Prevention of post-operative adhesions: Model development and pilot outcomes of human placental stem cell-based interventions.

BACKGROUND: Abdominal adhesions are the most common surgical complication and without reliable prophylactics. This study presents a novel rat model for abdominal adhesions and reports pilot results of human placental stem cell (hPSC)-based therapies. METHODS: Forty-four (n = 44) male Sprague-Dawley rats (250-350 g) were used in the experiment. Of these, thirty-eight (n = 38) were included in a preliminary data set to determine a minimum treatment effect. Adhesions were created in a reproducible model to the abdominal wall and between organs. Experimental groups included the control group (Model No Treatment, MNT), Plasmalyte A (Media Alone, MA, 10 mL), hPSC (5 × 106 cells/10 mL Plasmalyte A), hPSC-CM (hPSC secretome, conditioned media) in 10 mL Plasmalyte A, Seprafilm™ (Baxter, Deerfield, IL), and sham animals (laparotomy only). Treatments were inserted intraperitoneally (IP) and the study period was 14 days post-operation. Results are reported as the difference between means of an index statistic (AIS, Animal Index Score) and compared by ANOVA with pairwise comparison. RESULTS: The overall mean AIS was 23 (SD 6.16) for the MNT group with an average of 75% of ischemic buttons involved in abdominal adhesions. Treatment groups MA (mean overall AIS 17.33 SD 6.4), hPSC (mean overall AIS 13.86 SD 5.01), hPSC-CM (mean overall AIS 13.13 SD 6.15), and Seprafilm (mean overall AIS 13.43 SD 9.11) generated effect sizes of 5.67, 9.14, 9.87, and 9.57 decrease in mean overall AIS, respectively, versus the MNT. DISCUSSION: The presented rat model and scoring system represent the clinical adhesion disease process. hPSC-based interventions significantly reduce abdominal adhesions in this pilot dataset.

Estimation of opioid misuse prevalence in New York State counties, 2007-2018. A Bayesian spatio-temporal abundance model approach.

An important challenge to addressing the opioid overdose crisis is the lack of information on the size of the population of people who misuse opioids (PWMO) in local areas. This estimate is needed for better resource allocation, estimation of treatment and overdose outcome rates using appropriate denominators (i.e., the population at risk), and proper evaluation of intervention effects. In this study, we used a Bayesian hierarchical spatio-temporal integrated abundance model that integrates multiple types of county-level surveillance outcome data, state-level information on opioid misuse, and covariates to estimate the latent (hidden) counts and prevalence of PWMO across New York State counties (2007-2018). The model assumes that each opioid-related outcome reflects a partial count of the number of PWMO, and leverages these multiple sources of data to circumvent limitations of parameter estimation associated with other types of abundance models. Model estimates showed a reduction in the prevalence of PWMO during the study period, with important spatial and temporal variability. The model also provided county-level estimates of rates of treatment and opioid overdoses using the PWMO as denominators. This modeling approach can identify the size of hidden populations to guide public health efforts to confront the opioid overdose crisis across local areas.

Subjective Oral Dryness following Hematopoietic Cell Transplantation: A Report from the Orastem Study.

