Two-year prospective cohort of intensive care survivors enrolled on a digitally enabled recovery pathway focussed on individualised recovery goal attainment
Bibliographic record
Abstract
BACKGROUND: Despite substantial evidence documenting physical, psychological, and cognitive problems experienced by intensive care unit (ICU) survivors, few studies explore interventions supporting recovery after hospital discharge. Individualised recovery goal setting, the standard of care across many rehabilitation areas, is rarely used for ICU survivors. Digital health technologies may help to address current service fragmentation and gaps. We developed and implemented a digital ICU recovery pathway using the aTouchaway e-health platform. OBJECTIVES: The objective of this study was to explore recovery barriers and challenges; recovery goals set and achieved; self-reported patient outcomes; and healthcare costs of patients enrolled on a 12-week digital ICU recovery pathway after hospital discharge. METHODS: We conducted a prospective observational single-centre cohort study (June 2021 to May 2023) at a 90-bed tertiary critical care service in London, UK. We enrolled adults ventilated for ≥3 days who were able to participate in recovery activities. We ascertained baseline recovery challenges and identified recovery goals and achievement over 12 weeks. We collected patient-reported outcomes at 2-4, 12-14, 26-28 weeks and healthcare utilisation monthly for 28 weeks. RESULTS: We enrolled 105 participants (35% of eligible patients). Common rehabilitation challenges were standing balance (60%), walking indoors (56%), and washing (64%) and dressing (47%) abilities. Of 522 home recovery goals, 63% weekly, 48% monthly, and 38% aspirational goals were achieved. Most goals related to self-care: ability to move outside (91 goals, 55% achieved) and inside (45 goals, 47% achieved) the home and community access (65 goals, 48% achieved). Nottingham Extended Activities of Daily Living Scale scores improved from timepoints 1 to 2 (median [interquartile range]: 15 [7, 19] versus 19 [15, 21], P = 0.01). Total healthcare costs were £240,017 (median [interquartile range] cost per patient: £784 [£125, £4419]). CONCLUSIONS: This study found multiple ongoing functional deficits, challenges achieving recovery goals, and limited improvements in self-reported outcomes, with moderate healthcare costs after hospital discharge indicate substantial ongoing rehabilitative needs.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".