Frailty in intracranial meningioma resection: the risk analysis index demonstrates strong discrimination for predicting non-home discharge and in-hospital mortality.

PURPOSE: Frailty is an independent risk factor for adverse postoperative outcomes following intracranial meningioma resection (IMR). The role of the Risk Analysis Index (RAI) in predicting postoperative outcomes following IMR is nascent but may inform preoperative patient selection and surgical planning. METHODS: IMR patients from the Nationwide Inpatient Sample were identified using diagnostic and procedural codes (2019-2020). The relationship between preoperative RAI-measured frailty and primary outcomes (non-home discharge (NHD), in-hospital mortality) and secondary outcomes (extended length of stay (eLOS), complication rates) was assessed via multivariate analyses. The discriminatory accuracy of the RAI for primary outcomes was measured in area under the receiver operating characteristic (AUROC) curve analysis. RESULTS: A total of 23,230 IMR patients (mean age = 59) were identified, with frailty statuses stratified by RAI score: 0-20 "robust" (R)(N = 10,665, 45.9%), 21-30 "normal" (N)(N = 8,895, 38.3%), 31-40 "frail" (F)(N = 2,605, 11.2%), and 41+ "very frail" (VF)(N = 1,065, 4.6%). Rates of NHD (R 11.5%, N 29.7%, F 60.8%, VF 61.5%), in-hospital mortality (R 0.5%, N 1.8%, F 3.8%, VF 7.0%), eLOS (R 13.2%, N 21.5%, F 40.9%, VF 46.0%), and complications (R 7.5%, N 11.6%, F 15.7%, VF 16.0%) significantly increased with increasing frailty thresholds (p < 0.001). The RAI demonstrated strong discrimination for NHD (C-statistic: 0.755) and in-hospital mortality (C-statistic: 0.754) in AUROC curve analysis. CONCLUSION: Increasing RAI-measured frailty is significantly associated with increased complication rates, eLOS, NHD, and in-hospital mortality following IMR. The RAI demonstrates strong discrimination for predicting NHD and in-hospital mortality following IMR, and may aid in preoperative risk stratification.

Comparative analysis of exoscope-assisted spine surgery versus operating microscope: A systematic review.

Background: Limitations in the operative microscope (OM)'s mobility and suboptimal ergonomics created the opportunity for the development of the exoscope. This systematic review aims to evaluate the advantages and disadvantages of exoscopes and OMs in spine surgery. Methods: Following Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, a systematic search was conducted in the major research databases. All studies evaluating the exoscopes and/or OMs in spinal procedures were included. Results: There were 602 patients included in the 16 studies, with 539 spine surgery patients, 19 vascular cases, 1 neural pathology case, 19 cranial cases, and 24 tumor pathologies. When examining surgical outcomes with the exoscope, results were mixed. Compared to the OM, exoscope usage resulted in longer operative times in 7 studies, comparable times in 3 studies, and shorter operative times in 3 studies. Two studies found similar lengths of stay (LOS) for both tools, two reported longer LOS with exoscopes, and one indicated shorter hospital LOS with exoscopes. One study reported higher exoscope-related blood loss (EBL), but four other studies consistently showed reduced EBL. In terms of image quality, illumination, dynamic range, depth perception, ergonomics and cost-effectiveness, the exoscope was consistently rated superior, while findings across studies were mixed regarding the optical zoom ratio and mean scope adjustment (MSA). The learning curve for exoscope use was consistently reported as shorter in all studies. Conclusion: Exoscopes present a viable alternative to OMs in spine surgery, offering multiple advantages, which supports their promising role in modern neurosurgical practice.

The frailty-driven predictive model for failure to rescue among patients who experienced a major complication following cervical decompression and fusion: an ACS-NSQIP analysis of 3,632 cases (2011-2020).

BACKGROUND CONTEXT: Preoperative risk stratification for patients considering cervical decompression and fusion (CDF) relies on established independent risk factors to predict the probability of complications and outcomes in order to help guide pre and perioperative decision-making. PURPOSE: This study aims to determine frailty's impact on failure to rescue (FTR), or when a mortality occurs within 30 days following a major complication. STUDY DESIGN/SETTING: Cross-sectional retrospective analysis of retrospective and nationally-representative data. PATIENT SAMPLE: The American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database was queried for all CDF cases from 2011-2020. OUTCOME MEASURES: CDF patients who experienced a major complication were identified and FTR was calculated as death or hospice disposition within 30 days of a major complication. METHODS: Frailty was measured by the Risk Analysis Index-Revised (RAI-Rev). Baseline patient demographics and characteristics were compared for all FTR patients. Significant factors were assessed by univariate and multivariable regression for the development of a frailty-driven predictive model for FTR. The discriminative ability of the predictive model was assessed using a receiving operating characteristic (ROC) curve analysis. RESULTS: There were 3632 CDF patients who suffered a major complication and 7.6% (277 patients) subsequently expired or dispositioned to hospice, the definition of FTR. Independent predictors of FTR were nonelective surgery, frailty, preoperative intubation, thrombosis or embolic complication, unplanned intubation, on ventilator for >48 hours, cardiac arrest, and septic shock. Frailty, and a combination of preoperative and postoperative risk factors in a predictive model for FTR, achieved outstanding discriminatory accuracy (C-statistic = 0.901, CI: 0.883-0.919). CONCLUSION: Preoperative and postoperative risk factors, combined with frailty, yield a highly accurate predictive model for FTR in CDF patients. Our model may guide surgical management and/or prognostication regarding the likelihood of FTR after a major complication postoperatively with CDF patients. Future studies may determine the predictive ability of this model in other neurosurgical patient populations.

