Randomized Trial of Metformin, Ivermectin, and Fluvoxamine for Covid-19.

BACKGROUND: Early treatment to prevent severe coronavirus disease 2019 (Covid-19) is an important component of the comprehensive response to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. METHODS: In this phase 3, double-blind, randomized, placebo-controlled trial, we used a 2-by-3 factorial design to test the effectiveness of three repurposed drugs - metformin, ivermectin, and fluvoxamine - in preventing serious SARS-CoV-2 infection in nonhospitalized adults who had been enrolled within 3 days after a confirmed diagnosis of infection and less than 7 days after the onset of symptoms. The patients were between the ages of 30 and 85 years, and all had either overweight or obesity. The primary composite end point was hypoxemia (≤93% oxygen saturation on home oximetry), emergency department visit, hospitalization, or death. All analyses used controls who had undergone concurrent randomization and were adjusted for SARS-CoV-2 vaccination and receipt of other trial medications. RESULTS: A total of 1431 patients underwent randomization; of these patients, 1323 were included in the primary analysis. The median age of the patients was 46 years; 56% were female (6% of whom were pregnant), and 52% had been vaccinated. The adjusted odds ratio for a primary event was 0.84 (95% confidence interval [CI], 0.66 to 1.09; P = 0.19) with metformin, 1.05 (95% CI, 0.76 to 1.45; P = 0.78) with ivermectin, and 0.94 (95% CI, 0.66 to 1.36; P = 0.75) with fluvoxamine. In prespecified secondary analyses, the adjusted odds ratio for emergency department visit, hospitalization, or death was 0.58 (95% CI, 0.35 to 0.94) with metformin, 1.39 (95% CI, 0.72 to 2.69) with ivermectin, and 1.17 (95% CI, 0.57 to 2.40) with fluvoxamine. The adjusted odds ratio for hospitalization or death was 0.47 (95% CI, 0.20 to 1.11) with metformin, 0.73 (95% CI, 0.19 to 2.77) with ivermectin, and 1.11 (95% CI, 0.33 to 3.76) with fluvoxamine. CONCLUSIONS: None of the three medications that were evaluated prevented the occurrence of hypoxemia, an emergency department visit, hospitalization, or death associated with Covid-19. (Funded by the Parsemus Foundation and others; COVID-OUT ClinicalTrials.gov number, NCT04510194.).

Favorable Antiviral Effect of Metformin on SARS-CoV-2 Viral Load in a Randomized, Placebo-Controlled Clinical Trial of COVID-19.

BACKGROUND: Metformin has antiviral activity against RNA viruses including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The mechanism appears to be suppression of protein translation via targeting the host mechanistic target of rapamycin pathway. In the COVID-OUT randomized trial for outpatient coronavirus disease 2019 (COVID-19), metformin reduced the odds of hospitalizations/death through 28 days by 58%, of emergency department visits/hospitalizations/death through 14 days by 42%, and of long COVID through 10 months by 42%. METHODS: COVID-OUT was a 2 × 3 randomized, placebo-controlled, double-blind trial that assessed metformin, fluvoxamine, and ivermectin; 999 participants self-collected anterior nasal swabs on day 1 (n = 945), day 5 (n = 871), and day 10 (n = 775). Viral load was quantified using reverse-transcription quantitative polymerase chain reaction. RESULTS: The mean SARS-CoV-2 viral load was reduced 3.6-fold with metformin relative to placebo (-0.56 log10 copies/mL; 95% confidence interval [CI], -1.05 to -.06; P = .027). Those who received metformin were less likely to have a detectable viral load than placebo at day 5 or day 10 (odds ratio [OR], 0.72; 95% CI, .55 to .94). Viral rebound, defined as a higher viral load at day 10 than day 5, was less frequent with metformin (3.28%) than placebo (5.95%; OR, 0.68; 95% CI, .36 to 1.29). The metformin effect was consistent across subgroups and increased over time. Neither ivermectin nor fluvoxamine showed effect over placebo. CONCLUSIONS: In this randomized, placebo-controlled trial of outpatient treatment of SARS-CoV-2, metformin significantly reduced SARS-CoV-2 viral load, which may explain the clinical benefits in this trial. Metformin is pleiotropic with other actions that are relevant to COVID-19 pathophysiology. CLINICAL TRIALS REGISTRATION: NCT04510194.

