Clinical Trial Protocol for "Replace Cysto": Replacing Invasive Cystoscopy with Urine Testing for Non-muscle-invasive Bladder Cancer Surveillance-A Multicenter, Randomized, Phase 2 Healthcare Delivery Trial Comparing Quality of Life During Cancer Surveillance with Xpert Bladder Cancer Monitor or Bladder EpiCheck Urine Testing Versus Frequent Cystoscopy

"Replace Cysto" is a multisite randomized phase 2 trial including 240 participants with low-grade intermediate-risk non-muscle-invasive bladder cancer, in which participants will be randomized 1:1:1 to one of two urine marker-based approaches alternating a urine marker test (Xpert Bladder Cancer Monitor or Bladder EpiCheck) with cystoscopy or to frequent scheduled cystoscopy. The primary objective is to determine whether urinary quality of life after surveillance is significantly improved in the urine marker arms. The primary outcome will be the patient-reported urinary quality of life domain score of the validated QLQ-NMIBC24 instrument, measured 1-3 d after surveillance. Exploratory outcomes include discomfort after surveillance, the number of invasive procedures that participants undergo per 1000 person years, complications from these procedures per 1000 person years, nonurinary quality of life, acceptability of surveillance, and bladder cancer recurrence and progression. Comparators include surveillance using (1) the Xpert Bladder Cancer Monitor test, (2) the Bladder EpiCheck urinary marker, or (3) frequent cystoscopy alone. After a negative cystoscopy ≤4 mo following bladder tumor resection, all the participants will undergo surveillance at 6, 12, 18, and 24 mo (with time zero defined as the date of the most recent bladder tumor resection). In the urine marker arms, surveillance at 6 and 18 mo will be performed with the marker. Regardless of the arm, participants will undergo cystoscopy at 12 and 24 mo. End of study for each participant will be their 24-mo cystoscopy. Overall trial duration is estimated at 5 yr from when the study opens to enrollment until completion of data analyses. The trial is registered at clinicaltrials.gov (NCT05796375).

APPLICATION OF QUANTILE DISCRETIZATION AND BAYESIAN NETWORK ANALYSIS TO PUBLICLY AVAILABLE CYSTIC FIBROSIS DATA SETS

The availability of multiple publicly-available datasets studying the same phenomenon has the promise of accelerating scientific discovery. Meta-analysis can address issues of reproducibility and often increase power. The promise of meta-analysis is especially germane to rarer diseases like cystic fibrosis (CF), which affects roughly 100,000 people worldwide. A recent search of the National Institute of Health's Gene Expression Omnibus revealed 1.3 million data sets related to cancer compared to about 2,000 related to CF. These studies are highly diverse, involving different tissues, animal models, treatments, and clinical covariates. In our search for gene expression studies of primary human airway epithelial cells, we identified three studies with compatible methodologies and sufficient metadata: GSE139078, Sala Study, and PRJEB9292. Even so, experimental designs were not identical, and we identified significant batch effects that would have complicated functional analysis. Here we present quantile discretization and Bayesian network construction using the Hill climb method as a powerful tool to overcome experimental differences and reveal biologically relevant responses to the CF genotype itself, exposure to virus, bacteria, and drugs used to treat CF. Functional patterns revealed by cluster Profiler included interferon signaling, interferon gamma signaling, interleukins 4 and 13 signaling, interleukin 6 signaling, interleukin 21 signaling, and inactivation of CSF3/G-CSF signaling pathways showing significant alterations. These pathways were consistently associated with higher gene expression in CF epithelial cells compared to non-CF cells, suggesting that targeting these pathways could improve clinical outcomes. The success of quantile discretization and Bayesian network analysis in the context of CF suggests that these approaches might be applicable to other contexts where exactly comparable data sets are hard to find.

Automated classification of fat-infiltrated axillary lymph nodes on screening mammograms

OBJECTIVE

Fat-infiltrated axillary lymph nodes (LNs) are unique sites for ectopic fat deposition. Early studies showed a strong correlation between fatty LNs and obesity-related diseases. Confirming this correlation requires large-scale studies, hindered by scarce labeled data. With the long-term goal of developing a rapid and generalizable tool to aid data labeling, we developed an automated deep learning (DL)-based pipeline to classify the status of fatty LNs on screening mammograms.

METHODS

Our internal data set included 886 mammograms from a tertiary academic medical institution, with a binary status of the fat-infiltrated LNs based on the size and morphology of the largest visible axillary LN. A two-stage DL model training and fine-tuning pipeline was developed to classify the fat-infiltrated LN status using the internal training and development data set. The model was evaluated on a held-out internal test set and a subset of the Digital Database for Screening Mammography.

RESULTS

Our model achieved 0.97 (95% CI: 0.94-0.99) accuracy and 1.00 (95% CI: 1.00-1.00) area under the receiver operator characteristic curve on 264 internal testing mammograms, and 0.82 (95% CI: 0.77-0.86) accuracy and 0.87 (95% CI: 0.82-0.91) area under the receiver operator characteristic curve on 70 external testing mammograms.

CONCLUSION

This study confirmed the feasibility of using a DL model for fat-infiltrated LN classification. The model provides a practical tool to identify fatty LNs on mammograms and to allow for future large-scale studies to evaluate the role of fatty LNs as an imaging biomarker of obesity-associated pathologies.

ADVANCES IN KNOWLEDGE

Our study is the first to classify fatty LNs using an automated DL approach.

The association between cervical artery dissection and spinal manipulation among US adults

PURPOSE

Cervical artery dissection (CeAD), which includes both vertebral artery dissection (VAD) and carotid artery dissection (CAD), is the most serious safety concern associated with cervical spinal manipulation (CSM). We evaluated the association between CSM and CeAD among US adults.

METHODS

Through analysis of health claims data, we employed a case-control study with matched controls, a case-control design in which controls were diagnosed with ischemic stroke, and a case-crossover design in which recent exposures were compared to exposures in the same case that occurred 6-7 months earlier. We evaluated the association between CeAD and the 3-level exposure, CSM versus office visit for medical evaluation and management (E&M) versus neither, with E&M set as the referent group.

RESULTS

We identified 2337 VAD cases and 2916 CAD cases. Compared to population controls, VAD cases were 0.17 (95% CI 0.09 to 0.32) times as likely to have received CSM in the previous week as compared to E&M. In other words, E&M was about 5 times more likely than CSM in the previous week in cases, relative to controls. CSM was 2.53 (95% CI 1.71 to 3.68) times as likely as E&M in the previous week among individuals with VAD than among individuals experiencing a stroke without CeAD. In the case-crossover study, CSM was 0.38 (95% CI 0.15 to 0.91) times as likely as E&M in the week before a VAD, relative to 6 months earlier. In other words, E&M was approximately 3 times more likely than CSM in the previous week in cases, relative to controls. Results for the 14-day and 30-day timeframes were similar to those at one week.

CONCLUSION

Among privately insured US adults, the overall risk of CeAD is very low. Prior receipt of CSM was more likely than E&M among VAD patients as compared to stroke patients. However, for CAD patients as compared to stroke patients, as well as for both VAD and CAD patients in comparison with population controls and in case-crossover analysis, prior receipt of E&M was more likely than CSM.

Candidate pathway analysis of surfactant proteins identifies CTSH and SFTA2 that influences lung cancer risk

Pulmonary surfactant is a lipoprotein synthesized and secreted by alveolar type II cells in lung. We evaluated the associations between 200,139 single nucleotide polymorphisms (SNPs) of 40 surfactant-related genes and lung cancer risk using genotyped data from two independent lung cancer genome-wide association studies. Discovery data included 18,082 cases and 13,780 controls of European ancestry. Replication data included 1,914 cases and 3,065 controls of European descent. Using multivariate logistic regression, we found novel SNPs in surfactant-related genes CTSH [rs34577742 C > T, odds ratio (OR) = 0.90, 95% confidence interval (CI) = 0.89-0.93, P = 7.64 × 10-9] and SFTA2 (rs3095153 G > A, OR = 1.16, 95% CI = 1.10-1.21, P = 1.27 × 10-9) associated with overall lung cancer in the discovery data and validated in an independent replication data-CTSH (rs34577742 C > T, OR = 0.88, 95% CI = 0.80-0.96, P = 5.76 × 10-3) and SFTA2 (rs3095153 G > A, OR = 1.14, 95% CI = 1.01-1.28, P = 3.25 × 10-2). Among ever smokers, we found SNPs in CTSH (rs34577742 C > T, OR = 0.89, 95% CI = 0.85-0.92, P = 1.94 × 10-7) and SFTA2 (rs3095152 G > A, OR = 1.20, 95% CI = 1.14-1.27, P = 4.25 × 10-11) associated with overall lung cancer in the discovery data and validated in the replication data-CTSH (rs34577742 C > T, OR = 0.88, 95% CI = 0.79-0.97, P = 1.64 × 10-2) and SFTA2 (rs3095152 G > A, OR = 1.15, 95% CI = 1.01-1.30, P = 3.81 × 10-2). Subsequent transcriptome-wide association study using expression weights from a lung expression quantitative trait loci study revealed genes most strongly associated with lung cancer are CTSH (PTWAS = 2.44 × 10-4) and SFTA2 (PTWAS = 2.32 × 10-6).

Using New Hampshire Colonoscopy Registry data to assess United States and European post-polypectomy surveillance guidelines

BACKGROUND

Our goal was to compare the updated European Society of Gastrointestinal Endoscopy (ESGE) and United States Multi-Society Task Force on Colorectal Cancer (USMSTF) high risk groups in predicting metachronous advanced neoplasia on first follow-up colonoscopy and long-term colorectal cancer (CRC).

METHODS

We compared advanced metachronous neoplasia risk (serrated polyps ≥ 1 cm or with dysplasia, advanced adenomas [≥ 1 cm, villous, high grade dysplasia], CRC) on first surveillance colonoscopy in patients with high risk findings according to ESGE versus USMSTF guidelines. We also compared the positive and negative predictive values (PPV, NPV) of both guidelines for metachronous neoplasia.