RAI-measured frailty predicts non-home discharge following metastatic brain tumor resection: national inpatient sample analysis of 20,185 patients.

PURPOSE: Preoperative risk stratification for patients undergoing metastatic brain tumor resection (MBTR) is based on established tumor-, patient-, and disease-specific risk factors for outcome prognostication. Frailty, or decreased baseline physiologic reserve, is a demonstrated independent risk factor for adverse outcomes following MBTR. The present study sought to assess the impact of frailty, measured by the Risk Analysis Index (RAI), on MBTR outcomes. METHODS: All MBTR were queried from the National Inpatient Sample (NIS) from 2019 to 2020 using diagnosis and procedural codes. The relationship between preoperative RAI frailty score and our primary outcome - non-home discharge (NHD) - and secondary outcomes - complication rates, extended length of stay (eLOS), and mortality - were analyzed via univariate and multivariable analyses. Discriminatory accuracy was tested by computation of concordance statistics in area under the receiver operating characteristic (AUROC) curve analysis. RESULTS: There were 20,185 MBTR patients from the NIS database from 2019 to 2020. Each patient's frailty status was stratified by RAI score: 0-20 (robust): 34%, 21-30 (normal): 35.1%, 31-40 (very frail): 13.9%, 41+ (severely frail): 16.8%. Compared to robust patients, severely frail patients demonstrated increased complication rates (12.2% vs. 6.8%, p < 0.001), eLOS (37.6% vs. 13.2%, p < 0.001), NHD (52.0% vs. 20.6%, p < 0.001), and mortality (9.9% vs. 4.1%, p < 0.001). AUROC curve analysis demonstrated good discriminatory accuracy of RAI-measured frailty in predicting NHD after MBTR (C-statistic = 0.67). CONCLUSION: Increasing RAI-measured frailty status is significantly associated with increased complication rates, eLOS, NHD, and mortality following MBTR. Preoperative frailty assessment using the RAI may aid in preoperative surgical planning and risk stratification for patient selection.

Baseline labs predict adverse postoperative outcomes following metastatic brain tumor resection: Analysis of 5943 patients from a prospective surgical registry (2015-2019).

INTRODUCTION: The present study sought to evaluate the predictive accuracy of preoperative lab values (PLV) on postoperative metastatic brain tumor resection (MBTR) outcomes using data queried from a large prospective international surgical registry, representing over 700 hospitals in 11 countries. METHODS: Adult metastatic brain tumor patients (N = 5943) were queried from the American College of Surgeons National Quality Improvement Program (ACS-NSQIP) database, from 2015 to 2019, using diagnostic and procedural coding. The relationship between preoperative lab values and key indicators of adverse postoperative outcomes following metastatic brain tumor resection were assessed with univariate and multivariate analyses. Adverse postoperative outcomes of interest included: 30-day mortality, Clavien-Dindo Grade IV (CDIV) complications, extended length of stay (eLOS), and discharge to non-home destination (NHD), as well as secondary outcomes: non-Clavien-Dindo Grade IV complications, unplanned reoperation, and unplanned readmission. RESULTS: Independent PLV most strongly associated with 30-day mortality were hypernatremia, increased serum creatinine, and thrombocytopenia. Significant predictors of CDIV complications were hypoalbuminemia and thrombocytopenia. eLOS was associated with hypoalbuminemia, anemia, and hyponatremia. The strongest independent predictors of NHD were anemia, hyperbilirubinemia, and hypoalbuminemia. CONCLUSION: Several pre-operative lab values independently predicted worse outcomes for metastatic brain tumor resection patients. Hypoalbuminemia, thrombocytopenia, and anemia had the strongest association with the study's adverse postoperative outcomes. These baseline lab values may be considered for preoperative risk stratification of metastatic brain tumor patients.

Frailty Indexes in Metastatic Spine Tumor Surgery: A Narrative Review.

