Pharmacotherapy for Alcohol Use Disorder: A Systematic Review and Meta-Analysis.

Importance: Alcohol use disorder affects more than 28.3 million people in the United States and is associated with increased rates of morbidity and mortality. Objective: To compare efficacy and comparative efficacy of therapies for alcohol use disorder. Data Sources: PubMed, the Cochrane Library, the Cochrane Central Trials Registry, PsycINFO, CINAHL, and EMBASE were searched from November 2012 to September 9, 2022 Literature was subsequently systematically monitored to identify relevant articles up to August 14, 2023, and the PubMed search was updated on August 14, 2023. Study Selection: For efficacy outcomes, randomized clinical trials of at least 12 weeks' duration were included. For adverse effects, randomized clinical trials and prospective cohort studies that compared drug therapies and reported health outcomes or harms were included. Data Extraction and Synthesis: Two reviewers evaluated each study, assessed risk of bias, and graded strength of evidence. Meta-analyses used random-effects models. Numbers needed to treat were calculated for medications with at least moderate strength of evidence for benefit. Main Outcomes and Measures: The primary outcome was alcohol consumption. Secondary outcomes were motor vehicle crashes, injuries, quality of life, function, mortality, and harms. Results: Data from 118 clinical trials and 20 976 participants were included. The numbers needed to treat to prevent 1 person from returning to any drinking were 11 (95% CI, 1-32) for acamprosate and 18 (95% CI, 4-32) for oral naltrexone at a dose of 50 mg/d. Compared with placebo, oral naltrexone (50 mg/d) was associated with lower rates of return to heavy drinking, with a number needed to treat of 11 (95% CI, 5-41). Injectable naltrexone was associated with fewer drinking days over the 30-day treatment period (weighted mean difference, -4.99 days; 95% CI, -9.49 to -0.49 days) Adverse effects included higher gastrointestinal distress for acamprosate (diarrhea: risk ratio, 1.58; 95% CI, 1.27-1.97) and naltrexone (nausea: risk ratio, 1.73; 95% CI, 1.51-1.98; vomiting: risk ratio, 1.53; 95% CI, 1.23-1.91) compared with placebo. Conclusions and Relevance: In conjunction with psychosocial interventions, these findings support the use of oral naltrexone at 50 mg/d and acamprosate as first-line pharmacotherapies for alcohol use disorder.

A Cross-Sectional Study of Disparities in Screening Guideline Concordance Within a Student-Run Clinic.

Examination of screening guideline concordance can help clinics and institutions identify and understand disparities within their own practices. We conducted a study to examine whether screening completion rates within a student-run free clinic (SRFC) reflected, exacerbated, or narrowed population-level disparities in outcomes by race/ethnicity and primary language. We compared completion rates for cervical cancer (n = 114), diabetic retinopathy (n = 91), colorectal cancer (n = 114), and breast cancer (n = 63) by race/ethnicity (Black, n = 37; Hispanic, n = 133; white, n = 54; other, n = 29) and primary language (English, n = 106; Spanish, n = 136; other, n = 11) among patients at Shade tree clinic (STC), an SFRC in Nashville, TN. There were no differences in screening completion rate by race/ethnicity, and Spanish-speaking patients had slightly higher rates of cervical cancer screening [91% (95% confidence interval 84-97%)] than English-speaking patients [72% (57-86%)]. Overall screening rates were comparable to national averages, and in the case of screenings performed within clinic-cervical cancer [82%; (75-89%)] and diabetic retinopathy screening [86% (79-92%)]-exceeded national averages and/or affiliated academic medical center goals. These findings extend the existing literature supporting the ability of SRFCs to provide effective care by also demonstrating one measure of equity in clinic processes, providing a framework for future studies of equity within SRFCs and traditional primary care practices.

Ensemble learning to predict opioid-related overdose using statewide prescription drug monitoring program and hospital discharge data in the state of Tennessee.

