Relation of the Sequential Organ Failure Assessment Score to Morbidity and Mortality After Cardiac Surgery

Pätilä, Tommi; Kukkonen, Sinikka; Vento, Antti; Pettilä, Ville; Suojaranta-Ylinen, Raili

doi:10.1016/j.athoracsur.2006.06.025

Cited by 64 publications

(53 citation statements)

References 26 publications

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“…This often results in more complications after surgery and potential reduction in quality of life. [3][4][5] One method of assessing complications occurring directly after cardiac surgery is a prolonged stay in the intensive care unit (ICU). 6 -9 Prolonged ICU stay also leads to incremental use of resources.…”

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confidence: 99%

Prediction Models for Prolonged Intensive Care Unit Stay After Cardiac Surgery

et al. 2010

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Background-Several models have been developed to predict prolonged stay in the intensive care unit (ICU) after cardiac surgery. However, no extensive quantitative validation of these models has yet been conducted. This study sought to identify and validate existing prediction models for prolonged ICU length of stay after cardiac surgery. Methods and Results-After a systematic review of the literature, the identified models were applied on a large registry database comprising 11 395 cardiac surgical interventions. The probabilities of prolonged ICU length of stay based on the models were compared with the actual outcome to assess the discrimination and calibration performance of the models. Literature review identified 20 models, of which 14 could be included. Of the 6 models for the general cardiac surgery population, the Parsonnet model showed the best discrimination (area under the receiver operating characteristic curveϭ0.75 [95% confidence interval, 0.73 to 0.76]), followed by the European system for cardiac operative risk evaluation (EuroSCORE) (0.71 [0.70 to 0.72]) and a model by Huijskes and colleagues (0.71 [0.70 to 0.73]). Most of the models showed good calibration. Conclusions-In this validation of prediction models for prolonged ICU length of stay, 2 widely implemented models (Parsonnet, EuroSCORE), although originally designed for prediction of mortality, were superior in identifying patients with prolonged ICU length of stay. (Circulation. 2010;122:682-689.)Key Words: cardiovascular diseases Ⅲ complications Ⅲ epidemiology Ⅲ risk factors Ⅲ surgery I n the past decades, mortality during or shortly after cardiac surgery has decreased. 1 However, morbidity has increased, 2 mainly because cardiac surgery is increasingly utilized in older and more vulnerable patients. This often results in more complications after surgery and potential reduction in quality of life. [3][4][5] One method of assessing complications occurring directly after cardiac surgery is a prolonged stay in the intensive care unit (ICU). 6 -9 Prolonged ICU stay also leads to incremental use of resources. In practice, prediction models are being used for efficient use of ICU resources. Patients with a low risk of complications are being scheduled for surgery before patients with a high risk. [5][6][7][8][9][10][11][12][13] Various prediction models have been developed to preoperatively identify patients with an increased risk for postoperative complications and prolonged ICU stay. [12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28] Interestingly, all of these prediction models were derived from samples including different patients, as reflected by the different distributions of patient and outcome characteristics. Hence, which model should be preferred in which situation is still unclear. Recently, in a qualitative review, Messaoudi and colleagues 14 reviewed 13 of these prediction models by comparing their published prognostic values for predicting ICU stay. They found that the 13 different prediction models indeed used...

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Prediction Models for Prolonged Intensive Care Unit Stay After Cardiac Surgery

et al. 2010

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“…These differences illustrate very well that the cases with an initial labMELD score ≥30 that we investigated in this study actually displayed considerably more serious morbidity and organ system dysfunction prior to transplantation [18][19][20][21][22][23][24][25].…”

Section: Discussionmentioning

confidence: 96%

“…The SOFA score was originally developed to describe, quantify and predict organ dysfunction and failure for septic intensive care patients [18,19]. The SOFA score was subsequently also applied for the prediction of survival in intensive care patients after myocardial infarction, resuscitation, cardiac surgery, severe trauma and patients with other conditions that require intensive care treatment with or without sepsis [20][21][22][23][24][25].…”

Section: Introductionmentioning

confidence: 99%

Value of the SOFA score as a predictive model for short-term survival in high-risk liver transplant recipients with a pre-transplant labMELD score ≥30

Schrem

Reichert

et al. 2011

Langenbecks Arch Surg

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“…Data wereprospectively collectedonA VP-treated patients after cardiac surgery between January first, 2004 and December 31, 2004 at HelsinkiU niversity Hospital (17). The total number of patients treated in the cardiac surgical intensive careunit (ICU) during this observation period was 857 and 33 of those patients received AV Pi nfusion (Pitressin ® Pfizer,Karlsruhe, Germany) in addition to norepinephrine infusion (AVP group).…”

Section: Methodsmentioning

confidence: 99%

Vasopressin, When Added to Norepinephrine, Was Not Associated with Increased Predicted Mortality after Cardiac Surgery

et al. 2007

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Material and Methods: cardiac surgical patients who received aV pinaddition to ne (n =33, aV p-group) and 33 controlpatients (negroup) who were treated with an equal dose of NE compared with AV Ppatients when AV Pinfusion started. Data on preoperative risk factors according to EuroSCORE and predicted mortality calculated by logistic EuroSCORE were collected preoperatively.Data on hemodynamics, organ dysfunctions, length of intensive care unit stay and mortality were collected.Results: EuroSCORE did not differ between the groups, AV P:10,4 ±3,9 vs ne 8,9 ± 4.0. Observed 30 day mortality was lower than predicted in both groups, AV P: 7(21,7%) vs. predictedmortality 25.9% and NE: 2(6.1%) vs. 16.0%, respectively.There were morerenal complications (36.4% vs. 9.1%, p=0,008) and infections (30.3% vs. 3.0%, p=0.003) in patients receiving AV P. Cardiovascular complications did not differ between the groups.Conclusions: In this prospectivelyo bservedc ohort of cardiac surgical patients, AV P did not increase mortality predicted by Euroscore. Anyhow renal andinfectioncomplications were common. (1), that is refractory to catecholamines( 2). This adrenergic hyposensitivity results in administrationo fh igh cacholamine doses that may have adverse effects on outcome (3, 4). The vasodilatory shockafter cardiac surgery has been associated with low serum argininev asopressin concentration(2). In contrast, serum vasopressin concentration increased significantly after uncomplicated coronary artery bypass (CABG) in the early postoperative phase and returned to baselinev alues at 24 hours (5). Arginine vasopressin (AVP) is ap otent vasocon-

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Relation of the Sequential Organ Failure Assessment Score to Morbidity and Mortality After Cardiac Surgery

Cited by 64 publications

References 26 publications

Prediction Models for Prolonged Intensive Care Unit Stay After Cardiac Surgery

Prediction Models for Prolonged Intensive Care Unit Stay After Cardiac Surgery

Value of the SOFA score as a predictive model for short-term survival in high-risk liver transplant recipients with a pre-transplant labMELD score ≥30

Vasopressin, When Added to Norepinephrine, Was Not Associated with Increased Predicted Mortality after Cardiac Surgery

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