Quantification of preoperative frailty is an important prognostic tool in neurosurgical decision making. Metastatic spine tumor patients undergoing surgery are frail and have unfavorable outcomes that include an increased length of stay, unfavorable discharge disposition, and increased readmission rates. These undesirable outcomes result in higher treatment costs. A heterogeneous mixture of various frailty indexes is available with marked variance in their validation, leading to disparate clinical utility. The lack of a universally accepted definition for frailty, let alone in the method of creation or elements required in the formation of a frailty index, has resulted in a body of frailty literature lacking precision for predicting neurosurgical outcomes. In this review, we examine the role of reported frailty indexes in predicting postoperative outcomes after resection of metastatic spine tumors and aim to assist as a frailty guide for helping clinical decision making.

Frailty measured by risk analysis index and adverse discharge outcomes after adult spine deformity surgery: analysis of 3104 patients from a prospective surgical registry (2011-2020).

BACKGROUND CONTEXT: Measurement of frailty with the Risk Analysis Index (RAI) has demonstrated improved outcome prediction compared to other frailty indices across the surgical literature. However, the generalizability and clinical utility of preoperative RAI scoring for prediction of postoperative morbidity after adult spinal deformity surgery is presently unknown. Thus, recent studies have called for an RAI analysis of spine deformity outcomes. PURPOSE: The present study sought to evaluate the discriminatory accuracy of preoperative frailty, as measured by RAI, for predicting postoperative morbidity among adult spine deformity surgery patients using data queried from a large prospective surgical registry representing over 700 hospitals from 49 US states and 11 countries. STUDY DESIGN/SETTING: Secondary analysis of a prospective surgical registry. PATIENT SAMPLE: American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database (2011-2020). OUTCOME MEASURES: The primary endpoint was "adverse discharge outcome" (ADO) defined as discharge to a non-home, non-rehabilitation nursing/chronic care facility. METHODS: Adult spine deformity surgeries were queried from the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database (2011-2020) using diagnosis and procedure codes. The relationship between increasing preoperative RAI frailty score and increasing rate of primary endpoint (ADO) was assessed with Cochran-Armitage linear trend tests. Discriminatory accuracy was tested by computation of concordance statistics (with 95% confidence interval [CI]) in receiver operating characteristic (ROC) curve analysis. RESULTS: A total of 3104 patients underwent spine deformity surgery and were stratified by RAI score: 0-10: 22%, 11-15: 11%, 16-20: 29%, 21-25: 26%, 26-30: 8.0%, 31-35: 2.4%, and 36+: 1.4%. The rate of ADO was 14% (N=439/3094). The rate of ADO increased significantly with increasing RAI score (p<.0001). RAI demonstrated robust discriminatory accuracy for prediction of ADO in ROC analysis (C-statistic: 0.71, 95% CI: 0.69-0.74, p<.001). In pairwise comparison of ROC curves (DeLong test), RAI demonstrates superior discriminatory accuracy compared to the 5-factor modified frailty index (mFI-5; p<.001). CONCLUSION: Preoperative frailty, as measured by RAI, is a robust predictor of postoperative morbidity (measured by ADO) after adult spine deformity surgery. The frailty score may be translated directly to the bedside with a user-friendly risk calculator, deployed here: https://nsgyfrailtyoutcomeslab.shinyapps.io/spineDeformity.

A Predictive Model of Failure to Rescue After Thoracolumbar Fusion.

OBJECTIVE: Although failure to rescue (FTR) has been utilized as a quality-improvement metric in several surgical specialties, its current utilization in spine surgery is limited. Our study aims to identify the patient characteristics that are independent predictors of FTR among thoracolumbar fusion (TLF) patients. METHODS: Patients who underwent TLF were identified using relevant diagnostic and procedural codes from the National Surgical Quality Improvement Program (NSQIP) database from 2011-2020. Frailty was assessed using the risk analysis index (RAI). FTR was defined as death, within 30 days, following a major complication. Univariate and multivariable analyses were used to compare baseline characteristics and early postoperative sequelae across FTR and non-FTR cohorts. Receiver operating characteristic (ROC) curve analysis was used to assess the discriminatory accuracy of the frailty-driven predictive model for FTR. RESULTS: The study cohort (N = 15,749) had a median age of 66 years (interquartile range, 15 years). Increasing frailty, as measured by the RAI, was associated with an increased likelihood of FTR: odds ratio (95% confidence interval [CI]) is RAI 21-25, 1.3 [0.8-2.2]; RAI 26-30, 4.0 [2.4-6.6]; RAI 31-35, 7.0 [3.8-12.7]; RAI 36-40, 10.0 [4.9-20.2]; RAI 41- 45, 21.5 [9.1-50.6]; RAI ≥ 46, 45.8 [14.8-141.5]. The frailty-driven predictive model for FTR demonstrated outstanding discriminatory accuracy (C-statistic = 0.92; CI, 0.89-0.95). CONCLUSION: Baseline frailty, as stratified by type of postoperative complication, predicts FTR with outstanding discriminatory accuracy in TLF patients. This frailty-driven model may inform patients and clinicians of FTR risk following TLF and help guide postoperative care after a major complication.