RESULTS

The risk for metachronous neoplasia in our sample (n = 20 458) was higher in the high risk USMSTF (3 year) (13.6 %; 95 %CI 12.3-14.9) and ESGE groups (13.6 %; 95 %CI 12.3-15.0) compared with the lowest risk USMSTF (5.1 %; 95 %CI 4.7-5.5; P < 0.001) and ESGE categories (6.3 %; 95 %CI 6.0-6.7; P < 0.001), respectively. Adding other groups such as USMSTF 5-10-year and 3-5-year groups to the 3-year category resulted in minimal change in the PPV and NPV for metachronous advanced neoplasia. High risk ESGE (hazard ratio [HR] 3.03, 95 %CI 1.97-4.65) and USMSTF (HR 3.07, 95 %CI 2.03-4.66) designations were associated with similar long-term CRC risk (CRC per 100 000 person-years: USMSTF 3-year group 3.54, 95 %CI 2.68-4.68; ESGE high risk group: 3.43, 95 %CI 2.57-4.59).

CONCLUSION

Performance characteristics for the ESGE and USMSTF recommendations are similar in predicting metachronous advanced neoplasia and long-term CRC. The addition of risk groups, such as the USMSTF 5-10-year and 3-5-year groups to the USMSTF 3-year category did not alter the PPV or NPV significantly.

Novel integration of governmental data sources using machine learning to identify super-utilization among U.S. counties

Background

Super-utilizers consume the greatest share of resource intensive healthcare (RIHC) and reducing their utilization remains a crucial challenge to healthcare systems in the United States (U.S.). The objective of this study was to predict RIHC among U.S. counties, using routinely collected data from the U.S. government, including information on consumer spending, offering an alternative method for identifying super-utilization among population units rather than individuals.

Methods

Cross-sectional data from 5 governmental sources in 2017 were used in a machine learning pipeline, where target-prediction features were selected and used in 4 distinct algorithms. Outcome metrics of RIHC utilization came from the American Hospital Association and included yearly: (1) emergency rooms visit, (2) inpatient days, and (3) hospital expenditures. Target-prediction features included: 149 demographic characteristics from the U.S. Census Bureau, 151 adult and child health characteristics from the Centers for Disease Control and Prevention, 151 community characteristics from the American Community Survey, and 571 consumer expenditures from the Bureau of Labor Statistics. SHAP analysis identified important target-prediction features for 3 RIHC outcome metrics.

Results

2475 counties with emergency rooms and 2491 counties with hospitals were included. The median yearly emergency room visits per capita was 0.450 [IQR:0.318, 0.618], the median inpatient days per capita was 0.368 [IQR: 0.176, 0.826], and the median hospital expenditures per capita was $2104 [IQR: $1299.93, 3362.97]. The coefficient of determination (R2), calculated on the test set, ranged between 0.267 and 0.447. Demographic and community characteristics were among the important predictors for all 3 RIHC outcome metrics.

Conclusions

Integrating diverse population characteristics from numerous governmental sources, we predicted 3-outcome metrics of RIHC among U.S. counties with good performance, offering a novel and actionable tool for identifying super-utilizer segments in the population. Wider integration of routinely collected data can be used to develop alternative methods for predicting RIHC among population units.

Association between cervical artery dissection and spinal manipulative therapy -a medicare claims analysis

BACKGROUND

Cervical artery dissection and subsequent ischemic stroke is the most serious safety concern associated with cervical spinal manipulation.

METHODS

We evaluated the association between cervical spinal manipulation and cervical artery dissection among older Medicare beneficiaries in the United States. We employed case-control and case-crossover designs in the analysis of claims data for individuals aged 65+, continuously enrolled in Medicare Part A (covering hospitalizations) and Part B (covering outpatient encounters) for at least two consecutive years during 2007-2015. The primary exposure was cervical spinal manipulation; the secondary exposure was a clinical encounter for evaluation and management for neck pain or headache. We created a 3-level categorical variable, (1) any cervical spinal manipulation, 2) evaluation and management but no cervical spinal manipulation and (3) neither cervical spinal manipulation nor evaluation and management. The primary outcomes were occurrence of cervical artery dissection, either (1) vertebral artery dissection or (2) carotid artery dissection. The cases had a new primary diagnosis on at least one inpatient hospital claim or primary/secondary diagnosis for outpatient claims on at least two separate days. Cases were compared to 3 different control groups: (1) matched population controls having at least one claim in the same year as the case; (2) ischemic stroke controls without cervical artery dissection; and (3) case-crossover analysis comparing cases to themselves in the time period 6-7 months prior to their cervical artery dissection. We made each comparison across three different time frames: up to (1) 7 days; (2) 14 days; and (3) 30 days prior to index event.

RESULTS

The odds of cervical spinal manipulation versus evaluation and management did not significantly differ between vertebral artery dissection cases and any of the control groups at any of the timepoints (ORs 0.84 to 1.88; p > 0.05). Results for carotid artery dissection cases were similar.

CONCLUSION

Among Medicare beneficiaries aged 65 and older who received cervical spinal manipulation, the risk of cervical artery dissection is no greater than that among control groups.

Quantifying differences in packaged food and drink purchases among households with diet-related cardiometabolic multi-morbidity: a cross-sectional analysis

BACKGROUND

Diet is important for chronic disease management, with limited research understanding dietary choices among those with multi-morbidity, the state of having 2 or more chronic conditions. The objective of this study was to identify associations between packaged food and drink purchases and diet-related cardiometabolic multi-morbidity (DRCMM).

METHODS

Cross-sectional associations between packaged food and drink purchases and household DRCMM were investigated using a national sample of U.S. households participating in a research marketing study. DRCMM households were defined as household head(s) self-reporting 2 or more diet-related chronic conditions. Separate multivariable logistic regression models were used to model the associations between household DRCMM status and total servings of, and total calories and nutrients from, packaged food and drinks purchased per month, as well as the nutrient density (protein, carbohydrates, and fat per serving) of packaged food and drinks purchased per month, adjusted for household size.

RESULTS

Among eligible households, 3795 (16.8%) had DRCMM. On average, households with DRCMM versus without purchased 14.8 more servings per capita, per month, from packaged foods and drinks (p < 0.001). DRCMM households were 1.01 times more likely to purchase fat and carbohydrates in lieu of protein across all packaged food and drinks (p = 0.002, p = 0.000, respectively). DRCMM households averaged fewer grams per serving of protein, carbohydrates, and fat per month across all food and drink purchases (all p < 0.001). When carbonated soft drinks and juices were excluded, the same associations for grams of protein and carbohydrates per serving per month were seen (both p < 0.001) but the association for grams of fat per serving per month attenuated.

CONCLUSIONS

DRCMM households purchased greater quantities of packaged food and drinks per capita than non-DRCMM households, which contributed to more fat, carbohydrates, and sodium in the home. However, food and drinks in DRCMM homes on average were lower in nutrient-density. Future studies are needed to understand the motivations for packaged food and drink choices among households with DRCMM to inform interventions targeting the home food environment.

A robust hazard ratio for general modeling of survival-times

Hazard ratios (HR) associated with the well-known proportional hazard Cox regression models are routinely used for measuring the impact of one factor of interest on a time-to-event outcome. However, if the underlying real model does not fit with the theoretical requirements, the interpretation of those HRs is not clear. We propose a new index, gHR, which generalizes the HR beyond the underlying survival model. We consider the case in which the study factor is a binary variable and we are interested in both the unadjusted and adjusted effect of this factor on a time-to-event variable, potentially, observed in a right-censored scenario. We propose non-parametric estimations for unadjusted gHR and semi-parametric regression-induced techniques for the adjusted case. The behavior of those estimators is studied in both large and finite sample situations. Monte Carlo simulations reveal that both estimators provide good approximations of their respective inferential targets. Data from the Health and Lifestyle Study are used for studying the relationship of the tobacco use and the age of death and illustrate the practical application of the proposed technique. gHR is a promising index which can help facilitate better understanding of the association of one study factor on a time-dependent outcome.

Can diverse population characteristics be leveraged in a machine learning pipeline to predict resource intensive healthcare utilization among hospital service areas?

Background

Super-utilizers represent approximately 5% of the population in the United States (U.S.) and yet they are responsible for over 50% of healthcare expenditures. Using characteristics of hospital service areas (HSAs) to predict utilization of resource intensive healthcare (RIHC) may offer a novel and actionable tool for identifying super-utilizer segments in the population. Consumer expenditures may offer additional value in predicting RIHC beyond typical population characteristics alone.

Methods

Cross-sectional data from 2017 was extracted from 5 unique sources. The outcome was RIHC and included emergency room (ER) visits, inpatient days, and hospital expenditures, all expressed as log per capita. Candidate predictors from 4 broad groups were used, including demographics, adults and child health characteristics, community characteristics, and consumer expenditures. Candidate predictors were expressed as per capita or per capita percent and were aggregated from zip-codes to HSAs using weighed means. Machine learning approaches (Random Forrest, LASSO) selected important features from nearly 1,000 available candidate predictors and used them to generate 4 distinct models, including non-regularized and LASSO regression, random forest, and gradient boosting. Candidate predictors from the best performing models, for each outcome, were used as independent variables in multiple linear regression models. Relative contribution of variables from each candidate predictor group to regression model fit were calculated.

Results

The median ER visits per capita was 0.482 [IQR:0.351–0.646], the median inpatient days per capita was 0.395 [IQR:0.214–0.806], and the median hospital expenditures per capita was $2,302 [1$,544.70-$3,469.80]. Using 1,106 variables, the test-set coefficient of determination (R²) from the best performing models ranged between 0.184–0.782. The adjusted R² values from multiple linear regression models ranged from 0.311–0.8293. Relative contribution of consumer expenditures to model fit ranged from 23.4–33.6%.

Discussion

Machine learning models predicted RIHC among HSAs using diverse population data, including novel consumer expenditures and provides an innovative tool to predict population-based healthcare utilization and expenditures. Geographic variation in utilization and spending were identified.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-022-08154-4.

