Dataset Information

Development and validation of a nomogram model for early postoperative hyperlactatemia in patients undergoing cardiac surgery.

ABSTRACT:

Background

Postoperative hyperlactatemia (POHL) is common in patients undergoing cardiac surgery, associated with adverse outcomes. The aim of this study was to identify predictors for POHL after cardiac surgery and to develop and validate a predictive model.

Methods

Adult patients who underwent open heart surgery at our institution between 2016 and 2019 were retrospectively included. The patients were randomly divided into training and validation groups at a 2:1 ratio. Multivariate logistic regression was performed to identify independent predictors for POHL in the training set. A nomogram was then constructed and was validated in the validation set.

Results

POHL developed in 713 of the 5,323 patients (13.4%). The mortality rate was higher in patients with POHL compared with patients without that (9.5% vs. 2.1%, P<0.001). Age, white blood cell (WBC) count, left ventricular ejection fraction, renal insufficiency, cardiac surgery history, red blood cell (RBC) transfusion, and cardiopulmonary bypass (CPB) time were identified as independent risk factors. The nomogram based on these predictors indicated good discrimination in both the training (c-index: 0.787) and validation (c-index: 0.820) sets. The calibration was reasonable by both visual inspection and goodness-of-fit test. The decision and clinical impact curves demonstrated good clinical utility.

Conclusions

We identified 7 independent risk factors and derived a prediction model for POHL in patients undergoing cardiac surgery. The model may contribute significantly to early risk assessment and clinical intervention.

SUBMITTER: Wang S

PROVIDER: S-EPMC8482329 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature

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Publications

Development and validation of a nomogram model for early postoperative hyperlactatemia in patients undergoing cardiac surgery.

Wang Su S Wang Dashuai D Huang Xiaofan X Wang Hongfei H Le Sheng S Zhang Jinnong J Du Xinling X

Journal of thoracic disease 20210901 9

<h4>Background</h4>Postoperative hyperlactatemia (POHL) is common in patients undergoing cardiac surgery, associated with adverse outcomes. The aim of this study was to identify predictors for POHL after cardiac surgery and to develop and validate a predictive model.<h4>Methods</h4>Adult patients who underwent open heart surgery at our institution between 2016 and 2019 were retrospectively included. The patients were randomly divided into training and validation groups at a 2:1 ratio. Multivaria ...[more]

PMID: 34659806

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Project description:BackgroundThe ARISCAT score, a prospectively developed generic classification for postoperative pulmonary complications (PPCs), has shown excellent predictive performance in general surgery. However, there is no reliable classification instrument for PPCs prediciton in thoracic surgery.ObjectiveThis study aimed to develop and validate a novel nomogram for estimating the risk of pulmonary complications in older patients (≥ 65 years) within 30 days after NCTS.MethodsA nomogram was developed using predefined candidate predictors of 30-day PPCs. It was fitted with least absolute shrinkage and selection operator and logistic regression methods. Internal validation was performed using a bootstrap-resampling approach, while external validation used an independent, temporally separated cohort. The model's performance was assessed based on its discriminative potential (area under the receiver operating characteristic curve [AUC]), predictive ability (calibration plots), and clinical utility (net benefit).ResultsIn the development (n = 1449) and validation (n = 449) cohorts, 34.9% and 31.4% of patients, respectively, developed pulmonary complications 30 days post-surgery. The final nomogram incorporated eight predictors (age, surgical approach, desaturation of < 92% for more than 2 min, duration of surgery, smoking status, FEV1/FVC%, respiratory infection in the last 30 days, and neoadjuvant chemotherapy). The nomogram showed excellent discrimination (AUC = 0.866, 95% confidence interval [CI], 0.846-0.885), calibration (Hosmer- Lemeshow test, P = 0.97) and overall performance (Brier score = 0.014) in the development cohort. Similar results were observed in the external validation cohort (AUC = 0.825, 95% CI, 0.786-0.864). A decision curve analysis indicated that the nomogram offers a positive net benefit compared with the ARISCAT and LAS VEGAS scores.ConclusionsThis novel nomogram can reliably identify older patients with a high risk for pulmonary complications within 30 days after NCTS.Trial registrationChiCTR2100051170.

