Assessing and predicting successful tube placement outcomes in ALS patients
Bibliographic record
Abstract
This study reviews feeding tube placement outcomes in 69 ALS outpatients seen at an outpatient interdisciplinary ALS clinic in British Columbia, Canada. The objective was to determine at which point the risks outweigh the benefits of tube placement by reviewing outcomes against parameters of respiratory function, nutritional status and speech and swallowing deterioration. The study was a retrospective review of tube placements between January 2000 and 2005, analysing data on respiratory function (forced vital capacity and respiratory status), weight change from usual body weight (UBW) and speech/swallowing deterioration using ALS Severity Score ratings (Hillel et al., 1989) at time of tube placement. Results show a statistically significant association between nutritional status and successful tube placement outcomes (p=0.003), and none between respiratory status, speech/swallowing variables, or number of deteriorated variables in each patient. Study findings were impacted by lack of available respiratory data. The only study variable that predicted successful tube placement outcome was a body weight greater than or equal to 74% UBW at time of tube placement. In the absence of access to respiratory testing, the relatively simple assessment of weight may assist patients and caregivers in appropriate decisions around tube placement.
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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 | 0.007 |
| 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 | 0.001 | 0.001 |
| 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".