Inclusion of Frailty Improves Predictive Modeling for Postoperative Outcomes in Surgical Management of Primary and Secondary Lumbar Spine Tumors

Integration of Chronological Age Does Not Improve the Performance of a Mixed-Effect Model Using Comorbidity Burden and Frailty to Predict 90-Day Readmission After Surgery for Degenerative Scoliosis

OBJECTIVE

We evaluated the contributions of chronological age, comorbidity burden, and/or frailty in predicting 90-day readmission in patients undergoing degenerative scoliosis surgery.

METHODS

Patients were identified through the Healthcare Cost and Utilization Project Nationwide Readmissions Database. Frailty was assessed using the Johns Hopkins Adjusted Clinical Groups frailty-defining indicator. Comorbidity was assessed using the Elixhauser Comorbidity Index (ECI). Generalized linear mixed-effects models were created to predict readmission using age, frailty, and/or ECI. Area under the curve (AUC) was compared using DeLong's test.

RESULTS

A total of 8104 patients were identified. Readmission rate was 9.8%, with infection representing the most common cause (3.5%). Our first model utilized chronological age, ECI, and/or frailty as primary predictors. The combination of ECI + frailty + age performed best, but the inclusion of chronological age did not significantly improve performance compared to ECI + frailty alone (AUC 0.603 vs. 0.599, P = 0.290). A second model using only chronological age and frailty as primary predictors performed better, however the inclusion of chronological age worsened performance when compared to frailty alone (AUC 0.747 vs. 0.743, P = 0.043).

CONCLUSIONS

These data support frailty as a predictor of 90-day readmission within a nationally representative sample. Frailty alone performed better than combinations of ECI and age. Interestingly, the integration of chronological age did not dramatically improve the model's performance. Limitations include the use of a national registry and a single frailty index. This provides impetus to explore biological age, rather than chronological age, as a potential tool for surgical risk assessment.

Baseline Frailty Measured by the Risk Analysis Index and 30-Day Mortality After Surgery for Spinal Malignancy: Analysis of a Prospective Registry (2011-2020)

OBJECTIVE

To evaluate the prognostic utility of baseline frailty, measured by the Risk Analysis Index (RAI), for prediction of postoperative mortality among patients with spinal malignancy (SM) undergoing resection.

METHODS

SM surgery cases were queried from the American College of Surgeons - National Surgical Quality Improvement Program database (2011-2020). The relationship between preoperative RAI frailty score and increasing rate of primary endpoint (mortality or discharge to hospice within 30 days, "mortality/hospice") were assessed. Discriminatory accuracy was assessed by computation of C-statistics (with 95% confidence interval [CI]) in receiver operating characteristic (ROC) curve analysis.

RESULTS

A total of 2,235 cases were stratified by RAI score: 0-20, 22.7%; 21-30, 11.9%; 31-40, 54.7%; and ≥ 41, 10.7%. The rate of mortality/hospice was 6.5%, which increased linearly with increasing RAI score (p < 0.001). RAI was also associated with increasing rates of major complication, extended length of stay, and nonhome discharge (all p < 0.05). The RAI demonstrated acceptable discriminatory accuracy for prediction of primary endpoint (C-statistic, 0.717; 95% CI, 0.697-0.735). In pairwise ROC comparison, RAI demonstrated superiority versus modified frailty index-5 and chronological age (p < 0.001).

CONCLUSION

Preoperative frailty, as measured by RAI, is a robust predictor of mortality/ hospice after SM surgery. The frailty score may be applied in clinical settings using a user-friendly calculator, deployed here: https://nsgyfrailtyoutcomeslab.shinyapps.io/spinalMalignancyRAI/.

Developing Mixed-Effects Models to Compare the Predictive Ability of Various Comorbidity Indices in a Contemporary Cohort of Patients Undergoing Lumbar Fusion

BACKGROUND AND OBJECTIVE

As incidence of operative spinal pathology continues to grow, so do the rates of lumbar spinal fusion procedures. Comorbidity indices can be used preoperatively to predict potential complications. However, there is a paucity of research defining the optimal comorbidity indices in patients undergoing spinal fusion surgery. We aimed to use modeling strategies to evaluate the predictive validity of various comorbidity indices and combinations thereof.

METHODS

Patients who underwent spinal fusion were queried using data from the Nationwide Readmissions Database for the years 2016 through 2019. Using comorbidity indices as predictor variables, receiver operating characteristic curves were developed for pertinent complications such as mortality, nonroutine discharge, top-quartile cost, top-quartile length of stay, and 30-day readmission.

