Neurocrit Care DOI 10.1007/s12028-014-0053-1
ORIGINAL ARTICLE
Risk of Reintubation in Neurosurgical Patients Daniel Shalev • Hooman Kamel
Ó Springer Science+Business Media New York 2014
Abstract Background Reintubation among neurosurgical patients is poorly characterized. The aim of this study was to delineate the rate of reintubation among neurosurgical patients. In addition, we seek to characterize the patient demographic features, comorbidities, and surgical characteristics that may be associated with reintubation among neurosurgical patients. Methods This is a retrospective cohort study conducted in the setting of hospitals participating in the American College of Surgeons’ National Surgical Quality Improvement Program between 2005 and 2010. All adult patients undergoing neurosurgery under general anesthesia were included. Exclusion criteria were preoperative mechanical ventilation or pneumonia prior to surgery. Reintubation was defined as placement of an endotracheal tube or mechanical ventilation within 48 h after surgery. Results Among 17,483 eligible patients, 74 (0.42 %; 95 % CI 0.33–0.52 %) required reintubation within 48 h of surgery. In multiple logistic regression, the following were associated with increased risk of reintubation: age >65 years (OR 2.1; 95 % CI 1.3–3.4), preoperative renal failure (OR 2.9; 95 % CI 1.0–8.5), quadriplegia (OR 8.2; 95 % CI 3.3–20.3), COPD (OR 2.1; 95 % CI 1.0–4.3), operative time >3 h (OR 2.9; 95 % CI 1.8–4.8), and higher ASA class (OR per point, 2.1; 95 % CI 1.4–3.1). Spinal surgery was
D. Shalev H. Kamel Department of Neurology, Brain and Mind Research Institute, Weill Cornell Medical College, New York, NY, USA H. Kamel (&) 407 East 61st St, 5th Floor, New York, NY 10065, USA e-mail: [email protected]
found to be protective relative to cranial neurosurgery or endarterectomy (OR 0.3; 95 % CI 0.2–0.5). Conclusions Reintubation after neurosurgery is associated with older patients with a greater number of comorbidities. In particular, renal, pulmonary, and severe neurologic comorbidities; longer operative duration; and cranial, rather than spinal, pathology were associated with increased risk for reintubation. These findings may be helpful in triage decisions regarding postoperative intensity of care and monitoring. Keywords Neurosurgery Neurocritical Reintubation Neurology Extubation Airway management
Introduction Extubation failure is typically defined as reintubation within 48–72 h of extubation. Evidence suggests that extubation failure is itself associated with significantly increased morbidity and mortality. Even adjusting for severity of illness and comorbidities, reintubation is significantly associated with higher mortality, longer intensive care unit (ICU) course, increased risk of transfer to long term care facilities, higher incidence of nosocomial pneumonia, and a more expensive hospital course [1–4]. Current data suggest that reintubation occurs after approximately 10–25 % of neurosurgical operations [5–7]. However, these data are of limited application to a broad neurosurgical cohort of patients because they are primarily derived from very high-acuity cohorts of patients in the ICU. A disproportionate number of the patients comprising the existing data were admitted for intracranial hemorrhage and trauma, which are in and of themselves potentially neurologically devastating conditions. In addition, prior
123
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data on reintubation among neurosurgical patients have failed to distinguish surgical patients from the general neurocritical care patient population and have largely included non-surgical patients along with surgical patients [6, 7]. Currently, little data exist about the incidence of and risk factors for reintubation among the broader cohort of neurosurgical patients. Because there is a lack of data on reintubation rates and risk among neurosurgical patients, it has proven difficult to establish clinical guidelines on weaning neurosurgical patients [3]. Standard weaning criteria such as vital capacity, minute ventilation, maximum inspiratory pressure, and the rapid shallow breathing index are used as parameters for extubation in the general population of intubated patients; however, these parameters appear to translate poorly to patients with neurologic deficits. Although some studies have shown positive predictive value for higher P/F ratios and lower minute ventilation, other studies have not found any individual or combined standard weaning parameters to be useful in predicting extubation failure among neurosurgical patients [5, 8–10]. The insufficiency of traditional weaning parameters in predicting extubation failure among neurosurgical patients may reflect high rates of neurologic dysfunction that results in inability to protect the airway. Some investigators have found evidence that a Glasgow Coma Scale score > 8 predicts successful extubation, but these findings have not been widely reproducible [5–7]. Other studies have evaluated the FOUR Score scale and not found it to be of predictive value either [8]. Therefore, both level of consciousness and overall neurologic function may be factors in extubation outcomes, but they have not been translatable into successful predictive tools. Furthermore, these data also suffer from the problems described above in that they selectively evaluate only profoundly ill in the intensive care setting. Improved understanding of the incidence of reintubation among neurosurgical patients is an important first step in improving postoperative neurosurgical outcomes. Understanding the overall risk, as well as predictive factors, may help triage some neurosurgical patients away from intensive care settings postoperatively [11]. Such clinical decisions about level of postoperative care are fundamentally contingent on an accurate assessment of incidence of extubation complications such as reintubation among neurosurgical patients. Currently, there exists little data on the incidence of reintubation among the general cohort of neurosurgical patients. Those data that exist are derived from high-acuity patients in neurologic intensive care settings, some of whom have not undergone surgery. In addition, there is little evidence about risk factors for reintubation among neurosurgical patients despite existing data demonstrating
123
poor predictive value of traditional weaning parameters for this patient population.
