TY - JOUR
T1 - Prognostic value of oxygen saturation index trajectory phenotypes on ICU mortality in mechanically ventilated patients
T2 - a multi-database retrospective cohort study
AU - Shi, Xiawei
AU - Shi, Yangyang
AU - Fan, Liming
AU - Yang, Jia
AU - Chen, Hao
AU - Ni, Kaiwen
AU - Yang, Junchao
N1 - J.Y. received funding from Zhejiang Provincial Program for the Cultivation of High-Level Innovative Health Talents and the institution of Chinese medicine for respiratory disease of Zhejiang Chinese Medical University. X.S. received Zhejiang Chinese Medical University Postgraduate Scientific Research Fund Project (No. Y202351269).
Publisher Copyright:
© The Author(s) 2023.
PY - 2023/11/29
Y1 - 2023/11/29
N2 - Background: Heterogeneity among critically ill patients undergoing invasive mechanical ventilation (IMV) treatment could result in high mortality rates. Currently, there are no well-established indicators to help identify patients with a poor prognosis in advance, which limits physicians’ ability to provide personalized treatment. This study aimed to investigate the association of oxygen saturation index (OSI) trajectory phenotypes with intensive care unit (ICU) mortality and ventilation-free days (VFDs) from a dynamic and longitudinal perspective. Methods: A group-based trajectory model was used to identify the OSI-trajectory phenotypes. Associations between the OSI-trajectory phenotypes and ICU mortality were analyzed using doubly robust analyses. Then, a predictive model was constructed to distinguish patients with poor prognosis phenotypes. Results: Four OSI-trajectory phenotypes were identified in 3378 patients: low-level stable, ascending, descending, and high-level stable. Patients with the high-level stable phenotype had the highest mortality and fewest VFDs. The doubly robust estimation, after adjusting for unbalanced covariates in a model using the XGBoost method for generating propensity scores, revealed that both high-level stable and ascending phenotypes were associated with higher mortality rates (odds ratio [OR]: 1.422, 95% confidence interval [CI] 1.246–1.623; OR: 1.097, 95% CI 1.027–1.172, respectively), while the descending phenotype showed similar ICU mortality rates to the low-level stable phenotype (odds ratio [OR] 0.986, 95% confidence interval [CI] 0.940–1.035). The predictive model could help identify patients with ascending or high-level stable phenotypes at an early stage (area under the curve [AUC] in the training dataset: 0.851 [0.827–0.875]; AUC in the validation dataset: 0.743 [0.709–0.777]). Conclusions: Dynamic OSI-trajectory phenotypes were closely related to the mortality of ICU patients requiring IMV treatment and might be a useful prognostic indicator in critically ill patients.
AB - Background: Heterogeneity among critically ill patients undergoing invasive mechanical ventilation (IMV) treatment could result in high mortality rates. Currently, there are no well-established indicators to help identify patients with a poor prognosis in advance, which limits physicians’ ability to provide personalized treatment. This study aimed to investigate the association of oxygen saturation index (OSI) trajectory phenotypes with intensive care unit (ICU) mortality and ventilation-free days (VFDs) from a dynamic and longitudinal perspective. Methods: A group-based trajectory model was used to identify the OSI-trajectory phenotypes. Associations between the OSI-trajectory phenotypes and ICU mortality were analyzed using doubly robust analyses. Then, a predictive model was constructed to distinguish patients with poor prognosis phenotypes. Results: Four OSI-trajectory phenotypes were identified in 3378 patients: low-level stable, ascending, descending, and high-level stable. Patients with the high-level stable phenotype had the highest mortality and fewest VFDs. The doubly robust estimation, after adjusting for unbalanced covariates in a model using the XGBoost method for generating propensity scores, revealed that both high-level stable and ascending phenotypes were associated with higher mortality rates (odds ratio [OR]: 1.422, 95% confidence interval [CI] 1.246–1.623; OR: 1.097, 95% CI 1.027–1.172, respectively), while the descending phenotype showed similar ICU mortality rates to the low-level stable phenotype (odds ratio [OR] 0.986, 95% confidence interval [CI] 0.940–1.035). The predictive model could help identify patients with ascending or high-level stable phenotypes at an early stage (area under the curve [AUC] in the training dataset: 0.851 [0.827–0.875]; AUC in the validation dataset: 0.743 [0.709–0.777]). Conclusions: Dynamic OSI-trajectory phenotypes were closely related to the mortality of ICU patients requiring IMV treatment and might be a useful prognostic indicator in critically ill patients.
KW - Oxygen saturation index
KW - Invasive mechanical ventilation
KW - Intensive care unit
KW - Mortality
UR - http://www.scopus.com/inward/record.url?scp=85177772390&partnerID=8YFLogxK
U2 - 10.1186/s40560-023-00707-x
DO - 10.1186/s40560-023-00707-x
M3 - Journal article
AN - SCOPUS:85177772390
SN - 2052-0492
VL - 11
JO - Journal of Intensive Care
JF - Journal of Intensive Care
M1 - 59
ER -