RESULTS

A total of 750 183 patients were included. Nonroutine discharges occurred in 161 077 (21.5%) patients. The adjusted all-payer cost for the procedure was $37 616.97 ± $27 408.86 (top quartile: $45 409.20), and the length of stay was 4.1 ± 4.4 days (top quartile: 8.1 days). By comparing receiver operating characteristics of various models, it was found that models using Frailty + Elixhauser Comorbidity Index (ECI) as the primary predictor performed better than other models with statistically significant P -values on post hoc testing. However, for prediction of mortality, the model using Frailty + ECI was not better than the model using ECI alone ( P = .23), and for prediction of all-payer cost, the ECI model outperformed the models using frailty alone ( P < .0001) and the model using Frailty + ECI ( P < .0001).

CONCLUSION

This investigation is the first to use big data and modeling strategies to delineate the relative predictive utility of the ECI and Johns Hopkins Adjusted Clinical Groups comorbidity indices for the prognostication of patients undergoing lumbar fusion surgery. With the knowledge gained from our models, spine surgeons, payers, and hospitals may be able to identify vulnerable patients more effectively within their practice who may require a higher degree of resource utilization.

Nadir Hemoglobin Concentration After Spinal Tumor Surgery: Association With Risk of Composite Adverse Events

STUDY DESIGN

Retrospective case-control study.

OBJECTIVE

To explore the association of early postoperative nadir hemoglobin with risk of a composite outcome of anemia-related and other adverse events.

METHODS

We retrospectively analyzed data from spinal tumor patients who received intraoperative blood transfusion between September 1, 2013 and December 31, 2020. Uni- and multivariate logistic regression was used to explore relationships of clinicodemographic and surgical factors with risk of composite in-hospital adverse events, including death. Subgroup analysis explored the relationship between early postoperative nadir hemoglobin and composite adverse events.

RESULTS

Among the 345 patients, 331 (95.9%) experienced early postoperative anemia and 69 (20%) experienced postoperative composite adverse events. Multivariate logistic regression analysis showed that postoperative nadir Hb (OR = .818, 95% CI: .672-.995, P = .044), ASA ≥3 (OR = 2.007, 95% CI: 1.086-3.707, P = .026), intraoperative RBC infusion volume (OR = 1.133, 95% CI: 1.009-1.272, P = .035), abnormal hypertension (OR = 2.199, 95% CI: 1.085-4.457, P = .029) were correlated with composite adverse events. The lumbar spinal tumor was associated with composite adverse events with a decreased odds compared to thoracic spinal tumors (OR = .444, 95% CI: .226-.876, P = .019). Compared to patients with postoperative nadir hemoglobin ≥11.0 g/dL, those with nadir <9.0 g/dL were at significantly higher risk of postoperative composite adverse events (OR = 2.709, 95% CI: 1.087-6.754, P = .032).

CONCLUSION

Nadir hemoglobin <9.0 g/dL after spinal tumor surgery is associated with greater risk of postoperative composite adverse events in patients who receive intraoperative blood transfusion.

Preoperative frailty vs. cognitive impairment: Which one matters most for postoperative delirium among older adults with cancer?

INTRODUCTION

Limited data are available to explore the association between preoperative frailty and cognitive impairment with postoperative delirium among older adults with cancer. We explored this association in a single Comprehensive Cancer Center where postoperative delirium and frailty are assessed in routine care using the Confusion Assessment Method (CAM) and Memorial Sloan Kettering Frailty Index (MSK-FI), respectively.

MATERIALS AND METHODS

Retrospective study on patients with cancer, aged 65+, who underwent surgery from April 2018 to March 2019 with hospital stay ≥1 day. We used logistic regression with postoperative delirium as the outcome, primary predictor MSK-FI, adjusted for age, operative time, and preoperative albumin. As the MSK-FI includes a component related to cognitive impairment, we additionally evaluated the impact of this component, separately from the rest of the score, on the association between frailty and postoperative delirium.

RESULTS

Among 1,257 patients with available MSK-FI and CAM measures, 47 patients (3.7%) had postoperative delirium. Increased frailty was associated with increased risk of postoperative delirium (odds ratio [OR] 1.51; 95% confidence interval [CI] 1.26, 1.81; p < 0.001). However, this was largely related to the effect of cognitive impairment (OR 15.29; 95% CI 7.18; 32.56; p < 0.001). In patients with cognitive impairment, the association between frailty and postoperative delirium was not significant (OR 0.97; 95% CI 0.65, 1.44; p-value = 0.9), as having cognitive impairment put patients at high risk for postoperative delirium even without taking into account the other components of the MSK-FI. While the association between frailty and postoperative delirium in patients with intact cognitive function was statistically significant (OR 1.58; 95% CI 1.27, 1.96; p < 0.001), it was not clinically meaningful, particularly considering the low risk of delirium among patients with intact cognitive function (e.g., 1.3% vs 3.2% for MSK-FI 1 vs 3).

