Mechanical insufflation-exsufflation for the prevention and treatment of respiratory complications in acute cervical spinal cord injury: A retrospective service evaluation
Bibliographic record
Abstract
Background A cervical spinal cord injury (CSCI) is a life-changing event resulting in neurological weakness. Acutely, respiratory complications are the leading cause of mortality. Mechanical insufflation-exsufflation (MI-E) is used to augment cough and promote airway clearance in the prevention and treatment of respiratory complications in this population. The incidence of respiratory complications in subjects with CSCI who receive MI-E is not widely reported. Objectives To report on the incidence of respiratory complications and to evaluate the clinical application of MI-E in subjects with acute traumatic CSCI. Methods This was a retrospective case note review. Data was collected for subjects with a traumatic CSCI admitted to a U.K. major trauma centre between January 2017 and September 2018. The incidence of respiratory complications on admission and 3 weeks post-admission were collected. Where used, detail relating to MI-E clinical application was recorded. Results 33 subjects were eligible for inclusion. The overall incidence of respiratory complications was 21% (7/33). There was no significant difference in occurrence of respiratory complications between those who received MI-E and those who did not. There was a significant difference in the clinical application of therapeutic MI-E compared to prophylactic MI-E. The ‘number of cycles’ and ‘exhale pressure’ settings were found to be significantly greater in those receiving therapeutic treatment (p = <0.001; p = 0.002 respectively). Reporting of other MI-E parameters and treatment detail was poor. Conclusion Whilst the findings of this review may suggest that MI-E provides no additional benefit in the prevention of respiratory complications following acute traumatic CSCI, firm conclusions cannot be drawn due the small sample and poor treatment detail reporting. Further incidence reporting in a multi-site study, including those with thoracic injuries is warranted.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".