Project description:BackgroundPostoperative pulmonary complications (PPCs) remain a prevalent concern among elderly patients undergoing surgery, with a notably higher incidence observed in elderly patients undergoing thoracic surgery. This study aimed to develop a nomogram to predict the risk of PPCs in this population.MethodsA total of 2963 elderly patients who underwent thoracic surgery were enrolled and randomly divided into a training cohort (80%, n = 2369) or a validation cohort (20%, n = 593). Univariate and multivariate logistic regression analyses were conducted to identify risk factors for PPCs, and a nomogram was developed based on the findings from the training cohort. The validation cohort was used to validate the model. The predictive accuracy of the model was evaluated by receiver operating characteristic (ROC) curve, area under ROC (AUC), calibration curve, and decision curve analysis (DCA).ResultsA total of 918 (31.0%) patients reported PPCs. Nine independent risk factors for PPCs were identified: preoperative presence of chronic obstructive pulmonary disease (COPD), elevated leukocyte count, higher partial pressure of arterial carbon dioxide (PaCO2) level, surgical site, thoracotomy, intraoperative hypotension, blood loss > 100 mL, surgery duration > 180 min, and malignant tumor. The AUC value for the training cohort was 0.739 (95% CI: 0.719-0.762), and it was 0.703 for the validation cohort (95% CI: 0.657-0.749). The P-values for the Hosmer-Lemeshow test were 0.633 and 0.144 for the training and validation cohorts, respectively, indicating a notable calibration curve fit. The DCA curve indicated that the nomogram could be applied clinically if the risk threshold was between 12% and 84%, which was found to be between 8% and 82% in the validation cohort.ConclusionThis study highlighted the pressing need for early detection of PPCs in elderly patients undergoing thoracic surgery. The nomogram exhibited promising predictive efficacy for PPCs in elderly patients undergoing thoracic surgery, enabling the identification of high-risk patients and consequently aiding in the implementation of preventive interventions.

Project description:BackgroundSuccessful weaning and extubation after cardiac surgery is an important step of postoperative recovery. Delayed extubation is associated with poor prognosis and high mortality, thereby contributing to a substantial economic burden. The aim of this study was to develop and validate a prediction model estimate the risk of delayed extubation after cardiac surgery based on perioperative risk factors.MethodsWe performed a retrospective cohort study of adult patients undergoing cardiac surgery from 2014 to 2019. Eligible participants were randomly assigned into the development and validation cohorts, with a ratio of 7:3. Variables were selected using least absolute shrinkage and selection operator (LASSO) logistic regression model with 10-fold cross-validation. Multivariable logistic regression was applied to develop a predictive model by introducing the predictors selected from the LASSO regression. Receiver operating characteristic (ROC) curve, calibration plot, decision curve analysis (DCA) and clinical impact curve were used to evaluate the performance of the predictive risk score model.ResultsAmong the 3,919 adults included in our study, 533 patients (13.6%) experienced delayed extubation. The median ventilation time was 68 h in the group with delayed extubation and 21 h in the group without delayed extubation. A predictive scoring system was derived based on 10 identified risk factors based on 10 identified risk factors including age, BMI ≥ 28 kg/m2, EF < 50%, history of cardiac surgery, type of operation, emergency surgery, CPB ≥ 120 min, duration of surgery, IABP and eGFR < 60 mL/min/1.73 m2. According to the scoring system, the patients were classified into three risk intervals: low, medium and high risk. The model performed well in the validation set with AUC of 0.782 and a non-significant p-value of 0.901 in the Hosmer-Lemeshow test. The DCA curve and clinical impact curve showed a good clinical utility of this model.ConclusionsWe developed and validated a prediction score model to predict the risk of delayed extubation after cardiac surgery, which may help identify high-risk patients to target with potential preventive measures.

Dataset Information

Development and validation of a nomogram model for early postoperative hyperlactatemia in patients undergoing cardiac surgery.

Background

Methods

Results

Conclusions

Publications

Development and validation of a nomogram model for early postoperative hyperlactatemia in patients undergoing cardiac surgery.

Similar Datasets

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