Risk factors for reintubation after anterior cervical discectomy and fusion surgery: evaluation of three observational data sets

Wilson, Laird; Zubizarreta, Nicole; Bekeris, Janis; Poeran, Jashvant; Liu, Jiabin; Fiasconaro, Megan; Girardi, Federico P.; Elkassabany, Nabil; Memtsoudis, Stavros G.

doi:10.1007/s12630-019-01492-8

Cited by 16 publications

(21 citation statements)

References 29 publications

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“…were associated with a higher risk of unplanned re-intubation. 28 There are several potential limitations inherent to this study. First, the sample of patients undergoing ACDF may not have been accurately representative of all the patients who undergo ACDF.…”

Section: Discussionmentioning

confidence: 96%

An Artificial Intelligence Approach to Predicting Unplanned Intubation Following Anterior Cervical Discectomy and Fusion

Veeramani

Zhang

Blackburn

et al. 2022

Global Spine Journal

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Study Design Level III retrospective database study. Objectives The purpose of this study is to determine if machine learning algorithms are effective in predicting unplanned intubation following anterior cervical discectomy and fusion (ACDF). Methods The National Surgical Quality Initiative Program (NSQIP) was queried to select patients who had undergone ACDF. Machine learning analysis was conducted in Python and multivariate regression analysis was conducted in R. C-Statistics area under the curve (AUC) and prediction accuracy were used to measure the classifier’s effectiveness in distinguishing cases. Results In total, 54 502 patients met the study criteria. Of these patients, .51% underwent an unplanned re-intubation. Machine learning algorithms accurately classified between 72%-100% of the test cases with AUC values of between .52-.77. Multivariable regression indicated that the number of levels fused, male sex, COPD, American Society of Anesthesiologists (ASA) > 2, increased operating time, Age > 65, pre-operative weight loss, dialysis, and disseminated cancer were associated with increased risk of unplanned intubation. Conclusions The models presented here achieved high accuracy in predicting risk factors for re-intubation following ACDF surgery. Machine learning analysis may be useful in identifying patients who are at a higher risk of unplanned post-operative re-intubation and their treatment plans can be modified to prophylactically prevent respiratory compromise and consequently unplanned re-intubation.

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Section: Discussionmentioning

confidence: 96%

An Artificial Intelligence Approach to Predicting Unplanned Intubation Following Anterior Cervical Discectomy and Fusion

Veeramani

Zhang

Blackburn

et al. 2022

Global Spine Journal

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“…While previous studies have identified the incidence and risk factors for RC, 24 , 28 , 33 none have fully defined the short-term clinical course of patients who develop RC. This study demonstrates that patients who develop RC have high rates of both morbidity and mortality.…”

Section: Discussionmentioning

confidence: 99%

“…Prior studies have demonstrated increased pre-vertebral soft tissue swelling as a function of number of levels fused, corpectomies, and upper cervical spine surgery. 31,32 While previous studies have identified the incidence and risk factors for RC, 24,28,33 none have fully defined the shortterm clinical course of patients who develop RC. This study demonstrates that patients who develop RC have high rates of both morbidity and mortality.…”

Section: Discussionmentioning

confidence: 99%

Respiratory Compromise After Anterior Cervical Spine Surgery: Incidence, Subsequent Complications, and Independent Predictors

Boddapati

Lee

Mathew

et al. 2021

Global Spine Journal

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Study design: Retrospective cohort study. Objective: Respiratory compromise (RC) is a rare but catastrophic complication of anterior cervical spine surgery (ACSS) commonly due to compressive fluid collections or generalized soft tissue swelling in the cervical spine. Established risk factors include operative duration, size of surgical exposure, myelopathy, among others. The purpose of this current study is to identify the incidence and clinical course of patients who develop RC, and identify independent predictors of RC in patients undergoing ACSS for cervical spondylosis. Methods: A large, prospectively-collected registry was used to identify patients undergoing ACSS for spondylosis. Patients with posterior cervical procedures were excluded. Baseline patient characteristics were compared using bivariate analysis, and multivariate analysis was employed to compare postoperative complications and identify independent predictors of RC. Results: 298 of 52,270 patients developed RC (incidence 0.57%). Patients who developed RC had high rates of 30-day mortality (11.7%) and morbidity (75.8%), with unplanned reoperation and pneumonia the most common. The most common reason for reoperations were hematoma evacuation and tracheostomy. Independent patient-specific factors predictive of RC included increasing patient age, male gender, comorbidities such as chronic cardiac and respiratory disease, preoperative myelopathy, prolonged operative duration, and 2-level ACCFs. Conclusion: This is among the largest cohorts of patients to develop RC after ACSS identified to-date and validates a range of independent predictors, many previously only described in case reports. These results are useful for taking preventive measures, identifying high risk patients for preoperative risk stratification, and for surgical co-management discussions with the anesthesiology team.

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“…Finally, a total of 10 studies and 5,15,940 patients were included in this metaanalysis. (1,3,(13)(14)(15)(16)(17)(18)(19) The selection process and results are shown in Figure 1.…”

Section: Study Selectionmentioning

confidence: 99%

Risk Factors for Post-operative Planned Reintubation in Patients After General Anesthesia: A Systematic Review and Meta-Analysis

et al. 2022

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BackgroundThe occurrence of postoperative reintubation (POR) in patients after general anesthesia (GA) is often synonymous with a poor prognosis in patients. This is the first review analyzing scientific literature to identify risk factors of POR after general anesthesia. The purpose of this study was to collect currently published studies to determine the most common and consistent risk factors associated with POR after GA.MethodsWe have retrieved all relevant research published before April 2021 from PubMed, Embase, Web of Science, and the Cochrane Library electronic databases. These studies were selected according to the inclusion and exclusion criteria. The Z test determined the combined odds ratio (OR) of risk factors. We used OR and its corresponding 95% confidence interval (CI) to identify significant differences in risk factors. The quality of the study was evaluated with the NOS scale, and meta-analysis was carried out with Cochrane Collaboration's Revman 5.0 software.ResultsA total of 10 studies were included, with a total of 7,789 recipients of POR. We identified 7 risk factors related to POR after GA: ASA ≥ 3 (OR = 3.58), COPD (OR = 2.09), thoracic surgery (OR = 17.09), airway surgery (OR = 9.93), head-and-neck surgery (OR = 3.49), sepsis (OR = 3.50), DVT (OR = 4.94).ConclusionOur meta-analysis showed that ASA ≥ 3, COPD, thoracic surgery, airway surgery, head-and-neck surgery, sepsis and DVT were associated with POR after GA.Systematic Review Registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?, Identifier: CRD42021252466.

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Risk factors for reintubation after anterior cervical discectomy and fusion surgery: evaluation of three observational data sets

Cited by 16 publications

References 29 publications

An Artificial Intelligence Approach to Predicting Unplanned Intubation Following Anterior Cervical Discectomy and Fusion

An Artificial Intelligence Approach to Predicting Unplanned Intubation Following Anterior Cervical Discectomy and Fusion

Respiratory Compromise After Anterior Cervical Spine Surgery: Incidence, Subsequent Complications, and Independent Predictors

Risk Factors for Post-operative Planned Reintubation in Patients After General Anesthesia: A Systematic Review and Meta-Analysis

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