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Prediction of postoperative patient deterioration and unanticipated intensive care unit admission using perioperative factors.
Mestrom, Eveline H J; Bakkes, Tom H G F; Ourahou, Nassim; Korsten, Hendrikus H M; Serra, Paulo de Andrade; Montenij, Leon J; Mischi, Massimo; Turco, Simona; Bouwman, R Arthur.
Afiliación
  • Mestrom EHJ; Anesthesiology Department, Catharina Hospital Eindhoven, Eindhoven, The Netherlands.
  • Bakkes THGF; Signal Processing Department, Eindhoven University of Technology, Eindhoven, The Netherlands.
  • Ourahou N; Anesthesiology Department, Catharina Hospital Eindhoven, Eindhoven, The Netherlands.
  • Korsten HHM; Anesthesiology Department, Catharina Hospital Eindhoven, Eindhoven, The Netherlands.
  • Serra PA; Signal Processing Department, Eindhoven University of Technology, Eindhoven, The Netherlands.
  • Montenij LJ; Mathematics Department, VU Amsterdam, Amsterdam, The Netherlands.
  • Mischi M; Anesthesiology Department, Catharina Hospital Eindhoven, Eindhoven, The Netherlands.
  • Turco S; Signal Processing Department, Eindhoven University of Technology, Eindhoven, The Netherlands.
  • Bouwman RA; Signal Processing Department, Eindhoven University of Technology, Eindhoven, The Netherlands.
PLoS One ; 18(8): e0286818, 2023.
Article en En | MEDLINE | ID: mdl-37535542
BACKGROUND AND OBJECTIVES: Currently, no evidence-based criteria exist for decision making in the post anesthesia care unit (PACU). This could be valuable for the allocation of postoperative patients to the appropriate level of care and beneficial for patient outcomes such as unanticipated intensive care unit (ICU) admissions. The aim is to assess whether the inclusion of intra- and postoperative factors improves the prediction of postoperative patient deterioration and unanticipated ICU admissions. METHODS: A retrospective observational cohort study was performed between January 2013 and December 2017 in a tertiary Dutch hospital. All patients undergoing surgery in the study period were selected. Cardiothoracic surgeries, obstetric surgeries, catheterization lab procedures, electroconvulsive therapy, day care procedures, intravenous line interventions and patients under the age of 18 years were excluded. The primary outcome was unanticipated ICU admission. RESULTS: An unanticipated ICU admission complicated the recovery of 223 (0.9%) patients. These patients had higher hospital mortality rates (13.9% versus 0.2%, p<0.001). Multivariable analysis resulted in predictors of unanticipated ICU admissions consisting of age, body mass index, general anesthesia in combination with epidural anesthesia, preoperative score, diabetes, administration of vasopressors, erythrocytes, duration of surgery and post anesthesia care unit stay, and vital parameters such as heart rate and oxygen saturation. The receiver operating characteristic curve of this model resulted in an area under the curve of 0.86 (95% CI 0.83-0.88). CONCLUSIONS: The prediction of unanticipated ICU admissions from electronic medical record data improved when the intra- and early postoperative factors were combined with preoperative patient factors. This emphasizes the need for clinical decision support tools in post anesthesia care units with regard to postoperative patient allocation.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Hospitalización / Unidades de Cuidados Intensivos Tipo de estudio: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Adolescent / Female / Humans / Pregnancy Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2023 Tipo del documento: Article País de afiliación: Países Bajos Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Hospitalización / Unidades de Cuidados Intensivos Tipo de estudio: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Adolescent / Female / Humans / Pregnancy Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2023 Tipo del documento: Article País de afiliación: Países Bajos Pais de publicación: Estados Unidos