Abstract 245: Increased Prevalence Of Children With Congenital Heart Disease In Colorado From 2012 - 2019

Introduction: Congenital heart defects (CHD) are the most common birth defects and are estimated to affect almost 1% of births per year in the US. Most CHD prevalence estimates are based on data from population-based birth defects surveillance systems and these estimates are inconsistent due to varied definitions. It is therefore important to derive high-quality, population-based estimates of the prevalence of CHD to help care for this vulnerable population.

Methods: We analyzed all payer claims data (APCD) from Colorado from 2012-2019. Children with CHD were identified by applying CHD ICD-9 and ICD-10 diagnoses codes from the Society of Thoracic Surgeons (STS) International Society for Nomenclature of Paediatric and Congenital Heart Disease (ISNPCHD) harmonized cardiac codes. We included children with CHD < 18 years of age who resided in Colorado, had a documented zip code, and had at least one ambulatory healthcare claim. We analyzed the test for linear trends in the proportion of CHD diagnoses from 2012-2019 with the Cochran-Armitage (Z) test. Differences among patient characteristics and CHD diagnosis were tested using the Pearson Chi-square test and Wilcoxon rank sum tests as appropriate.

Results: Overall the current study analyzed 1,565,438 children with 36,567 CHD diagnoses (i.e. 23.4 per 1,000 live births), comprising 2.3% of the pediatric population. Between 2012 and 2019 the statewide rate of children diagnosed with CHD significantly increased from 21.9 to 32.3 per 1,000 children per year (Z: 5.38; p<0.001). There were statistically significant differences in the magnitude of the trend in CHD prevalence rate by region (Z: -31.82), urban-rural residence (Z:-24.02), degree of chronic complex conditions (Z: -38.78), disease severity (Z: -44.11), age (Z: -72.89), insurance type (Z: 46.51) and median household income (Z: 12.87; all p<0.001).

Conclusion: The current study is the first population-level analysis of pediatric CHD in the US and these findings suggest that the statewide CHD prevalence rate has increased significantly since 2012. Children with CHD are a priority population for quality improvement in pediatrics given their growing prevalence and corresponding risk of adverse outcomes.

Estimating population-averaged hazard ratios in the presence of unmeasured confounding

The Cox regression model and its associated hazard ratio (HR) are frequently used for summarizing the effect of treatments on time to event outcomes. However, the HR's interpretation strongly depends on the assumed underlying survival model. The challenge of interpreting the HR has been the focus of a number of recent papers. Several alternative measures have been proposed in order to deal with these concerns. The marginal Cox regression models include an identifiable hazard ratio without individual but populational causal interpretation. In this work, we study the properties of one particular marginal Cox regression model and consider its estimation in the presence of omitted confounder from an instrumental variable-based procedure. We prove the large sample consistency of an estimation score which allows non-binary treatments. Our Monte Carlo simulations suggest that finite sample behavior of the procedure is adequate. The studied estimator is more robust than its competitor (Wang et al.) for weak instruments although it is slightly more biased for large effects of the treatment. The practical use of the presented techniques is illustrated through a real practical example using data from the vascular quality initiative registry. The used R code is provided as Supplementary material.

Initial Choice of Spinal Manipulation Reduces Escalation of Care for Chronic Low Back Pain Among Older Medicare Beneficiaries

STUDY DESIGN

We combined elements of cohort and crossover-cohort design.

OBJECTIVE

The objective of this study was to compare longterm outcomes for spinal manipulative therapy (SMT) and opioid analgesic therapy (OAT) regarding escalation of care for patients with chronic low back pain (cLBP).

SUMMARY OF BACKGROUND DATA

Current evidence-based guidelines for clinical management of cLBP include both OAT and SMT. For long-term care of older adults, the efficiency and value of continuing either OAT or SMT are uncertain.

METHODS

We examined Medicare claims data spanning a five-year period. We included older Medicare beneficiaries with an episode of cLBP beginning in 2013. All patients were continuously enrolled under Medicare Parts A, B, and D. We analyzed the cumulative frequency of encounters indicative of an escalation of care for cLBP, including hospitalizations, emergency department visits, advanced diagnostic imaging, specialist visits, lumbosacral surgery, interventional pain medicine techniques, and encounters for potential complications of cLBP.

RESULTS

SMT was associated with lower rates of escalation of care as compared to OAT. The adjusted rate of escalated care encounters was approximately 2.5 times higher for initial choice of OAT vs. initial choice of SMT (with weighted propensity scoring: rate ratio 2.67, 95% confidence interval 2.64-2.69, P < .0001).

CONCLUSION

Among older Medicare beneficiaries who initiated long-term care for cLBP with opioid analgesic therapy, the adjusted rate of escalated care encounters was significantly higher as compared to those who initiated care with spinal manipulative therapy.Level of Evidence: 3.

Association between chiropractic care and use of prescription opioids among older medicare beneficiaries with spinal pain: a retrospective observational study

Background

The burden of spinal pain can be aggravated by the hazards of opioid analgesics, which are still widely prescribed for spinal pain despite evidence-based clinical guidelines that identify non-pharmacological therapies as the preferred first-line approach. Previous studies have found that chiropractic care is associated with decreased use of opioids, but have not focused on older Medicare beneficiaries, a vulnerable population with high rates of co-morbidity and polypharmacy. The purpose of this investigation was to evaluate the association between chiropractic utilization and use of prescription opioids among older adults with spinal pain.

Methods

We conducted a retrospective observational study in which we examined a nationally representative multi-year sample of Medicare claims data, 2012–2016. The study sample included 55,949 Medicare beneficiaries diagnosed with spinal pain, of whom 9,356 were recipients of chiropractic care and 46,593 were non-recipients. We measured the adjusted risk of filling a prescription for an opioid analgesic for up to 365 days following diagnosis of spinal pain. Using Cox proportional hazards modeling and inverse weighted propensity scoring to account for selection bias, we compared recipients of both primary care and chiropractic to recipients of primary care alone regarding the risk of filling a prescription.

Results

The adjusted risk of filling an opioid prescription within 365 days of initial visit was 56% lower among recipients of chiropractic care as compared to non-recipients (hazard ratio 0.44; 95% confidence interval 0.40–0.49).

Conclusions

Among older Medicare beneficiaries with spinal pain, use of chiropractic care is associated with significantly lower risk of filling an opioid prescription.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12998-022-00415-7.

Long-Term Medicare Costs Associated With Opioid Analgesic Therapy vs Spinal Manipulative Therapy for Chronic Low Back Pain in a Cohort of Older Adults

OBJECTIVES

The purpose of this study was to compare Medicare healthcare expenditures for patients who received long-term treatment of chronic low back pain (cLBP) with either opioid analgesic therapy (OAT) or spinal manipulative therapy (SMT).

METHODS

We conducted a retrospective observational study using a cohort design for analysis of Medicare claims data. The study population included Medicare beneficiaries enrolled under Medicare Parts A, B, and D from 2012 through 2016. We assembled cohorts of patients who received long-term management of cLBP with OAT or SMT (such as delivered by chiropractic or osteopathic practitioners) and evaluated the comparative effect of OAT vs SMT upon expenditures, using multivariable regression to control for beneficiary characteristics and measures of health status, and propensity score weighting and binning to account for selection bias.

RESULTS

The study sample totaled 28,160 participants, of whom 77% initiated long-term care of cLBP with OAT, and 23% initiated care with SMT. For care of low back pain specifically, average long-term costs for patients who initiated care with OAT were 58% lower than those who initiated care with SMT. However, overall long-term healthcare expenditures under Medicare were 1.87 times higher for patients who initiated care via OAT compared with those initiated care with SMT (95% CI 1.65-2.11; P < .0001).

CONCLUSIONS

Adults aged 65 to 84 who initiated long-term treatment for cLBP via OAT incurred lower long-term costs for low back pain but higher long-term total healthcare costs under Medicare compared with patients who initiated long-term treatment with SMT.

Using Satellite Images and Deep Learning to Identify Associations Between County-Level Mortality and Residential Neighborhood Features Proximal to Schools: A Cross-Sectional Study

What is the relationship between mortality and satellite images as elucidated through the use of Convolutional Neural Networks? Background: Following a century of increase, life expectancy in the United States has stagnated and begun to decline in recent decades. Using satellite images and street view images, prior work has demonstrated associations of the built environment with income, education, access to care, and health factors such as obesity. However, assessment of learned image feature relationships with variation in crude mortality rate across the United States has been lacking. Objective: We sought to investigate if county-level mortality rates in the U.S. could be predicted from satellite images. Methods: Satellite images of neighborhoods surrounding schools were extracted with the Google Static Maps application programming interface for 430 counties representing ~68.9% of the US population. A convolutional neural network was trained using crude mortality rates for each county in 2015 to predict mortality. Learned image features were interpreted using Shapley Additive Feature Explanations, clustered, and compared to mortality and its associated covariate predictors. Results: Predicted mortality from satellite images in a held-out test set of counties was strongly correlated to the true crude mortality rate (Pearson r = 0.72). Direct prediction of mortality using a deep learning model across a cross-section of 430 U.S. counties identified key features in the environment (e.g., sidewalks, driveways, and hiking trails) associated with lower mortality. Learned image features were clustered, and we identified 10 clusters that were associated with education, income, geographical region, race, and age. Conclusions: The application of deep learning techniques to remotely-sensed features of the built environment can serve as a useful predictor of mortality in the United States. Although we identified features that were largely associated with demographic information, future modeling approaches that directly identify image features associated with health-related outcomes have the potential to inform targeted public health interventions.

Evaluation of an Artificial Intelligence-Augmented Digital System for Histologic Classification of Colorectal Polyps

Importance

Colorectal polyps are common, and their histopathologic classification is used in the planning of follow-up surveillance. Substantial variation has been observed in pathologists' classification of colorectal polyps, and improved assessment by pathologists may be associated with reduced subsequent underuse and overuse of colonoscopy.

Objective

To compare standard microscopic assessment with an artificial intelligence (AI)-augmented digital system that annotates regions of interest within digitized polyp tissue and predicts polyp type using a deep learning model to assist pathologists in colorectal polyp classification.

