Does the treatment of gastroesophageal reflux disease (GERD) meet patients’ needs? A survey‐based study
Bibliographic record
Abstract
OBJECTIVE: Symptoms of gastroesophageal reflux disease (GERD) affect approximately 20% of people on a weekly basis. A number of different therapies are prescribed to control the disease. This survey-based study was carried out to assess patients' and physicians' perceptions of GERD and its treatment. METHODS: Randomly selected general practitioners (GPs) from five countries (USA, UK, Japan, Germany and France) took part in a faceto-face interview, using a standard questionnaire, concerning the last four GERD patients (those taking GERD medication) who had consulted them and who consented to be interviewed. Those patients were then interviewed via telephone, also using a standard questionnaire. RESULTS: Completed questionnaires were available for 927 of the 1044 patients who were identified. The mean length of time that patients suffered GERD symptoms prior to consultation was more than 1.5 years, with 52.3% of those consulting a GP stating the reason they sought medical attention was that 'symptoms were too uncomfortable to bear'. Only 36% of patients receiving prescription therapy reported that they were currently asymptomatic; 20.5% of patients were also taking at least one over-the-counter (OTC) medication. CONCLUSIONS: In the primary care setting, many patients receiving GERD therapy do not have fully controlled symptoms. It is recommended that GPs question patients routinely about persistent symptoms on therapy, and OTC use, in order that effective treatment choices are made in the management of GERD.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".