OBJECTIVE: To develop and validate algorithms for predicting 30-day fatal and nonfatal opioid-related overdose using statewide data sources including prescription drug monitoring program data, Hospital Discharge Data System data, and Tennessee (TN) vital records. Current overdose prevention efforts in TN rely on descriptive and retrospective analyses without prognostication. MATERIALS AND METHODS: Study data included 3 041 668 TN patients with 71 479 191 controlled substance prescriptions from 2012 to 2017. Statewide data and socioeconomic indicators were used to train, ensemble, and calibrate 10 nonparametric "weak learner" models. Validation was performed using area under the receiver operating curve (AUROC), area under the precision recall curve, risk concentration, and Spiegelhalter z-test statistic. RESULTS: Within 30 days, 2574 fatal overdoses occurred after 4912 prescriptions (0.0069%) and 8455 nonfatal overdoses occurred after 19 460 prescriptions (0.027%). Discrimination and calibration improved after ensembling (AUROC: 0.79-0.83; Spiegelhalter P value: 0-.12). Risk concentration captured 47-52% of cases in the top quantiles of predicted probabilities. DISCUSSION: Partitioning and ensembling enabled all study data to be used given computational limits and helped mediate case imbalance. Predicting risk at the prescription level can aggregate risk to the patient, provider, pharmacy, county, and regional levels. Implementing these models into Tennessee Department of Health systems might enable more granular risk quantification. Prospective validation with more recent data is needed. CONCLUSION: Predicting opioid-related overdose risk at statewide scales remains difficult and models like these, which required a partnership between an academic institution and state health agency to develop, may complement traditional epidemiological methods of risk identification and inform public health decisions.

Phenotyping coronavirus disease 2019 during a global health pandemic: Lessons learned from the characterization of an early cohort.

From the start of the coronavirus disease 2019 (COVID-19) pandemic, researchers have looked to electronic health record (EHR) data as a way to study possible risk factors and outcomes. To ensure the validity and accuracy of research using these data, investigators need to be confident that the phenotypes they construct are reliable and accurate, reflecting the healthcare settings from which they are ascertained. We developed a COVID-19 registry at a single academic medical center and used data from March 1 to June 5, 2020 to assess differences in population-level characteristics in pandemic and non-pandemic years respectively. Median EHR length, previously shown to impact phenotype performance in type 2 diabetes, was significantly shorter in the SARS-CoV-2 positive group relative to a 2019 influenza tested group (median 3.1 years vs 8.7; Wilcoxon rank sum P = 1.3e-52). Using three phenotyping methods of increasing complexity (billing codes alone and domain-specific algorithms provided by an EHR vendor and clinical experts), common medical comorbidities were abstracted from COVID-19 EHRs, defined by the presence of a positive laboratory test (positive predictive value 100%, recall 93%). After combining performance data across phenotyping methods, we observed significantly lower false negative rates for those records billed for a comprehensive care visit (p = 4e-11) and those with complete demographics data recorded (p = 7e-5). In an early COVID-19 cohort, we found that phenotyping performance of nine common comorbidities was influenced by median EHR length, consistent with previous studies, as well as by data density, which can be measured using portable metrics including CPT codes. Here we present those challenges and potential solutions to creating deeply phenotyped, acute COVID-19 cohorts.

Association of Individual and Community Factors With Hepatitis C Infections Among Pregnant People and Newborns.

Importance: The opioid crisis has increasingly affected pregnant people and infants. Hepatitis C virus (HCV) infections, a known complication of opioid use, grew in parallel with opioid-related complications; however, the literature informing individual and community risks associated with maternal HCV infection is sparse. Objectives: To determine (1) individual and county-level factors associated with HCV among pregnant people and their newborn infants, and (2) how county-level factors influence individual risk among the highest risk individuals. Design Setting and Participants: This time-series analysis of retrospective, repeated cross-sectional data included pregnant people in all US counties from 2009 to 2019. We constructed mixed-effects logistic regression models to explore the association between HCV infection and individual and county-level covariates. Analyses were conducted between June 2019 and September 2021. Exposures: Individual-level: race and ethnicity, education, marital status, insurance type; county-level: rurality, employment, density of obstetricians. Main Outcomes and Measures: Hepatitis C virus as indicated on the newborn's birth certificate. Results: Between 2009 and 2019, there were 39 380 122 pregnant people who met inclusion criteria, among whom 138 343 (0.4%) were diagnosed with HCV. People with HCV were more likely to be White (79.9% vs 53.5%), American Indian or Alaska Native (AI/AN) (2.9% vs 0.9%), be without a 4-year degree (93.2% vs 68.6%), and be unmarried (73.7% vs 38.8%). The rate (per 1000 live births) of HCV among pregnant people increased from 1.8 to 5.1. In adjusted analyses, the following factors were associated with higher rates of HCV: individuals identified as White (adjusted odds ratio [aOR], 7.37; 95% CI, 7.20-7.55) and AI/AN (aOR, 7.94; 95% CI, 7.58-8.31) compared with Black individuals, those without a 4-year degree (aOR, 3.19; 95% CI, 3.11-3.28), those with Medicaid vs private insurance (aOR, 3.27; 95% CI, 3.21-3.33), and those who were unmarried (aOR, 2.80; 95% CI, 2.76-2.84); whereas, rural residence, higher rates of employment, and greater density of obstetricians was associated with lower risk of HCV. Among individuals at the highest risk of HCV, higher levels of county employment, accounting for other factors, were associated with less of a rise in HCV infections over time. Conclusions and Relevance: In this cross-sectional study, maternal and newborn HCV infections increased substantially between 2009 and 2019, disproportionately among White and AI/AN people without a 4-year degree. County-level factors, including higher levels of employment, were associated with lower individual risks of acquiring the virus.