Design, Setting, and Participants

In this diagnostic study conducted at a tertiary academic medical center and a community hospital in New Hampshire, 100 slides with colorectal polyp samples were read by 15 pathologists using a microscope and an AI-augmented digital system, with a washout period of at least 12 weeks between use of each modality. The study was conducted from February 10 to July 10, 2020.

Main Outcomes and Measures

Accuracy and time of evaluation were used to compare pathologists' performance when a microscope was used with their performance when the AI-augmented digital system was used. Outcomes were compared using paired t tests and mixed-effects models.

Results

In assessments of 100 slides with colorectal polyp specimens, use of the AI-augmented digital system significantly improved pathologists' classification accuracy compared with microscopic assessment from 73.9% (95% CI, 71.7%-76.2%) to 80.8% (95% CI, 78.8%-82.8%) (P < .001). The overall difference in the evaluation time per slide between the digital system (mean, 21.7 seconds; 95% CI, 20.8-22.7 seconds) and microscopic examination (mean, 13.0 seconds; 95% CI, 12.4-13.5 seconds) was -8.8 seconds (95% CI, -9.8 to -7.7 seconds), but this difference decreased as pathologists became more familiar and experienced with the digital system; the difference between the time of evaluation on the last set of 20 slides for all pathologists when using the microscope and the digital system was 4.8 seconds (95% CI, 3.0-6.5 seconds).

Conclusions and Relevance

In this diagnostic study, an AI-augmented digital system significantly improved the accuracy of pathologic interpretation of colorectal polyps compared with microscopic assessment. If applied broadly to clinical practice, this tool may be associated with decreases in subsequent overuse and underuse of colonoscopy and thus with improved patient outcomes and reduced health care costs.

Factors associated with complete clip closure after endoscopic mucosal resection of large colorectal polyps

BACKGROUND AND STUDY AIM : Delayed bleeding is a common adverse event following endoscopic mucosal resection (EMR) of large colorectal polyps. Prophylactic clip closure of the mucosal defect after EMR of nonpedunculated polyps larger than 20 mm reduces the incidence of severe delayed bleeding, especially in proximal polyps. This study aimed to evaluate factors associated with complete prophylactic clip closure of the mucosal defect after EMR of large polyps. METHODS : This is a post hoc analysis of the CLIP study (NCT01936948). All patients randomized to the clip group were included. Main outcome was complete clip closure of the mucosal resection defect. The defect was considered completely closed when no remaining mucosal defect was visible and clips were less than 1 cm apart. Factors associated with complete closure were evaluated in multivariable analysis. RESULTS : In total, 458 patients (age 65, 58 % men) with 494 large polyps were included. Complete clip closure of the resection defect was achieved for 338 polyps (68.4 %); closure was not complete for 156 (31.6 %). Factors associated with complete closure in adjusted analysis were smaller polyp size (odds ratio 1.06 for every millimeter decrease [95 % confidence interval 1.02-1.08]), good access (OR 3.58 [1.94-9.59]), complete submucosal lifting (OR 2.28 [1.36-3.90]), en bloc resection (OR 5.75 [1.48-22.39]), and serrated histology (OR 2.74 [1.35-5.56]). CONCLUSIONS : Complete clip closure was not achieved for almost one in three resected large nonpedunculated polyps. While stable access and en bloc resection facilitate clip closure, most factors associated with clip closure are not modifiable. This highlights the need for alternative closure options and measures to prevent bleeding.

Fat-enlarged axillary lymph nodes are associated with node-positive breast cancer in obese patients

PURPOSE

Obesity associated fat infiltration of organ systems is accompanied by organ dysfunction and poor cancer outcomes. Obese women demonstrate variable degrees of fat infiltration of axillary lymph nodes (LNs), and they are at increased risk for node-positive breast cancer. However, the relationship between enlarged axillary nodes and axillary metastases has not been investigated. The purpose of this study is to evaluate the association between axillary metastases and fat-enlarged axillary nodes visualized on mammograms and breast MRI in obese women with a diagnosis of invasive breast cancer.

METHODS

This retrospective case-control study included 431 patients with histologically confirmed invasive breast cancer. The primary analysis of this study included 306 patients with pre-treatment and pre-operative breast MRI and body mass index (BMI) > 30 (201 node-positive cases and 105 randomly selected node-negative controls) diagnosed with invasive breast cancer between April 1, 2011, and March 1, 2020. The largest visible LN was measured in the axilla contralateral to the known breast cancer on breast MRI. Multivariate logistic regression models were used to assess the association between node-positive status and LN size adjusting for age, BMI, tumor size, tumor grade, tumor subtype, and lymphovascular invasion.

RESULTS

A strong likelihood of node-positive breast cancer was observed among obese women with fat-expanded lymph nodes (adjusted OR for the 4th vs. 1st quartile for contralateral LN size on MRI: 9.70; 95% CI 4.26, 23.50; p < 0.001). The receiver operating characteristic curve for size of fat-enlarged nodes in the contralateral axilla identified on breast MRI had an area under the curve of 0.72 for predicting axillary metastasis, and this increased to 0.77 when combined with patient and tumor characteristics.

CONCLUSION

Fat expansion of axillary lymph nodes was associated with a high likelihood of axillary metastases in obese women with invasive breast cancer independent of BMI and tumor characteristics.

Time dependent hazard ratio estimation using instrumental variables without conditioning on an omitted covariate

Background

Estimation that employs instrumental variables (IV) can reduce or eliminate bias due to confounding. In observational studies, instruments result from natural experiments such as the effect of clinician preference or geographic distance on treatment selection. In randomized studies the randomization indicator is typically a valid instrument, especially if the study is blinded, e.g. no placebo effect. Estimation via instruments is a highly developed field for linear models but the use of instruments in time-to-event analysis is far from established. Various IV-based estimators of the hazard ratio (HR) from Cox’s regression models have been proposed.

Methods

We extend IV based estimation of Cox’s model beyond proportionality of hazards, and address estimation of a log-linear time dependent hazard ratio and a piecewise constant HR. We estimate the marginal time-dependent hazard ratio unlike other approaches that estimate the hazard ratio conditional on the omitted covariates. We use estimating equations motivated by Martingale representations that resemble the partial likelihood score statistic. We conducted simulations that include the use of copulas to generate potential times-to-event that have a given marginal structural time dependent hazard ratio but are dependent on omitted covariates. We compare our approach to the partial likelihood estimator, and two other IV based approaches. We apply it to estimation of the time dependent hazard ratio for two vascular interventions.

Results

The method performs well in simulations of a stepwise time-dependent hazard ratio, but illustrates some bias that increases as the hazard ratio moves away from unity (the value that typically underlies the null hypothesis). It compares well to other approaches when the hazard ratio is stepwise constant. It also performs well for estimation of a log-linear hazard ratio where no other instrumental variable approaches exist.

Conclusion

The estimating equations we propose for estimating a time-dependent hazard ratio using an IV perform well in simulations. We encourage the use of our procedure for time-dependent hazard ratio estimation when unmeasured confounding is a concern and a suitable instrumental variable exists.

Temporal Trends and Geographic Variations in the Supply of Clinicians Who Provide Spinal Manipulation to Medicare Beneficiaries: A Serial Cross-Sectional Study

OBJECTIVE

Spinal manipulation (SM) is recommended for first-line treatment of patients with low back pain. Inadequate access to SM may result in inequitable spine care for older US adults, but the supply of clinicians who provide SM under Medicare is uncertain. The purpose of this study was to measure temporal trends and geographic variations in the supply of clinicians who provide SM to Medicare beneficiaries.

METHODS

Medicare is a US government-administered health insurance program that provides coverage primarily for older adults and people with disabilities. We used a serial cross-sectional design to examine Medicare administrative data from 2007 to 2015 for SM services identified by procedure code. We identified unique providers by National Provider Identifier and distinguished between chiropractors and other specialties by Physician Specialty Code. We calculated supply as the number of providers per 100 000 beneficiaries, stratified by geographic location and year.

RESULTS

Of all clinicians who provide SM to Medicare beneficiaries, 97% to 98% are doctors of chiropractic. The geographic supply of doctors of chiropractic providing SM services in 2015 ranged from 20/100 000 in the District of Columbia to 260/100 000 in North Dakota. The supply of other specialists performing the same services ranged from fewer than 1/100 000 in 11 states to 8/100 000 in Colorado. Nationally, the number of Medicare-active chiropractors declined from 47 102 in 2007 to 45 543 in 2015. The count of other clinicians providing SM rose from 700 in 2007 to 1441 in 2015.

CONCLUSION

Chiropractors constitute the vast majority of clinicians who bill for SM services to Medicare beneficiaries. The supply of Medicare-active SM providers varies widely by state. The overall supply of SM providers under Medicare is declining, while the supply of nonchiropractors who provide SM is growing.

Development of Electronic Health Record-Based Prediction Models for 30-Day Readmission Risk Among Patients Hospitalized for Acute Myocardial Infarction

IMPORTANCE

In the US, more than 600 000 adults will experience an acute myocardial infarction (AMI) each year, and up to 20% of the patients will be rehospitalized within 30 days. This study highlights the need for consideration of calibration in these risk models.

OBJECTIVE

To compare multiple machine learning risk prediction models using an electronic health record (EHR)-derived data set standardized to a common data model.

DESIGN, SETTING, AND PARTICIPANTS

This was a retrospective cohort study that developed risk prediction models for 30-day readmission among all inpatients discharged from Vanderbilt University Medical Center between January 1, 2007, and December 31, 2016, with a primary diagnosis of AMI who were not transferred from another facility. The model was externally validated at Dartmouth-Hitchcock Medical Center from April 2, 2011, to December 31, 2016. Data analysis occurred between January 4, 2019, and November 15, 2020.

EXPOSURES

Acute myocardial infarction that required hospital admission.