Xerostomia, or subjective oral dryness, is a serious complaint after hematopoietic cell transplantation (HCT). Xerostomia is rated as one of the most bothersome symptoms by HCT recipients, negatively affecting quality of life. This substudy of the Orastem study, a prospective longitudinal, international, observational, multicenter study, aimed to describe the prevalence and severity of xerostomia following HCT. Furthermore, the effect of the conditioning regimen, type of transplantation, and oral mucosal changes related to chronic graft-versus-host disease (cGVHD) in the development of xerostomia were studied. All HCT recipients rated xerostomia on a scale of 0 to 10 before the conditioning regimen, several times early post-HCT, and at 3 months post-HCT, and only allogeneic HCT recipients also rated xerostomia at 6 and 12 months post-HCT. In addition, stimulated whole mouth saliva was collected several times. Linear regression models and longitudinal mixed-effects models were created to investigate the influence of risk indicators on xerostomia. A total of 99 autologous and 163 allogeneic HCT recipients were included from 6 study sites in Sweden, Canada, the Netherlands, and the United States. The prevalence of xerostomia was 40% before the conditioning regimen, 87% early post-HCT, and 64% at 3 months post-HCT. Complaints after autologous HCT were transient in nature, while the severity of xerostomia in allogeneic HCT recipients remained elevated at 12 months post-HCT. Compared to autologous HCT recipients, allogeneic HCT recipients experienced 1.0 point more xerostomia (95% confidence interval [CI], .1 to 2.0) early post-HCT and 1.7 points more (95% CI, .4 to 3.0) at 3 months post-HCT. Allogeneic HCT recipients receiving a high-intensity conditioning regimen experienced more xerostomia compared to those receiving a nonmyeloablative or reduced-intensity conditioning regimen. The difference was 2.0 points (95% CI, 1.1 to 2.9) early post-HCT, 1.8 points (95% CI, .3 to 3.3) after 3 months, and 1.7 points (95% CI, .0 to 3.3) after 12 months. Total body irradiation as part of the conditioning regimen and oral mucosal changes related to cGVHD did not significantly influence the severity of xerostomia. Conditioning regimen intensity was a significant risk indicator in the development of xerostomia, whereas total body irradiation was not. Allogeneic HCT recipients experienced more xerostomia than autologous HCT recipients, a difference that cannot be explained by a reduction in stimulated salivary flow rate or the development of oral mucosal changes related to cGVHD.

Lenalidomide in the treatment of anti-myelin-associated glycoprotein neuropathy: A phase 1 study to identify the maximum tolerated dose.

BACKGROUND: Anti-myelin-associated glycoprotein (MAG) neuropathy is a debilitating demyelinating polyneuropathy with no approved therapies. Our primary objective was to ascertain lenalidomide safety and maximum tolerated dose (MTD) in anti-MAG neuropathy. METHODS: This phase 1b, open-label, single-arm, dose-finding trial was conducted from 2019 through 2022. The original design included a dose-escalation/extension phase followed by a dose-expansion phase. Three doses of lenalidomide were evaluated: 10, 15, and 25 mg. The main outcome was the MTD. RESULTS: Eleven patients enrolled (10 men), with a mean age of 67.6 years (SD = 6.18, range 58-77 years) and mean disease duration of 8.5 years (SD = 10.9, range 1-40 years). The study terminated early due to higher-than-expected non-dose-limiting toxicity venous thromboembolism (VTE) events. The calculated MTD was 25 mg (posterior mean of toxicity probability was 0.01 with a 95% credible interval of 0.00, 0.06), but a recommended phase 2 dose of 15 mg was advised. For secondary exploratory outcomes, only EQ-5D (-0.95, 95% CI -1.81 to -0.09) and total IgM (-162 mg/dL, 95% CI -298 to -26) showed signs of improvement by month 12. CONCLUSIONS: Lenalidomide was associated with higher-than-expected VTE events in anti-MAG neuropathy patients, despite a calculated MTD of 25 mg. A recommended phase 2 dose of 15 mg was advised. Lenalidomide did not improve disability or impairment at 12 months, although this study was not powered for efficacy. The risks of long term lenalidomide may outweigh benefit for patients with anti-MAG neuropathy. Any future efficacy study should address VTE risk, as current myeloma guidelines appear inadequate. TRIAL REGISTRATION: Lenalidomide in Anti-MAG Neuropathy: Phase 1b Study, ClinicalTrials.gov Identifier: NCT03701711, https://clinicaltrials.gov/ct2/show/NCT03701711. First submitted October 10, 2018. First patient enrolled in January 2019.

Describing the monthly variability of hospital-onset Clostridioides difficile during early coronavirus disease 2019 (COVID-19) using electronic health record data.

