Nausea and vomiting of pregnancy: what about quality of life?
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to determine the impact of nausea and vomiting of pregnancy (NVP) and other determinants on generic and NVP-specific health-related quality of life (QOL) in the first trimester of pregnancy. DESIGN: Prospective study. SETTING: Centre Hospitalier Universitaire (CHU) Sainte-Justine or René-Laennec clinics, Montreal, Quebec, Canada. POPULATION: Pregnant women attending the clinics for their prenatal care from 2004 to 2006. Women were eligible if they were > or =18 years of age and < or =16 weeks of gestation at the time of their first prenatal visit. METHODS: After their first prenatal visit, women were asked to fill out a questionnaire covering maternal characteristics, presence and severity of NVP, and health-related QOL. MAIN OUTCOME MEASURES: QOL was measured by the generic 12-item Short Form Health Survey v.1 (SF-12) and the NVP-specific Quality of Life for Nausea and Vomiting during Pregnancy. RESULTS: Of the 367 pregnant women included in the study, 78.5% of women reported NVP in the first trimester of pregnancy. Multivariable linear models showed that presence of NVP in the first trimester of pregnancy was significantly associated with a lower physical component summary scale (P < 0.0001) and mental component summary scale (P = 0.0066) of the SF-12 scores. More severe NVP (moderate versus mild: P = 0.0002; severe versus mild: P = 0.0177 as measured by the validated modified Pregnancy-Unique Quantification of Emesis and Nausea index), intensity of nausea symptoms reported on a visual analogue scale (P < 0.0001), and nonpharmacological methods used to ease NVP symptoms in the first trimester of pregnancy (P = 0.0059) were significantly associated with poorer NVP-specific QOL among women suffering from NVP. CONCLUSION: These findings show that presence and severity of NVP have a negative impact on health-related QOL, which emphasises the importance of an optimal management of NVP.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 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".