EuroSCORE II was launched as a risk score model for prediction of in-hospital mortality in cardiac surgery

To replace mechanical ventilation (MV), which represents the cornerstone therapy in severe COVID-19 cases, high-flow nasal oxygen (HFNO) therapy has recently emerged as a less-invasive therapeutic possibility for those patients. Respecting the risk of MV delay as a result of HFNO use, we aimed to evaluate which parameters could determine the risk of in-hospital mortality in HFNO-treated COVID-19 patients. This single-center cohort study included 102 COVID-19-positive patients treated with HFNO. Standard therapeutic methods and up-to-date protocols were used. Patients who underwent a fatal event (41.2%) were significantly older, mostly male patients, and had higher comorbidity burdens measured by CCI. In a univariate analysis, older age, shorter HFNO duration, ventilator initiation, higher CCI and lower ROX index all emerged as significant predictors of adverse events (p < 0.05). Variables were dichotomized and included in the multivariate analysis to define their relative weights in the computed risk score model. Based on this, a risk score model for the prediction of in-hospital mortality in COVID-19 patients treated with HFNO consisting of four variables was defined: CCI > 4, ROX index ≤ 4.11, LDH-to-WBC ratio, age > 65 years (CROW-65). The main purpose of CROW-65 is to address whether HFNO should be initiated in the subgroup of patients with a high risk of in-hospital mortality.

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Predictive risk score model for severe fever with thrombocytopenia syndrome mortality based on qSOFA and SIRS scoring system

10.21203/rs.2.18479/v2 ◽

2020 ◽

Author(s):

Li Wang ◽

Zhiqiang Zou ◽

Kun Ding ◽

Chunguo Hou ◽

Song Qin

Keyword(s):

Risk Factors ◽

Hospital Mortality ◽

Risk Score ◽

Predictive Value ◽

Multivariable Logistic Regression Analysis ◽

Predictive Values ◽

Independent Risk Factors ◽

Score Model ◽

Qsofa Score ◽

Severe Fever

Abstract Background: Severe fever with thrombocytopenia syndrome (SFTS) is a severe systemic virus infectious disease usually having multi-organ dysfunction which resembles sepsis. Methods: Data of 321 patients with laboratory-confirmed SFTS from May 2013 to July 2017 were retrospectively analyzed. Demographic and clinical characteristics, calculated quick sequential organ failure assessment (qSOFA) score and systemic inflammatory response syndrome (SIRS) criteria for survivors and nonsurvivors were compared. Independent risk factors associated with in-hospital mortality were obtained using multivariable logistic regression analysis. Risk score models containing different risk factors for mortality in stratified patients were established whose predictive values were evaluated using the area under ROC curve (AUC). Results: Of 321 patients, 87 died (27.1%). Age ( p <0.001) and percentage numbers of patients with qSOFA≥2 and SIRS≥2 ( p <0.0001) were profoundly greater in nonsurvivors than in survivors. Age, qSOFA, SIRS score and aspartate aminotransferase (AST) were independent risk factors for mortality for all patients. And qSOFA score was the only common risk factor in all patients, those age≥60 years and those enrolled in the intensive care unit (ICU). A risk score model containing all these risk factors (Model1) has high predictive value for in-hospital mortality in these three groups with AUCs (95% CI): 0.919 (0.883-0.946), 0.929 (0.862-0.944) and 0.815 (0.710-0.894), respectively. A model only including age and qSOFA also has high predictive value for mortality in these groups with AUCs (95% CI): 0.872 (0.830-0.906), 0.885(0.801-0.900) and 0.865 (0.767-0.932), respectively. Conclusions: Risk models containing qSOFA have high predictive validity for SFTS mortality.

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A risk score model to predict in-hospital mortality of patients with end-stage renal disease and acute myocardial infarction

Internal and Emergency Medicine ◽

10.1007/s11739-020-02529-3 ◽

2020 ◽

Author(s):

Yuan Fu ◽

Hao Sun ◽

Zongsheng Guo ◽

Li Xu ◽

Xinchun Yang ◽

...

Keyword(s):

Myocardial Infarction ◽

Acute Myocardial Infarction ◽

Renal Disease ◽

Hospital Mortality ◽

Risk Score ◽

End Stage Renal Disease ◽

Score Model ◽

Stage Renal Disease ◽

End Stage

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Predictive risk score model for severe fever with thrombocytopenia syndrome mortality based on qSOFA and SIRS scoring system

10.21203/rs.2.18479/v3 ◽

2020 ◽

Author(s):

Li Wang ◽

Zhiqiang Zou ◽

Kun Ding ◽

Chunguo Hou

Keyword(s):

