IMPACT OF THE COVID-19 PANDEMIC ON THE INITIATION OF ANTIHYPERTENSIVE DRUG THERAPY IN FRANCE
Bibliographic record
Abstract
Objective: The objective was to analyze time-trends in the rates of patients who had at least one reimbursement of an antihypertensive drug without reimbursement in the past 12 month for each year from 2017 to 2021, and to study changes according to sex, age, history of cardiovascular diseases, group of antihypertensive drugs and lockdown/curefew periods. Design and method: We used data from the French national healthcare database (“Systéme National des données de Santé”-SNDS) covering 99% of the French population. For each year and weeks from 1st January 2017 to 23 of May 2021, patients who initiated an antihypertensive drug treatment in France were selected. Crude and age-standardized rates of patients initiating an antihypertensive drug in overall population living in France were calculated and compared with the 2017–2019 incidence with incidence rate ratio (IRR) adjusted for age and time-trends. Consultations (with general practitioner (GP) or cardiologist) were also recorded over the study period Results: In 2020, 1,518,686 persons initiated an antihypertensive therapy in France which was less than the mean number 2017–2019 (n = 1,549,215). The age-standardized incidence in the French population were 2.2% for 2017, 2.3% for 2018, 2.4% for 2019 and 2.2% for 2020. The initiation of an antihypertensive treatment declined by 11% in 2020 as compared to 2017–2019 (reaching -30% during the first national lockdown), with a major differences between men (-5%) and women (-16%), and age groups (-2% in people aged < 45 years old, and -17% in more than 85 years). A similar decline was found between people with a personal history of cardiovascular disease and those without. Among antihypertensive treatments, the greater decrease in the initiation was observed for diuretics (-20%) and ARBs (-19%). In 2021, initiation of antihypertensive drugs were still diminished compared to 2017–2019 but in a lower extent (-4%). An increase was even observed in the youngest age group (+6%) and in men (+4%). Conclusions: The pandemic had a major impact on the initiation of antihypertensive drugs and therefore the incidence and/or screening of hypertension with an important age and sex effect and no catch-up effect was observed in 2021.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".