The effect of an opioid prescription days' supply limit on patients receiving long-term opioid treatment.

BACKGROUND: Since 2016, an increasing number of states have passed laws restricting the days' supply for opioid prescriptions, yet little is known about how these laws affect patients. This study evaluates the effect of the Tennessee Prescription Regulatory Act, which was implemented on Oct. 1st, 2013 and restricted the maximum days' supply that could be dispensed for any opioid prescription by any prescriber to 30 days, on patients receiving long-term opioid treatment. METHODS: A quasi experimental model, an interrupted time series (ITS), was used with observational data to estimate the effect of the policy on monthly patient opioid prescription outcomes. Data for this study came from the Tennessee Controlled Substance Monitoring Database between October 1st, 2012 and October 31st, 2014. The study population included patients receiving long-term opioid treatment who filled an opioid prescription in at least 4 months in the 12-month pre-policy period and received at least one prescription in the pre-policy period with a days' supply exceeding 30 days. Three outcomes were measured each month for every patient based on their opioid prescriptions: per-prescription days' supply per-prescription, daily morphine milligram equivalent (DMME), and total opioid prescriptions. All models controlled for individual fixed effects, age, and benzodiazepine prescriptions and utilized cluster robust standard errors to address serial correlation. RESULTS: The change in law was associated with a decline in the average days' supply by -5.30 days (95% CI: -5.64, -4.96), and number of prescriptions by -1.3% (95% CI: -3%, -0.07%), but an increase in the average DMME by 1.41 (95% CI: 0.37, 2.45). CONCLUSIONS: Prescribers responded to the Addison Sharp Prescription Regulatory Act by significantly decreasing the days' supply in opioid prescriptions among current patients receiving long-term opioid treatment who had at least one prescription exceeding the maximum days' supply set by the law in the pre-policy period.

Record Linkage Approaches Using Prescription Drug Monitoring Program and Mortality Data for Public Health Analyses and Epidemiologic Studies.

BACKGROUND: The use of Prescription Drug Monitoring Program (PDMP) data has greatly increased in recent years as these data have accumulated as part of the response to the opioid epidemic in the United States. We evaluated the accuracy of record linkage approaches using the Controlled Substance Monitoring Database (Tennessee's [TN] PDMP, 2012-2016) and mortality data on all drug overdose decedents in Tennessee (2013-2016). METHODS: We compared total, missed, and false positive (FP) matches (with manual verification of all FPs) across approaches that included a variety of data cleaning and matching methods (probabilistic/fuzzy vs. deterministic) for patient and death linkages, and prescription history. We evaluated the influence of linkage approaches on key prescription measures used in public health analyses. We evaluated characteristics (e.g., age, education, sex) of missed matches and incorrect matches to consider potential bias. RESULTS: The most accurate probabilistic/fuzzy matching approach identified 4,714 overdose deaths (vs. the deterministic approach, n = 4,572), with a low FP linkage error (<1%) and high correct match proportion (95% vs. 92% and ~90% for probabilistic approaches not using comprehensive data cleaning). Estimation of all prescription measures improved (vs. deterministic approach). For example, frequency (%) of decedents filling an oxycodone prescription in the last 60 days (n = 1,371 [32%] vs. n = 1,443 [33%]). Missed overdose decedents were more likely to be younger, male, nonwhite, and of higher education. CONCLUSION: Implications of study findings include underreporting, prescribing and outcome misclassification, and reduced generalizability to population risk groups, information of importance to epidemiologists and researchers using PDMP data.