OBJECTIVE: To assess the relative risk of hospital-onset Clostridioides difficile (HO-CDI) during each month of the early coronavirus disease 2019 (COVID-19) pandemic and to compare it with historical expectation based on patient characteristics. DESIGN: This study used a retrospective cohort design. We collected secondary data from the institution's electronic health record (EHR). SETTING: The Ohio State University Wexner Medical Center, Ohio, a large tertiary healthcare system in the Midwest. PATIENTS OR PARTICIPANTS: All adult patients admitted to the inpatient setting between January 2018 and May 2021 were eligible for the study. Prisoners, children, individuals presenting with Clostridioides difficile on admission, and patients with <4 days of inpatient stay were excluded from the study. RESULTS: After controlling for patient characteristics, the observed numbers of HO-CDI cases were not significantly different than expected. However, during 3 months of the pandemic period, the observed numbers of cases were significantly different from what would be expected based on patient characteristics. Of these 3 months, 2 months had more cases than expected and 1 month had fewer. CONCLUSIONS: Variations in HO-CDI incidence seemed to trend with COVID-19 incidence but were not fully explained by our case mix. Other factors contributing to the variability in HO-CDI incidence beyond listed patient characteristics need to be explored.

Exploring Individual and Contextual Factors Associated With Sexual Risk and Substance Use Among Underserved GBQMSM and Transgender and Nonbinary Persons in South Central Appalachia.

Gay, bisexual, queer, and other men who have sex with men (GBQMSM) and transgender and nonbinary persons are at elevated risk for HIV, sexually transmitted infections (STIs), and hepatitis C (HCV); in Appalachia, these communities experience more disease burden. However, little is known about the factors influencing risk. Sixteen semistructured in-depth interviews were conducted examining factors influencing prevention and care. Data were analyzed using constant comparison methodology. Fifteen themes emerged within four domains: social environment (e.g., microaggressions across gender, sexual orientation, and racial identities), substance use (e.g., high prevalence, use as coping mechanism), sexual health (e.g., misinformation and denial of risk for HIV and STIs), and access to health care (e.g., cost and transportation barriers, lack of local respectful care). Findings highlighted salient barriers and assets influencing prevention and care and suggest that multilevel interventions are needed to improve access to and use of HIV, STI, and HCV prevention and care services.

A spatio-temporal hierarchical model to account for temporal misalignment in American Community Survey explanatory variables.

The American Community Survey (ACS) is one of the most vital public sources for demographic and socioeconomic characteristics of communities in the United States and is administered by the U.S. Census Bureau every year. The ACS publishes 5-year estimates of community characteristics for all geographical areas and 1-year estimates for areas with population of at least 65,000. Many epidemiological and public health studies use 5-year ACS estimates as explanatory variables in models. However, doing so ignores the uncertainty and averages over variability during the time-period which may lead to biased estimates of covariate effects of interest. In this paper, we propose a Bayesian hierarchical model that accounts for the uncertainty and disentangles the temporal misalignment in the ACS multi-year time-period estimates. We show via simulation that our proposed model more accurately recovers covariate effects compared to models that ignore the temporal misalignment. Lastly, we implement our proposed model to quantify the relationship between yearly, county-level characteristics and the prevalence of frequent mental distress for counties in North Carolina from 2014 to 2018.

An integrated abundance model for estimating county-level prevalence of opioid misuse in Ohio.

Opioid misuse is a national epidemic and a significant drug related threat to the United States. While the scale of the problem is undeniable, estimates of the local prevalence of opioid misuse are lacking, despite their importance to policy-making and resource allocation. This is due, in part, to the challenge of directly measuring opioid misuse at a local level. In this paper, we develop a Bayesian hierarchical spatio-temporal abundance model that integrates indirect county-level data on opioid-related outcomes with state-level survey estimates on prevalence of opioid misuse to estimate the latent county-level prevalence and counts of people who misuse opioids. A simulation study shows that our integrated model accurately recovers the latent counts and prevalence. We apply our model to county-level surveillance data on opioid overdose deaths and treatment admissions from the state of Ohio. Our proposed framework can be applied to other applications of small area estimation for hard to reach populations, which is a common occurrence with many health conditions such as those related to illicit behaviors.

A Descriptive Study on Opioid Misuse Prevalence and Office-Based Buprenorphine Access in Ohio Prior to the Removal of the Drug Addiction Treatment Act of 2000 Waiver.