An intersectional framework for counterfactual fairness in risk prediction.

Along with the increasing availability of health data has come the rise of data-driven models to inform decision making and policy. These models have the potential to benefit both patients and health care providers but can also exacerbate health inequities. Existing "algorithmic fairness" methods for measuring and correcting model bias fall short of what is needed for health policy in two key ways. First, methods typically focus on a single grouping along which discrimination may occur rather than considering multiple, intersecting groups. Second, in clinical applications, risk prediction is typically used to guide treatment, creating distinct statistical issues that invalidate most existing techniques. We present novel unfairness metrics that address both challenges. We also develop a complete framework of estimation and inference tools for our metrics, including the unfairness value ("u-value"), used to determine the relative extremity of unfairness, and standard errors and confidence intervals employing an alternative to the standard bootstrap. We demonstrate application of our framework to a COVID-19 risk prediction model deployed in a major Midwestern health system.

Financial strain across 25 years and women's bladder health: a life course perspective.

BACKGROUND: A small number of cross-sectional studies have found that financial insecurity-a social determinant of health-is associated with lower urinary tract symptoms. OBJECTIVE: This study aimed to examine (1) whether women in the Coronary Artery Risk Development in Young Adult Study with higher levels of financial strain, assessed at 7 time points across 25 years beginning in 1985-1986, were more likely to report lower urinary tract symptoms and impact after the 2010-2011 financial strain assessment and (2) whether healthcare access and comorbidities mediated potential associations. STUDY DESIGN: This prospective cohort study recruited Black and White participants aged 18 to 30 years at baseline (1985-1986) from the populations of 4 US cities. The analytical sample was composed of women with complete data for analyses involving financial strain trajectories across 7 assessments (n=841) and mediation tests of data collected at 4 assessments (n=886). The outcome variable was previously developed through a cluster analysis of urinary incontinence severity, urinary incontinence impact, other lower urinary tract symptoms severity, and their impact in 2012-2013, which yielded 4 lower urinary tract symptoms and impact cluster categories: women with no symptom or very mild symptoms and no impact vs women with mild, moderate, or severe symptoms and impact. Financial strain was defined as finding it "very hard," "hard," or "somewhat hard" (vs "not very hard") to pay for the very basics, such as food, heating, and medical care. Using proportional odds logistic regression, cluster categories were regressed on the financial strain trajectory group, adjusting for age, race, education, and parity. For mediation analyses, separate financial strain variables (difficulty paying for the very basics, such as food and heating, and difficulty paying for medical care) were created by combining 1995-1996 and 2000-2001 values. Two healthcare access variables (difficulty receiving care and underutilization of care) and a single comorbidity index (smoking, physical inactivity, body mass index, hypertension, diabetes mellitus, and depressive symptoms) were created by combining 2005-2006 and 2010-2011 values. Regression analyses and structural equation modeling were used to test whether healthcare access and comorbidities mediated associations between financial strain and lower urinary tract symptoms and impact cluster categories. RESULTS: In comparison to women who were consistently not financially strained, women who were consistently strained (odds ratio, 2.10; 95% confidence interval, 1.13-3.91), shifted into being strained (odds ratio, 2.00; 95% confidence interval, 1.29-3.10), or experienced >1 shift in strain (odds ratio, 1.99; 95% confidence interval, 1.46-2.71) had roughly twice the odds of reporting greater lower urinary tract symptoms and impact. Underutilization of healthcare and comorbidities mediated the association between difficulty paying for medical care and lower urinary tract symptoms and impact. In the structural equation model, difficulty paying for medical care and underutilization of care were associated (ß=.31; P<.01), as was underutilization of care and greater lower urinary tract symptoms and impact (ß=.09; P<.01). Moreover, difficulty paying for medical care and the comorbidity index were associated (ß=.34; P<.01), as was the comorbidity index and greater lower urinary tract symptoms and impact (ß=.24; P<.01). Collectively, these mediation pathways eliminated a direct association between difficulty paying for medical care and lower urinary tract symptoms and impact. CONCLUSION: Underutilization of healthcare and comorbidities explained an association between financial strain (difficulty paying for medical care) and lower urinary tract symptoms and impact. Research is needed to confirm the findings and examine other mechanisms that may further explain the association. Accumulated evidence may inform future policies and practices.

