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

Development and validation of a clinical prediction model for early ventilator weaning in post-cardiac surgery

Background

Weaning patients from mechanical ventilation is a critical clinical challenge post cardiac surgery. The effective liberation of patients from the ventilator significantly improves their recovery and survival rates. This study aimed to develop and validate a clinical prediction model to evaluate the likelihood of successful extubation in post-cardiac surgery patients.

Method

A predictive nomogram was constructed for extubation success in individual patients, and receiver operating characteristic (ROC) and calibration curves were generated to assess its predictive capability. The superior performance of the model was confirmed using Delong's test in the ROC analysis. A decision curve analysis (DCA) was conducted to evaluate the clinical utility of the nomogram.

Results

Among 270 adults included in our study, 107 (28.84%) experienced delayed extubation. A predictive nomogram system was derived based on five identified risk factors, including the proportion of male patients, EuroSCORE II, operation time, pump time, bleeding during operation, and brain natriuretic peptide (BNP) level. Based on the predictive system, five independent predictors were used to construct a full nomogram. The area under the curve values of the nomogram were 0.880 and 0.753 for the training and validation cohorts, respectively. The DCA and clinical impact curves showed good clinical utility of this model.

Conclusion

Delayed extubation and weaning failure, common and potentially hazardous complications following cardiac surgery, vary in timing based on factors such as sex, EuroSCORE II, pump duration, bleeding, and postoperative BNP reduction. The nomogram developed and validated in this study can accurately predict when extubation should occur in these patients. This tool is vital for assessing risks on an individual basis and making well-informed clinical decisions.

Effects of norepinephrine infusion during cardiopulmonary bypass on perioperative changes in lactic acid level (Norcal)

INTRODUCTION

Hyperlactatemia, a problem reported in up to 30% of cardiac surgery patients, results from excessive production of or decreased clearance of lactate. It is typically a symptom of tissue hypoperfusion and may be associated with the prevalence of postoperative acute mesenteric ischemia and renal failure, or prolonged intensive care unit (ICU) and hospital stay, and increased 30-day mortality.

METHODS AND MEASUREMENTS

Eighty cardiac surgery patients using cardiopulmonary bypass (CPB) were randomly assigned into either a placebo (n = 39) or norepinephrine 0.05-0.2 µg/kg/min (n = 41) as well as norepinephrine boluses during CPB to maintain mean arterial blood pressure (MAP) at 65 to 80 mm Hg. Patient assignments were done after receiving ethical approval to proceed. The primary result was the perioperative changes in lactic acid level. Secondary findings were also recorded, including hemodynamic variables, the incidence of vasoplegia, intraoperative hypotension, myocardial ischemia, the need for vasopressor support, postoperative complications, and mortality.

RESULTS

The peak levels and perioperative changes in blood lactate during the first 24 postoperative hours, the number of patients who experienced early hyperlactatemia on admission to the ICU (Placebo: 46.2%, Norepinephrine: 51.2%, p = .650), vasoplegia, hemodynamic changes, incidences of intraoperative hypotension, myocardial ischemia, postoperative complications, and mortality rates were similar in the two groups. Patients in the norepinephrine group received lower intraoperative rescue norepinephrine boluses to maintain the target MAP (p = .039) and had higher MAP values during the CPB and intraoperative blood loss [mean difference [95% confidence interval]; 177 [20.9-334.3] ml, p = .027].

CONCLUSION

norepinephrine and placebo infusions during the CPB with the maintenance of MAP from 65 to 80 mmHg had comparative effects on the changes in blood lactate and incidence of vasoplegia after cardiac surgery. Norepinephrine infusion maintained higher MAP values during the CPB.

Nomogram and risk calculator for severe hypoxemia after heart valve surgery

Background

Hypoxemia is a very common issue in patients undergoing heart valve surgery (HVS), related to poor clinical outcomes. However, studies on severe hypoxemia (SH) after HVS have not been reported. The aims of this study were to identify predictors for SH in patients undergoing HVS and to develop and validate a risk prediction model.

Methods

Patients undergoing HVS between 2016 and 2019 in a cardiovascular center were enrolled and were assigned to training and validation sets by a 7:3 ratio. Based on whether patients developed SH, they were divided into two groups. By univariate and multivariate analysis, predictors for SH were identified. Based on the predictors and logistic rule, a nomogram and a risk calculator were generated. The model was evaluated using calibration, discrimination and clinical utility.

Results

The incidence rates of SH, moderate hypoxemia and mild hypoxemia were respectively 2.4, 23.9, and 58.2%. By multivariate analysis, seven independent risk factors for SH after HVS were identified, including body mass index, chronic obstructive pulmonary disease, renal insufficiency, white blood cell count, serum globulin, cardiopulmonary bypass time, and surgical types. The logistic model demonstrated satisfactory discrimination, calibration and clinical utility in both the training and validation sets. A nomogram and a risk calculator based on the logistic model were generated for easy application. Risk stratification was performed and three risk intervals were defined according to the nomogram and clinical practice. In addition, compared to patients without SH, patients with SH had significantly poorer clinical outcomes.

Conclusions

Postoperative hypoxemia was prevalent after HVS, related to poor clinical outcomes. A logistic model including seven independent predictors for SH after HVS were established and validated, which demonstrated satisfactory discrimination, calibration and clinical utility. The results of this study may provide help to individualized risk assessment, early prevention and perioperative management.