Background Medications for the treatment of opioid use disorder (MOUD) are effective evidence-based strategies to reduce opioid overdose deaths. Strategies to optimize MOUD availability and uptake are needed. Objective We aim to describe the spatial relationship between the estimated prevalence of opioid misuse and office-based buprenorphine access in the state of Ohio prior to the removal of the Drug Addiction Treatment Act of 2000 (DATA 2000) waiver requirement. Methods We conducted a descriptive ecological study of county-level (N=88) opioid misuse prevalence and office-based buprenorphine prescribing access in Ohio in 2018. Counties were categorized into urban (with and without a major metropolitan area) and rural. The county-level prevalence estimates of opioid misuse per 100,000 were derived from integrated abundance modeling. Utilizing data from the Ohio Department of Mental Health and Addiction Services, as well as the state's Physician Drug Monitoring Program (PDMP), buprenorphine access per 100,000 was estimated by the number of patients in each county that could be served by office-based buprenorphine (prescribing capacity) and the number of patients served by office-based buprenorphine (prescribing frequency) for opioid use disorder. The ratios of opioid misuse prevalence to both prescribing capacity and frequency were calculated by county and mapped. Results Less than half of the 1,828 waivered providers in the state of Ohio in 2018 were prescribing buprenorphine, and 25% of counties had no buprenorphine access. The median estimated opioid misuse prevalence and buprenorphine prescribing capacity per 100,000 were highest in urban counties, particularly those with a major metropolitan area. Although the median estimated opioid misuse prevalence was lower in rural counties, all counties in the highest quartile of estimated misuse prevalence were rural. In addition, the median buprenorphine prescribing frequency was highest in rural counties. While the ratio of opioid misuse prevalence to buprenorphine prescribing capacity was lowest in urban counties, the ratio of opioid misuse prevalence to buprenorphine prescribing frequency was lowest in rural counties. Opioid misuse prevalence and buprenorphine prescribing frequency demonstrated similar spatial patterns, with highest levels in the southern and eastern portions of the state, while office-based buprenorphine prescribing capacity did not. Conclusion Urban counties had higher buprenorphine capacity relative to their burden of opioid misuse; however, access was limited by buprenorphine prescribing frequency. In contrast, in rural counties, a minimal gap was evident between prescribing capacity and frequency, suggesting that buprenorphine prescribing capacity was the major factor limiting access. While the recent deregulation of buprenorphine prescribing should help improve buprenorphine access, future research should investigate whether deregulation similarly impacts buprenorphine prescribing capacity and buprenorphine prescribing frequency.

Geographic Variation in Operative Management of Adhesive Small Bowel Obstruction.

INTRODUCTION: Variation in surgical management exists nationally. We hypothesize that geographic variation exists in adhesive small bowel obstruction (aSBO) management. MATERIALS AND METHODS: A retrospective analysis of a national commercial insurance claims database (MarketScan) sample (2017-2019) was performed in adults with hospital admission due to aSBO. Geographic variation in rates of surgical intervention for aSBO was evaluated by state and compared to a risk-adjusted national baseline using a Bayesian spatial rates Poisson regression model. For individual-level analysis, patients were identified in 2018, with 365-d look back and follow-up periods. Logistic regression was performed for individual-level predictors of operative intervention for aSBO. RESULTS: Two thousand one hundred forty-five patients were included. State-level analysis revealed rates of operative intervention for aSBO were significantly higher in Missouri and lower in Florida. On individual-level analysis, age (P < 0.01) and male sex (P < 0.03) but not comorbidity profile or prior aSBO, were negatively associated with undergoing operative management for aSBO. Patients presenting in 2018 with a history of admission for aSBO the year prior experienced a five-fold increase in odds of representation (odds ratio: 5.4, 95% confidence interval: 3.1-9.6) in 2019. Patients who received an operation for aSBO in 2018 reduced the odds of readmission in the next year by 77% (odds ratio: 0.23, 95% confidence interval: 0.1-0.5). The volume of operations performed within a state did not influence readmission. CONCLUSIONS: Surgical management of aSBO varies across the continental USA. Operative intervention is associated with decreased rates of representation in the following year. These data highlight a critical need for standardized guidelines for emergency general surgery patients.

Childhood environment early life stress, caregiver warmth, and associations with the cortisol diurnal curve in adulthood: The coronary artery risk development in young adults (CARDIA) study.

