulfonylureas (OR, 2.301; 95% CI, 1.160 to 4.563; P=0.017), and dipeptidyl peptidase 4 inhibitors (DPP4is) (OR, 3.430; 95% CI, 2.004 to 5.871; P<0.001) were more likely to be prescribed a SGLT2i. Conversely, patients with chronic kidney disease (CKD) were less likely to be prescribed a SGLT2i (OR, 0.359; 95% CI, 0.148 to 0.872; P=0.024). Conclusion: SGLT2is have largely replaced sulfonylureas in clinical practice in Qatar, with a greater utilization for empagliflozin over dapagliflozin. SGLT2is were very likely to be prescribed for an appropriate indication. Gender, baseline HbA1c level, history of ASCVD, history of CKD, and the use of metformin, sulfonylureas, or DPP4is were associated with initiating SGLT2is. Exploring the prescribing pattern of oral ADDs and how their trend was affected by the addition of SGLT2is, as well as evaluating the appropriate usage of this class based on indication, dosing, and contraindication is necessary. Further detailed investigation of the factors associated with prescribing SGLT2is at the patient-, provider-, and hospital- level may help to get a more comprehensive evaluation of the possible predictors for prescribing these novel agents.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.451
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.014
GPT teacher head0.215
Teacher spread0.201 · 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.

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

Citations0
Published2023
Admission routes1
Has abstractyes

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