Implementation of BMI field charts for nutritional assessment in adult patients with tuberculosis in Karnataka
Bibliographic record
Abstract
BACKGROUND We tested the operational feasibility of body mass index (BMI) field charts in nutritional assessment of adult patients with tuberculosis (PwTB), which obviate calculations and provide nutritional status based on BMI and the ideal weight (BMI = 21 kg/m 2 ). METHODS We trained primary health care providers (HCPs) in 39 primary health centres for nutritional assessment and classification and identifying the ideal weight using BMI field charts in PwTB. Using the descriptive statistics method, we analysed the collected data and reported the nutritional status in PwTB and the uptake of the field charts among the HCPs. RESULTS The median (interquartile range [IQR]) weight and BMI were 44 kg (37.0, 50.0) and 16.9 kg/m 2 (15.2, 18.9), respectively, in 214 PwTB, of which 146 (68.2%) patients had a BMI of <18.5 kg/m 2 . The HCPs documented the ideal weight in 155 (72.4%) patients, which was correct in 147 (94.8%) patients. The median (IQR) weight deficit to achieve the ideal weight was 10.4 kg (7.3, 12.8) in men and 11.9 kg (7.0, 17.9) in women. For a BMI of 18.5 kg/m 2 , the deficit was 6.4 kg (3.4, 8.5) in men and 11.3 kg (4.6, 13.6) in women. CONCLUSION The magnitude and severity of undernutrition in adult PwTB in a well-performing district of Karnataka in South India were high. A single training session successfully improved nutritional assessment and BMI field chart usage among the primary HCPs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".