Job strain, occupation, and bladder health among women.

OBJECTIVES: Lower urinary tract symptoms (LUTS) are common among employed women. An underexplored topic is whether characteristics of women's occupations may influence LUTS. The present study examined whether job strain and its individual components (psychological demands, decision latitude) were associated with greater LUTS and their impact and whether, compared to managerial and professional occupations, occupations characterized by manual labor, sales, service, nursing, and teaching were associated with greater LUTS and their impact. METHODS: Coronary Artery Risk Development in Young Adults cohort study data were analyzed. Job strain and occupation were assessed in 1987-88 and 1995-96. In 2012-13, LUTS and their impact were assessed. LUTS/impact category (a composite variable ranging from bladder health to mild, moderate, and severe LUTS/impact) was regressed on job strain and occupation in separate analyses, adjusting for age, race, parity, education, and financial hardship (n = 1006). RESULTS: Job strain and its individual components were not associated with LUTS/impact. In comparison to managerial and professional occupations, service occupations in 1987-88 and 1995-96 were both associated with greater odds of LUTS/impact in proportional odds logistic regression analyses. Employment as a nurse, health assistant, or health aide in 1995-96 was associated with greater odds of any LUTS/impact versus bladder health. Support positions in 1987-88 and sales positions in 1995-96 were associated with greater odds of moderate or severe LUTS/impact versus bladder health or mild LUTS/impact. CONCLUSIONS: Future research should examine characteristics of workplaces that may promote or constrain bladder health (e.g., time and autonomy to void when desired, infrastructure to void).

Characterizing the spectrum of bladder health and lower urinary tract symptoms among men: Results from the CARDIA study.

OBJECTIVES: To operationalize a new definition for bladder health, we examined the distribution and impact of lower urinary tract symptoms (LUTS), along with risk factors, among men in the Coronary Artery Risk Development in Young Adults (CARDIA) study. METHODS: LUTS were defined by American Urologic Association Symptom Index (AUASI) scores and impact on quality of life (QoL). Separate questions assessed urinary incontinence (UI) and postvoid dribbling. We performed cluster analyses using AUASI scores, with and without urine incontinence and postvoid dribbling, and impact collected in 2010-11. We performed analyses to evaluate sociodemographic and cardiovascular risk factors between clusters. RESULTS: Among CARDIA men (mean age: 50.0, SD = 3.6; range: 42-56 years) with complete LUTS data (n = 929), we identified and compared four clusters: men who reported no or very mild symptoms and no impact on well-being (bladder health, n = 696, 75%), men with moderate symptoms and moderate impact on well-being (moderate symptoms/impact, n = 84, 9%), men with high symptoms and high impact on well-being (severe symptoms/impact, n = 117, 13%), and a separate group that reported moderate symptoms and UI with a high impact on well-being (UI + moderate symptoms/severe impact, n = 32, 3%). Exploration of the groupings showed a large percentage of postvoid dribbling across groups (overall 69%). Sociodemographic and cardiovascular risk factors were not associated with symptom/impact groups. CONCLUSIONS: Bladder health clustered into four categories. A majority of middle-aged men in the community showed no or mild bladder symptoms without impact on QoL. Postvoid dribbling is pervasive but did not cluster with a specific LUTS or impact category.

Comparison of Weighting Methods to Understand Improved Outcomes Attributable to Public Health Nursing Interventions.