Prescribing patterns before and after a non-fatal drug overdose using Tennessee's controlled substance monitoring database linked to hospital discharge data.

We performed a statewide evaluation of prescribing patterns of controlled substances (CS) before and after an overdose, using Tennessee's Hospital Discharge Data System and the Controlled Substance Monitoring Database (CSMD). Adults' first non-fatal overdose discharges either from the emergency department (ED) or inpatient (IP) stay occurring between 2013 and 2016 were linked to prescriptions in the CSMD. The difference in the proportion of patients filling a prescription before versus after an overdose was calculated. Included were 49,398 patients with an overdose and a prescription record; most (60.5%) were treated in the ED. Among any drug type overdose the percentage of patients who filled a CS prescription within a year of experiencing an overdose was as follows: opioid analgesics: 59.1%, benzodiazepines: 37.3%, stimulants: 5.0%, muscle relaxants: 3.4%, concurrent opioid-benzodiazepines: 24.0% with the percent difference from before to after similar in both settings. Among patients treated for an opioid overdose, this represented a decrease in opioid analgesics filled by 9.7% (95%CI: -11.2, -8.3) among those treated in the ED, and by 7.1% (95% CI: -8.3, -5.9) among treated inpatients. Among patients treated for a heroin overdose, 12.2% (95%CI: -15.2, -9.3) fewer of those treated in the ED and 8.8% (95%CI: -15.0, -2.7%) fewer of treated inpatients filled a CS prescription in that year. The most common opioid analgesics included hydrocodone and oxycodone. The number of patients filling buprenorphine for treatment increased in the year after overdoses associated with any drug or opioids but decreased among those treated for a heroin overdose.

Prevalence and Risk Factors Associated With Long-term Opioid Use After Injury Among Previously Opioid-Free Workers.

Importance: Using opioids for acute pain can lead to long-term use and associated morbidity and mortality. Injury has been documented as a gateway to long-term opioid use in some populations, but data are limited for injured workers. Objective: To evaluate the prevalence and risk factors of long-term opioid use after injury among workers in Tennessee who were opioid free at the time of injury. Design, Setting, and Participants: This cohort study identified injured workers aged 15 to 99 years who reported only 1 injury to the Tennessee Bureau of Workers' Compensation from March 2013 to December 2015 and had no opioid prescription in the 60 days before injury. Participants were matched to their prescription history in Tennessee's prescription drug monitoring program. Analysis was conducted from November 2017 to March 2018. Logistic regression models were used to calculate adjusted odds ratios (ORs) and 95% CIs for associations of demographic, injury, and opioid use variables with long-term use. Main Outcomes and Measures: The primary outcome was long-term opioid use, defined as having an opioid supplied for 45 or more days in the 90 days after injury. Results: Among 58 278 injured workers who received opioids after injury (18 977 [32.5%] aged 15-34 years, 27 514 [47.2%] aged 35-54 years, and 11 787 [20.2%] aged 55-99 years; 32 607 [56.0%] men), 46 399 (79.6%) were opioid free at the time of injury. Among opioid-free injured workers, 1843 (4.0%) began long-term opioid use. After controlling for covariates, long-term use was associated with receiving 20 or more days' supply in the initial opioid prescription compared with receiving less than 5 days' supply (OR, 28.94; 95% CI, 23.44-35.72) and visiting 3 or more prescribers in the 90 days after injury compared with visiting 1 prescriber (OR, 14.91; 95% CI, 12.15-18.29). However, even just 5 days' to 9 days' supply was associated with an increase in the odds of long-term use compared with less than 5 days' supply (OR, 1.83; 95% CI, 1.56-2.14). Conclusions and Relevance: In this study of injured workers, injury was associated with long-term opioid use. The number of days' supply of the initial opioid prescription was the strongest risk factor of developing long-term use, highlighting the importance of careful prescribing for initial opioid prescriptions.

Prescription opioid use by injured workers in Tennessee: a descriptive study using linked statewide databases.

