Antihypertensive Medication Use Trajectories After Bariatric Surgery: A Matched Cohort Study
Bibliographic record
Abstract
BACKGROUND: Metabolic and bariatric surgery (MBS) is the most effective and durable treatment for obesity. We aimed to compare the trajectories of antihypertensive medication (AHM) use among obese individuals treated and not treated with MBS. METHODS: Adults with a body mass index of ≥35 kg/m 2 were identified in the Merative Database (US employer-based claims database). Individuals treated with versus without MBS were matched 1:1 using baseline demographic and clinical characteristics as well as AHM utilization. Monthly AHM use was examined in the 3 years after the index date using generalized estimating equations. Subanalyses investigated rates of AHM discontinuation, AHM initiation, and apparent treatment-resistant hypertension. RESULTS: The primary cohort included 43 206 adults who underwent MBS matched with 43 206 who did not. Compared with no MBS, those treated with MBS had sustained, markedly lower rates of AHM use (31% versus 15% at 12 months; 32% versus 17% at 36 months). Among patients on AHM at baseline, 42% of patients treated with MBS versus 7% treated medically discontinued AHM use ( P <0.01). The risk of apparent treatment-resistant hypertension was 3.41× higher (95% CI, 2.91–4.01; P <0.01) 2 years after the index date in patients who did not undergo MBS. Among those without hypertension treated with MBS versus no MBS, 7% versus 21% required AHM at 2 years. CONCLUSIONS: MBS is associated with lower rates of AHM use, higher rates of AHM discontinuation, and lower rates of AHM initiation among patients not taking AHM. These findings suggest that MBS is both an effective treatment and a preventative measure for hypertension.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".