P5709External validation of the ACEF II operative risk model in a cardiac surgery population: an interim evaluation

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
M Georgievska ◽  
R Saiti ◽  
D Popevski ◽  
T Gramosli ◽  
E Stoicovski ◽  
...  

Abstract Background The ACEF II score has been proposed as a parsimonious, alternative, operative mortality risk prediction model for cardiac surgery. External validation is warranted to establish its use. Aim The primary goal was to evaluate the ACEF II model performance for cardiac surgery mortality risk stratification. We also tested the discriminatory power to classify patients in need of prolonged postoperative respiratory support and hospitalisation. Methods We evaluated 743 Cardiac Surgery patients – median age 65 (range 20–80 years), 27.4% females - operated between November 2017 and October 2018. Receiver Operating Curves (ROC) were generated based on a dichotomous outcome, “yes/no”, for intrahospital mortality, prolonged mechanical ventilation time (>24 hours), ICU length-of-stay (>48 hours) and postoperative hospitalisation (>7 days). The ACEF II was compared to the ACEF I and the EuroSCORE II (ESII). The DeLong method was used to test the statistical significance of the difference between the areas under different dependent ROC curves. Results The median ACEF II scores for low risk (= ESII <2%), medium risk (= ESII ≥2–≤5%) and high-risk patients (= ESII >5%) were 1.24 (IQR 1.05–1.505), 1.48 (IQR 1.28–1.928) and 2.240 (IQR 1.560–2.933), respectively. The observed mortality for low risk, medium risk and high-risk patients were 1.48% (5/337), 3.26% (9/275) and 19.23% (25/130), respectively. ACEF II outperformed the ACEF I but was similar to the EuroSCORE II in discriminating intrahospital mortality cases and patients in need of prolonged mechanical ventilation (Table 1). All risk models lacked sufficient power to classify patients requiring prolonged ICU-LOS and postoperative hospitalisation time (AUC <0.7). Table 1. Pairwise comparison of ROC Risk Score Model AUC + CI95% – Intrahospital Mortality Area difference when compared to ACEF II AUC + CI95% p-value ACEF II 0.766 [0.733 to 0.796] ACEF I 0.645 [0.609 to 0.679] 0.121 [0.0288 to 0.212] 0.0100 EuroSCORE II 0.809 [0.778 to 0.836] 0.0429 [−0.0431 to 0.129] 0.3284 AUC + CI95% – Prolonged MVT Area difference when compared to ACEF II AUC + CI95% p-value ACEF II 0.721 [0.687 to 0.753] ACEF I 0.632 [0.596 to 0.667] 0.0891 [0.0224 to 0.156] 0.0088 EuroSCORE II 0.721 [0.687 to 0.753] 0.000128 [−0.0732 to 0.0735] 0.9973 AUC = Area Under the Curve, DeLong et al., 1988 – Binomial exact CI95% for the AUC, MVT = Mechanical Ventilation time. Conclusion The ACEF II risk model has a fair discriminative capacity to classify intrahospital mortality cases and patients who will require prolonged mechanical respiratory support following cardiac surgery. Acknowledgement/Funding None

BMC Surgery ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xiaoqiang Yin ◽  
Mei Xin ◽  
Sheng Ding ◽  
Feng Gao ◽  
Fan Wu ◽  
...  

Abstract Background We aimed to explore the relationship between the neutrophil to lymphocyte ratio (NLR) and the early clinical outcomes in children with congenital heart disease (CHD) associated with pulmonary arterial hypertension (PAH) after cardiac surgery. Methods A retrospective observational study involving 190 children from January 2013 to August 2019 was conducted. Perioperative clinical and biochemical data were collected. Results We found that pre-operative NLR was significantly correlated with AST, STB, CR and UA (P < 0.05), while post-operative NLR was significantly correlated with ALT, AST, BUN (P < 0.05). Increased post-operative neutrophil count and NLR as well as decreased lymphocyte count could be observed after cardiac surgery (P < 0.05). Level of pre-operative NLR was significantly correlated with mechanical ventilation time, ICU stay time and total length of stay (P < 0.05), while level of post-operative NLR was only significantly correlated to the first two (P < 0.05). By using ROC curve analysis, relevant areas under the curve for predicting prolonged mechanical ventilation time beyond 24 h, 48 h and 72 h by NLR were statistically significant (P < 0.05). Conclusion For patients with CHD-PAH, NLR was closely related to early post-operative complications and clinical outcomes, and could act as a novel marker to predict the occurrence of prolonged mechanical ventilation.


2014 ◽  
Vol 3 ◽  
pp. 252-256 ◽  
Author(s):  
Mehmet Kalender ◽  
Taylan Adademir ◽  
Mehmet Tasar ◽  
Ata Niyazi Ecevit ◽  
Okay Guven Karaca ◽  
...  

2019 ◽  
Vol 33 (10) ◽  
pp. 2709-2716 ◽  
Author(s):  
Lara Hessels ◽  
Tim G. Coulson ◽  
Siven Seevanayagam ◽  
Paul Young ◽  
David Pilcher ◽  
...  

2018 ◽  
Vol 21 (5) ◽  
pp. E387-E391 ◽  
Author(s):  
Binfei Li ◽  
Geqin Sun ◽  
Zhou Cheng ◽  
Chuangchuang Mei ◽  
Xiaozu Liao ◽  
...  

Objectives: This study aims to analyze the nosocomial infection factors in post–cardiac surgery extracorporeal membrane oxygenation (ECMO) supportive treatment (pCS-ECMO). Methods: The clinical data of the pCS-ECMO patients who obtained nosocomial infections (NI) were collected and analyzed retrospectively. Among the 74 pCS-ECMO patients, 30 occurred with NI, accounting for 40.5%; a total of 38 pathogens were isolated, including 22 strains of Gram-negative bacteria (57.9%), 15 strains of Gram-positive bacteria (39.5%), and 1 fungus (2.6%). Results: Multidrug-resistant strains were highly concentrated, among which Acinetobacter baumannii and various coagulase-negative staphylococci were the main types; NI was related to mechanical ventilation time, intensive care unit (ICU) residence, ECMO duration, and total hospital stay, and the differences were statistically significant (P < .05). The binary logistic regression analysis indicated that ECMO duration was a potential independent risk factor (OR = 0.992, P = .045, 95.0% CI = 0.984-1.000). Conclusions: There existed significant correlations between the secondary infections of pCS-ECMO and mechanical ventilation time, ICU residence, ECMO duration, and total hospital stay; therefore, hospitals should prepare appropriate preventive measures to reduce the incidence of ECMO secondary infections.


2015 ◽  
Vol 3 (S1) ◽  
Author(s):  
M Pérez Cheng ◽  
P Pabón Osuna ◽  
JM González Santos ◽  
A Rodríguez Encinas

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