Measuring Gastric pH in Tube‐fed Children With Neurologic Impairments and Gastroesophageal Disease
Bibliographic record
Abstract
OBJECTIVES: The aim of the study was to determine the extent of agreement between pH paper and handheld pH meter with a laboratory pH meter for gastric pH measurement in children with neurologic impairments and gastrostomy tubes who have gastroesophageal reflux disease (GERD). METHODS: In this prospective observational study, gastric contents were aspirated from gastric or nasogastric tubes and the pH measured using 3 techniques: pH paper, handheld pH meter, and laboratory pH meter (the gold standard). Agreement between techniques was assessed with intraclass correlation coefficient (ICC), Bland-Altman analysis, and kappa statistic. RESULTS: Among 43 patients contributing 67 gastric samples, the ICC was 0.75 (95% confidence interval [CI]: 0.69-0.97) between the handheld and laboratory meters, 0.69 (95% CI: 0.63--0.94) between the pH paper and laboratory meter and 0.69 (95% CI: 0.63-0.94) between the handheld meter and paper. The Bland-Altman analysis between the handheld and lab meters showed a mean difference of -0.03 pH units (limits of agreement: -0.52 to 0.47 pH units) and 0.17 pH units (limits of agreement: -0.99 to 1.33 pH units) between the paper and lab meter. The kappa coefficients for a pH ≥4 were 1.0 (95% CI: 1.0--1.0) between the handheld and lab meters and 0.9 (95% CI: 0.77--1.0) between the paper and lab meter. CONCLUSIONS: The findings suggest that both point-of-care tests, the pH meter and pH paper, correlate well with the gold standard for testing pH with a laboratory pH meter, indicating usefulness in point-of-care testing for monitoring gastric pH in tube-fed children with neurologic impairments and GERD.
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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".