Nutrition scores and MUAC of adult surgical orthopaedic inpatients at a teaching hospital in Lusaka province, Zambia
Bibliographic record
Abstract
Abstract Background Poor nutrition status among hospitalised patients has been shown to increase length of hospital stay, as well as contribute to increased morbidity and mortality. The purpose of the study was to evaluate the nutrition status of adult surgical orthopaedic patients attending a teaching hospital in Zambia. Methods This study adopted a hospital-based cross-sectional study design to collect data from 98 adult patients aged 18 - 64 years. A structured questionnaire, the Subjective Global Assessment (SGA) tool, mid-upper arm circumference (MUAC) tape were used to collect data during the study period of three months in 2015. Results The mean age of the patients was 36.4 plus or minus 9.44 years, while the mean length of hospital stay was 17.33 plus or minus 10.91 days. Nutrition-focused physical examination revealed that majority (89.8%) of the patients were of acceptable weight with no weight loss reported in 70.4% of the patients. Poor appetite was only reported by 10.2% of the patients. SGA findings suggest that most of the patients (79.6%) were well-nourished. The mean mid-upper arm circumference of the study participants during hospitalization was 25.09 plus or minus 2.85 cm. An association was found between length of hospital stay and mid-upper arm circumference of the patients (p<0.001). Conclusion Subjective Global Assessment has the potential to evaluate the nutrition status of surgical patients in resource-poor settings such as Zambia. However, the use of SGA should be supplemented by other tools such as MUAC which has the potential to screen for adult malnutrition in clinical settings with limited resources.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".