Methods Design We assessed risk factors for reintubation within 48 h of surgery in a cohort of neurosurgical patients prospectively assembled by the American College of Surgeons National Surgical Quality Improvement Program (NSQIP). The NSQIP is a national registry promoting quality improvement by comparing risk-adjusted 30-day surgical outcomes across surgical centers with varying surgical volume and subspecialty expertise. NSQIP included 121 centers in 2005, but grew to 258 by 2010. The methodology of the NSQIP has been described elsewhere; in brief, a dedicated surgical clinician reviewer works with a coordinator at each institution to collect and input data collected from medical charts and provider interviews [12–14]. Data collectors undergo standardized training, and inter-rater variability is measured at under 2 % [15]. Data are collected on patient demographic characteristics, comorbidities, laboratory values, operative factors, and 30day postoperative outcomes. Our analysis was exempt from evaluation by our institutional review board because we employed only publicly available, deidentified data. Patients The NSQIP includes patients undergoing both inpatient and outpatient surgical procedures. Trauma and transplant cases are excluded. For our analysis, we used the NSQIP designations of surgical type to identify patients over 18 years old who underwent neurologic surgery under general anesthesia. We excluded patients who had evidence of pneumonia prior to surgery (based on physical examination findings, chest imaging, and sputum culture) or who were ventilator dependent at any point during the 48 h before surgery. Measurements Our outcome of interest was reintubation which was defined as placement of an endotracheal tube and mechanical or assisted ventilation due to hypoxia, hypercapnia, severe respiratory distress, or respiratory acidosis secondary to cardiac or respiratory failure after postsurgical extubation. We chose to focus on patients who were extubated soon after surgery, since this population is most relevant for making perioperative decisions about disposition (i.e., ICU versus less monitored settings), and therefore
Neurocrit Care
limited our outcome to reintubations occurring within 48 h of surgery. We divided potential risk factors for reintubation into three general categories, and collected data accordingly: patient demographic characteristics, comorbidities, and operative type and course. With regards to patient demographics, we considered patient age, sex, and race (white, black, Native American, Native Hawaiian/Pacific Islander, Asian, or unknown). We noted patient comorbidities previously identified as associated with reintubation: diabetes mellitus, congestive heart failure (CHF), history of recent myocardial infarction (MI), hypertension (blood pressure > 140/90 mmHg requiring antihypertensive medication), acute renal failure (worsening azotemia and a creatinine over 2 mg/dL), and chronic obstructive pulmonary disease (COPD was diagnosed based on functional disability, past hospitalization for specific treatment, chronic bronchodilator therapy, or an FEV1 < 75 % of predicted) [16–21]. A smoking history of >30 pack years was also noted because of an association between smoking and postoperative pulmonary complications among cancer patients [22]. Quadriplegia and hemiplegia were used as proxies for neurologic function, recognizing that both of these variables are limited by the lack of standardized definitions in the NSQIP. We employed Current Procedural Terminology (CPT) codes to separate patients whose procedures were peripheral, spinal, and intracranial. Given the likely differences in reintubation risk for elective versus non-elective surgery, we included as a variable the elective versus non-elective status of the surgery in our models [16]. Additionally, we included in our model American Society of Anesthesiologists (ASA) Physical Status classifications and operating room (OR) time >3 h because of previously demonstrated value of these variables in predicting non-neurosurgical reintubation [16, 17]. Statistical Analysis All statistical analysis was performed using Stata MP (Version 12, StataCorp, College Station, TX). Our primary dependent variable was reintubation. Descriptive statistics were used to present medians and interquartile ranges for continuous variables, and counts and percentages with exact binomial confidence intervals (CI) for categorical variables. Categorical variables were compared using v2 and Fisher’s exact tests as appropriate. Continuous variables were compared using Student’s t test or the Mann– Whitney test depending on their distribution. Multivariable analysis was performed by logistic regression. Backward stepwise selection was used to determine the final regression model, with p < 0.2 in the univariate analysis set as the threshold for inclusion. Of note, the regression was also
run among the cranial surgery cohort in order to compare incidence of reintubation and risk factors to the larger group. Statistical significance was set as p < 0.05. In a sensitivity analysis, we excluded hemiplegia and quadriplegia from our model to assess the effects of these possibly imprecise variables.
