Tension–Time Index as a Predictor of Extubation Outcome in Ventilated Children
Bibliographic record
Abstract
RATIONALE: Indices that assess the load on the respiratory muscles, such as the tension-time index (TTI), may predict extubation outcome. OBJECTIVES: To evaluate the performance of a noninvasive assessment of TTI, the respiratory muscle tension time index (TTmus), by comparison to that of the diaphragm tension time index (TTdi) and other predictors of extubation outcome in ventilated children. METHODS: Eighty children (median [range] age 2.1 yr [0.15-16]) admitted to pediatric intensive care units at King's College and St Mary's Hospitals who required mechanical ventilation for more than 24 hours were studied. MEASUREMENTS AND MAIN RESULTS: TTmus, maximal inspiratory pressure, respiratory drive, respiratory system mechanics, and functional residual capacity using a helium dilution technique, the rapid shallow breathing and CROP indices (compliance, rate, oxygenation, and pressure) indexed for body weight were measured and standard clinical data recorded in all patients. TTdi was measured in 28 of the 80 children using balloon catheters. Eight children (three in the TTdi group) failed extubation. TTmus (0.199 vs. 0.09) and TTdi (0.157 vs. 0.07) were significantly higher in children who failed extubation. TTmus greater than 0.18 (n = 80) and TTdi greater than 0.15 (n = 28) had sensitivities and specificities of 100% in predicting extubation failure. The other predictors performed less well. CONCLUSIONS: Invasive and noninvasive measurements of TTI may provide accurate prediction of extubation outcome in mechanically ventilated children.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".