PURPOSE: This is the first study in Tennessee to measure opioid use in injured workers and among the first nationally to use a prescription drug monitoring program to do so. We conducted a retrospective cohort study to evaluate the prevalence of opioid use after injury and associated characteristics among workers reporting one injury to Tennessee Workers' Compensation. METHODS: Injured workers identified in Workers' Compensation records 2013-2015 were linked to their prescription history in Tennessee's prescription drug monitoring database. RESULTS: Among 172,256 injured workers, the prevalence of receiving an opioid after injury was 22.8% in 1 week, 29.7% in 1 month, and 33.3% in 6 months. Receiving an opioid was associated with having a fracture (odds ratio, 4.9; 95% confidence interval, 4.64-5.11 vs. other injuries). Hydrocodone short-acting was the most commonly received opioid (69.5% of injured workers), and the mean of each worker's maximum dose was 42.8 morphine milligram equivalents (SD 39.26). Ten percent of injured workers who received opioids also received a benzodiazepine. CONCLUSIONS: Injured workers have a high prevalence of opioid use after injury, but prescribing patterns generally tend to follow Tennessee prescribing guidelines.

Maintaining automated measurement of Choosing Wisely adherence across the ICD 9 to 10 transition.

BACKGROUND: It remains unclear how to incorporate terminology changes, such as the International Classification of Disease (ICD) transition from ICD-9 to ICD-10, into established automated healthcare quality metrics. OBJECTIVE: To evaluate whether general equivalence mapping (GEM) can apply ICD-9 based metrics to ICD-10 patient data. To develop and validate novel ICD-10 reference codesets. DESIGN: Retrospective analysis for eleven Choosing Wisely (CW) metrics was performed using three scripted algorithms on an institutional clinical data warehouse. ICD-10 data were compared against published ICD-9 based metric definitions using two equivalence mapping algorithms. A third algorithm implemented novel reference ICD-10 codes matching the original ICD-9 codes' intent for comparison with patient ICD-10 data. PARTICIPANTS: All adult patients seen at Vanderbilt University Medical Center, April - September 2016. MAIN MEASURES: The prevalence of eleven CW services during the six-month period. KEY RESULTS: The three algorithms found similar prevalence of avoidable CW services, with an unweighted-mean of 8.4% (range: 0.16-65%), or approximately 20,000 CW services out of 240,000 potential cases in 515,406 unique patients. The algorithms' median sensitivity was 0.80 (interquartile range: 0.75-0.95), median specificity was 0.88 (IQR: 0.77-0.94), and median Rand accuracy was 0.84 (IQR: 0.79-0.89). The attributed waste of these eleven services for the period ranged from $871,049 to $951,829 between methods. Accuracy assessment demonstrated that the GEM-based methods suffered recall losses for metrics requiring multistep mapping due to incompleteness, while novel ICD-10 metric definitions avoided these challenges. CONCLUSIONS: Comprehensive mapping enables use of legacy metrics across ICD generations, but requires computational complexity that can be avoided with novel ICD-10 based metric definitions. Variation in the dollars attributed to waste due to ICD mapping introduces ambiguity that may affect quality-based reimbursement.

Sociodemographic factors, prescription history and opioid overdose deaths: a statewide analysis using linked PDMP and mortality data.

BACKGROUND: Opioid overdose deaths have continued to rise in Tennessee (TN) with fentanyl emerging as a major contributor. Current data are needed to identify at-risk populations to guide prevention strategies. We conducted a large statewide observational study among TN adult decedents (2013-2016) to evaluate the association of sociodemographic factors and prescribing patterns with opioid overdose deaths. METHODS: Among drug overdose decedents identified using death certificate data (n = 5483), we used logistic regression to estimate adjusted odds ratios and 95% confidence intervals for characteristics associated with prescription opioid (PO) (excluding fentanyl), fentanyl, and heroin alone overdoses. Among decedents linked to TN's Prescription Drug Monitoring Database using deterministic algorithms, we obtained prescription history in the year before death (n = 3971), which was evaluated by type of overdose using descriptive statistics. RESULTS: Younger, non-White decedents had lower odds of PO overdose, while females and benzodiazepines as a contributing cause were associated with increased odds of PO overdose. Younger age, Non-Hispanic Black race/ethnicity, greater than high school education, and cocaine/other stimulants as a contributing cause were associated with increased odds of fentanyl or heroin overdoses. Over 55% of PO, 39.2% of fentanyl, and 20.7% of heroin overdoses had an active opioid prescription at death. For PO, fentanyl, and heroin decedents, respectively, 46.0%, 30.5%, and 26.2% had an active prescription for benzodiazepines at death. CONCLUSIONS: Prescription opioid overdose deaths were associated with different sociodemographic profiles and prescribing history compared to fentanyl and heroin overdose deaths in TN. Data can guide prevention strategies to reduce opioid overdose mortality.