Results We identified 17,483 neurosurgical patients without pneumonia or ventilator dependence prior to surgery. Among these eligible patients, 74 (0.42 %; 95 % CI 0.33– 0.52 %) required reintubation within 48 h of surgery (Table 1). As expected, patients who required reintubation were more likely to be >65 years of age (OR, 2.1; 95 % CI 1.3– 3.4; p = 0.003), and to have a greater number of comorbidities prior to surgery. In particular, the following comorbid conditions were independently associated with increased odds of reintubation: preoperative renal failure (OR, 2.9; 95 % CI 1.0–8.5; p = 0.046), preoperative quadriplegia (OR, 8.2; 95 % CI 3.3–20.3; p < 0.001), ASA class (OR per point, 2.1; 95 % CI 1.4–3.1; p < 0.001), and preoperative COPD (OR, 2.1; 95 % CI 1.0–4.3; p = 0.049). Procedures lasting over 3 h were associated with greater likelihood of reintubation (OR, 2.9; 95 % CI 1.8-4.8; p < 0.001). Non-elective (emergency) surgery was associated with reintubation, but this was not significant, likely due to the relatively low number of emergent cases included (OR, 1.9; 95 % CI 1.0–3.8; p = 0.053). Patients undergoing spinal surgery were less likely to be reintubated compared to those undergoing endarterectomy or cranial surgery (OR, 0.3; 95 % CI 0.2-0.5; p < 0.001). Our findings were essentially unchanged in models excluding hemiplegia and quadriplegia as variables. In order to better understand the relationship between risk of reintubation and surgery type, we also ran our regression among only the 4,325 cranial surgery patients. In this cohort, the rate of reintubation was 1.0 % (95 % CI 0.7–1.3 %). Overall, the major risk factors identified were similar to the larger cohort: age over 65 (OR, 3.1; 95 % CI 1.6–5.8; p = 0.001) and operative time of over 3 h (OR, 3.6; 95 % CI 1.8–7.2; p < 0.001) remained significant predictors of reintubation. Interestingly, among the cranial surgery cohort, non-elective (emergency) surgery was a strong predictor of reintubation (OR, 3.3; 95 % CI 1.6–6.8; p = 0.001). Furthermore, renal failure was also a much stronger predictor than in the broader cohort (OR, 6.8; 95 % CI 1.9–23.8; p = 0.003), although it was also a significant predictor in the cohort at large. Despite being statistically significant risk factors in the broader analysis,
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Neurocrit Care Table 1 Cohort and surgical characteristics stratified by reintubation status Characteristicsa
Reintubation n = 74 (0.42 %)
No reintubation n = 17,409
Patient demographics Age, mean, years
61.88 ± 14.01
55.57 ± 15.25
Age > 65
50
27.8
White
76.7
77.7
Black
15.1
8.1
Race
Hispanic
4.1
5.8
Asian
1.4
1.5
American Indian
2.7
6.9
COPD
12.2
4
Congestive heart failure
0
0.2
Coronary heart disease
12.2
5.4
Diabetes Hypertension
20.3 64.9
9.4 46.5
Preoperative hemiplegia
10.8
3.9
Preoperative quadriplegia
8.1
0.8
Renal failure
5.4
1
Tobacco use
24.3
26.3
Patient comorbidities
ASA class 1
0
4.9
2
10.8
46.1
3
64.9
43.6
4
24.3
5.2
5
0
0.1
Cranial
58.1
24.6
Endarterectomy
2.7
Neurosurgical type
Spine 39.2 Other surgical characteristics
0.6 74.8
Operative time > 3 h
59.5
31.5
Non-elective case
17.6
4.4
a
All values expressed in % except as otherwise indicated
COPD and ASA class were not significant in this group, perhaps due to the smaller sample size.