DISCUSSION

Cognitive function should be a greater focus than frailty, as measured by the MSK-FI, in preoperative assessment for the prediction of postoperative delirium.

The 5-factor modified Frailty Index (mFI-5) predicts adverse outcomes after elective Anterior Lumbar Interbody Fusion (ALIF)

Background

The 5-factor modified frailty index (mFI-5) has been shown to be a concise and effective tool for predicting adverse events following various spine procedures. However, there have been no studies assessing its utility in patients undergoing anterior lumbar interbody fusion (ALIF). Therefore, the aim of this study was to analyze the predictive capabilities of the mFI-5 for 30-day postoperative adverse events following elective ALIF.

Methods

The National Surgical Quality Improvement Program (NSQIP) database was queried from 2010 through 2019 to identify patients who underwent elective ALIF using Current Procedural Terminology (CPT) codes in patients over the age of 50. The mFI-5 score was calculated using variables for hypertension, congestive heart failure, comorbid diabetes, chronic obstructive pulmonary disease, and partially or fully dependent functional status which were each assigned 1 point. Univariate analysis and multivariate logistic regression models were utilized to identify the associations between mFI-5 scores, and 30-day rates of overall complications, readmissions, reoperations, and mortality.

Results

11,711 patients were included (mFI-5=0: 4,026 patients, mFI-5=1: 5,392, mFI-5=2: 2,102, mFI-5=3+: 187. Multivariate logistic regression revealed that mFI-5 scores of 1 (OR: 2.2, CI: 1.2-4.2, p=0.02), 2 (OR: 3.6, CI: 1.8-7.3, p<0.001), and 3+ (OR: 7.0, CI: 2.5-19.3, p<0.001) versus a score of 0 were significant predictors of pneumonia. An mFI-5 score of 2 (OR: 1.3; CI: 1.01-1.6, p=0.04), and 3+ (OR: 1.9; CI: 1.1-3.1; p=0.01) were both independent predictors of related readmissions. An mFI score of 3+ was an independent predictor of any complication (OR: 1.5, CI: 1.01-2.2, p=0.004), UTI (OR: 2.4, CI: 1.1-5.2, p=0.02), and unplanned intubation (OR: 4.5, CI: 1.3-16.1, p=0.02).

Conclusions

The mFI-5 is an independent predictor for 30-day postoperative complications, readmissions, UTI, pneumonia, and unplanned intubations following elective ALIF surgery in adults over the age of 50.

Evaluating the predictive value of comorbidity indices in pituitary surgery: a mixed-effects modeling study using the Nationwide Readmissions Database

OBJECTIVE

Although pituitary adenomas (PAs) are common intracranial tumors, literature evaluating the utility of comorbidity indices for predicting postoperative complications in patients undergoing pituitary surgery remains limited, thereby hindering the development of complex models that aim to identify high-risk patient populations. We utilized comparative modeling strategies to evaluate the predictive validity of various comorbidity indices and combinations thereof in predicting key pituitary surgery outcomes.

METHODS

The Nationwide Readmissions Database was used to identify patients who underwent pituitary tumor operations (n = 19,653) in 2016-2017. Patient frailty was assessed using the Johns Hopkins Adjusted Clinical Groups (ACG) System. The Charlson Comorbidity Index (CCI) and Elixhauser Comorbidity Index (ECI) were calculated for each patient. Five sets of generalized linear mixed-effects models were developed, using as the primary predictors 1) frailty, 2) CCI, 3) ECI, 4) frailty + CCI, or 5) frailty + ECI. Complications of interest investigated included inpatient mortality, nonroutine discharge (e.g., to locations other than home), length of stay (LOS) within the top quartile (Q1), cost within Q1, and 1-year readmission rates.