BACKGROUND: The complex work of public health nurses (PHNs) specifically related to mental health assessment, intervention, and outcomes makes it difficult to quantify and evaluate the improvement in client outcomes attributable to their interventions. OBJECTIVES: We examined heterogeneity across parents of infants served by PHNs receiving different interventions, compared the ability of traditional propensity scoring methods versus energy-balancing weight (EBW) techniques to adjust for the complex and stark differences in baseline characteristics among those receiving different interventions, and evaluated the causal effects of the quantity and variety of PHN interventions on client health and social outcomes. METHODS: This retrospective study of 4,109 clients used existing Omaha System data generated during the routine documentation of PHN home visit data. We estimated the effects of intervention by computing and comparing weighted averages of the outcomes within the different treatment groups using two weighting methods: (a) inverse probability of treatment (propensity score) weighting and (b) EBWs. RESULTS: Clients served by PHNs differed in baseline characteristics with clients with more signs/symptoms. Both weighting methods reduced heterogeneity in the sample. EBWs were more effective than inverse probability of treatment weighting in adjusting for multifaceted confounding and resulted in close balance of 105 baseline characteristics. Weighting the sample changed outcome patterns, especially when using EBWs. Clients who received more PHN interventions and a wider variety of them had improved knowledge, behavior, and status outcomes with no plateau over time, whereas the unweighted sample showed plateaus in outcomes over the course of home-visiting services. DISCUSSION: Causal analysis of PHN-generated data demonstrated PHN intervention effectiveness for clients with mental health signs/symptoms. EBWs are a promising tool for evaluating the true causal effect of PHN home-visiting interventions.

Impact of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Vaccination and Booster on Coronavirus Disease 2019 (COVID-19) Symptom Severity Over Time in the COVID-OUT Trial.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination has decreasing protection from acquiring any infection with emergence of new variants; however, vaccination continues to protect against progression to severe coronavirus disease 2019 (COVID-19). The impact of vaccination status on symptoms over time is less clear. METHODS: Within a randomized trial on early outpatient COVID-19 therapy testing metformin, ivermectin, and/or fluvoxamine, participants recorded symptoms daily for 14 days. Participants were given a paper symptom diary allowing them to circle the severity of 14 symptoms as none (0), mild (1), moderate (2), or severe (3). This is a secondary analysis of clinical trial data on symptom severity over time using generalized estimating equations comparing those unvaccinated, SARS-CoV-2 vaccinated with primary vaccine series only, or vaccine-boosted. RESULTS: The parent clinical trial prospectively enrolled 1323 participants, of whom 1062 (80%) prospectively recorded some daily symptom data. Of these, 480 (45%) were unvaccinated, 530 (50%) were vaccinated with primary series only, and 52 (5%) vaccine-boosted. Overall symptom severity was least for the vaccine-boosted group and most severe for unvaccinated at baseline and over the 14 days (P < .001). Individual symptoms were least severe in the vaccine-boosted group including cough, chills, fever, nausea, fatigue, myalgia, headache, and diarrhea, as well as smell and taste abnormalities. Results were consistent over Delta and Omicron variant time periods. CONCLUSIONS: SARS-CoV-2 vaccine-boosted participants had the least severe symptoms during COVID-19, which abated the quickest over time. Clinical Trial Registration. NCT04510194.

Adverse Childhood Experiences and Lower Urinary Tract Symptoms and Impact Among Women.

PURPOSE: This study utilizes CARDIA (Coronary Artery Risk Development in Young Adults) cohort study data to examine whether (1) family-based adverse childhood experiences, recalled by women aged 32 to 47, are associated with lower urinary tract symptoms and their impact, a composite variable with 4 levels (bladder health and mild, moderate, or severe lower urinary tract symptoms/impact), and (2) extensiveness of women's social networks in adulthood attenuates an association between adverse childhood experiences and lower urinary tract symptoms/impact. MATERIALS AND METHODS: In 2000-2001, frequency of adverse childhood experiences exposure was retrospectively assessed. In 2000-2001, 2005-2006, and 2010-2011, extensiveness of social networks was assessed; scores were averaged. In 2012-2013, lower urinary tract symptoms/impact data were collected. Logistic regression analyses examined whether adverse childhood experiences, extensiveness of social networks, and their interaction were associated with lower urinary tract symptoms/impact, adjusting for age, race, education, and parity (n=1,302). RESULTS: Recall of more frequent family-based adverse childhood experiences was associated with report of more lower urinary tract symptoms/impact over 10 years later (OR=1.26, 95% CI=1.07, 1.48). Social networks during adulthood appeared to attenuate the association between adverse childhood experiences and lower urinary tract symptoms/impact (OR=0.64, 95% CI=0.41, 1.02). Among women with less extensive social networks, estimated probability of experiencing moderate or severe lower urinary tract symptoms/impact vs bladder health or mild lower urinary tract symptoms/impact was 0.29 and 0.21 for those reporting an adverse childhood experiences frequency corresponding to more than "a little" vs "rarely or none of the time," respectively. Among women with more extensive social networks, estimated probabilities were 0.20 and 0.21, respectively. CONCLUSIONS: Family-based adverse childhood experiences are related to lower urinary tract symptoms/impact vs bladder health in adulthood. Additional research is needed to corroborate the potentially attenuating effect of social networks.