Tennessee's In-state Vulnerability Assessment for a "Rapid Dissemination of Human Immunodeficiency Virus or Hepatitis C Virus Infection" Event Utilizing Data About the Opioid Epidemic.

Background: Knowing which factors contribute to county-level vulnerability to a human immunodeficiency virus (HIV)/hepatitis C virus (HCV) outbreak, and which counties are most vulnerable, guides public health and clinical interventions. We therefore examined the impact of locally available indicators related to the opioid epidemic on prior national models of HIV/HCV outbreak vulnerability. Methods: Tennessee's 95 counties were the study sample. Predictors from 2012 and 2013 were used, mirroring prior methodology from the US Centers for Disease Control and Prevention (CDC). Acute HCV incidence was the proxy measure of county-level vulnerability. Seventy-eight predictors were identified as potentially predictive for HIV/HCV vulnerability. We used multiple dimension reduction techniques to determine predictors for inclusion and Poisson regression to generate a composite index score ranking county-level vulnerability for HIV/HCV. Results: There was overlap of high-risk counties with the national analysis (25 of 41 counties). The distribution of vulnerability reinforces earlier research indicating that eastern Tennessee is at particularly high risk but also demonstrates that the entire state has high vulnerability. Conclusions: Prior research placed Tennessee among the top states for opioid prescribing, acute HCV infection, and greatest risk for an HIV/HCV outbreak. Given this confluence of risk, the Tennessee Department of Health expanded upon prior work to include more granular, local data, including on opioid prescribing. We also explored nonfatal and fatal overdoses. The more complete statewide view of risk generated, not only in eastern counties but also in the western corridor, will enable local officials to monitor vulnerability and better target resources.

AHRQ series on complex intervention systematic reviews-paper 4: selecting analytic approaches.

BACKGROUND: Systematic reviews of complex interventions can vary widely in purpose, data availability and heterogeneity, and stakeholder expectations. RATIONALE: This article addresses the uncertainty that systematic reviewers face in selecting methods for reviews of complex interventions. Specifically, it lays out parameters for systematic reviewers to consider when selecting analytic approaches that best answer the questions at hand and suggests analytic techniques that may be appropriate in different circumstances. DISCUSSION: Systematic reviews of complex interventions comprising multiple questions may use multiple analytic approaches. Parameters to consider when choosing analytic methods for complex interventions include nature and timing of the decision (clinical practice guideline, policy, or other); purpose of the review; extent of existing evidence; logistic factors such as the timeline, process, and resources for deciding the scope of the review; and value of information to be obtained from choosing specific systematic review methods. Reviewers may elect to revise their analytic approach based on new or changing considerations during the course of the review but should guard against bias through transparency of reporting.

Nutritional and Dietary Interventions for Autism Spectrum Disorder: A Systematic Review.

CONTEXT: Children with autism spectrum disorder (ASD) frequently use special diets or receive nutritional supplements to treat ASD symptoms. OBJECTIVES: Our objective was to evaluate the effectiveness and safety of dietary interventions or nutritional supplements in ASD. DATA SOURCES: Databases, including Medline and PsycINFO. STUDY SELECTION: Two investigators independently screened studies against predetermined criteria. DATA EXTRACTION: One investigator extracted data with review by a second investigator. Investigators independently assessed the risk of bias and strength of evidence (SOE) (ie, confidence in the estimate of effects). RESULTS: Nineteen randomized controlled trials (RCTs), 4 with a low risk of bias, evaluated supplements or variations of the gluten/casein-free diet and other dietary approaches. Populations, interventions, and outcomes varied. Ω-3 supplementation did not affect challenging behaviors and was associated with minimal harms (low SOE). Two RCTs of different digestive enzymes reported mixed effects on symptom severity (insufficient SOE). Studies of other supplements (methyl B12, levocarnitine) reported some improvements in symptom severity (insufficient SOE). Studies evaluating gluten/casein-free diets reported some parent-rated improvements in communication and challenging behaviors; however, data were inadequate to make conclusions about the body of evidence (insufficient SOE). Studies of gluten- or casein-containing challenge foods reported no effects on behavior or gastrointestinal symptoms with challenge foods (insufficient SOE); 1 RCT reported no effects of camel's milk on ASD severity (insufficient SOE). Harms were disparate. LIMITATIONS: Studies were small and short-term, and there were few fully categorized populations or concomitant interventions. CONCLUSIONS: There is little evidence to support the use of nutritional supplements or dietary therapies for children with ASD.