Discussion In a cohort of neurosurgical patients, we found older age, renal and pulmonary comorbidity, preexisting quadriplegia, longer procedure time, and non-spinal neurosurgery were independently associated with reintubation within 48 h. Among patients undergoing cranial surgery, the strongest
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risk factors were older age, longer operative time, renal failure, and non-elective (emergency) surgery. Interestingly, preexisting cardiovascular disease (CHF, history of MI, hypertension) is not associated with reintubation. This may be because very few patients undergoing surgery had heart failure (0.25 %), suggesting that even among patients with hypertension and recent MI, cardiac function was not significantly impaired. Prior data have indicated that reintubation rates among neurosurgical or neurologically impaired patients range from 10 to 25 % [5–7]. This data, however, are based on patients in neurocritical care settings, some of whom were not surgical patients. Our data analysis is the first to examine rates of reintubation in a broader neurosurgical cohort spanning a variety of emergent and non-emergent procedures. Our findings show that unlike those patients in neurocritical care settings, the risk for reintubation among neurosurgical patients is quite low (0.42 %), even among patients undergoing cranial surgery (0.99 %). Although prior data have demonstrated associations between renal, cardiac, pulmonary morbidity, and reintubation among general patients, these findings had not been confirmed in neurosurgical patients, for whom standard predictors of reintubation risk have not been successful [8, 9, 16–21]. We found that many of these risk factors are applicable to neurosurgical patients. In addition, we found that procedural factors such as prolonged OR time, which have been associated with an increased risk of reintubation in general post-anesthesia care units and in cardiac patients, are also risk factors among neurosurgical patients [16, 17]. There were a number of limitations in our study. Our ability to delineate precise neurological function was limited by the NSQIP definitions. We attempted to use hemiplegia and quadriplegia as proxies for neurologic function, but these are suboptimal because they do not address directly the relevant degree of functional impairment. However, the associations we found were essentially unchanged when we removed quadriplegia from our model, suggesting that even if our characterization of the relationship between quadriplegia and reintubation is imprecise, our other findings are unaffected. We also excluded patients who were ventilator dependent prior to surgery in order to avoid confounding, but in doing so, we may have excluded sicker neurosurgical cases involving patients with significant neurologic impairment prior to surgery. In essence, our exclusion of ventilator-dependent patients from our data set means that we may have examined the cohort of neurosurgical patients excluded from prior high-acuity trials, and the actual incidence of reintubation may be somewhere between our data and those data derived from intensive care settings only. Our data do not provide a clear distinction between correlative and causative factors. We believe that the risk
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factors we have identified are pertinent for predictive purposes. Some of the factors we have identified, such as preexisting cardiopulmonary disease, are likely to be causal. Other identified factors, such as older age, are likely to simply be associated with poorer overall functional status. For many of the risk factors we identified, however, causality is not clear and merits further investigation in studies of interventions to reduce the rate of postsurgical reintubation in this population. Risk factors for reintubation among neurosurgical patients have been poorly delineated. Traditional weaning parameters have not translated into successful extubation parameters for this patient population [8]. However, decisions about triage and discharge disposition in the postneurosurgical care setting are complex and need to take into account the likelihood of a patient requiring reintubation. Therefore, our parameters may assist intensivists and neurosurgeons in making triage decisions for patients in whom the readiness for extubation is not patently clear. Conflict of interest Daniel Shalev and Hooman Kamel declare they have no conflict of interest.
References 1. Epstein SK, Ciubotaru RL, Wong JB. Effect of failed extubation on the outcome of mechanical ventilation. Chest. 1997;112:186– 92. 2. Epstein SK, Ciubotaru RL. Independent effects of etiology of failure and time to reintubation on outcome for patients failing extubation. Am J Respir Crit Care Med. 1998;158:489–93. 3. Rothaar RC, Epstein SK. Extubation failure: magnitude of the problem, impact on outcomes, and prevention. Curr Opin Crit Care. 2003;9:59–66. 4. Torres A, Gatell JM, Aznar E, El-Ebiary M, de la Bellacasa JP, Gonza´lez J, et al. Re-intubation increases the risk of nosocomial pneumonia in patients needing mechanical ventilation. Am J Respir Crit Care Med. 1995;152:137–41. 5. Namen AM, Ely EW, Tatter SB, Case LD, Lucia MA, Smith A, et al. Predictors of successful extubation in neurosurgical patients. Am J Respir Crit Care Med. 2001;163:658–64. 6. Anderson CD, Bartscher JF, Scripko PD, Biffi A, Chase D, Guanci M, et al. Neurologic examination and extubation outcome in the neurocritical care unit. Neurocrit Care. 2011;15:490–7. 7. Coplin WM, Pierson DJ, Cooley KD, Newell DW, Rubenfeld GD. Implications of extubation delay in brain-injured patients meeting standard weaning criteria. Am J Respir Crit Care Med. 2000;161:1530–6. 8. Ko R, Ramos L, Chalela JA. Conventional weaning parameters do not predict extubation failure in neurocritical care patients. Neurocrit Care. 2009;10:269–73.