MAIN OUTCOMES AND MEASURES

The main outcome was thirty-day hospital readmission. A total of 141 candidate variables were considered from administrative codes, medication orders, and laboratory tests. Multiple risk prediction models were developed using parametric models (elastic net, least absolute shrinkage and selection operator, and ridge regression) and nonparametric models (random forest and gradient boosting). The models were assessed using holdout data with area under the receiver operating characteristic curve (AUROC), percentage of calibration, and calibration curve belts.

RESULTS

The final Vanderbilt University Medical Center cohort included 6163 unique patients, among whom the mean (SD) age was 67 (13) years, 4137 were male (67.1%), 1019 (16.5%) were Black or other race, and 933 (15.1%) were rehospitalized within 30 days. The final Dartmouth-Hitchcock Medical Center cohort included 4024 unique patients, with mean (SD) age of 68 (12) years; 2584 (64.2%) were male, 412 (10.2%) were rehospitalized within 30 days, and most of the cohort were non-Hispanic and White. The final test set AUROC performance was between 0.686 to 0.695 for the parametric models and 0.686 to 0.704 for the nonparametric models. In the validation cohort, AUROC performance was between 0.558 to 0.655 for parametric models and 0.606 to 0.608 for nonparametric models.

CONCLUSIONS AND RELEVANCE

In this study, 5 machine learning models were developed and externally validated to predict 30-day readmission AMI hospitalization. These models can be deployed within an EHR using routinely collected data.

Factors correlated with intracranial interictal epileptiform discharges in refractory epilepsy

OBJECTIVE

This study was undertaken to evaluate the influence that subject-specific factors have on intracranial interictal epileptiform discharge (IED) rates in persons with refractory epilepsy.

METHODS

One hundred fifty subjects with intracranial electrodes performed multiple sessions of a free recall memory task; this standardized task controlled for subject attention levels. We utilized a dominance analysis to rank the importance of subject-specific factors based on their relative influence on IED rates. Linear mixed-effects models were employed to comprehensively examine factors with highly ranked importance.

RESULTS

Antiseizure medication (ASM) status, time of testing, and seizure onset zone (SOZ) location were the highest-ranking factors in terms of their impact on IED rates. The average IED rate of electrodes in SOZs was 34% higher than the average IED rate of electrodes outside of SOZs (non-SOZ; p < .001). However, non-SOZ electrodes had similar IED rates regardless of the subject's SOZ location (p = .99). Subjects on older generation (p < .001) and combined generation (p < .001) ASM regimens had significantly lower IED rates relative to the group taking no ASMs; newer generation ASM regimens demonstrated a nonsignificant association with IED rates (p = .13). Of the ASMs included in this study, the following ASMs were associated with significant reductions in IED rates: levetiracetam (p < .001), carbamazepine (p < .001), lacosamide (p = .03), zonisamide (p = .01), lamotrigine (p = .03), phenytoin (p = .03), and topiramate (p = .01). We observed a nonsignificant association between time of testing and IED rates (morning-afternoon p = .15, morning-evening p = .85, afternoon-evening p = .26).

SIGNIFICANCE

The current study ranks the relative influence that subject-specific factors have on IED rates and highlights the importance of considering certain factors, such as SOZ location and ASM status, when analyzing IEDs for clinical or research purposes.

A new efficient method to detect genetic interactions for lung cancer GWAS

BACKGROUND

Genome-wide association studies (GWAS) have proven successful in predicting genetic risk of disease using single-locus models; however, identifying single nucleotide polymorphism (SNP) interactions at the genome-wide scale is limited due to computational and statistical challenges. We addressed the computational burden encountered when detecting SNP interactions for survival analysis, such as age of disease-onset. To confront this problem, we developed a novel algorithm, called the Efficient Survival Multifactor Dimensionality Reduction (ES-MDR) method, which used Martingale Residuals as the outcome parameter to estimate survival outcomes, and implemented the Quantitative Multifactor Dimensionality Reduction method to identify significant interactions associated with age of disease-onset.

METHODS

To demonstrate efficacy, we evaluated this method on two simulation data sets to estimate the type I error rate and power. Simulations showed that ES-MDR identified interactions using less computational workload and allowed for adjustment of covariates. We applied ES-MDR on the OncoArray-TRICL Consortium data with 14,935 cases and 12,787 controls for lung cancer (SNPs = 108,254) to search over all two-way interactions to identify genetic interactions associated with lung cancer age-of-onset. We tested the best model in an independent data set from the OncoArray-TRICL data.

RESULTS

Our experiment on the OncoArray-TRICL data identified many one-way and two-way models with a single-base deletion in the noncoding region of BRCA1 (HR 1.24, P = 3.15 × 10-15), as the top marker to predict age of lung cancer onset.

CONCLUSIONS

From the results of our extensive simulations and analysis of a large GWAS study, we demonstrated that our method is an efficient algorithm that identified genetic interactions to include in our models to predict survival outcomes.

Ischemic Stroke Occurs Less Frequently in Patients With COVID-19: A Multicenter Cross-Sectional Study

Supplemental Digital Content is available in the text.

The impact of coronavirus disease 2019 (COVID-19) on the occurrence of ischemic stroke has been the subject of increased speculation but has not been confirmed in large observational studies. We investigated the association between COVID-19 and stroke.

Summarizing causal differences in survival curves in the presence of unmeasured confounding

Proportional hazard Cox regression models are frequently used to analyze the impact of different factors on time-to-event outcomes. Most practitioners are familiar with and interpret research results in terms of hazard ratios. Direct differences in survival curves are, however, easier to understand for the general population of users and to visualize graphically. Analyzing the difference among the survival curves for the population at risk allows easy interpretation of the impact of a therapy over the follow-up. When the available information is obtained from observational studies, the observed results are potentially subject to a plethora of measured and unmeasured confounders. Although there are procedures to adjust survival curves for measured covariates, the case of unmeasured confounders has not yet been considered in the literature. In this article we provide a semi-parametric procedure for adjusting survival curves for measured and unmeasured confounders. The method augments our novel instrumental variable estimation method for survival time data in the presence of unmeasured confounding with a procedure for mapping estimates onto the survival probability and the expected survival time scales.

The impact of low- versus high-intensity surveillance cystoscopy on surgical care and cancer outcomes in patients with high-risk non-muscle-invasive bladder cancer (NMIBC)

Purpose

To assess the association of low- vs. guideline-recommended high-intensity cystoscopic surveillance with outcomes among patients with high-risk non-muscle invasive bladder cancer (NMIBC).

Materials & methods

A retrospective cohort study of Veterans Affairs patients diagnosed with high-risk NMIBC between 2005 and 2011 with follow-up through 2014. Patients were categorized by number of surveillance cystoscopies over two years following diagnosis: low- (1–5) vs. high-intensity (6 or more) surveillance. Propensity score adjusted regression models were used to assess the association of low-intensity cystoscopic surveillance with frequency of transurethral resections, and risk of progression to invasive disease and bladder cancer death.

Results

Among 1,542 patients, 520 (33.7%) underwent low-intensity cystoscopic surveillance. Patients undergoing low-intensity surveillance had fewer transurethral resections (37 vs. 99 per 100 person-years; p<0.001). Risk of death from bladder cancer did not differ significantly by low (cumulative incidence [CIn] 8.4% [95% CI 6.5–10.9) at 5 years) vs. high-intensity surveillance (CIn 9.1% [95% CI 7.4–11.2) at 5 years, p = 0.61). Low vs. high-intensity surveillance was not associated with increased risk of bladder cancer death among patients with Ta (CIn 5.7% vs. 8.2% at 5 years p = 0.24) or T1 disease at diagnosis (CIn 10.2% vs. 9.1% at 5 years, p = 0.58). Among patients with Ta disease, low-intensity surveillance was associated with decreased risk of progression to invasive disease (T1 or T2) or bladder cancer death (CIn 19.3% vs. 31.3% at 5 years, p = 0.002).

Conclusions

Patients with high-risk NMIBC undergoing low- vs. high-intensity cystoscopic surveillance underwent fewer transurethral resections, but did not experience an increased risk of progression or bladder cancer death. These findings provide a strong rationale for a clinical trial to determine whether low-intensity surveillance is comparable to high-intensity surveillance for cancer control in high-risk NMIBC.

Antiepileptic drug effects on subjective and objective cognition

RATIONALE

Cognitive impairment is one of the most common complaints for persons with epilepsy (PWE). These impairments are not only associated with seizures, but are also regularly reported as adverse effects of antiepileptic drugs (AEDs). Previous studies have examined cognitive effects of both AED monotherapy and polytherapy, yet there is limited research on these differences with respect to both subjective and objective cognition. The current study uses data from previous research conducted by the Centers for Disease Control and Prevention (CDC)-sponsored Managing Epilepsy Well (MEW) Network collaborative. We used three distinct archival datasets from the following: (1) the HOBSCOTCH efficacy trial at Dartmouth-Hitchcock Medical Center (HOB-1), (2) the multisite replication trial (HOB-2), and (3) epilepsy self-management research conducted at the NYU School of Medicine.

METHODS

This retrospective analysis combined baseline data from three datasets to determine how the number of AEDs and the type of AEDs were associated with subjective (patient-reported) and objective (examiner-assessed) cognition. Subjective cognition was captured using the cognitive subscale of the Quality of Life in Epilepsy Inventory (QOLIE-31) in all three datasets (n = 224), while objective cognition was measured using the Repeated Battery for the Assessment of Neuropsychological Status (RBANS) in the HOB-1 dataset (n = 65) and the Brief Test of Adult Cognition by Telephone (BTACT) in the HOB-2 dataset (n = 91). Multivariable linear regression was utilized for our initial assessments, followed by propensity score matching to provide stronger control of covariates. Matching was based on significantly different covariates, such as education, depression, and history of prior epilepsy surgery. Nonparametric statistical tests were utilized to compare these matched subjects.

