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Record W4413284211 · doi:10.1227/neu.0000000000003713

In Reply: Optimal Tracheostomy Timing After Traumatic Complete Spinal Cord Injury: A Comparative Analysis of Ultraearly, Early, and Delayed Practice

2025· article· en· W4413284211 on OpenAlexaff
Ahmad Essa, Armaan K. Malhotra, Eva Y. Yuan, Christopher D. Witiw

Bibliographic record

VenueNeurosurgery · 2025
Typearticle
Languageen
FieldMedicine
TopicTracheal and airway disorders
Canadian institutionsSt. Michael's HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineNeurosurgeryIntensive care unitTracheotomySpinal cord injuryMechanical ventilationSurgerySpinal cordAnesthesiaIntensive care medicine

Abstract

fetched live from OpenAlex

To the Editor: We sincerely thank Dr Feng and Dr Jiang1 for their thoughtful commentary on our article, “Optimal Tracheostomy Timing After Traumatic Complete Spinal Cord Injury: A Comparative Analysis of Ultraearly, Early, and Delayed Practice.”2 We are encouraged that our findings have generated academic dialog and appreciate the opportunity to address the points raised. Regarding the definitions of tracheostomy timing, we agree that standardization across studies would improve consistency and comparability.1 In our study, we defined ultraearly tracheostomy as ≤3 days postsurgery, early as 4-7 days, and delayed as >7 days. The results showed that both ultraearly and early tracheostomy were associated with significantly lower in-hospital complications, shorter intensive care unit and hospital lengths of stay, and reduced mechanical ventilation duration compared with delayed tracheostomy. Moreover, outcomes were comparable between the ultraearly and early groups, suggesting flexibility in timing within the first postoperative week.2 We appreciate the concern raised about early tracheostomy after anterior cervical spine surgery due to the perceived risk of wound contamination or hardware infection.1 To address this, we conducted a secondary analysis adjusting for surgical approach using a similar multivariable model to the primary analysis. The findings remained consistent, indicating that early tracheostomy did not increase the risk of surgical site infection, even among patients undergoing anterior or combined approaches. These results align with a previous study performed by our group published in Neurosurgery,3 as well as other studies cited by Dr Feng and Dr Jiang4,5 These studies add to the growing body of evidence that early tracheostomy can be safely performed after anterior cervical spine surgery. We also acknowledge the limitation noted regarding tracheostomy technique.1 The data set we used did not distinguish whether tracheostomies were performed percutaneously or by open surgical approach. The Trauma Quality Improvement Program used International Classification of Disease-9 procedure codes through 2016-2017 and transitioned to International Classification of Disease-10 codes thereafter, limiting our ability to consistently differentiate tracheostomy technique across the full data set. However, in a separate study by our group evaluating the association between tracheostomy timing and spinal surgical approach, we were able to account for tracheostomy technique.3 In that analysis, which compared early (≤7 days) vs late (>7 days) tracheostomy while adjusting for both spine and tracheostomy approaches (percutaneous vs open), early tracheostomy remained associated with favorable outcomes. In summary, we appreciate the detailed appraisal of our work by Dr Feng and Dr Jiang and recognize their call for prospective, ideally randomized studies to better establish causality and refine optimal tracheostomy timing in this population. We share the authors' commitment to advancing care for patients with traumatic spinal cord injury and welcome ongoing dialog in this important area.

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 imitation

Not 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.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.098
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.012
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.098
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0020.002
Scholarly communication0.0020.004
Open science0.0030.001
Research integrity0.0120.015
Insufficient payload (model declined to judge)0.0050.002

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.

Opus teacher head0.047
GPT teacher head0.356
Teacher spread0.309 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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