Persistent Racial Disparities in Deep Brain Stimulation for Parkinson's Disease.

We sought to determine whether racial and socioeconomic disparities in the utilization of deep brain stimulation (DBS) for Parkinson's disease (PD) have improved over time. We examined DBS utilization and analyzed factors associated with placement of DBS. The odds of DBS placement increased across the study period, whereas White patients with PD were 5 times more likely than Black patients to undergo DBS. Individuals, regardless of racial background, with 2 or more comorbidities were 14 times less likely to undergo DBS. Privately insured patients were 1.6 times more likely to undergo DBS. Despite increasing DBS utilization, significant disparities persist in access to DBS. ANN NEUROL 2022;92:246-254.

Comparable safety profile between neuro-oncology procedures involving stereotactic needle biopsy (SNB) followed by laser interstitial thermal therapy (LITT) and LITT alone procedures.

INTRODUCTION: Tissue diagnosis through stereotactic needle biopsy (SNB) is often needed prior to laser interstitial thermal therapy (LITT). Whether these procedures should be performed in the same surgery or in separate settings remain unclear. As a first step to address this question, we assess safety profile of procedures involving LITT alone versus SNB + LITT. METHODS: Using International Classification of Disease (ICD) codes, we queried the National Readmissions Database (NRD, 2010-2018) for malignant brain tumor patients who underwent either (1) LITT alone or (2) elective LITT in combination with SNB (SNB + LITT). Survey regression methods were utilized. Additionally, the procedural outcome of LITT or SNB + LITT performed by the senior surgeon (2014-2022) were reviewed. RESULTS: During the study period, an estimated 678 malignant brain tumor patients underwent LITT alone versus 373 patients that underwent SNB + LITT. Patients undergoing LITT and SNB + LITT exhibited statistically comparable median lengths of hospital stay (IQR; LITT = 2 day [1, 3]; SNB + LITT = 1 day [1, 3]; p = 0.405) and likelihood of routine discharge (LITT = 73.5%; SNB + LITT = 81.1%; p = 0.068). The odds of 30-day medical or neurological readmissions were comparable between LITT and SNB + LITT treated patients (all p ≥ 0.793). In the single surgeon experience of 218 procedures performed over an eight year period (2014-2022), the complications (LITT = 3.9%; SNB + LITT = 2.6%, p = 0.709), discharge within 48 h (LITT = 84.5%; SNB + LITT = 87.8%; p = 0.556), routine discharge (LITT = 91.3%; SNB + LITT = 93.9%; p = 0.604), and unplanned 30-day readmission (LITT = 3.9%; SNB + LITT = 1.7%; p = 0.423) were similarly comparable between LITT and SNB + LITT. CONCLUSION: The length of hospital stay, the likelihood of routine discharge, and 30-day readmission for malignant brain tumor patients who underwent LITT and SNB + LITT were comparable.

Doubly structured sparsity for grouped multivariate responses with application to functional outcome score modeling.

This work is motivated by the need to accurately model a vector of responses related to pediatric functional status using administrative health data from inpatient rehabilitation visits. The components of the responses have known and structured interrelationships. To make use of these relationships in modeling, we develop a two-pronged regularization approach to borrow information across the responses. The first component of our approach encourages joint selection of the effects of each variable across possibly overlapping groups of related responses and the second component encourages shrinkage of effects towards each other for related responses. As the responses in our motivating study are not normally-distributed, our approach does not rely on an assumption of multivariate normality of the responses. We show that with an adaptive version of our penalty, our approach results in the same asymptotic distribution of estimates as if we had known in advance which variables have non-zero effects and which variables have the same effects across some outcomes. We demonstrate the performance of our method in extensive numerical studies and in an application in the prediction of functional status of pediatric patients using administrative health data in a population of children with neurological injury or illness at a large children's hospital.

