There is growing interest among payers in profiling hospital value and quality-of-care, including both the cost and safety of common surgeries, such as lumbar fusion. Nonetheless, there is sparse ...evidence describing the statistical reliability of such measures when applied to lumbar fusion for spondylolisthesis.
To evaluate the reliability of 90-day inpatient hospital costs, overall complications, and rates of serious complications for profiling hospital performance in lumbar fusion surgery for spondylolisthesis.
Data for this analysis came from State Inpatient Databases from nine states made available through the Healthcare Cost and Utilization Project.
Patients undergoing elective lumbar spine fusion for spondylolisthesis from 2010 to 2017 in participating states.
Statistical reliability, defined as the ability to distinguish true performance differences across hospitals relative to statistical noise. Reliability was assessed separately for 90-day inpatient costs (standardized across years to 2019 dollars), overall complications, and serious complication rates.
Statistical reliability was measured as the amount of variation between hospitals relative to the total amount of variation for each measure. Total variation includes both between-hospital variation (“signal”) and within-hospital variation (“statistical noise”). Thus, reliability equals signal over (signal plus noise) and ranges from 0 to 1. To adjust for differences in patient-level risk and procedural characteristics, hierarchical linear and logistic regression models were created for the cost and complication outcomes. Random hospital intercepts were used to assess between-hospital variation. We evaluated the reliability of each measure by study year and examined the number of hospitals meeting different thresholds of reliability by year.
We included a total of 66,571 elective lumbar fusion surgeries for spondylolisthesis performed at 244 hospitals during the study period. The mean 90-day hospital cost was $30,827 (2019 dollars). 12.0% of patients experienced a complication within 90 days of surgery, including 7.8% who had a serious complication. The median reliability of 90-day cost ranged from 0.97to 0.99 across study years, and there was a narrow distribution of reliability values. By comparison, the median reliability for the overall complication metric ranged from 0.22 to 0.44, and the reliability of the serious complication measure ranged from 0.30 to 0.49 across the study years. At least 96% of hospitals had high (> 0.7) reliability for cost in any year, whereas only 0-9% and 0-11% of hospitals reached this cutoff for the overall and serious complication rate in any year, respectively. By comparison, 10%–69% of hospitals per year achieved a more moderate threshold of 0.4 reliability for overall complications, compared to 21%–80% of hospitals who achieved this lower reliability threshold for serious complications.
90-day inpatient costs are highly reliable for assessing variation across hospitals, whereas overall and serious complications are only moderately reliable for profiling performance. These results support the viability of emerging bundled payment programs that assume true differences in costs of care exist across hospitals.
BACKGROUND:Outcomes research on Chiari malformation type 1 (CM-1) is impeded by a reliance on small, single-center cohorts.
OBJECTIVE:To study the complications and resource use associated with adult ...CM-1 surgery using administrative data.
METHODS:We used a recently validated International Classification of Diseases, Ninth Revision, Clinical Modification code algorithm to retrospectively study adult CM-1 surgeries from 2004 to 2010 in California, Florida, and New York using State Inpatient Databases. Outcomes included complications and resource use within 30 and 90 days of treatment. We used multivariable logistic regression to identify risk factors for morbidity and negative binomial models to determine risk-adjusted costs.
RESULTS:We identified 1947 CM-1 operations. Surgical complications were more common than medical complications at both 30 days (14.3% vs 4.4%) and 90 days (18.7% vs 5.0%) postoperatively. Certain comorbidities were associated with increased morbidity; for example, hydrocephalus increased the risk for surgical (odds ratio OR = 4.51) and medical (OR = 3.98) complications. Medical but not surgical complications were also more common in older patients (OR = 5.57 for oldest vs youngest age category) and male patients (OR = 3.19). Risk-adjusted hospital costs were $22530 at 30 days and $24852 at 90 days postoperatively. Risk-adjusted 90-day costs were more than twice as high for patients experiencing surgical ($46264) or medical ($65679) complications than for patients without complications ($18880).
CONCLUSION:Complications after CM-1 surgery are common, and surgical complications are more frequent than medical complications. Certain comorbidities and demographic characteristics are associated with increased risk for complications. Beyond harming patients, complications are also associated with substantially higher hospital costs. These results may help guide patient management and inform decision making for patients considering surgery.