RESULTS

Subjective cognitive impairment was significantly worse among individuals on polytherapy (2 + AEDs) compared with those on monotherapy (1 AED) (adjusted p  =  0.041). These findings were consistent with our propensity score matched comparison of monotherapy and polytherapy, which indicated that polytherapy was associated with worse overall subjective cognition (adjusted p = 0.01), in addition to impairments on the RBANS (Total score p = 0.05) and specific subdomains of the BTACT (Episodic Verbal Memory p < 0.01, Working Memory p < 0.01, Processing Speed p < 0.01). Interestingly, older generation AEDs were associated with better language performance than newer generation and combined generation AED therapy (RBANS Language p = 0.03). These language-specific findings remained significant after controlling for the effects of topiramate and zonisamide (p = 0.04).

CONCLUSIONS

A greater number of AEDs is significantly and negatively associated with subjective and objective cognition in PWE, and is in line with previous research. Antiepileptic drug type did not, in itself, appear to be associated with subjective cognition. Our findings suggest that ineffective AEDs should be replaced, rather than introducing additional AEDs to a treatment regimen. Further, while subjective and objective cognition assessments were both sensitive at detecting differences based on AED status, the neuropsychological objective subdomains offer additional and specific insights into how cognition is impaired with AEDs.

The Association between Cytokines and 365-Day Readmission or Mortality in Adult Cardiac Surgery

Cardiac surgery results in a multifactorial systemic inflammatory response with inflammatory cytokines, such as interleukin-10 and 6 (IL-10 and IL-6), shown to have potential in the prediction of adverse outcomes including readmission or mortality. This study sought to measure the association between IL-6 and IL-10 levels and 1-year hospital readmission or mortality following cardiac surgery. Plasma biomarkers IL-6 and IL-10 were measured in 1,047 patients discharged alive after isolated coronary artery bypass graft surgery from eight medical centers participating in the Northern New England Cardiovascular Disease Study Group between 2004 and 2007. Readmission status and mortality were ascertained using Medicare, state all-payer claims, and the National Death Index. We evaluated the association between preoperative and postoperative cytokines and 1-year readmission or mortality using Kaplan-Meier estimates and Cox's proportional hazards modeling, adjusting for covariates used in the Society of Thoracic Surgeons 30-day readmission model. The median follow-up time was 1 year. After adjustment, patients in the highest tertile of postoperative IL-6 values had a significantly increased risk of readmission or death within 1 year (HR: 1.38; 95% CI: 1.03-1.85), and an increased risk of death within 1 year of discharge (HR: 4.88; 95% CI: 1.26-18.85) compared with patients in the lowest tertile. However, postoperative IL-10 levels, although increasing through tertiles, were not found to be significantly associated independently with 1-year readmission or mortality (HR: 1.25; 95% CI: .93-1.69). Pro-inflammatory cytokine IL-6 and anti-inflammatory cytokine IL-10 may be postoperative markers of cardiac injury, and IL-6, specifically, shows promise in predicting readmission and mortality following cardiac surgery.

Outcomes of Elective Cerebral Aneurysm Treatment Performed by Attending Neurosurgeons after Night Work

BACKGROUND

The association between long work hours and outcomes among attending surgeons remains an issue of debate.

OBJECTIVE

To investigate whether operating emergently the night before an elective case was associated with inferior outcomes among attending neurosurgeons.

METHODS

We executed a cohort study with unruptured cerebral aneurysm patients, who underwent endovascular coiling or surgical clipping from 2009 to 2013 and were registered in the Statewide Planning and Research Cooperative System database. We investigated the association of treatment by surgeons performing emergency procedures the night before with outcomes of elective cerebral aneurysm treatment using an instrumental variable analysis.

RESULTS

Overall, 4700 patients underwent treatment for unruptured cerebral aneurysms. There was no difference in inpatient mortality (adjusted difference, -0.7%; 95% confidence interval [CI], -1.4% to 0.02%), discharge to a facility (adjusted difference, -0.1%; 95% CI, -1.2% to 1.2%), or length of stay (adjusted difference, -0.58; 95% CI, -1.66 to 0.50) between patients undergoing elective cerebral aneurysm treatment by surgeons who performed emergency procedures the night before, and those who did not.

CONCLUSION

Using a comprehensive patient cohort in New York State for elective treatment of unruptured cerebral aneurysms, we did not identify an association of treatment by surgeons performing emergency procedures the night before, with mortality, discharge to a facility, or length of stay. Our study had 80% power to detect differences in mortality (our primary outcome), as small as 4.1%. The results of the present study do not support the argument for regulation of attending work hours.

Galectin-3 as a Predictor of Long-term Survival After Isolated Coronary Artery Bypass Grafting Surgery

BACKGROUND

Galectin-3 (Gal-3) is a well-established biomarker of adverse clinical outcomes, but its prognostic value for long-term survival after cardiac surgery is not well understood. Elevated levels of Gal-3 have been found to be remarkably associated with higher risk of death in both acute decompensated and chronic heart failure populations. Its prognostic value for long-term survival after cardiac surgery is not known.

METHODS

A sample of patients contributing to the Northern New England Cardiovascular Disease Study Group Cardiac Surgery Registry from 2004 to 2007 were enrolled in a prospective biomarker cohort (N = 1690). Preoperative Gal-3 levels were measured and categorized by quartile. We used Kaplan-Meier survival analysis and Cox regression models, adjusting for variables in The Society of Thoracic Surgeons Collaboration on the Comparative Effectiveness of Revascularization Strategy probability calculator to evaluate the association between elevated Gal-3 levels and survival to 6 years.

RESULTS

Preoperative Gal-3 levels ranged from 1.72 to 28.89 ng/mL (mean, 8.96 ng/mL; median, 8.06 ng/mL; interquartile range, 5.42-11.08 ng/mL). Crude survival decreased by increasing quartile. After adjustment, serum levels of Gal-3 in the highest quartile of the cohort were associated with significantly decreased survival compared with the lowest quartile (hazard ratio [HR] 2.22; 95% confidence interval [CI], 1.40-3.54; P = .001). No decrease in survival was found for the middle quartiles (HR 1.36; 95% CI, 0.87-2.12; P = .177).

CONCLUSIONS

A substantial association was found between elevated preoperative Gal-3 levels and risk of mortality after isolated coronary artery bypass grafting surgery. An assessment of the relationship between preoperative serum biomarkers and long-term survival can be used for risk stratification or estimating postsurgical prognosis.

Cardiac Biomarkers Predict Long-term Survival After Cardiac Surgery

BACKGROUND

Cardiac biomarkers soluble ST-2 (sST-2) and N-terminal prohormone B-type natriuretic peptide (NT-proBNP) may be associated with long-term survival after cardiac surgery. This study explored the relationship between long-term survival after cardiac surgery and serum biomarker levels.

METHODS

Patients undergoing cardiac surgery from 2004 to 2007 were enrolled in a prospective biomarker cohort in the Northern New England Cardiovascular Disease Study Group Registry. Preoperative serum biomarker levels, postoperative serum biomarker levels, and the change in serum biomarker levels were categorized by quartile. The study used Kaplan-Meier survival analysis and Cox regression models adjusted for variables in the American College of Cardiology Foundation-Society of Thoracic Surgeons Collaboration on the Comparative Effectiveness of Revascularization Strategy (ASCERT) long-term survival calculator to study the association of biomarker levels with long-term survival. After Kaplan-Meier analysis, quartiles 2 and 3 were found to have similar survival and were therefore combined into 1 category.

RESULTS

In the study cohort (n = 1648), median follow-up time was 8.5 years (interquartile range, 7.6-9.7 years), during which there were 227 deaths. The 10-year survival rate was 86%. Kaplan-Meier survival analysis demonstrated a significant (P < .001) difference across quartiles of each biomarker level measurement. After adjustment, preoperative levels, postoperative levels, and the change in biomarker levels in quartile 4 (highest serum levels or change) were significantly predictive of worse survival (hazard ratio range, 1.77-2.89; all P < .05) compared with quartile 1; however, levels of sST-2 and NT-proBNP in quartiles 2 and 3 demonstrated a nonstatistically significant trend with long-term survival.

CONCLUSIONS

Elevated preoperative and postoperative levels of sST-2 or NT-proBNP and large changes in these biomarkers' levels are associated with an increased risk of worse survival after cardiac surgery. These biomarkers can be used for risk stratification or assessing postsurgical prognosis.

Multicenter, Open-Label, Phase II Study of Bendamustine and Rituximab Followed by 90-Yttrium (Y) Ibritumomab Tiuxetan for Untreated Follicular Lymphoma (Fol-BRITe)

PURPOSE

Bendamustine and rituximab (BR) has been established as a superior frontline therapy over R-CHOP in the treatment of follicular lymphoma (FL). Yttrium-90 Ibritumomab tiuxetan (⁹⁰YIT) is an effective consolidation strategy after chemotherapy induction. This prospective, single-arm, multicenter, phase II trial evaluated the response rate, progression-free survival (PFS), and tolerability of BR followed by consolidation with ⁹⁰YIT in patients with untreated FL.

PATIENTS AND METHODS

The study included grade 1 to 3a FL patients aged ≥18 years, chemotherapy-naïve, and requiring treatment for stage II-IV disease. Study treatment included an initial rituximab treatment, followed by four cycles of BR. Patients were eligible for consolidation with ⁹⁰YIT, 6 to 12 weeks after BR, if they obtained at least a partial response after induction had adequate count recovery and bone marrow infiltration < 25%.

RESULTS

Thirty-nine patients were treated. Eighty-two percent had an intermediate or high-risk Follicular Lymphoma International Prognostic Index score, and 6 of 39 (15%) were grade 3a. The response rate was 94.8%, and the complete response(CR)/CR unconfirmed (CRu) rate was 77% in the intention-to-treat analysis. The conversion rate from PR to CR/Cru after ⁹⁰YIT was 81%. After median follow-up of 45 months, the PFS was 0.71 (95% confidence interval, 0.57-0.89).

CONCLUSIONS

This report demonstrates that four cycles of BR followed by consolidation with ⁹⁰YIT achieve high response rates that are durable. In addition, consolidation with ⁹⁰YIT results in a high conversion rate of PR to CR/CRu. A short course of BR followed by ⁹⁰YIT is a safe and effective regimen for frontline treatment of FL.