9. Vidotto MC, Sogame LCM, Calciolari CC, Nascimento OA, Jardim JR. The prediction of extubation success of postoperative neurosurgical patients using frequency–tidal volume ratios. Neurocrit Care. 2008;9:83–9. 10. Navalesi P, Frigerio P, Moretti MP, Sommariva M, Vesconi S, Baiardi P, et al. Rate of reintubation in mechanically ventilated neurosurgical and neurologic patients: evaluation of a systematic approach to weaning and extubation. Crit Care Med. 2008;36:2986–92. 11. Rhondali O, Genty C, Halle C, Gardellin M, Ollinet C, Oddoux M, et al. Do patients still require admission to an intensive care unit after elective craniotomy for brain surgery? J Neurosurg Anesthesiol. 2011;23:118–23. 12. Hammermeister K. The National Surgical Quality Improvement Program: learning from the past and moving to the future. Am J Surg. 2009;198:S69–73. 13. Henderson WG, Daley J. Design and statistical methodology of the National Surgical Quality Improvement Program: why is it what it is? Am J Surg. 2009;198:S19–27. 14. Neumayer L. How do (and why should) I use the National Surgical Quality Improvement Program? Am J Surg. 2009;198:S36– 40. 15. Shiloach M, Frencher SK Jr, Steeger JE, Rowell KS, Bartzokis K, Tomeh MG, et al. Toward robust information: data quality and inter-rater reliability in the American College of Surgeons National Surgical Quality Improvement Program. J Am Coll Surg. 2010;210:6–16. 16. Rujirojindakul P, Geater AF, McNeil EB, Vasinanukorn P, Prathep S, Asim W, et al. Risk factors for reintubation in the postanaesthetic care unit: a case–control study. Br J Anaesth. 2012;109:636–42. 17. Engoren M, Buderer NF, Zacharias A, Habib RH. Variables predicting reintubation after cardiac surgical procedures. Ann Thorac Surg. 1999;67:661–5. 18. Rady MY, Ryan T. Perioperative predictors of extubation failure and the effect on clinical outcome after cardiac surgery. Crit Care Med. 1999;27:340–7. 19. Hodari A, Reddy S, Eichenhorn M, Rubinfeld I, Horst M. Exploring NSQIP respiratory comorbidities: developing our predictive understanding of postoperative respiratory occurrences, Clavien 4 complications, and death. Chest J. 2011;140:880A. 20. Cumpeeravut P, Visudharom K, Jotisakulratana V, Pitiguagool V, Banyatpiyaphod S, Pamornsing P. Off-pump coronary artery bypass surgery: evaluation of extubation time and predictors of failed early extubation. J Med Assoc Thai. 2003;86(Suppl 1):S28–35. 21. Dorsa AG, Rossi AI, Thierer J, Lupian˜ez B, Vrancic JM, Vaccarino GN, et al. Immediate extubation after off-pump coronary artery bypass graft surgery in 1, 196 consecutive patients: feasibility, safety and predictors of when not to attempt it. J Cardiothorac Vasc Anesth. 2011;25:431–6. 22. Gajdos C, Hawn MT, Campagna EJ, Henderson WG, Singh JA, Houston T. Adverse effects of smoking on postoperative outcomes in cancer patients. Ann Surg Oncol. 2012;19:1430–8.
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ORIGINAL ARTICLE
Risk of Reintubation in Neurosurgical Patients Daniel Shalev • Hooman Kamel
Ó Springer Science+Business Media New York 2014
Abstract Background Reintubation among neurosurgical patients is poorly characterized. The aim of this study was to delineate the rate of reintubation among neurosurgical patients. In addition, we seek to characterize the patient demographic features, comorbidities, and surgical characteristics that may be associated with reintubation among neurosurgical patients. Methods This is a retrospective cohort study conducted in the setting of hospitals participating in the American College of Surgeons’ National Surgical Quality Improvement Program between 2005 and 2010. All adult patients undergoing neurosurgery under general anesthesia were included. Exclusion criteria were preoperative mechanical ventilation or pneumonia prior to surgery. Reintubation was defined as placement of an endotracheal tube or mechanical ventilation within 48 h after surgery. Results Among 17,483 eligible patients, 74 (0.42 %; 95 % CI 0.33–0.52 %) required reintubation within 48 h of surgery. In multiple logistic regression, the following were associated with increased risk of reintubation: age >65 years (OR 2.1; 95 % CI 1.3–3.4), preoperative renal failure (OR 2.9; 95 % CI 1.0–8.5), quadriplegia (OR 8.2; 95 % CI 3.3–20.3), COPD (OR 2.1; 95 % CI 1.0–4.3), operative time >3 h (OR 2.9; 95 % CI 1.8–4.8), and higher ASA class (OR per point, 2.1; 95 % CI 1.4–3.1). Spinal surgery was
D. Shalev H. Kamel Department of Neurology, Brain and Mind Research Institute, Weill Cornell Medical College, New York, NY, USA H. Kamel (&) 407 East 61st St, 5th Floor, New York, NY 10065, USA e-mail: [email protected]
found to be protective relative to cranial neurosurgery or endarterectomy (OR 0.3; 95 % CI 0.2–0.5). Conclusions Reintubation after neurosurgery is associated with older patients with a greater number of comorbidities. In particular, renal, pulmonary, and severe neurologic comorbidities; longer operative duration; and cranial, rather than spinal, pathology were associated with increased risk for reintubation. These findings may be helpful in triage decisions regarding postoperative intensity of care and monitoring. Keywords Neurosurgery Neurocritical Reintubation Neurology Extubation Airway management
Introduction Extubation failure is typically defined as reintubation within 48–72 h of extubation. Evidence suggests that extubation failure is itself associated with significantly increased morbidity and mortality. Even adjusting for severity of illness and comorbidities, reintubation is significantly associated with higher mortality, longer intensive care unit (ICU) course, increased risk of transfer to long term care facilities, higher incidence of nosocomial pneumonia, and a more expensive hospital course [1–4]. Current data suggest that reintubation occurs after approximately 10–25 % of neurosurgical operations [5–7]. However, these data are of limited application to a broad neurosurgical cohort of patients because they are primarily derived from very high-acuity cohorts of patients in the ICU. A disproportionate number of the patients comprising the existing data were admitted for intracranial hemorrhage and trauma, which are in and of themselves potentially neurologically devastating conditions. In addition, prior