BACKGROUND: Early life stress (ELS) is associated with increased morbidity and mortality across the lifecourse. Studies observing a relationship between ELS and stress physiology (cortisol), may help explain the connection to poor health outcomes, but have been limited by cortisol measures used. PURPOSE: We examined the association between ELS measured by a Risky Family (RF) environment questionnaire, and adult diurnal cortisol profile inclusive of multiple cortisol measures. METHODS: RF and cortisol were collected from Coronary Artery Risk Development in Young Adults Study participants at follow-up (Year 15). Complete case (n = 672) data were included in multi-variable regression analyses with log transformed cortisol measures (outcomes) including wake-up cortisol, cortisol awakening response [CAR], AUC and five other cortisol diurnal curve measures. RESULTS: Participants were age 39.9 + /- 3.7 years and 51.6% Black. For every 1 unit increase in RF, there was a 1.4% greater wake-up cortisol and flatter CAR after adjustment for age, sex, income, and smoking (B=0.014, p = 0.023; B=-0.014, p = 0.028, respectively). Each unit increase in caregiver warmth/affection was associated with a 6.9% higher (steeper) CAR (B=0.069, p = 0.03). Results remained significant after adjusting for other covariates except social support in adulthood. An interaction between child abuse and caregiver warmth was nearly significant (p = 0.068), such that for those with exposure to the greatest caregiver warmth and lowest child abuse, CAR was steepest CONCLUSIONS: We demonstrate that ELS is associated with altered cortisol regulation in adulthood. However, further research is needed to assess how healthy relationships throughout the life course may modulate cortisol regulation in adulthood.

Association Between Social Determinants of Health and Glycemic Control Among African American People with Type 2 diabetes: The Jackson Heart Study.

BACKGROUND: Social determinants of health have a significant impact on health outcomes. However, the complexity and interaction of multiple factors influencing glycemic control remain understudied. PURPOSE: This study examined associations of socioeconomic position (income, education, and occupation), environmental (physical activity facilities, neighborhood social cohesion, neighborhood problem, and violence), behavioral (physical activity, nutrition, and smoking), and psychological factors (depressive symptoms, stress, and discrimination) with glycemic control (hemoglobin A1c [A1c]) using the World Health Organization Social Determinants of Health framework in African American adults with type 2 diabetes. METHODS: A secondary data analysis was conducted using a longitudinal cohort of 1,240 African American adults with type 2 diabetes who participated in the community-based Jackson Heart Study. Socioeconomic position, environmental, behavioral, and psychological factors were measured using validated instruments in the Jackson Heart Study. Longitudinal structural equation modeling was used with glycemic control (A1c) collected over time (Exams 1-3) as the study outcome. RESULTS: Our study presents the complex interplay of socioeconomic determinants of health and glycemic control over time. Higher socioeconomic position (higher income, higher level of education, and professional occupation) was directly associated with improvement in glycemic control over time. An association of socioeconomic position on glycemic control mediated through health behavior factors was also observed. CONCLUSIONS: In this analysis, socioeconomic position components were determinants of glycemic control in African American adults with type 2 diabetes. Future studies aimed at reducing health disparities and achieving equality of outcomes in this population will benefit from embedding socioeconomic position components into their design.

Examining the Drivers of Racial/Ethnic Disparities in Non-Adherence to Antihypertensive Medications and Mortality Due to Heart Disease and Stroke: A County-Level Analysis.

