Complication rates of open surgical versus percutaneous tracheostomy in critically ill patients
Bibliographic record
Abstract
BACKGROUND: In the setting of critical care, the most common indications for tracheostomy include: prolonged intubation, to facilitate weaning from mechanical ventilation, and for pulmonary toileting. In this setting, tracheostomy can be performed either via open surgical or percutaneous technique. Advantages for percutaneous dilatational tracheostomy (PDT) include: simplicity, smaller incision, less tissue trauma, lower incidence of wound infection, lower incidence of peristomal bleeding, decreased morbidity from patient transfer, and cost-effectiveness. Despite many studies comparing surgical tracheostomy (ST) versus PDT, there remains no consensus on which of these techniques minimizes complications in critically ill patients. PURPOSE: To provide an updated meta-analysis to answer the following question: Is there a difference in complication rates between ST and PDT in the setting of critically ill patients? Our secondary outcome of interest was to examine the difference in procedure time in the ST versus PDT groups. METHODS: We conducted a literature search using the following databases: Ovid MEDLINE, Embase, Google Scholar, and Cochrane Database of Systematic Reviews. Studies from 1985 until October 2014 published in French or English languages in peer-reviewed journals were included. RESULTS: With regard to rates of mortality, intraoperative hemorrhage, and postoperative hemorrhage, there was no statistically significant difference between the two techniques. Evaluation of infections rates and operative time, however, revealed a statistically significant difference, favoring PDT over ST. CONCLUSION: In critically ill patients, PDT appears to be a safe and efficient alternative to open ST. LEVEL OF EVIDENCE: NA Laryngoscope, 126:2459-2467, 2016.
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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 | 0.007 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.009 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".