Prediction of the Evolution to Brain Death in the Neurocritical Patient: SPN Model Showed Better Performance Than Simplified Acute Physiology Score II and Acute Physiology and Chronic Health Evaluation II

Godino, M.; Tommasino, N.; Mizraji, R.; Carámbula, Agustín; Cacciatori, A.; Leyes, Laureano; Bengochea, Milka

doi:10.1016/j.transproceed.2020.02.069

Cited by 5 publications

(3 citation statements)

References 7 publications

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“…Baseline characteristics and admission information: age, gender, admission type, surgery type, body mass index (BMI), and severity score measured by the sequential organ failure assessment (SOFA) score, the oxford acute severity of illness score (OASIS), acute physiology score III (APSIII), the simplified acute physiology score II (SAPSII) and the Charlson comorbidity score were calculated as described in previous studies. [16][17][18][19][20] Commodities including hypertension, diabetes, chronic kidney disease (CKD), congestive heart failure (CHF), myocardial infarct and liver disease were also collected for analysis based on the (ICD-9/10) codes in the MIMIC-III database. Use of mechanical ventilation (MV), vasopressors and renal replacement therapy before the diagnosis of AKI were also recorded in this study.…”

Section: Variable Extractionmentioning

confidence: 99%

Preoperative Glucose-to-Lymphocyte Ratio is an Independent Predictor for Acute Kidney Injury After Cardiac Surgery in Patients in Intensive Care Unit

Li¹,

Zou²

2021

IJGM

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Background:We aimed to investigate the association between preoperative glucose-tolymphocyte ratio (GLR) and cardiac surgery associated with acute kidney injury (CSA-AKI) in patients in the intensive care unit (ICU). Methods: The Medical Information Mart for Intensive Care IV (MIMIC-IV version 1.0) database was used to identify adults' patients who performed cardiac surgery during ICU stay. The primary outcome was the development of AKI based on the KDIGO criteria. Multivariable logistic regression was applied to investigate the association between GLR and clinical outcomes, and propensity score matching (PSM) and inverse probability of treatment weighting (IPTW) were also used to validate our findings. Results: The optimal cut-off value for GLR was 1.28. Among the 7181 patients who conducted cardiac surgery, 2072 high-GLR group (≥1.28) patients and 2072 low-GLR group (<1.28) patients, had similar propensity scores were included in this study. After matching, the high-GLR group had a significantly higher incidence of AKI (odds ratio, OR, 3.28, 95% confidence index, 95% CI, 2.81-3.84, P <0.001) even after adjustment for confounding factors. Moreover, the performance of GLR was superior to that of SOFA scores and GLR plus clinical model could add more net benefit for CSA-AKI than clinical model alone. Conclusion:Preoperative GLR could serve as a good predictor for CSA-AKI in patients in ICU.

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Section: Variable Extractionmentioning

confidence: 99%

Preoperative Glucose-to-Lymphocyte Ratio is an Independent Predictor for Acute Kidney Injury After Cardiac Surgery in Patients in Intensive Care Unit

Li¹,

Zou²

2021

IJGM

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“…The Acute Physiology and Chronic Health Assessment (APACHE) II score system is used to assess the severity of critical illness and risk of mortality, and it has been used extensively in the ICU for more than 30 years [ 4 , 5 ]. It has been validated as a predictor of survival time and mortality in many studies of neurocritical patients, those with terminal diseases, and clinical purposes [ 6 – 11 ].…”

Section: Introductionmentioning

confidence: 99%

Prediction of survival time after terminal extubation: the balance between critical care unit utilization and hospice medicine in the COVID-19 pandemic era

et al. 2023

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Background We established 1-h and 1-day survival models after terminal extubation to optimize ventilator use and achieve a balance between critical care for COVID-19 and hospice medicine. Methods Data were obtained from patients with end-of-life status at terminal extubation from 2015 to 2020. The associations between APACHE II scores and parameters with survival time were analyzed. Parameters with a p-value ≤ 0.2 in univariate analysis were included in multivariate models. Cox proportional hazards regression analysis was used for the multivariate analysis of survival time at 1 h and 1 day. Results Of the 140 enrolled patients, 76 (54.3%) died within 1 h and 35 (25%) survived beyond 24 h. No spontaneous breathing trial (SBT) within the past 24 h, minute ventilation (MV) ≥ 12 L/min, and APACHE II score ≥ 25 were associated with shorter survival in the 1 h regression model. Lower MV, SpO2 ≥ 96% and SBT were related to longer survival in the 1-day model. Hospice medications did not influence survival time. Conclusion An APACHE II score of ≥ 25 at 1 h and SpO2 ≥ 96% at 1 day were strong predictors of disposition of patients to intensivists. These factors can help to objectively tailor pathways for post-extubation transition and rapidly allocate intensive care unit resources without sacrificing the quality of palliative care in the era of COVID-19. Trial registration They study was retrospectively registered. IRB No.: 202101929B0.

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“…The Acute Physiology and Chronic Health Assessment (APACHE) II score system is used to assess the severity of critical illness and risk of mortality, and it has been used extensively in the ICU for more than 30 years [3,4]. It has been validated as a predictor of survival time and mortality in many studies of neurocritical patients, those with terminal diseases, and clinical purposes [5][6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Prediction of Survival Time after Terminal Extubation: the Balance between Critical Care Unit Utilization and Hospice Medicine in the COVID-19 Pandemic Era

Zheng

Huang

Chen

et al. 2022

Preprint

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Background We established 1-hour and 1-day survival models after terminal extubation to optimize ventilator use and achieve a balance between critical care for COVID-19 and hospice medicine. Methods Data were obtained from patients with end-of-life status at terminal extubation from 2015 to 2020. The associations between APACHE II scores and parameters with survival time were analyzed. Parameters with a p-value ≤ 0.2 in univariate analysis were included in multivariate models. Cox proportional hazards regression analysis was used for the multivariate analysis of survival time at 1 hour and 1 day. Results Of the 140 enrolled patients, 76 (54.3%) died within 1 hour and 35 (25%) survived beyond 24 hours. No spontaneous breathing trial (SBT) within the past 24 hours, minute ventilation (MV) ≥ 12 L/min, and APACHE II score ≥ 25 were associated with shorter survival in the 1-hour regression model. Lower MV, SpO2 ≥ 96% and SBT were related to longer survival in the 1-day model. Hospice medications did not influence survival time. Conclusion An APACHE II score of ≥ 25 at 1 hour and SpO2 ≥ 96% at 1 day were strong predictors of disposition of patients to intensivists. These factors can help to objectively tailor pathways for post-extubation transition and rapidly allocate intensive care unit resources without sacrificing the quality of palliative care in the era of COVID-19. Trial registration They study was retrospectively registered. IRB No.: 202101929B0

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Prediction of the Evolution to Brain Death in the Neurocritical Patient: SPN Model Showed Better Performance Than Simplified Acute Physiology Score II and Acute Physiology and Chronic Health Evaluation II

Cited by 5 publications

References 7 publications

Preoperative Glucose-to-Lymphocyte Ratio is an Independent Predictor for Acute Kidney Injury After Cardiac Surgery in Patients in Intensive Care Unit

Preoperative Glucose-to-Lymphocyte Ratio is an Independent Predictor for Acute Kidney Injury After Cardiac Surgery in Patients in Intensive Care Unit

Prediction of survival time after terminal extubation: the balance between critical care unit utilization and hospice medicine in the COVID-19 pandemic era

Prediction of Survival Time after Terminal Extubation: the Balance between Critical Care Unit Utilization and Hospice Medicine in the COVID-19 Pandemic Era

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