A method for comparing multiple imputation techniques: A case study on the U.S. national COVID cohort collaborative.

Healthcare datasets obtained from Electronic Health Records have proven to be extremely useful for assessing associations between patients' predictors and outcomes of interest. However, these datasets often suffer from missing values in a high proportion of cases, whose removal may introduce severe bias. Several multiple imputation algorithms have been proposed to attempt to recover the missing information under an assumed missingness mechanism. Each algorithm presents strengths and weaknesses, and there is currently no consensus on which multiple imputation algorithm works best in a given scenario. Furthermore, the selection of each algorithm's parameters and data-related modeling choices are also both crucial and challenging. In this paper we propose a novel framework to numerically evaluate strategies for handling missing data in the context of statistical analysis, with a particular focus on multiple imputation techniques. We demonstrate the feasibility of our approach on a large cohort of type-2 diabetes patients provided by the National COVID Cohort Collaborative (N3C) Enclave, where we explored the influence of various patient characteristics on outcomes related to COVID-19. Our analysis included classic multiple imputation techniques as well as simple complete-case Inverse Probability Weighted models. Extensive experiments show that our approach can effectively highlight the most promising and performant missing-data handling strategy for our case study. Moreover, our methodology allowed a better understanding of the behavior of the different models and of how it changed as we modified their parameters. Our method is general and can be applied to different research fields and on datasets containing heterogeneous types.

Using Billing Codes to Create a Pediatric Functional Status e-Score for Children Receiving Inpatient Rehabilitation.

OBJECTIVE: Provide proof-of-concept for development of a Pediatric Functional Status eScore (PFSeS). Demonstrate that expert clinicians rank billing codes as relevant to patient functional status and identify the domains that codes inform in a way that reliably matches analytical modeling. DESIGN: Retrospective chart review, modified Delphi, and nominal group techniques. SETTING: Large, urban, quaternary care children's hospital in the Midwestern United States. PARTICIPANTS: Data from 1955 unique patients and 2029 hospital admissions (2000-2020); 12 expert consultants representing the continuum of rehabilitation care reviewed 2893 codes (procedural, diagnostic, pharmaceutical, durable medical equipment). MAIN OUTCOME MEASURES: Consensus voting to determine whether codes were associated with functional status at discharge and, if so, what domains they informed (self-care, mobility, cognition/ communication). RESULTS: The top 250 and 500 codes identified by statistical modeling were mostly composed of codes selected by the consultant panel (78%-80% of the top 250 and 71%-78% of the top 500). The results provide evidence that clinical experts' selection of functionally meaningful codes corresponds with codes selected by statistical modeling as most strongly associated with WeeFIM domain scores. The top 5 codes most strongly related to functional independence ratings from a domain-specific assessment indicate clinically sensible relationships, further supporting the use of billing data in modeling to create a PFSeS. CONCLUSIONS: Development of a PFSeS that is predicated on billing data would improve researchers' ability to assess the functional status of children who receive inpatient rehabilitation care for a neurologic injury or illness. An expert clinician panel, representing the spectrum of medical and rehabilitative care, indicated that proposed statistical modeling identifies relevant codes mapped to 3 important domains: self-care, mobility, and cognition/communication.

Public Health Nurse Tailored Home Visiting and Parenting Behavior for Families at Risk for Referral to Child Welfare Services, Colorado: 2018-2019.