Background: Prior research has identified disparities in anti-hypertensive medication (AHM) non-adherence between Black/African Americans (BAAs) and non-Hispanic Whites (nHWs) but the role of determinants of health in these gaps is unclear. Non-adherence to AHM may be associated with increased mortality (due to heart disease and stroke) and the extent to which such associations are modified by contextual determinants of health may inform future interventions. Methods: We linked the Centers for Disease Control and Prevention (CDC) Atlas of Heart Disease and Stroke (2014-2016) and the 2016 County Health Ranking (CHR) dataset to investigate the associations between AHM non-adherence, mortality, and determinants of health. A proportion of days covered (PDC) with AHM < 80%, was considered as non-adherence. We computed the prevalence rate ratio (PRR)-the ratio of the prevalence among BAAs to that among nHWs-as an index of BAA-nHW disparity. Hierarchical linear models (HLM) were used to assess the role of four pre-defined determinants of health domains-health behaviors, clinical care, social and economic and physical environment-as contributors to BAA-nHW disparities in AHM non-adherence. A Bayesian paradigm framework was used to quantify the associations between AHM non-adherence and mortality (heart disease and stroke) and to assess whether the determinants of health factors moderated these associations. Results: Overall, BAAs were significantly more likely to be non-adherent: PRR = 1.37, 95% Confidence Interval (CI):1.36, 1.37. The four county-level constructs of determinants of health accounted for 24% of the BAA-nHW variation in AHM non-adherence. The clinical care (ß = -0.21, p < 0.001) and social and economic (ß = -0.11, p < 0.01) domains were significantly inversely associated with the observed BAA-nHW disparity. AHM non-adherence was associated with both heart disease and stroke mortality among both BAAs and nHWs. We observed that the determinants of health, specifically clinical care and physical environment domains, moderated the effects of AHM non-adherence on heart disease mortality among BAAs but not among nHWs. For the AHM non-adherence-stroke mortality association, the determinants of health did not moderate this association among BAAs; the social and economic domain did moderate this association among nHWs. Conclusions: The socioeconomic, clinical care and physical environmental attributes of the places that patients live are significant contributors to BAA-nHW disparities in AHM non-adherence and mortality due to heart diseases and stroke.

A MULTIVARIATE SPATIOTEMPORAL CHANGE-POINT MODEL OF OPIOID OVERDOSE DEATHS IN OHIO.

Ohio is one of the states most impacted by the opioid epidemic and experienced the second highest age-adjusted fatal drug overdose rate in 2017. Initially it was believed prescription opioids were driving the opioid crisis in Ohio. However, as the epidemic evolved, opioid overdose deaths due to fentanyl have drastically increased. In this work we develop a Bayesian multivariate spatiotemporal model for Ohio county overdose death rates from 2007 to 2018 due to different types of opioids. The log-odds are assumed to follow a spatially varying change point regression model. By assuming the regression coefficients are a multivariate conditional autoregressive process, we capture spatial dependence within each drug type and also dependence across drug types. The proposed model allows us to not only study spatiotemporal trends in overdose death rates but also to detect county-level shifts in these trends over time for various types of opioids.

The Relationship Between Hepatitis C Virus Rates and Office-Based Buprenorphine Access in Ohio.

BACKGROUND: The United States is experiencing an epidemic of hepatitis C virus (HCV) infections due to injection drug use, primarily of opioids and predominantly in rural areas. Buprenorphine, a medication for opioid use disorder, may indirectly prevent HCV transmission. We assessed the relationship of HCV rates and office-based buprenorphine prescribing in Ohio. METHODS: We conducted an ecological study of the county-level (n = 88) relationship between HCV case rates and office-based buprenorphine prescribing in Ohio. We fit adjusted negative binomial models between the county-level acute and total HCV incidence rates during 2013-2017 and 1) the number of patients in each county that could be served by office-based buprenorphine (prescribing capacity) and 2) the number served by office-based buprenorphine (prescribing frequency) from January-March, 2018. RESULTS: For each 10% increase in acute HCV rate, office-based buprenorphine prescribing capacity differed by 1% (95% CI: -1%, 3%). For each 10% increase in total HCV rate, office-based buprenorphine prescribing capacity was 12% (95% CI: 7%, 17%) higher. For each 10% increase in acute HCV rate, office-based buprenorphine prescribing frequency was 1% (95% CI: -1%, 3%) higher. For each 10% increase in total HCV rate, office-based buprenorphine prescribing frequency was 14% (95% CI: 7%, 20%) higher. CONCLUSIONS: Rural counties in Ohio have less office-based buprenorphine and higher acute HCV rates versus urban counties, but a similar relationship between office-based buprenorphine prescribing and HCV case rates. To adequately prevent and control HCV rates, certain rural counties may need more office-based buprenorphine prescribing in areas with high HCV case rates.

Multistate model of the patient flow process in the pediatric emergency department.