RESULTS

Postoperative mortality occurred in 73 patients (0.4%), 1-year readmission was reported in 2994 patients (15.2%), and nonroutine discharge occurred in 2176 patients (11.1%). The mean adjusted all-payer cost for the procedure was USD $25,553.85 ± $26,518.91 (Q1 $28,261.20), and the mean LOS was 4.8 ± 7.4 days (Q1 5.0 days). The model using frailty + ECI as the primary predictor consistently outperformed other models, with statistically significant p values as determined by comparing areas under the curve (AUCs) for most complications. For prediction of mortality, however, the frailty + ECI model (AUC 0.831) was not better than the ECI model alone (AUC 0.831; p = 0.95). For prediction of readmission, the frailty + ECI model (AUC 0.617) was not better than the frailty model alone (AUC 0.606; p = 0.10) or the frailty + CCI model (AUC 0.610; p = 0.29).

CONCLUSIONS

This investigation is to the authors' knowledge the first to implement mixed-effects modeling to study the utility of common comorbidity indices in a large, nationwide cohort of patients undergoing pituitary surgery. Knowledge gained from these models may help neurosurgeons identify high-risk patients who require additional clinical attention or resource utilization prior to surgical planning.

A Cohort Study of the Surgical Risks and Prediction of Complications in Surgical Tracheostomies

BACKGROUND

Current protocols favor percutaneous tracheostomies over open procedures. We analyzed the effects of this conversion from the open approach to the percutaneous procedure in terms of relevant clinical status, complications, and mortality in surgical open tracheostomies. Relevant laboratory and clinical parameters, potentially associated with complications, were also examined.

MAIN OUTCOME MEASURES

Comparison of clinical, laboratory data and outcome of surgical tracheostomy during the two eras. Investigate potential pertinent predictive parameters associated with complications.

METHODS

A single center retrospective case series of consecutive patients who underwent surgical tracheostomy between the years 2006-2009 ("early era") and 2016-2020 ("late era").

RESULTS

The study included 304 patients, 160 in the "early" and 144 in the "late" era. Despite a 78% increase in patient volume in the intensive care units, there was a 55% decrease in surgical tracheostomy during the "late era". Significantly more patients with structural deformities (p < 0.001), insulin dependent diabetes mellitus (p = 0.004), extreme (high and low) body weight (p = 0.006), anemia (p < 0.001) and coagulation disorders (p < 0.001), were referred for an open tracheostomy during the "late era". The complication rate was significantly higher during the "late era" (11.7 vs. 2.5%, OR 6.09 CI 95% [1.91-19.39], p = 0.001). Diabetes mellitus (p = 0.005), anemia (p = 0.033), malnutrition (p = 0.017), thrombocytopenia (p = 0.002) and poor renal function, (p = 0.008), were all significantly associated with higher complication rates.

CONCLUSIONS

Risk assessment and training programs must reflect the decrease in surgical volume of open tracheostomies and consequently reduced experience. The increase of a patient subset characterized by pertinent comorbidities should reflect this change.

The impact of frailty on postoperative complications in geriatric patients undergoing multi-level lumbar fusion surgery

STUDY DESIGN

Retrospective Cohort Study.

PURPOSE

This study evaluates the impact of patient frailty status on postoperative complications in those undergoing multi-level lumbar fusion surgery.

METHODS

The Nationwide Readmission Database (NRD) was retrospectively queried between 2016 and 2017 for patients receiving multi-level lumbar fusion surgery. Demographics, frailty status, and relevant complications were queried at index admission and readmission intervals. Primary outcome measures included perioperative complications and 30-, 90-, and 180-day complication and readmission rates. Perioperative complications of interest were infection, urinary tract infection (UTI), and posthemorrhagic anemia. Secondary outcome measures included inpatient length of stay (LOS), adjusted all-payer costs, and discharge disposition. Nearest-neighbor propensity score matching for demographics was implemented to identify non-frail patients with similar diagnoses and procedures. Subgroup analysis of minimally invasive surgery (MIS) versus open surgery within frail and non-frail cohorts was conducted to evaluate differences in surgical and medical complication rates. The analysis used nonparametric Mann-Whitney U testing and odds ratios.

RESULTS

Frail patients encountered higher rates perioperative complications including posthemorrhagic anemia (OR: 1.73, 95%CI 1.50-2.00, p < 0.0001), infection (OR: 2.94, 95%CI 2.04-4.36, p < 0.0001), UTI (OR: 2.57, 95%CI 2.04-3.26, p < 0.0001), and higher rates of non-routine discharge (OR: 2.07, 95%CI 1.80-2.38, p < 0.0001). Frail patients had significantly greater LOS and total all-payer inpatient costs compared to non-frail patients (p < 0.0001). Frailty was associated with significantly higher rates of 90- (OR: 1.43, 95%CI 1.18-1.74, p = 0.0003) and 180-day (OR: 1.28, 95%CI 1.03-1.60, p = 0.02) readmissions along with higher rates of wound dehiscence (OR: 2.21, 95%CI 1.17-4.44, p = 0.02) at 90 days. Subgroup analysis revealed that frail patients were at significantly higher risk for surgical complications with open surgery (16%) compared to MIS (0%, p < 0.0001). No significant differences were found between surgical approaches with respect to medical complications in both cohorts, nor surgical complications in non-frail patients.