ABBREVIATIONS:CM-1, Chiari malformation type 1ICD-9-CM, International Classification of Diseases, Ninth Revision, Clinical ModificationOR, odds ratioSID, State Inpatient Database
OBJECTIVES/GOALS: Diffusion basis spectrum imaging (DBSI) allows for detailed evaluation of white matter microstructural changes present in cervical spondylotic myelopathy (CSM). Our goal is to ...utilize multidimensional clinical and quantitative imaging data to characterize disease severity and predict long-term outcomes in CSM patients undergoing surgery. METHODS/STUDY POPULATION: A single-center prospective cohort study enrolled fifty CSM patients who underwent surgical decompression and twenty healthy controls from 2018-2021. All patients underwent diffusion tensor imaging (DTI), DBSI, and complete clinical evaluations at baseline and 2-years follow-up. Primary outcome measures were the modified Japanese Orthopedic Association score (mild mJOA 15-17, moderate mJOA 12-14, severe mJOA 0-11) and SF-36 Physical and Mental Component Summaries (PCS and MCS). At 2-years follow-up, improvement was assessed via established MCID thresholds. A supervised machine learning classification model was used to predict treatment outcomes. The highest-performing algorithm was a linear support vector machine. Leave-one-out cross-validation was utilized to test model performance. RESULTS/ANTICIPATED RESULTS: A total of 70 patients – 20 controls, 25 mild, and 25 moderate/severe CSM patients – were enrolled. Baseline clinical and DTI/DBSI measures were significantly different between groups. DBSI Axial and Radial Diffusivity were significantly correlated with baseline mJOA and mJOA recovery, respectively (r=-0.33, p<0.01; r=-0.36, p=0.02). When predicting baseline disease severity (mJOA classification), DTI metrics alone performed with 38.7% accuracy (AUC: 72.2), compared to 95.2% accuracy (AUC: 98.9) with DBSI metrics alone. When predicting improvement after surgery (change in mJOA), clinical variables alone performed with 33.3% accuracy (AUC: 0.40). When combining DTI or DBSI parameters with key clinical covariates, model accuracy improved to 66.7% (AUC: 0.65) and 88.1% (AUC: 0.95) accuracy, respectively. DISCUSSION/SIGNIFICANCE: DBSI metrics correlate with baseline disease severity and outcome measures at 2-years follow-up. Our results suggest that DBSI may serve as a valid non-invasive imaging biomarker for CSM disease severity and potential for postoperative improvement.
When evaluating children with mild traumatic brain injuries (mTBIs) and intracranial injuries (ICIs), neurosurgeons intuitively consider injury size. However, the extent to which such measures (eg, ...hematoma size) improve risk prediction compared with the kids intracranial injury decision support tool for traumatic brain injury (KIIDS-TBI) model, which only includes the presence/absence of imaging findings, remains unknown.
To determine the extent to which measures of injury size improve risk prediction for children with mild traumatic brain injuries and ICIs.
We included children ≤18 years who presented to 1 of the 5 centers within 24 hours of TBI, had Glasgow Coma Scale scores of 13 to 15, and had ICI on neuroimaging. The data set was split into training (n = 1126) and testing (n = 374) cohorts. We used generalized linear modeling (GLM) and recursive partitioning (RP) to predict the composite of neurosurgery, intubation >24 hours, or death because of TBI. Each model's sensitivity/specificity was compared with the validated KIIDS-TBI model across 3 decision-making risk cutoffs (<1%, <3%, and <5% predicted risk).
The GLM and RP models included similar imaging variables (eg, epidural hematoma size) while the GLM model incorporated additional clinical predictors (eg, Glasgow Coma Scale score). The GLM (76%-90%) and RP (79%-87%) models showed similar specificity across all risk cutoffs, but the GLM model had higher sensitivity (89%-96% for GLM; 89% for RP). By comparison, the KIIDS-TBI model had slightly higher sensitivity (93%-100%) but lower specificity (27%-82%).
Although measures of ICI size have clear intuitive value, the tradeoff between higher specificity and lower sensitivity does not support the addition of such information to the KIIDS-TBI model.
Introduction
We hypothesize that surgical decompression for Chiari malformation type 1 (CM-1) is associated with statistically significant decrease in tonsillar pulsatility and that the degree of ...pulsatility can be reliably assessed regardless of the experience level of the reader.
Methods
An Institutional Review Board (IRB)-approved Health Insurance Portability and Accountability Act (HIPAA)-compliant retrospective study was performed on 22 children with CM-1 (8 males; mean age 11.4 years) who had cardiac-gated true-FISP sequence and phase-contrast cerebrospinal fluid (CSF) flow imaging as parts of routine magnetic resonance (MR) imaging before and after surgical decompression. The surgical technique (decompression with or without duraplasty) was recorded for each patient. Three independent radiologists with different experience levels assessed tonsillar pulsatility qualitatively and quantitatively and assessed peritonsillar CSF flow qualitatively. Results were analyzed. To evaluate reliability, Fleiss kappa for multiple raters on categorical variables and intra-class correlation for agreement in pulsatility ratings were calculated.
Results
After surgical decompression, the degree of tonsillar pulsatility appreciably decreased, confirmed by
t
test, both qualitatively (
p
values <0.001, <0.001, and 0.045 for three readers) and quantitatively (amount of decrease/
p
value for three readers 0.7 mm/<0.001, 0.7 mm/<0.001, and 0.5 mm/0.022). There was a better agreement among the readers in quantitative assessment of tonsillar pulsatility (kappa 0.753–0.834), compared to qualitative assessment of pulsatility (kappa 0.472–0.496) and qualitative assessment of flow (kappa 0.056 to 0.203). Posterior fossa decompression with duraplasty led to a larger decrease in tonsillar pulsatility, compared to posterior fossa decompression alone.
