Comparison of Valvulopathy Risk with Lorcaserin and Phenterminetopiramate for Weight Loss
Bibliographic record
Abstract
Background: Lorcaserin and phentermine-topiramate are two drugs marketed for obesity that have shown moderate efficacy after one year of use. However, concerns over risks of serious cardiovascular harms including valvulopathy have been brought up for both drugs, prompting an epidemiologic investigation to quantify this adverse outcome using real-world clinical data. </P><P> Objective: To compare rates of valvulopathy between the weight-loss drugs lorcaserin and phentermine-topiramate. </P><P> Methods: A retrospective cohort study using the PharMetrics database from the United States was conducted. From approximately 9 million subjects captured in the database from 2006 to 2016, we identified all patients who had received at least one prescription for lorcaserin or phentermine-topiramate. Users of either drug were followed to the first mutually exclusive diagnosis of non-congenital valvulopathy defined as having received an international classification for diseases, ninth revision clinical modification [ICD-9- CM] code for valvulopathy, or to the end of the study period. A Cox Proportional Hazards model was then constructed to compute adjusted hazard ratios (HRs) to compare the rates of valvulopathy between users of the two drugs. </P><P> Results: We identified 1,981 lorcaserin users and 1,806 phentermine-topiramate users. Rates of valvulopathy for lorcaserin and phentermine-topiramate cohorts were 26 and 24 per 1000-person-years, respectively. The crude and adjusted hazard ratios (HRs) comparing the two cohorts with respect to valvulopathy were 1.28 (95% CI: 0.73,2.26) and 1.16 (95% CI: 0.65-2.05), respectively. </P><P> Conclusion: Our analysis suggests comparable rates of valvulopathy between lorcaserin and phentermine-topiramate users. Clinicians are advised to consider the risk of valvular disease when medically managing obesity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".