CONCLUSIONS

Frailty was associated with higher odds of all perioperative complications, LOS, and all-payer costs following multi-level lumbar fusion. Frail patients had significantly higher rates of 90 and 180-day readmission and higher rates of wound disruption at 90-days. On subgroup analysis, MIS was associated with significantly reduced rates of surgical complications specifically in frail patients. Our results suggest frailty status to be an important predictor of perioperative complications and long-term readmissions in geriatric patients receiving multi-level lumbar fusions. Frail patients should undergo surgery utilizing minimally invasive techniques to minimize risk of surgical complications. Future studies should explore the utility of implementing frailty in risk stratification assessments for patients undergoing spine surgery.

The role of frailty in the clinical management of neurofibromatosis type 1: a mixed-effects modeling study using the Nationwide Readmissions Database

OBJECTIVE

Frailty embodies a state of increased medical vulnerability that is most often secondary to age-associated decline. Recent literature has highlighted the role of frailty and its association with significantly higher rates of morbidity and mortality in patients with CNS neoplasms. There is a paucity of research regarding the effects of frailty as it relates to neurocutaneous disorders, namely, neurofibromatosis type 1 (NF1). In this study, the authors evaluated the role of frailty in patients with NF1 and compared its predictive usefulness against the Elixhauser Comorbidity Index (ECI).

METHODS

Publicly available 2016–2017 data from the Nationwide Readmissions Database was used to identify patients with a diagnosis of NF1 who underwent neurosurgical resection of an intracranial tumor. Patient frailty was queried using the Johns Hopkins Adjusted Clinical Groups frailty-defining indicator. ECI scores were collected in patients for quantitative measurement of comorbidities. Propensity score matching was performed for age, sex, ECI, insurance type, and median income by zip code, which yielded 60 frail and 60 nonfrail patients. Receiver operating characteristic (ROC) curves were created for complications, including mortality, nonroutine discharge, financial costs, length of stay (LOS), and readmissions while using comorbidity indices as predictor values. The area under the curve (AUC) of each ROC served as a proxy for model performance.

RESULTS

After propensity matching of the groups, frail patients had an increased mean ± SD hospital cost ($85,441.67 ± $59,201.09) compared with nonfrail patients ($49,321.77 ± $50,705.80) (p = 0.010). Similar trends were also found in LOS between frail (23.1 ± 14.2 days) and nonfrail (10.7 ± 10.5 days) patients (p = 0.0020). For each complication of interest, ROC curves revealed that frailty scores, ECI scores, and a combination of frailty+ECI were similarly accurate predictors of variables (p > 0.05). Frailty+ECI (AUC 0.929) outperformed using only ECI for the variable of increased LOS (AUC 0.833) (p = 0.013). When considering 1-year readmission, frailty (AUC 0.642) was outperformed by both models using ECI (AUC 0.725, p = 0.039) and frailty+ECI (AUC 0.734, p = 0.038).

CONCLUSIONS

These findings suggest that frailty and ECI are useful in predicting key complications, including mortality, nonroutine discharge, readmission, LOS, and higher costs in NF1 patients undergoing intracranial tumor resection. Consideration of a patient’s frailty status is pertinent to guide appropriate inpatient management as well as resource allocation and discharge planning.

PRESENTATION OF THE MULTICENTRIC COLLECTION SPINE SURGERY DATABASE

ABSTRACT Objectives: To present the Spine Surgery Database developed by the Brazilian Spine Study Group and the methodology involved in its creation, in addition to presenting initial informationabout the use of the database. Methods: Description of the steps for selecting the questionnaires and variables to be included in the database, initial expansion of the use of the database tophysicians close to the BSSG, a brief exploration of quality control and methods for the inclusion ofnew centers, and training on the database, in addition to a brief descriptionof some of the data included in the database. Results: Currently, the database includes 428 patients who already underwent spine surgery and 9 collection centers with at least one patient collected. Conclusion: The Brazilian Spine Study Group’s Multicentric Collection Database is a viable tool that allows patients from different sourcesto be included within a common flow. Level of Evidence V; Expert opinion.