Interventions Targeting Sensory Challenges in Autism Spectrum Disorder: A Systematic Review.

CONTEXT: Sensory challenges are common among children with autism spectrum disorder (ASD). OBJECTIVE: To evaluate the effectiveness and safety of interventions targeting sensory challenges in ASD. DATA SOURCES: Databases, including Medline and PsycINFO. STUDY SELECTION: Two investigators independently screened studies against predetermined criteria. DATA EXTRACTION: One investigator extracted data with review by a second. Investigators independently assessed risk of bias and strength of evidence (SOE), or confidence in the estimate of effects. RESULTS: Twenty-four studies, including 20 randomized controlled trials (RCTs), were included. Only 3 studies had low risk of bias. Populations, interventions, and outcomes varied. Limited, short-term studies reported potential positive effects of several approaches in discrete skill domains. Specifically, sensory integration-based approaches improved sensory and motor skills-related measures (low SOE). Environmental enrichment improved nonverbal cognitive skills (low SOE). Studies of auditory integration-based approaches did not improve language (low SOE). Massage improved symptom severity and sensory challenges in studies with likely overlapping participants (low SOE). Music therapy studies evaluated different protocols and outcomes, precluding synthesis (insufficient SOE). Some positive effects were reported for other approaches, but findings were inconsistent (insufficient SOE). LIMITATIONS: Studies were small and short-term, and few fully categorized populations. CONCLUSIONS: Some interventions may yield modest short-term (<6 months) improvements in sensory- and ASD symptom severity-related outcomes; the evidence base is small, and the durability of the effects is unclear. Although some therapies may hold promise, substantial needs exist for continuing improvements in methodologic rigor.

Patient-Reported Outcome Measures in Upper Airway-Related Dyspnea: A Systematic Review.

Importance: Patient-reported outcome (PRO) measures address the need for patient-centered data and are now used in diverse clinical, research, and policy pursuits. They are important in conditions causing upper airway-related dyspnea in which the patient's reported experience and physiological data can be discrepant. Objectives: To perform a systematic review of the literature on upper airway dyspnea-related PRO measures and to rigorously evaluate each measure's developmental properties, validation, and applicability. Evidence Review: This study strictly adhered to Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) guidelines. MEDLINE via the PubMed interface, the Cumulative Index to Nursing and Allied Health Literature (CINAHL), and the Health and Psychosocial Instruments (HaPI) database were searched using relevant vocabulary terms and key terms related to PRO measures and upper airway-related dyspnea. Three investigators performed abstract review, and 2 investigators independently performed full-text review by applying an established checklist to evaluate the conceptual model, content validity, reliability, construct validity, scoring and interpretability, and respondent burden and presentation of each identified instrument. The initial literature search was conducted in November 2014 and was updated in April 2016. Findings: Of 1269 studies reviewed, 3 upper airway-related dyspnea PRO measures met criteria for inclusion. One PRO measure was designed de novo to assess upper airway-related dyspnea symptoms and monitor treatment outcomes, while 2 were adapted from established instruments designed for lower airway disease. Measurement properties and psychometric characteristics differed, and none met all checklist criteria. Two met a criterion in each of 7 domains evaluated. Two demonstrated test-retest and internal consistency reliability, and 2 showed that their scores were responsive to change. Thematic deficiencies in current upper airway-related dyspnea PRO measures are lack of patient involvement in item development (content validity), plan for interpretation, and literacy level assessments. Conclusions and Relevance: PRO measures are critical in the assessment of patients with upper airway-related dyspnea. Three instruments with disparate developmental rigor have been designed or adapted to assess this construct. Care must be taken to understand the measurement characteristics and contextual relevance before applying these PRO measures for clinical, research, or quality initiatives.