Risk Factors ◽

Hospital Mortality ◽

Risk Score ◽

Predictive Value ◽

Multivariable Logistic Regression Analysis ◽

Predictive Values ◽

Independent Risk Factors ◽

Score Model ◽

Qsofa Score ◽

Severe Fever

Abstract Background: Severe fever with thrombocytopenia syndrome (SFTS) is a severe systemic virus infectious disease usually having multi-organ dysfunction which resembles sepsis.Methods: Data of 321 patients with laboratory-confirmed SFTS from May 2013 to July 2017 were retrospectively analyzed. Demographic and clinical characteristics, calculated quick sequential organ failure assessment (qSOFA) score and systemic inflammatory response syndrome (SIRS) criteria for survivors and nonsurvivors were compared. Independent risk factors associated with in-hospital mortality were obtained using multivariable logistic regression analysis. Risk score models containing different risk factors for mortality in stratified patients were established whose predictive values were evaluated using the area under ROC curve (AUC).Results: Of 321 patients, 87 died (27.1%). Age (p<0.001) and percentage numbers of patients with qSOFA≥2 and SIRS≥2 (p<0.0001) were profoundly greater in nonsurvivors than in survivors. Age, qSOFA, SIRS score and aspartate aminotransferase (AST) were independent risk factors for mortality for all patients. And qSOFA score was the only common risk factor in all patients, those age≥60 years and those enrolled in the intensive care unit (ICU). A risk score model containing all these risk factors (Model1) has high predictive value for in-hospital mortality in these three groups with AUCs (95% CI): 0.919 (0.883-0.946), 0.929 (0.862-0.944) and 0.815 (0.710-0.894), respectively. A model only including age and qSOFA also has high predictive value for mortality in these groups with AUCs (95% CI): 0.872 (0.830-0.906), 0.885(0.801-0.900) and 0.865 (0.767-0.932), respectively.Conclusions: Risk models containing qSOFA have high predictive validity for SFTS mortality.

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TRI-SCORE: a new risk score for in-hospital mortality prediction after isolated tricuspid valve surgery

European Heart Journal ◽

10.1093/eurheartj/ehab679 ◽

2021 ◽

Author(s):

Julien Dreyfus ◽

Etienne Audureau ◽

Yohann Bohbot ◽

Augustin Coisne ◽

Yoan Lavie-Badie ◽

...

Keyword(s):

Hospital Mortality ◽

Tricuspid Valve ◽

Risk Score ◽

Tricuspid Regurgitation ◽

Left Ventricular ◽

Valve Surgery ◽

Left Ventricular Ejection ◽

Ventricular Ejection Fraction ◽

Tricuspid Valve Surgery ◽

Score Model

Abstract Aims Isolated tricuspid valve surgery (ITVS) is considered to be a high-risk procedure, but in-hospital mortality is markedly variable. This study sought to develop a dedicated risk score model to predict the outcome of patients after ITVS for severe tricuspid regurgitation (TR). Methods and results All consecutive adult patients who underwent ITVS for severe non-congenital TR at 12 French centres between 2007 and 2017 were included. We identified 466 patients (60 ± 16 years, 49% female, functional TR in 49%). In-hospital mortality rate was 10%. We derived and internally validated a scoring system to predict in-hospital mortality using multivariable logistic regression and bootstrapping with 1000 re-samples. The final risk score ranged from 0 to 12 points and included eight parameters: age ≥70 years, New York Heart Association Class III–IV, right-sided heart failure signs, daily dose of furosemide ≥125 mg, glomerular filtration rate <30 mL/min, elevated bilirubin, left ventricular ejection fraction <60%, and moderate/severe right ventricular dysfunction. Tricuspid regurgitation mechanism was not an independent predictor of outcome. Observed and predicted in-hospital mortality rates increased from 0% to 60% and from 1% to 65%, respectively, as the score increased from 0 up to ≥9 points. Apparent and bias-corrected areas under the receiver operating characteristic curves were 0.81 and 0.75, respectively, much higher than the logistic EuroSCORE (0.67) or EuroSCORE II (0.63). Conclusion We propose TRI-SCORE as a dedicated risk score model based on eight easy to ascertain parameters to inform patients and physicians regarding the risk of ITVS and guide the clinical decision-making process of patients with severe TR, especially as transcatheter therapies are emerging (www.tri-score.com).

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Predictive risk score model for severe fever with thrombocytopenia syndrome mortality based on qSOFA and SIRS scoring system

10.21203/rs.2.18479/v1 ◽

2019 ◽

Author(s):

Li Wang ◽

Kun Ding ◽

Chunguo Hou ◽

Zhiqiang Zou ◽

Song Qin

Keyword(s):

Risk Factors ◽

Hospital Mortality ◽

Risk Score ◽

Risk Groups ◽

Multivariable Logistic Regression Analysis ◽

Predictive Values ◽

Independent Risk Factors ◽

Score Model ◽

Qsofa Score ◽

Severe Fever

Abstract Background: Severe fever with thrombocytopenia syndrome (SFTS) is a severe systemic virus infectious disease usually having multi-organ dysfunction which resembles sepsis.Methods: A total of 321 patients with laboratory-confirmed SFTS from May 2013 to July 2017 were retrospectively analysed. Demographic and clinical characteristics, calculated quick sequential organ failure assessment (qSOFA) score and systemic inflammatory response syndrome (SIRS) criteria for survivors and nonsurvivors were compared. Independent risk factors associated with in-hospital mortality were obtained using multivariable logistic regression analysis. Risk score models containing different risk factors for mortality in stratified patients were established whose predictive values were evaluated using area under ROC curve (AUC).Results: Of 321 patients, 87 died (27.1%). Age (p<0.001) and percentage numbers of patients with qSOFA≥2 and SIRS≥2 (p<0.0001) were profoundly greater in nonsurvivors than in survivors. Age, qSOFA, SIRS score and aspartate aminotransferase (AST) were independent risk factors for mortality for all patients. And qSOFA score was the only common risk factor in all patients, those of age≥60 years and those enrolled in intensive care unit (ICU). A risk score model containing all these risk factors (Model1) has high predictive value for in-hospital mortality in these three groups with AUCs (95% CI): 0.919 (0.883-0.946), 0.929 (0.862-0.944) and 0.815 (0.710-0.894), respectively. Kaplan-Meier survival analysis showed a strong difference between high-risk and low-risk groups at a cutoff value > 9.22 (log-rank c2 = 126.3, p <0.0001) Conclusions: qSOFA and risk models containing qSOFA have high predictive validity for SFTS in-hospital mortality.

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