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Tendency of dynamic vasoactive and inotropic medications data as a robust predictor of mortality in patients with septic shock: An analysis of the MIMIC-IV database.
Ning, Yi-Le; Sun, Ce; Xu, Xiang-Hui; Li, Li; Ke, Yan-Ji; Mai, Ye; Lin, Xin-Feng; Yang, Zhong-Qi; Xian, Shao-Xiang; Chen, Wei-Tao.
Afiliação
  • Ning YL; Department of Pulmonary and Critical Care Medicine (PCCM), Bao'an District Hospital of Chinese Medicine, Shenzhen, China.
  • Sun C; The First Clinical School, Guangzhou University of Chinese Medicine, Guangzhou, China.
  • Xu XH; Department of Critical Care Medicine, Meizhou Hospital of Chinese Medicine, Meizhou, China.
  • Li L; The First Clinical School, Guangzhou University of Chinese Medicine, Guangzhou, China.
  • Ke YJ; Department of Critical Care Medicine, Bao'an District Hospital of Chinese Medicine, Shenzhen, China.
  • Mai Y; Department of Pulmonary and Critical Care Medicine (PCCM), The First People's Hospital of Kashgar Prefecture, Kashgar, China.
  • Lin XF; Department of Critical Care Medicine, The Fourth People's Hospital of Foshan, Foshan, China.
  • Yang ZQ; Department of Critical Care Medicine, Chinese Medicine Hospital of Hainan Province, Haikou, China.
  • Xian SX; Department of Critical Care Medicine, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
  • Chen WT; The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
Front Cardiovasc Med ; 10: 1126888, 2023.
Article em En | MEDLINE | ID: mdl-37082452
Background: Septic shock patients fundamentally require delicate vasoactive and inotropic agent administration, which could be quantitatively and objectively evaluated by the vasoactive-inotropic score (VIS); however, whether the dynamic trends of high-time-resolution VIS alter the clinical outcomes remains unclear. Thus, this study proposes the term VIS Reduction Rate (VRR) to generalise the tendency of dynamic VIS, to explore the association of VRR and mortality for patients with septic shock. Methods: We applied dynamic and static VIS data to predict ICU mortality by two models: the long short-term memory (LSTM) deep learning model, and the extreme gradient boosting (XGBoost), respectively. The specific target cohort was extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database by the sophisticated structured query language (SQL). Enrolled patients were divided into four groups by VRR value: ≥50%, 0 ~ 50%, -50% ~ 0, and < -50%. Statistical approaches included pairwise propensity score matching (PSM), Cox proportional hazards regression, and two doubly robust estimation models to ensure the robustness of the results. The primary and secondary outcomes were ICU mortality and in-hospital mortality, respectively. Results: VRR simplifies the dosing trends of vasoactive and inotropic agents represented by dynamic VIS data while requiring fewer data. In total, 8,887 septic shock patients were included. Compared with the VRR ≥50% group, the 0 ~ 50%, -50% ~ 0, and < -50% groups had significantly higher ICU mortality [hazard ratio (HR) 1.32, 95% confidence interval (CI) 1.17-1.50, p < 0.001; HR 1.79, 95% CI 1.44-2.22, p < 0.001; HR 2.07, 95% CI 1.61-2.66, p < 0.001, respectively] and in-hospital mortality [HR 1.43, 95% CI 1.28-1.60, p < 0.001; HR 1.75, 95% CI 1.45-2.11, p < 0.001; HR 2.00, 95% CI 1.61-2.49, p < 0.001, respectively]. Similar findings were observed in two doubly robust estimation models. Conclusion: The trends of dynamic VIS in ICU might help intensivists to stratify the prognosis of adult patients with septic shock. A lower decline of VIS was remarkably associated with higher ICU and in-hospital mortality among septic shock patients receiving vasoactive-inotropic therapy for more than 24 h.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Cardiovasc Med Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Cardiovasc Med Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China