Bibliographic record
Abstract
BACKGROUND: The present study aimed to explore the consultation prevalence, differential diagnoses, and management of patients presenting with nausea or vomiting to their family doctors. METHODS: Cross-sectional data were collected from randomly selected patients during the SESAM 2 study (October 1, 1999 to September 30, 2000). We contacted 2510 doctors; 270 (10.8%) of them participated in the study. Data were collected from randomly selected patients previously known to the general practitioner. Unpublished but publicly available data from the Dutch Transition Project were also analysed. RESULTS: One hundred and sixty-nine of the total 8874 patients consulted their general practitioner for nausea/vomiting; 97 (57.4%) were female and 72 (42.6%) were male. Most patients suffering from nausea or vomiting in general practice were aged between 15 and 64 years. Nearly all patients were given a physical examination. Most diagnoses were made without further investigation, additional diagnostic procedures were found to be necessary in only 7 patients. Drugs were prescribed as the most frequent form of medical treatment, in 76.3% of cases. Non-infectious gastroenteritis or colitis was the most frequent diagnosis. Nausea or vomiting was associated with diarrhoea, fever, and abdominal pain. Headache, general weakness, and epigastric pain were also statistically significantly associated with nausea or vomiting. CONCLUSIONS: Many disorders cause nausea or vomiting. Although most of the patients were diagnosed with non-infectious gastroenteritis or colitis, the general practitioner also has to bear in mind that nausea and vomiting may be alarm symptoms. Medication was prescribed in most of the cases and there were only a few referrals to a specialist or hospital. Life-threatening disorders (appendicitis, bowel obstruction/ileus) were found in a few cases presenting with nausea or vomiting. KEYWORDS: Nausea; Vomiting; General practice; Primary care.
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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 | 0.000 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".