Objectives. To examine public health nurse (PHN) intervention tailoring through the Colorado Nurse Support Program (NSP). Our 2 specific aims were to describe the NSP program and its outcomes and to determine the effects of modifying interventions on short- and long-term outcomes among NSP clients. Methods. In our retrospective causal investigation of 150 families in Colorado in 2018-2019, intervention effects were modeled via longitudinal modified treatment policy analyses. Results. Families served by PHNs improved in terms of knowledge, behavior, and status outcomes after receiving multidimensional, tailored home visiting interventions. Case management interventions provided in the first month of PHN home visits had lasting effects on behavior outcomes, and 2 additional case management interventions in the first month were estimated to have even more of an impact. Conclusions. Modern causal inference methods and real-world PHN data revealed a nuanced, fine-grained understanding of the real impact of tailored PHN interventions. Public Health Implications PHN programs such as the NSP and use of the Omaha System should be supported and extended to advance evaluations of intervention effectiveness and knowledge discovery and improve population health. (Am J Public Health. 2022;112(S3):S306-S313. https://doi.org/10.2105/AJPH.2022.306792).

Readmission risk of malignant brain tumor patients undergoing laser interstitial thermal therapy (LITT) and stereotactic needle biopsy (SNB): a covariate balancing weights analysis of the National Readmissions Database (NRD).

PURPOSE: Despite procedural similarities between laser interstitial thermal therapy (LITT) and stereotactic needle biopsy (SNB), LITT induces delayed, pro-inflammatory responses not associated with SNB that may increase the risk of readmission within 30- or 90- days. Here, we explore this hypothesis. METHODS: We queried the National Readmissions Database (NRD, 2010-18) for malignant brain tumor patients who underwent elective LITT or SNB using International Classification of Diseases codes. Readmissions were defined as non-elective inpatient hospitalizations. Survey regression methods and a weighted analysis were utilized to adjust for demographic and clinical differences between LITT and SNB cohorts. RESULTS: During the study period, an estimated 685 malignant brain patients underwent elective LITT and 15,177 underwent elective SNB. Patients undergoing LITT and SNB exhibited comparable median lengths of hospital stay [IQR; LITT = 2 (1, 3); SNB = 1 (1, 2); p = 0.820]. Likelihood of routine discharge was not significantly different between the two procedures (p = 0.263). No significant differences were observed in the odds of 30- or 90-day unplanned readmission between the LITT and SNB cohorts after multivariable adjustment (all p ≥ 0.177). The covariate balancing weighted analysis confirmed comparable 30 or 90-day readmission risk between LITT and SNB treated patients (all p ≥ 0.201). CONCLUSION: The likelihood of 30- and 90-day readmission for malignant brain tumor patients who underwent LITT or SNB are comparable, supporting the safety profile of LITT as therapy for malignant brain cancers.

Sufficient dimension reduction for populations with structured heterogeneity.

A key challenge in building effective regression models for large and diverse populations is accounting for patient heterogeneity. An example of such heterogeneity is in health system risk modeling efforts where different combinations of comorbidities fundamentally alter the relationship between covariates and health outcomes. Accounting for heterogeneity arising combinations of factors can yield more accurate and interpretable regression models. Yet, in the presence of high-dimensional covariates, accounting for this type of heterogeneity can exacerbate estimation difficulties even with large sample sizes. To handle these issues, we propose a flexible and interpretable risk modeling approach based on semiparametric sufficient dimension reduction. The approach accounts for patient heterogeneity, borrows strength in estimation across related subpopulations to improve both estimation efficiency and interpretability, and can serve as a useful exploratory tool or as a powerful predictive model. In simulated examples, we show that our approach often improves estimation performance in the presence of heterogeneity and is quite robust to deviations from its key underlying assumptions. We demonstrate our approach in an analysis of hospital admission risk for a large health system and demonstrate its predictive power when tested on further follow-up data.

Impactability Modeling for Reducing Medicare Accountable Care Organization Payments and Hospital Events in High-Need High-Cost Patients: Longitudinal Cohort Study.

