Impact of a Postintensive Care Unit Multidisciplinary Follow-up on the Quality of Life (SUIVI-REA): Protocol for a Multicenter Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Critically ill patients are at risk of developing a postintensive care syndrome (PICS), which is characterized by physical, psychological, and cognitive impairments and which dramatically impacts the patient's quality of life (QoL). No intervention has been shown to improve QoL. We hypothesized that a medical, psychological, and social follow-up would improve QoL by mitigating the PICS. OBJECTIVE: This multicenter, randomized controlled trial (SUIVI-REA) aims to compare a multidisciplinary follow-up with a standard postintensive care unit (ICU) follow-up. METHODS: Patients were randomized to the control or intervention arm. In the intervention arm, multidisciplinary follow-up involved medical, psychological, and social evaluation at ICU discharge and at 3, 6, and 12 months thereafter. In the placebo group, patients were seen only at 12 months by the multidisciplinary team. Baseline characteristics at ICU discharge were collected for all patients. The primary outcome was QoL at 1 year, assessed using the Euro Quality of Life-5 dimensions (EQ5D). Secondary outcomes were mortality, cognitive, psychological, and functional status; social and professional reintegration; and the rate of rehospitalization and outpatient consultations at 1 year. RESULTS: The study was funded by the Ministry of Health in June 2010. It was approved by the Ethics Committee on July 8, 2011. The first and last patient were randomized on December 20, 2012, and September 1, 2017, respectively. A total of 546 patients were enrolled across 11 ICUs. At present, data management is ongoing, and all parties involved in the trial remain blinded. CONCLUSIONS: The SUVI-REA multicenter randomized controlled trial aims to assess whether a post-ICU multidisciplinary follow-up improves QoL at 1 year. TRIAL REGISTRATION: Clinicaltrials.gov NCT01796509; https://clinicaltrials.gov/ct2/show/NCT01796509. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/30496.
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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 | 0.031 | 0.027 |
| Meta-epidemiology (narrow) | 0.008 | 0.003 |
| Meta-epidemiology (broad) | 0.015 | 0.006 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.046 | 0.008 |
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".