123
Neurocrit Care
data on reintubation among neurosurgical patients have failed to distinguish surgical patients from the general neurocritical care patient population and have largely included non-surgical patients along with surgical patients [6, 7]. Currently, little data exist about the incidence of and risk factors for reintubation among the broader cohort of neurosurgical patients. Because there is a lack of data on reintubation rates and risk among neurosurgical patients, it has proven difficult to establish clinical guidelines on weaning neurosurgical patients [3]. Standard weaning criteria such as vital capacity, minute ventilation, maximum inspiratory pressure, and the rapid shallow breathing index are used as parameters for extubation in the general population of intubated patients; however, these parameters appear to translate poorly to patients with neurologic deficits. Although some studies have shown positive predictive value for higher P/F ratios and lower minute ventilation, other studies have not found any individual or combined standard weaning parameters to be useful in predicting extubation failure among neurosurgical patients [5, 8–10]. The insufficiency of traditional weaning parameters in predicting extubation failure among neurosurgical patients may reflect high rates of neurologic dysfunction that results in inability to protect the airway. Some investigators have found evidence that a Glasgow Coma Scale score > 8 predicts successful extubation, but these findings have not been widely reproducible [5–7]. Other studies have evaluated the FOUR Score scale and not found it to be of predictive value either [8]. Therefore, both level of consciousness and overall neurologic function may be factors in extubation outcomes, but they have not been translatable into successful predictive tools. Furthermore, these data also suffer from the problems described above in that they selectively evaluate only profoundly ill in the intensive care setting. Improved understanding of the incidence of reintubation among neurosurgical patients is an important first step in improving postoperative neurosurgical outcomes. Understanding the overall risk, as well as predictive factors, may help triage some neurosurgical patients away from intensive care settings postoperatively [11]. Such clinical decisions about level of postoperative care are fundamentally contingent on an accurate assessment of incidence of extubation complications such as reintubation among neurosurgical patients. Currently, there exists little data on the incidence of reintubation among the general cohort of neurosurgical patients. Those data that exist are derived from high-acuity patients in neurologic intensive care settings, some of whom have not undergone surgery. In addition, there is little evidence about risk factors for reintubation among neurosurgical patients despite existing data demonstrating
123
poor predictive value of traditional weaning parameters for this patient population.
Methods Design We assessed risk factors for reintubation within 48 h of surgery in a cohort of neurosurgical patients prospectively assembled by the American College of Surgeons National Surgical Quality Improvement Program (NSQIP). The NSQIP is a national registry promoting quality improvement by comparing risk-adjusted 30-day surgical outcomes across surgical centers with varying surgical volume and subspecialty expertise. NSQIP included 121 centers in 2005, but grew to 258 by 2010. The methodology of the NSQIP has been described elsewhere; in brief, a dedicated surgical clinician reviewer works with a coordinator at each institution to collect and input data collected from medical charts and provider interviews [12–14]. Data collectors undergo standardized training, and inter-rater variability is measured at under 2 % [15]. Data are collected on patient demographic characteristics, comorbidities, laboratory values, operative factors, and 30day postoperative outcomes. Our analysis was exempt from evaluation by our institutional review board because we employed only publicly available, deidentified data. Patients The NSQIP includes patients undergoing both inpatient and outpatient surgical procedures. Trauma and transplant cases are excluded. For our analysis, we used the NSQIP designations of surgical type to identify patients over 18 years old who underwent neurologic surgery under general anesthesia. We excluded patients who had evidence of pneumonia prior to surgery (based on physical examination findings, chest imaging, and sputum culture) or who were ventilator dependent at any point during the 48 h before surgery. Measurements Our outcome of interest was reintubation which was defined as placement of an endotracheal tube and mechanical or assisted ventilation due to hypoxia, hypercapnia, severe respiratory distress, or respiratory acidosis secondary to cardiac or respiratory failure after postsurgical extubation. We chose to focus on patients who were extubated soon after surgery, since this population is most relevant for making perioperative decisions about disposition (i.e., ICU versus less monitored settings), and therefore
Neurocrit Care