Conclusion
Tonsillar pulsatility in CM-1 is significantly reduced after surgical decompression. Quantitative assessment of tonsillar pulsatility was more reliable across readers than qualitative assessments of tonsillar pulsatility or CSF flow.
Background
Clinical decision support (CDS) may improve the postneuroimaging management of children with mild traumatic brain injuries (mTBI) and intracranial injuries. While the CHIIDA score has been ...proposed for this purpose, a more sensitive risk model may have broader use. Consequently, this study's objectives were to: (1) develop a new risk model with improved sensitivity compared to the CHIIDA model and (2) externally validate the new model and CHIIDA model in a multicenter data set.
Methods
We analyzed children ≤18 years old with mTBI and intracranial injuries included in the PECARN head injury data set (2004–2006). We used binary recursive partitioning to predict the composite outcome of neurosurgical intervention, intubation for > 24 h due to TBI, or death due to TBI. The new model was externally validated in a separate data set that included children treated at any one of six centers from 2006 to 2019.
Results
Based on 839 patients from the PECARN data set, a new risk model, the KIIDS‐TBI model, was developed that incorporated imaging (e.g., midline shift) and clinical (e.g., Glasgow Coma Scale score) findings. Based on the model‐predicted probability of the composite outcome, three cutoffs were evaluated to classify patients as “high risk” for level of care decisions. In the external validation data set consisting of 1,630 patients, the most conservative cutoff (i.e., any predictor present) identified 119 of 119 children with the composite outcome (sensitivity = 100%), but had the lowest specificity (26.3%). The other two decision‐making cutoffs had worse sensitivity (94.1%–96.6%) but improved specificity (67.4%–81.3%). The CHIIDA model lacked the most conservative cutoff and otherwise showed the same or slightly worse performance compared to the other two cutoffs.
Conclusions
The KIIDS‐TBI model has high sensitivity and moderate specificity for risk stratifying children with mTBI and intracranial injuries. Use of this CDS tool may help improve the safe, resource‐efficient management of this important patient population.
Cerebral amyloid angiopathy (CAA) is characterized by deposition of fibrillar amyloid β (Aβ) within cerebral vessels. It is commonly seen in the elderly and almost universally present in patients ...with Alzheimer's Disease (AD). In both patient populations, CAA is an independent risk factor for lobar hemorrhage, ischemic stroke, and dementia. To date, definitive diagnosis of CAA requires obtaining pathological tissues via brain biopsy (which is rarely clinically indicated) or at autopsy. Though amyloid tracers labeled with positron-emitting radioligands such as 11CPIB have shown promise for non-invasive amyloid imaging in AD patients, to date they have been unable to clarify whether the observed amyloid load represents neuritic plaques versus CAA due in large part to the low resolution of PET imaging and the almost equal affinity of these tracers for both vascular and parenchymal amyloid. Therefore, the development of a precise and specific non-invasive technique for diagnosing CAA in live patients is desired.
We found that the phenoxazine derivative resorufin preferentially bound cerebrovascular amyloid deposits over neuritic plaques in the aged Tg2576 transgenic mouse model of AD/CAA, whereas the congophilic amyloid dye methoxy-X34 bound both cerebrovascular amyloid deposits and neuritic plaques. Similarly, resorufin-positive staining was predominantly noted in fibrillar Aβ-laden vessels in postmortem AD brain tissues. Fluorescent labeling and multi-photon microscopy further revealed that both resorufin- and methoxy-X34-positive staining is colocalized to the vascular smooth muscle (VSMC) layer of vessel segments that have severe disruption of VSMC arrangement, a characteristic feature of CAA. Resorufin also selectively visualized vascular amyloid deposits in live Tg2576 mice when administered topically, though not systemically. Resorufin derivatives with chemical modification at the 7-OH position of resorufin also displayed a marked preferential binding affinity for CAA, but with enhanced lipid solubility that indicates their use as a non-invasive imaging tracer for CAA is feasible.
To our knowledge, resorufin analogs are the fist class of amyloid dye that can discriminate between cerebrovascular and neuritic forms of amyloid. This unique binding selectivity suggests that this class of dye has great potential as a CAA-specific amyloid tracer that will permit non-invasive detection and quantification of CAA in live patients.
Chiari malformation type 1 (CM-I) is a common and often debilitating neurologic disease. Reliable evaluation of treatments has been hampered by inconsistent use of clinical outcome measures. A ...variety of outcome measurement tools are available, although few have been validated in CM-I. The recent development of the Chicago Chiari Outcome Scale and the Chiari Symptom Profile provides CM-I-specific instruments to measure outcomes in adults and children, although validation and refinement may be necessary.
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