The impact of frequent cystoscopy on surgical care and cancer outcomes among patients with low-risk, non-muscle-invasive bladder cancer

BACKGROUND

Surveillance recommendations for patients with low-risk, non-muscle-invasive bladder cancer (NMIBC) are based on limited evidence. The objective of this study was to add to the evidence by assessing outcomes after frequent versus recommended cystoscopic surveillance.

METHODS

This was a retrospective cohort study of patients diagnosed with low-risk (low-grade Ta (AJCC)) NMIBC from 2005 to 2011 with follow-up through 2014 from the Department of Veterans Affairs. Patients were classified as having undergone frequent versus recommended cystoscopic surveillance (>3 vs 1-3 cystoscopies in the first 2 years after diagnosis). By using propensity score-adjusted models, the authors estimated the impact of frequent cystoscopy on the number of transurethral resections, the number of resections without cancer in the specimen, and the risk of progression to muscle-invasive cancer or bladder cancer death.

RESULTS

Among 1042 patients, 798 (77%) had more frequent cystoscopy than recommended. In adjusted analyses, the frequent cystoscopy group had twice as many transurethral resections (55 vs 26 per 100 person-years; P < .001) and more than 3 times as many resections without cancer in the specimen (5.7 vs 1.6 per 100 person-years; P < .001). Frequent cystoscopy was not associated with time to progression or bladder cancer death (3% at 5 years in both groups; P = .990).

CONCLUSIONS

Frequent cystoscopy among patients with low-risk NMIBC was associated with twice as many transurethral resections and did not decrease the risk for bladder cancer progression or death, supporting current guidelines.

Middle-aged death and taxes in the USA: Association of state tax burden and expenditures in 2005 with survival from 2006 to 2015

Background

Longevity in the United States ranks below most other Western nations despite spending more on healthcare per capita than any other country. Across the world, mortality has been declining, but in the USA the trend toward improvement has stalled in some middle-aged demographic groups. Cross-national studies suggest that social welfare is positively associated with longevity. The United States has less government sponsored welfare, education and healthcare than almost all other Western nations, but the level of this social welfare commitment varies across the states. In this study we examined the association of state tax burden and state government expenditures with subsequent middle-aged mortality.

Methods

The primary exposure was state tax burden in 2005, defined as proportion of all state income paid to the state. We also examined the impact of state expenditures per capita in 2005 for education, healthcare, welfare, police and highways. The dependent variable was mortality during the subsequent 10 years. Death counts and population sizes by sex, age group and race strata for 2006–2015 were abstracted from CDC WONDER. Binomial logistic regression was employed based on the number of deaths and underlying population within each county-sex-age-race bin.

Results

State tax burden in 2005 varied from 5.8% to 12.2%. An increase of 1.0 percentage point in state tax burden was associated with a 5.8% (SE = 0.1%) reduction in mortality adjusted for sex, age and race, but was associated with a 1.1% (SE = 0.1%) reduction when further adjusting for state income and education levels. Controlling for sex, age and race each type of state expenditures was associated with decreases in middle aged mortality, notably K-12 education (reduction of 4.7%, SE = 0.1%, per 10% expenditure increase) except healthcare but all types were associated with mortality decreases further controlling for state income and education.

Conclusion

The residents of states with higher state taxation and higher expenditures per capita have lower middle aged mortality rates.

Modeling a bivariate residential-workplace neighborhood effect when estimating the effect of proximity to fast-food establishments on body mass index

Hierarchical modeling is the preferred approach of modeling neighborhood effects. When both residential and workplace neighborhoods are known, a bivariate (residential-workplace) neighborhood random effect that quantifies the extent that a neighborhood's residential and workplace effects are correlated may be modeled. However, standard statistical software for hierarchical models does not easily allow correlations between the random effects of distinct clustering variables to be incorporated. To overcome this challenge, we develop a Bayesian model and an accompanying estimation procedure that allows for correlated bivariate neighborhood effects and allows individuals to reside or work in multiple neighborhoods, cross-sectional and longitudinal heterogeneity between individuals, and serial correlation between repeated observations over time. Simulation studies that vary key model parameters evaluate how well each aspect of the model is identified by the data. We apply the model to the motivating Framingham Heart Study linked food establishment data to examine whether (i) proximity to fast-food establishments is associated with body mass index, (ii) workplace neighborhood exposure associations are larger than those for residential neighborhood exposure, and (iii) residential neighborhood exposure associations correlate with workplace neighborhood exposure. Comparisons of the full model to models with restricted versions of the covariance structure illustrate the impact of including each feature of the covariance structure.

sST2 as a novel biomarker for the prediction of in-hospital mortality after coronary artery bypass grafting

Objectives: Soluble suppression of tumorigenicity 2 (sST2) biomarker is an emerging predictor of adverse clinical outcomes, but its prognostic value for in-hospital mortality after coronary artery bypass grafting (CABG) is not well understood. This study measured the association between operative sST2 levels and in-hospital mortality after CABG. Methods: A prospective cohort of 1560 CABG patients were analyzed from the Northern New England Cardiovascular Disease Study Group Biomarker Study. The primary outcome was in-hospital mortality after CABG surgery (n = 32). Results: After risk adjustment, patients in the third tercile of pre-, post- and pre-to-postoperative sST2 values experienced significantly greater odds of in-hospital death compared to patients in the first tercile of sST2 values. The addition of both postoperative and pre-to-postoperative sST2 biomarker significantly improved ability to predict in-hospital mortality status following CABG surgery, compared to using the EuroSCORE II mortality model alone, (c-statistic: 0.83 [95% CI: 0.75, 0.92], p value 0.0213) and (c-statistic: 0.83 [95% CI: 0.75, 0.92], p value 0.0215), respectively. Conclusion: sST2 values are associated with in-hospital mortality after CABG surgery and postoperative and pre-to-post operative sST2 values improve prediction. Our findings suggest that sST2 can be used as a biomarker to identify adult patients at greatest risk of in-hospital death after CABG surgery.

Prevalence rates of arthritis among US older adults with varying degrees of depression: Findings from the 2011 to 2014 National Health and Nutrition Examination Survey

OBJECTIVE

Arthritis and depressive symptoms often interact and negatively influence one another to worsen mental and physical health outcomes. Better characterization of arthritis rates among older adults with different levels of depressive symptoms is an important step toward informing mental health professionals of the need to detect and respond to arthritis and related mental health complications. The primary objective is to determine arthritis rates among US older adults with varying degrees of depression.

METHODS

Using National Health and Nutrition Examination Survey 2011 to 2014 data (N = 4792), we first identified participants aged ≥50 years. Measures screened for depressive symptoms and self-reported doctor-diagnosed arthritis. Weighted logistic regression models were conducted.

RESULTS

Prevalence of arthritis was 55.0%, 62.9%, and 67.8% in participants with minor, moderate, and severe depression, respectively. In both unadjusted and adjusted regression models, a significant association between moderate depression and arthritis persisted. There were also significant associations between minor and severe depression with arthritis.

CONCLUSIONS

Arthritis is commonly reported in participants with varying degrees of depression. This study highlights the importance of screening for and treating arthritis-related pain in older adults with depressive symptoms and the need for future geriatric psychiatry research on developing integrated biopsychosocial interventions for these common conditions.

Statins associate with improved mortality among patients with certain histological subtypes of lung cancer

OBJECTIVES

To measure the association between statin exposure and mortality in lung cancer patients belonging to different categories of histological subtype.

MATERIALS AND METHODS

A cohort of 19,974 individuals with incident lung cancer between 2007 and 2011 was identified using the SEER-Medicare linked database. Statin exposure both pre- and post-diagnosis was analyzed to identify a possible association with cancer-specific mortality in patients stratified by histological subtype. Intention-to-treat analyses and time-dependent Cox regression models were used to calculate hazard ratios and 95% confidence intervals (95% CIs) corresponding to statin exposure both pre- and post-diagnosis, respectively.

RESULTS

Overall baseline statin exposure was associated with a decrease in mortality risk for squamous-cell carcinoma patients (HR = 0.89, 95% CI = 0.82-0.96) and adenocarcinoma patients (HR = 0.87, 95% CI = 0.82-0.94), but not among those with small-cell lung cancer. Post-diagnostic statin exposure was associated with prolonged survival in squamous-cell carcinoma patients (HR = 0.68, 95% CI = 0.59-0.79) and adenocarcinoma patients (HR = 0.78, 95% CI = 0.68-0.89) in a dose-dependent manner.

CONCLUSION

There is consistent evidence indicating that baseline or post-diagnostic exposure to simvastatin and atorvastatin is associated with extended survival in non-small-cell lung cancer subtypes. These results warrant further randomized clinical trials to evaluate subtype-specific effects of certain statins in patient cohorts with characteristics similar to those examined in this study.

Comparing Long-term Mortality After Carotid Endarterectomy vs Carotid Stenting Using a Novel Instrumental Variable Method for Risk Adjustment in Observational Time-to-Event Data

IMPORTANCE

Choosing between competing treatment options is difficult for patients and clinicians when results from randomized and observational studies are discordant. Observational real-world studies yield more generalizable evidence for decision making than randomized clinical trials, but unmeasured confounding, especially in time-to-event analyses, can limit validity.

OBJECTIVES

To compare long-term survival after carotid endarterectomy (CEA) and carotid artery stenting (CAS) in real-world practice using a novel instrumental variable method designed for time-to-event outcomes, and to compare the results with traditional risk-adjustment models used in observational research for survival analyses.

DESIGN, SETTING, AND PARTICIPANTS

A multicenter cohort study was performed. The Vascular Quality Initiative, an observational quality improvement registry, was used to compare long-term mortality after CEA vs CAS. The study included 86 017 patients who underwent CEA (n = 73 312) or CAS (n = 12 705) between January 1, 2003, and December 31, 2016. Patients were followed up for long-term mortality assessment by linking the registry data to Medicare claims. Medicare claims data were available through September 31, 2015.

EXPOSURE

Procedure type (CEA vs CAS).