BACKGROUND: Impactability modeling promises to help solve the nationwide crisis in caring for high-need high-cost patients by matching specific case management programs with patients using a "benefit" or "impactability" score, but there are limitations in tailoring each model to a specific program and population. OBJECTIVE: We evaluated the impact on Medicare accountable care organization savings from developing a benefit score for patients enrolled in a historic case management program, prospectively implementing the score, and evaluating the results in a new case management program. METHODS: We conducted a longitudinal cohort study of 76,140 patients in a Medicare accountable care organization with multiple before-and-after measures of the outcome, using linked electronic health records and Medicare claims data from 2012 to 2019. There were 489 patients in the historic case management program, with 1550 matched comparison patients, and 830 patients in the new program, with 2368 matched comparison patients. The historic program targeted high-risk patients and assigned a centrally located registered nurse and social worker to each patient. The new program targeted high- and moderate-risk patients and assigned a nurse physically located in a primary care clinic. Our primary outcomes were any unplanned hospital events (admissions, observation stays, and emergency department visits), count of event-days, and Medicare payments. RESULTS: In the historic program, as expected, high-benefit patients enrolled in case management had fewer events, fewer event-days, and an average US $1.15 million reduction in Medicare payments per 100 patients over the subsequent year when compared with the findings in matched comparison patients. For the new program, high-benefit high-risk patients enrolled in case management had fewer events, while high-benefit moderate-risk patients enrolled in case management did not differ from matched comparison patients. CONCLUSIONS: Although there was evidence that a benefit score could be extended to a new case management program for similar (ie, high-risk) patients, there was no evidence that it could be extended to a moderate-risk population. Extending a score to a new program and population should include evaluation of program outcomes within key subgroups. With increased attention on value-based care, policy makers and measure developers should consider ways to incorporate impactability modeling into program design and evaluation.

Pattern of technology diffusion in the adoption of stereotactic laser interstitial thermal therapy (LITT) in neuro-oncology.

PURPOSE: Understanding factors that influence technology diffusion is central to clinical translation of novel therapies. We characterized the pattern of adoption for laser interstitial thermal therapy (LITT), also known as stereotactic laser ablation (SLA), in neuro-oncology using the National Inpatient Sample (NIS) database. METHODS: We identified patients age ≥ 18 in the NIS (2012-2018) with a diagnosis of primary or metastatic brain tumor that underwent LITT or craniotomy. We compared characteristics and outcomes for patients that underwent these procedures. RESULTS: LITT utilization increased ~ 400% relative to craniotomy during the study period. Despite this increase, the total number of LITT procedures performed for brain tumor was < 1% of craniotomy. After adjusting for this time trend, LITT patients were less likely to have > 2 comorbidities (OR 0.64, CI95 0.51-0.79) or to be older (OR 0.92, CI95 0.86-0.99) and more likely to be female (OR 1.35, CI95 1.08-1.69), Caucasian compared to Black (OR 1.94, CI95 1.12-3.36), and covered by private insurance compared to Medicare or Medicaid (OR 1.38, CI95 1.09-1.74). LITT hospital stays were 50% shorter than craniotomy (IRR 0.52, CI95 0.45-0.61). However, charges related to the procedures were comparable between LITT and craniotomy ($1397 greater for LITT, CI95 $-5790 to $8584). CONCLUSION: For neuro-oncology indications, LITT utilization increased ~ 400% relative to craniotomy. Relative to craniotomy-treated patients, LITT-treated patients were likelier to be young, female, non-Black race, covered by private insurance, or with < 2 comorbidities. While the total hospital charges were comparable, LITT was associated with a shorter hospitalization relative to craniotomy.

Instrumental variable based estimation under the semiparametric accelerated failure time model.

Randomized controlled trials are the gold standard for estimating causal effects of treatments or interventions, but in many cases are too costly, too difficult, or even unethical to conduct. Hence, many pressing medical questions can only be investigated using observational studies. However, direct statistical modeling of observational data can result in biased estimates of treatment effects due to unmeasured confounding. In certain cases, instrumental variable based techniques can be used to remove such biases. These techniques are indeed widely studied and used in econometrics under parametric outcome models, however limited works have focused on the utilization of instrumental variables in survival analysis, where semiparametric models are often necessary. The additional challenge in analyzing survival data is the presence of censoring. In this paper, we introduce an instrumental variable method that relaxes the strong assumptions of previous works and provides consistent estimation of the causal effect of a treatment on a survival outcome. We demonstrate the efficacy of our method in various simulated settings and an analysis of Medicare enrollment data comparing two prevalent surgical procedures for abdominal aortic aneurysm from an observational study.