OBJECTIVES: The main purpose of this paper was to model the process by which patients enter the ED, are seen by physicians, and discharged from the Emergency Department at Nationwide Children's Hospital, as well as identify modifiable factors that are associated with ED lengths of stay through use of multistate modeling. METHODS: In this study, 75,591 patients admitted to the ED from March 1st, 2016 to February 28th, 2017 were analyzed using a multistate model of the ED process. Cox proportional hazards models with transition-specific covariates were used to model each transition in the multistate model and the Aalen-Johansen estimator was used to obtain transition probabilities and state occupation probabilities in the ED process. RESULTS: Acuity level, season, time of day and number of ED physicians had significant and varying associations with the six transitions in the multistate model. Race and ethnicity were significantly associated with transition to left without being seen, but not with the other transitions. Conversely, age and gender were significantly associated with registration to room and subsequent transitions in the model, though the magnitude of association was not strong. CONCLUSIONS: The multistate model presented in this paper decomposes the overall ED length of stay into constituent transitions for modeling covariate-specific effects on each transition. This allows physicians to understand the ED process and identify which potentially modifiable covariates would have the greatest impact on reducing the waiting times in each state in the model.

Nonspecific Symptoms Lack Diagnostic Accuracy for Infection in Older Patients in the Emergency Department.

OBJECTIVES: To determine if nonspecific symptoms and fever affect the posttest probability of acute bacterial infection in older patients in the emergency department (ED). DESIGN: Preplanned, secondary analysis of a prospective observational study. SETTING: Tertiary care, academic ED. PARTICIPANTS: A total of 424 patients in the ED, 65 years or older, including all chief complaints. MEASUREMENTS: We identified presence of altered mental status, malaise/lethargy, and fever, as reported by the patient, as documented in the chart, or both. Bacterial infection was adjudicated by agreement among two or more of three expert reviewers. Odds ratios were calculated using univariable logistic regression. Positive and negative likelihood ratios (PLR and NLR, respectively) were used to determine each symptom's effect on posttest probability of infection. RESULTS: Of 424 subjects, 77 (18%) had bacterial infection. Accounting for different reporting methods, presence of altered mental status (PLR range, 1.40-2.53) or malaise/lethargy (PLR range, 1.25-1.34) only slightly increased posttest probability of infection. Their absence did not assist with ruling out infection (NLR, greater than 0.50 for both). Fever of 38°C or higher either before or during the ED visit had moderate to large increases in probability of infection (PLR, 5.15-18.10), with initial fever in the ED perfectly predictive, but absence of fever did not rule out infection (NLR, 0.79-0.92). Results were similar when analyzing lower respiratory, gastrointestinal, and urinary tract infections (UTIs) individually. Of older adults diagnosed as having UTIs, 47% did not complain of UTI symptoms. CONCLUSIONS: The presence of either altered mental status or malaise/lethargy does not substantially increase the probability of bacterial infection in older adults in the ED and should not be used alone to indicate infection in this population. Fever of 38°C or higher is associated with increased probability of infection. J Am Geriatr Soc 67:484-492, 2019.

Muscle contractility dysfunction precedes loss of motor unit connectivity in SOD1(G93A) mice.

INTRODUCTION: Electrophysiological measurements are used in longitudinal clinical studies to provide insight into the progression of amyotrophic lateral sclerosis (ALS) and the relationship between muscle weakness and motor unit (MU) degeneration. Here, we used a similar longitudinal approach in the Cu/Zn superoxide dismutase (SOD1[G93A]) mouse model of ALS. METHODS: In vivo muscle contractility and MU connectivity assays were assessed longitudinally in SOD1(G93A) and wild type mice from postnatal days 35 to 119. RESULTS: In SOD1(G93A) males, muscle contractility was reduced by day 35 and preceded MU loss. Muscle contractility and motor unit reduction were delayed in SOD1(G93A) females compared with males, but, just as with males, muscle contractility reduction preceded MU loss. DISCUSSION: The longitudinal contractility and connectivity paradigm employed here provides additional insight into the SOD1(G93A) mouse model and suggests that loss of muscle contractility is an early finding that may precede loss of MUs and motor neuron death. Muscle Nerve 59:254-262, 2019.