A survey of preoperative surgical nutrition practices, opinions, and barriers across Canada
Bibliographic record
Abstract
Malnutrition is prevalent among surgical candidates and associated with adverse outcomes. Despite being potentially modifiable, malnutrition risk screening is not a standard preoperative practice. We conducted a cross-sectional survey to understand healthcare professionals’ (HCPs) opinions and barriers regarding screening and treatment of malnutrition. HCPs working with adult surgical patients in Canada were invited to complete an online survey. Barriers to preoperative malnutrition screening were assessed using the Capability Opportunity Motivation-Behaviour model. Quantitative data were analyzed using descriptive statistics and qualitative data were analyzed using summative content analysis. Of the 225 HCPs surveyed ( n = 111 dietitians, n = 72 physicians, n = 42 allied HCPs), 96%–100% agreed that preoperative malnutrition is a modifiable risk factor associated with worse surgical outcomes and is a treatment priority. Yet, 65% ( n = 142/220; dietitians: 88% vs. physicians: 40%) reported screening for malnutrition, which mostly occured in the postoperative period ( n = 117) by dietitians ( n = 94). Just 42% (48/113) of non-dietitian respondents referred positively screened patients to a dietitian for further assessment and treatment. The most prevalent barriers for malnutrition screening were related to opportunity, including availability of resources (57%, n = 121/212), time (40%, n = 84/212) and support from others (38%, n = 80/212). In conclusion, there is a gap between opinion and practice among surgical HCPs pertaining to malnutrition. Although HCPs agreed malnutrition is a surgical priority, the opportunity to screen for nutrition risk was a great barrier.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".