Hypoxic-ischemic spinal cord injury following resuscitated cardiac arrest: a case series and rapid literature review
Bibliographic record
Abstract
PURPOSE: Cardiac arrest can cause hypoxic-ischemic injury and result in both spinal cord injury and death determination by neurologic criteria (DNC). The presence and severity of hypoxic-ischemic spinal cord injury (HISCI) impacts neuro-prognostication, rehabilitation, and may confound DNC evaluation in patients by interfering with motor responses and respiratory muscle function in apnea testing. We describe five children with postarrest HISCI detected on magnetic resonance imaging (MRI) and supplement our observations with a literature review. CLINICAL FEATURES: Postarrest HISCI was identified in five consecutive pediatric cases of prolonged cardiac arrest and hypoxic-ischemic brain injury in a single centre. All patients had cardiopulmonary resuscitation for > 30 min and resultant severe hypoxic-ischemic brain injury. Spinal MRI indications were loss of rectal tone (n = 3), focal deficit (n = 1), and practice change related to recent cases (n = 1). A rapid review of the literature yielded case reports, case series, and retrospective reviews describing 90 patients (81 adults; nine pediatric) with postarrest HISCI. Ischemia distribution was variable, most frequently reported at the cervical and thoracic levels, although some patients had ischemia of the entire cord. Paraplegia was the most common deficit among survivors. There were no reports of HISCI in patients who underwent assessment for DNC. CONCLUSIONS: This case series and rapid literature review highlights that both adults and children may be at risk of HISCI after prolonged cardiac arrest. Our findings suggest that further research should focus on determining the incidence and sequelae of HISCI after resuscitated cardiac arrest, as well as evaluating its potential impact on DNC practice and neuro-prognostication.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".