Long-term survival, functional capacity and quality of life after refractory out-of-hospital cardiac arrest treated with mechanical circulatory support
Bibliographic record
Abstract
Introduction: Studies on long-term outcomes after refractory out-of-hospital cardiac arrest (OHCA) treated with mechanical circulatory support (MCS) are limited. This study aimed to evaluate long-term neurologically intact survival, functional capacity and quality of life after refractory OHCA treated with MCS. Methods: This was a follow-up study of survivors after refractory OHCA treated with MCS. Follow-up examinations comprised clinical assessment with transthoracic echocardiography and cardiopulmonary exercise test (CPX). Neurological and cognitive screening was evaluated with the Cerebral Performance Category (CPC) and Montreal Cognitive Assessment (MoCA test). A good neurological outcome was defined as CPC 1 or CPC 2. Health-related quality of life was measured by questionnaires (Short Form-36 (SF-36)). Results: A total of 101 patients with refractory OHCA were treated with MCS at Aarhus University Hospital between 2015 and 2019. The total low-flow time was median 105 min [IQR, 94-123] minutes. The hospital discharge rate was 27%. At a mean follow-up time of 4.8 years ± 1.6 (range 2.8-6.1 years), 21 patients remained alive of whom 15 consented to participate in the present study. Good neurological outcome with CPC 1-2 was found in 93% (14/15) patients. No severe cognitive function was discovered; mean MoCA score of 26.4 ± 3.1. Functional capacity examined by CPX showed acceptable VO2 max values (23.9 ± 6.3 mL/kg/min). Mean SF-36 scores revealed an overall high level of quality of life in long-term survivors. Conclusions: Long-term survival with a good neurological outcome with functional recovery was high in patients with refractory OHCA treated with MCS. These patients may expect a reasonable quality of life after discharge despite prolonged resuscitation.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".