limited our outcome to reintubations occurring within 48 h of surgery. We divided potential risk factors for reintubation into three general categories, and collected data accordingly: patient demographic characteristics, comorbidities, and operative type and course. With regards to patient demographics, we considered patient age, sex, and race (white, black, Native American, Native Hawaiian/Pacific Islander, Asian, or unknown). We noted patient comorbidities previously identified as associated with reintubation: diabetes mellitus, congestive heart failure (CHF), history of recent myocardial infarction (MI), hypertension (blood pressure > 140/90 mmHg requiring antihypertensive medication), acute renal failure (worsening azotemia and a creatinine over 2 mg/dL), and chronic obstructive pulmonary disease (COPD was diagnosed based on functional disability, past hospitalization for specific treatment, chronic bronchodilator therapy, or an FEV1 < 75 % of predicted) [16–21]. A smoking history of >30 pack years was also noted because of an association between smoking and postoperative pulmonary complications among cancer patients [22]. Quadriplegia and hemiplegia were used as proxies for neurologic function, recognizing that both of these variables are limited by the lack of standardized definitions in the NSQIP. We employed Current Procedural Terminology (CPT) codes to separate patients whose procedures were peripheral, spinal, and intracranial. Given the likely differences in reintubation risk for elective versus non-elective surgery, we included as a variable the elective versus non-elective status of the surgery in our models [16]. Additionally, we included in our model American Society of Anesthesiologists (ASA) Physical Status classifications and operating room (OR) time >3 h because of previously demonstrated value of these variables in predicting non-neurosurgical reintubation [16, 17]. Statistical Analysis All statistical analysis was performed using Stata MP (Version 12, StataCorp, College Station, TX). Our primary dependent variable was reintubation. Descriptive statistics were used to present medians and interquartile ranges for continuous variables, and counts and percentages with exact binomial confidence intervals (CI) for categorical variables. Categorical variables were compared using v2 and Fisher’s exact tests as appropriate. Continuous variables were compared using Student’s t test or the Mann– Whitney test depending on their distribution. Multivariable analysis was performed by logistic regression. Backward stepwise selection was used to determine the final regression model, with p < 0.2 in the univariate analysis set as the threshold for inclusion. Of note, the regression was also
run among the cranial surgery cohort in order to compare incidence of reintubation and risk factors to the larger group. Statistical significance was set as p < 0.05. In a sensitivity analysis, we excluded hemiplegia and quadriplegia from our model to assess the effects of these possibly imprecise variables.
Results We identified 17,483 neurosurgical patients without pneumonia or ventilator dependence prior to surgery. Among these eligible patients, 74 (0.42 %; 95 % CI 0.33– 0.52 %) required reintubation within 48 h of surgery (Table 1). As expected, patients who required reintubation were more likely to be >65 years of age (OR, 2.1; 95 % CI 1.3– 3.4; p = 0.003), and to have a greater number of comorbidities prior to surgery. In particular, the following comorbid conditions were independently associated with increased odds of reintubation: preoperative renal failure (OR, 2.9; 95 % CI 1.0–8.5; p = 0.046), preoperative quadriplegia (OR, 8.2; 95 % CI 3.3–20.3; p < 0.001), ASA class (OR per point, 2.1; 95 % CI 1.4–3.1; p < 0.001), and preoperative COPD (OR, 2.1; 95 % CI 1.0–4.3; p = 0.049). Procedures lasting over 3 h were associated with greater likelihood of reintubation (OR, 2.9; 95 % CI 1.8-4.8; p < 0.001). Non-elective (emergency) surgery was associated with reintubation, but this was not significant, likely due to the relatively low number of emergent cases included (OR, 1.9; 95 % CI 1.0–3.8; p = 0.053). Patients undergoing spinal surgery were less likely to be reintubated compared to those undergoing endarterectomy or cranial surgery (OR, 0.3; 95 % CI 0.2-0.5; p < 0.001). Our findings were essentially unchanged in models excluding hemiplegia and quadriplegia as variables. In order to better understand the relationship between risk of reintubation and surgery type, we also ran our regression among only the 4,325 cranial surgery patients. In this cohort, the rate of reintubation was 1.0 % (95 % CI 0.7–1.3 %). Overall, the major risk factors identified were similar to the larger cohort: age over 65 (OR, 3.1; 95 % CI 1.6–5.8; p = 0.001) and operative time of over 3 h (OR, 3.6; 95 % CI 1.8–7.2; p < 0.001) remained significant predictors of reintubation. Interestingly, among the cranial surgery cohort, non-elective (emergency) surgery was a strong predictor of reintubation (OR, 3.3; 95 % CI 1.6–6.8; p = 0.001). Furthermore, renal failure was also a much stronger predictor than in the broader cohort (OR, 6.8; 95 % CI 1.9–23.8; p = 0.003), although it was also a significant predictor in the cohort at large. Despite being statistically significant risk factors in the broader analysis,
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Neurocrit Care Table 1 Cohort and surgical characteristics stratified by reintubation status Characteristicsa
Reintubation n = 74 (0.42 %)
No reintubation n = 17,409
Patient demographics Age, mean, years
61.88 ± 14.01
55.57 ± 15.25
Age > 65
50
27.8
White
76.7
77.7
Black
15.1
8.1
Race
Hispanic
4.1
5.8
Asian
1.4
1.5
American Indian
2.7
6.9
COPD
12.2
4
Congestive heart failure
0
0.2
Coronary heart disease
12.2
5.4
Diabetes Hypertension
20.3 64.9
9.4 46.5
Preoperative hemiplegia
10.8
3.9
Preoperative quadriplegia
8.1
0.8
Renal failure
5.4
1
Tobacco use
24.3
26.3
Patient comorbidities
ASA class 1
0
4.9
2
10.8
46.1
3
64.9
43.6
4
24.3
5.2
5
0
0.1
Cranial
58.1
24.6
Endarterectomy
2.7
Neurosurgical type
Spine 39.2 Other surgical characteristics
0.6 74.8
Operative time > 3 h
59.5
31.5
Non-elective case
17.6
4.4
a
All values expressed in % except as otherwise indicated
COPD and ASA class were not significant in this group, perhaps due to the smaller sample size.