MAIN OUTCOMES AND MEASURES

The hazard ratios (HRs) of all-cause mortality using unadjusted, adjusted, propensity-matched, and instrumental variable methods were examined. The instrumental variable was the proportion of CEA among the total carotid procedures (endarterectomy and stenting) performed at each hospital in the 12 months before each patient's index operation and therefore varies over the study period.

RESULTS

Participants who underwent CEA had a mean (SD) age of 70.3 (9.4) years compared with 69.1 (10.4) years for CAS, and most were men (44 191 [60.4%] for CEA and 8117 [63.9%] for CAS). The observed 5-year mortality was 12.8% (95% CI, 12.5%-13.2%) for CEA and 17.0% (95% CI, 16.0%-18.1%) for CAS. The unadjusted HR of mortality for CEA vs CAS was 0.67 (95% CI, 0.64-0.71), and Cox-adjusted and propensity-matched HRs were similar (0.69; 95% CI, 0.65-0.74 and 0.71; 95% CI, 0.65-0.77, respectively). These findings are comparable with published observational studies of CEA vs CAS. However, the association between CEA and mortality was more modest when estimated by instrumental variable analysis (HR, 0.83; 95% CI, 0.70-0.98), a finding similar to data reported in randomized clinical trials.

CONCLUSIONS AND RELEVANCE

The study found a survival advantage associated with CEA over CAS in unadjusted and Cox-adjusted analyses. However, this finding was more modest when using an instrumental variable method designed for time-to-event outcomes for risk adjustment. The instrumental variable-based results were more similar to findings from randomized clinical trials, suggesting this method may provide less biased estimates of time-dependent outcomes in observational analyses.

Extent of Risk-Aligned Surveillance for Cancer Recurrence Among Patients With Early-Stage Bladder Cancer

IMPORTANCE

Cancer care guidelines recommend aligning surveillance frequency with underlying cancer risk, ie, more frequent surveillance for patients at high vs low risk of cancer recurrence.

OBJECTIVE

To assess the extent to which such risk-aligned surveillance is practiced within US Department of Veterans Affairs facilities by classifying surveillance patterns for low- vs high-risk patients with early-stage bladder cancer.

DESIGN SETTING AND PARTICIPANTS

US national retrospective cohort study of a population-based sample of patients diagnosed with low-risk or high-risk early-stage bladder between January 1, 2005, and December 31, 2011, with follow-up through December 31, 2014. Analyses were performed March 2017 to April 2018. The study included all Veterans Affairs facilities (n = 85) where both low-and high-risk patients were treated.

EXPOSURES

Low-risk vs high-risk cancer status, based on definitions from the European Association of Urology risk stratification guidelines and on data extracted from diagnostic pathology reports via validated natural language processing algorithms.

MAIN OUTCOMES AND MEASURES

Adjusted cystoscopy frequency for low-risk and high-risk patients for each facility, estimated using multilevel modeling.

RESULTS

The study included 1278 low-risk and 2115 high-risk patients (median [interquartile range] age, 77 [71-82] years; 99% [3368 of 3393] male). Across facilities, the adjusted frequency of surveillance cystoscopy ranged from 3.7 to 6.2 (mean, 4.8) procedures over 2 years per patient for low-risk patients and from 4.6 to 6.0 (mean, 5.4) procedures over 2 years per patient for high-risk patients. In 70 of 85 facilities, surveillance was performed at a comparable frequency for low- and high-risk patients, differing by less than 1 cystoscopy over 2 years. Surveillance frequency among high-risk patients statistically significantly exceeded surveillance among low-risk patients at only 4 facilities. Across all facilities, surveillance frequencies for low- vs high-risk patients were moderately strongly correlated (r = 0.52; P < .001).

CONCLUSIONS AND RELEVANCE

Patients with early-stage bladder cancer undergo cystoscopic surveillance at comparable frequencies regardless of risk. This finding highlights the need to understand barriers to risk-aligned surveillance with the goal of making it easier for clinicians to deliver it in routine practice.

Surgical outcomes for patients diagnosed with dementia: A coarsened exact matching study

BACKGROUND

An increasing number of elderly patients with dementia are undergoing surgical operations. Little is known about the differential impact of dementia on surgical outcomes. We investigated whether demented patients undergoing surgical operations have worse outcomes than their non-demented counterparts.

METHODS

We performed a cohort study of all patients undergoing a series of surgical operations who were registered in the New York Statewide Planning and Research Cooperative System (SPARCS) database from 2009 to 2013. We examined the association of dementia with inpatient case-fatality, discharge to a facility, and length of stay (LOS). Coarsened exact matching was used to balance comorbidities among the comparison groups, and mixed effect methods were used to control for clustering at the hospital level.

RESULTS

During the study period, 342,075 patients underwent surgical operations that met the inclusion criteria. Multivariable logistic regression models, after coarsened exact matching, demonstrated that demented patients were not associated with higher case-fatality (OR, 0.43; 95% CI, 0.13-1.36), but were associated with higher rates of discharge to a facility (OR, 1.71; 95% CI, 1.26-2.31) and longer LOS (Adjusted difference, 31%; 95% CI, 26%-36%). These persisted in pre-specified subgroups stratified on particular operations.

CONCLUSIONS

Using a comprehensive all-payer cohort of surgical patients in New York State we identified an association of dementia with increased rate of discharge to rehabilitation and longer LOS. No difference was identified in the case fatality of the two groups. Policy makers, payers, and physicians should take these findings into account when designing new policies, and when counseling patients.

Correlation of hospital magnet status with the quality of physicians performing neurosurgical procedures in New York State

PURPOSE

The quality of physicians practicing in hospitals recognized for nursing excellence by the American Nurses Credentialing Center has not been studied before. We investigated whether Magnet hospital recognition is associated with higher quality of physicians performing neurosurgical procedures.

MATERIALS AND METHODS

We performed a cohort study of patients undergoing neurosurgical procedures from 2009-2013, who were registered in the New York Statewide Planning and Research Cooperative System (SPARCS) database. Propensity score adjusted multivariable regression models were used to adjust for known confounders, with mixed effects methods to control for clustering at the facility level. An instrumental variable analysis was used to control for unmeasured confounding and simulate the effect of a randomized trial.

RESULTS

During the study period, 185,277 patients underwent neurosurgical procedures, and met the inclusion criteria. Of these, 66,607 (35.6%) were hospitalized in Magnet hospitals, and 118,670 (64.4%) in non-Magnet institutions. Instrumental variable analysis demonstrated that undergoing neurosurgical operations in Magnet hospitals was associated with a 13.6% higher chance of being treated by a physician with superior performance in terms of mortality (95% CI, 13.2% to 14.1%), and a 4.3% higher chance of being treated by a physician with superior performance in terms of length-of-stay (LOS) (95% CI, 3.8% to 4.7%) in comparison to non-Magnet institutions. The same associations were present in propensity score adjusted mixed effects models.

CONCLUSIONS

Using a comprehensive all-payer cohort of neurosurgical patients in New York State we identified an association of Magnet hospital recognition with superior physician performance.

Correlation of Subjective Hospital Compare Metrics With Objective Outcomes of Cranial Neurosurgical Procedures in New York State

Background

Public reporting is at the forefront of health care reform.

Objective

To investigate whether patient satisfaction as expressed in a public reporting platform correlates with objective outcomes for cranial neurosurgery patients.

Methods

We performed a cohort study involving patients undergoing cranial neurosurgery from 2009 to 2013 who were registered in the Statewide Planning and Research Cooperative System database. This cohort was merged with the corresponding data from the Centers for Medicare and Medicaid Services Hospital Compare website. The association of patient satisfaction metrics with outcomes was examined with the use of a propensity-adjusted regression model.

Results

Overall, 19 591 patients underwent cranial neurosurgery during the study. Using a propensity-adjusted multivariable regression analysis, we demonstrated that hospitals with a greater percentage of patient-assigned "high" scores had decreased mortality (OR, 0.60; 95% CI, 0.53-0.67), rate of discharge to rehabilitation (OR, 0.93; 95% CI, 0.88-0.98), length of stay (adjusted difference, -1.29; 95% CI, -1.46 to -1.13), and hospitalization charges (adjusted difference, -23%; 95% CI, -36% to -9%) after cranial neurosurgery. Similar associations were identified for hospitals with a higher percentage of patients, who would recommend these institutions to others.

Conclusion

In a Centers for Medicare and Medicaid Services Hospital Compare-Statewide Planning and Research Cooperative System merged dataset, we observed an association of higher performance in patient satisfaction measures with decreased mortality, rate of discharge to rehabilitation, hospitalization charges, and length of stay.

Association of Hospital Teaching Status with Neurosurgical Outcomes: An Instrumental Variable Analysis

BACKGROUND

The interpretation of the results of prior studies on the association of hospital teaching status with surgical outcomes is limited by selection bias. We investigated whether undergoing surgical operations in teaching hospitals is associated with improved outcomes.

METHODS

We performed a cohort study of all patients undergoing spine and cranial operations who were registered in the New York Statewide Planning and Research Cooperative System database from 2009 to 2013. We examined the association of teaching status (defined as academic affiliation for the primary analysis) with inpatient case fatality, discharge to a facility, and length of stay (LOS). An instrumental variable analysis was used to control for unmeasured confounding and to simulate the effect of a randomized trial.

RESULTS

During the study period, 186,483 patients underwent surgical operations that met the inclusion criteria. Instrumental variable analysis demonstrated that hospitalization in teaching hospitals was associated with higher rates of case fatality (adjusted difference, 25%; 95% confidence interval [CI], 4%-46%), discharge to a facility (adjusted difference, 5.7%; 95% CI, 4.5%-7.0%), and longer LOS (adjusted difference, 31.4%; 95% CI, 16.0%-46.1%) in comparison with nonteaching hospitals. The same associations were present in propensity score adjusted mixed effects models. These persisted in prespecified subgroups stratified on particular operations and for different definitions of teaching hospitals.

CONCLUSIONS

Using a comprehensive all-payer cohort of surgical patients in New York State, we identified an association of treatment in teaching hospitals with increased case fatality, rate of discharge to rehabilitation, and longer LOS. Further research into the factors contributing to superior outcomes in nonteaching institutions is warranted.