A Screening Tool to Predict Post-intensive Care Syndrome (PICS) in the Critically Ill
Notice bibliographique
Résumé
Abstract RATIONALE: Many ICU patients experience physical, psychological, and cognitive impairments following resolution of critical illness, collectively referred to as post-intensive care syndrome (PICS). PICS has become widely recognized within the critical care field, but how to screen for PICS does not currently have consensus. Development of a validated, concise PICS screening tool would allow for rapid identification of this vulnerable and understudied population. Therefore, this study's goal was to develop and evaluate a screening tool to identify patients at risk for PICS. METHODS: We performed a prospective cohort study in a quaternary academic hospital. We included adults ≥ 18 years old with ≥48 hours spent in an ICU. Exclusion criteria were admission for suicide attempt, severe cognitive impairment/dementia, life expectancy <3 months, and non-English speaking. We assessed mental, cognitive, and physical function following ICU discharge and at 3 months using Hospital Anxiety and Depression Scale, Impact of Event Scale-Revised, Montreal Cognitive Assessment-blind, and Barthel Index. Our team, including critical care physicians, psychiatrists, psychologists, physical and occupational therapists, and nurses, developed a brief 15-item PICS screening tool (5 questions/domain). This tool was administered after patients were discharged from ICU stay to general care to assess its effectiveness in predicting impairments in all 3 domains at discharge and again at three months after hospital discharge, in comparison to previously mentioned validated questionnaires. Youden index statistical methods were used to determine potential “cutoff” values (scores) for the tool to maximize sensitivity and specificity. RESULTS: A total of 194 patients from 6 ICUs were recruited and completed the initial questionnaire, and 109 (56%) patients completed 3-month follow-up. Median age was 65 years (IQR 57-72) and 49% (95/194) were female. Screening tool is depicted in Figure 1. Overall, the screening tool weakly-to-moderately correlated with continuous outcomes of the validated measures upon ICU discharge and 3-month follow-up. When evaluating sensitivity and specificity for individual domains, the tool had an area under the receiver operating curve of >0.7 for the following domains: cognitive, anxiety, and physical impairments, indicating moderate-to-good sensitivity and specificity. CONCLUSIONS: This PICS screening tool was correlated with validated measures of PICS upon ICU discharge and at 3-month follow-up for all three domains. The tool's strength lies in its concise nature, making it easier for those caring for this patient population to screen for long-term effects of an ICU stay. Our proposed next step is validation of the PICS screening tool in an external cohort.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».