Discussion In a cohort of neurosurgical patients, we found older age, renal and pulmonary comorbidity, preexisting quadriplegia, longer procedure time, and non-spinal neurosurgery were independently associated with reintubation within 48 h. Among patients undergoing cranial surgery, the strongest
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risk factors were older age, longer operative time, renal failure, and non-elective (emergency) surgery. Interestingly, preexisting cardiovascular disease (CHF, history of MI, hypertension) is not associated with reintubation. This may be because very few patients undergoing surgery had heart failure (0.25 %), suggesting that even among patients with hypertension and recent MI, cardiac function was not significantly impaired. Prior data have indicated that reintubation rates among neurosurgical or neurologically impaired patients range from 10 to 25 % [5–7]. This data, however, are based on patients in neurocritical care settings, some of whom were not surgical patients. Our data analysis is the first to examine rates of reintubation in a broader neurosurgical cohort spanning a variety of emergent and non-emergent procedures. Our findings show that unlike those patients in neurocritical care settings, the risk for reintubation among neurosurgical patients is quite low (0.42 %), even among patients undergoing cranial surgery (0.99 %). Although prior data have demonstrated associations between renal, cardiac, pulmonary morbidity, and reintubation among general patients, these findings had not been confirmed in neurosurgical patients, for whom standard predictors of reintubation risk have not been successful [8, 9, 16–21]. We found that many of these risk factors are applicable to neurosurgical patients. In addition, we found that procedural factors such as prolonged OR time, which have been associated with an increased risk of reintubation in general post-anesthesia care units and in cardiac patients, are also risk factors among neurosurgical patients [16, 17]. There were a number of limitations in our study. Our ability to delineate precise neurological function was limited by the NSQIP definitions. We attempted to use hemiplegia and quadriplegia as proxies for neurologic function, but these are suboptimal because they do not address directly the relevant degree of functional impairment. However, the associations we found were essentially unchanged when we removed quadriplegia from our model, suggesting that even if our characterization of the relationship between quadriplegia and reintubation is imprecise, our other findings are unaffected. We also excluded patients who were ventilator dependent prior to surgery in order to avoid confounding, but in doing so, we may have excluded sicker neurosurgical cases involving patients with significant neurologic impairment prior to surgery. In essence, our exclusion of ventilator-dependent patients from our data set means that we may have examined the cohort of neurosurgical patients excluded from prior high-acuity trials, and the actual incidence of reintubation may be somewhere between our data and those data derived from intensive care settings only. Our data do not provide a clear distinction between correlative and causative factors. We believe that the risk
Neurocrit Care
factors we have identified are pertinent for predictive purposes. Some of the factors we have identified, such as preexisting cardiopulmonary disease, are likely to be causal. Other identified factors, such as older age, are likely to simply be associated with poorer overall functional status. For many of the risk factors we identified, however, causality is not clear and merits further investigation in studies of interventions to reduce the rate of postsurgical reintubation in this population. Risk factors for reintubation among neurosurgical patients have been poorly delineated. Traditional weaning parameters have not translated into successful extubation parameters for this patient population [8]. However, decisions about triage and discharge disposition in the postneurosurgical care setting are complex and need to take into account the likelihood of a patient requiring reintubation. Therefore, our parameters may assist intensivists and neurosurgeons in making triage decisions for patients in whom the readiness for extubation is not patently clear. Conflict of interest Daniel Shalev and Hooman Kamel declare they have no conflict of interest.
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