Factors affecting reintubations after cardiac and thoracic surgeries in cardiac intensive care unit of a tertiary care hospital

Developing a calculable risk prediction model for sternal wound infection after median sternotomy: a retrospective study

Background

Diagnosing sternal wound infection (SWI) following median sternotomy remains laborious and troublesome, resulting in high mortality rates and great harm to patients. Early intervention and prevention are critical and challenging. This study aimed to develop a simple risk prediction model to identify high-risk populations of SWI and to guide examination programs and intervention strategies.

Methods

A retrospective analysis was conducted on the clinical data obtained from 6715 patients who underwent median sternotomy between January 2016 and December 2020. The least absolute shrink and selection operator (LASSO) regression method selected the optimal subset of predictors, and multivariate logistic regression helped screen the significant factors. The nomogram model was built based on all significant factors. Area under the curve (AUC), calibration curve and decision curve analysis (DCA) were used to assess the model's performance.

Results

LASSO regression analysis selected an optimal subset containing nine predictors that were all statistically significant in multivariate logistic regression analysis. Independent risk factors of SWI included female [odds ratio (OR) = 3.405, 95% confidence interval (CI) = 2.535-4.573], chronic obstructive pulmonary disease (OR = 4.679, 95% CI = 2.916-7.508), drinking (OR = 2.025, 95% CI = 1.437-2.855), smoking (OR = 7.059, 95% CI = 5.034-9.898), re-operation (OR = 3.235, 95% CI = 1.087-9.623), heart failure (OR = 1.555, 95% CI = 1.200-2.016) and repeated endotracheal intubation (OR = 1.975, 95% CI = 1.405-2.774). Protective factors included bone wax (OR = 0.674, 95% CI = 0.538-0.843) and chest physiotherapy (OR = 0.446, 95% CI = 0.248-0.802). The AUC of the nomogram was 0.770 (95% CI = 0.745-0.795) with relatively good sensitivity (0.798) and accuracy (0.620), exhibiting moderately good discernment. The model also showed an excellent fitting degree on the calibration curve. Finally, the DCA presented a remarkable net benefit.

Conclusions

A visual and convenient nomogram-based risk calculator built on disease-associated predictors might help clinicians with the early identification of high-risk patients of SWI and timely intervention.

Prediction and prognosis of reintubation after surgery for Stanford type A aortic dissection

Background

Reintubation is a serious adverse respiratory event after Stanford type A aortic dissection surgery (AADS), however, published studies focused on reintubation after AADS are very limited worldwide. The objectives of the current study were to establish an early risk prediction model for reintubation after AADS and to clarify its relationship with short-term and long-term prognosis.

Methods

Patients undergoing AADS between 2016–2019 in a single institution were identified and divided into two groups based on whether reintubation was performed. Independent predictors were identified by univariable and multivariable analysis and a clinical prediction model was then established. Internal validation was performed using bootstrap method with 1,000 replications. The relationship between reintubation and clinical outcomes was determined by univariable and propensity score matching analysis.

Results

Reintubation were performed in 72 of the 492 included patients (14.6%). Three preoperative and one intraoperative predictors for reintubation were identified by multivariable analysis, including older age, smoking history, renal insufficiency and transfusion of intraoperative red blood cells. The model established using the above four predictors showed moderate discrimination (AUC = 0.753, 95% CI, [0.695–0.811]), good calibration (Hosmer-Lemeshow χ² value = 3.282, P = 0.915) and clinical utility. Risk stratification was performed and three risk intervals were identified. Reintubation was closely associated with poorer in-hospital outcomes, however, no statistically significant association between reintubation and long-term outcomes has been observed in patients who were discharged successfully after surgery.

Conclusions

The requirement of reintubation after AADS is prevalent, closely related to adverse in-hospital outcomes, but there is no statistically significant association between reintubation and long-term outcomes. Predictors were identified and a risk model predicting reintubation was established, which may have clinical utility in early individualized risk assessment and targeted intervention.

Incidence and Causes of Reintubation Other Than Reopening of the Chest in Post-Cardiac Surgical Patients in a Tertiary Care Hospital

Objective

To determine the incidence of endotracheal reintubation, excluding surgical reopening, in post-cardiac surgical patients in a tertiary care hospital.

Material and methods

A retrospective descriptive analysis of 408 patients who underwent different cardiac surgeries during this period. Post-operative extubation was performed when patients fulfilled the preset criteria for extubation, which include consciousness (awake and aware), stable vital signs, acceptable arterial blood gases, acceptable respiratory mechanics, a maximum inspiratory force greater than 20-25 cm H₂O, chest tube drainage less than 100 ml per hour, normal temperature and electrolytes. The total number of patients who were reintubated within 72 hours of extubation was noted. The criteria for reintubation included altered conscious level with Glasgow Coma Score (GCS) of less than 8, respiratory failure, unstable hemodynamics, and arrhythmias such as ventricular tachycardia (VT) and fibrillation. All of the information was collected retrospectively on a specifically prepared form. Data was entered and evaluated in Statistical Package for the Social Sciences.

The research was piloted in the Cardiac Intensive Care Unit (CICU) of Northwest General Hospital and Research Center, Hayatabad, Peshawar from December 2018 to March 2020.

Results

Out of 408 patients who had cardiac surgeries, only nine (2.2%) were reintubated after initial extubation. The average time for which patients remained on the ventilator was 8 ± 2 hours. The reasons for reintubation were recorded. Among those reintubated, eight patients (88.88%) had undergone coronary artery bypass grafting (CABG) whereas one patient (11.11%) had undergone mitral valve replacement (MVR). In three (33.33%) patients, stroke (hemiplegia in two and global brain ischemia in one) with low GCS was the primary cause of reintubation. Arrhythmias - which included VT, ventricular fibrillation (VF), and supraventricular tachyarrhythmias (SVT) - were responsible for three (33.33%) cases of reintubation. Respiratory failure - with a partial pressure of oxygen in arterial blood less than 60 mmHg, along with tachypnea - was responsible for reintubation in two (22.22%) patients. In one (11.11%) patient who had MVR, cardiac arrest was the underlying reason; the cause of arrest could not be retrieved from the retrospective data. Notably, as a common variable, five (62.5%) out of the eight reintubated CABG patients had a poor left ventricular function. 

Conclusion

Causes of reintubation were primarily cardiac (arrhythmias) and neurological, followed by respiratory causes in our center. Patients with poor left ventricular function and diffuse coronary artery disease appear to have a higher incidence of reintubation which can lead to extended CICU and hospital stay, elevated mortality, and higher costs.