The Increase in Household Transmission of Pertussis Associated With Diagnostic Delays.

BACKGROUND: Pertussis is a highly contagious respiratory illness that can be especially dangerous to young children. Transmission of pertussis often occurs in household settings and is impacted by the timing of treatment and postexposure chemoprophylaxis. This study analyzes the risk for secondary household transmission and if delays in diagnosing pertussis increased the risk for household transmission. METHODS: We conducted 2 population-based studies using a large nationally representative administrative claims database. The first study utilized a stratified monthly incidence model to compare the incidence of pertussis among enrollees exposed to a family member with pertussis versus those not exposed. The second study was conducted at a household level following the index case of pertussis in each household. We identified diagnostic delays in the initial household case and used a logistic regression model to evaluate if such delays were associated with a greater risk for transmission. RESULTS: The incidence rate ratio of pertussis was 938.99 [95% confidence interval (CI): 880.19-1001.73] among enrollees exposed to a family member with pertussis relative to those not exposed. The odds of secondary household transmission in households where the index case experienced a diagnostic delay was 5.10 (CI: 4.44-5.85) times the odds of transmission when the index case was not delayed. We found that longer delays were associated with a greater risk for secondary household transmission (P < 0.0001). CONCLUSIONS: There is a high rate of secondary transmission of pertussis in household settings. Diagnostic delays increase the likelihood that pertussis will transmit in the household.

Cystic Fibrosis Carrier States Are Associated With More Severe Cases of Bronchiectasis.

Background: People with cystic fibrosis (CF) are at increased risk for bronchiectasis, and several reports suggest that CF carriers may also be at higher risk for developing bronchiectasis. The purpose of this study was to determine if CF carriers are at risk for more severe courses or complications of bronchiectasis. Methods: Using MarketScan data (2001-2021), we built a cohort consisting of 105 CF carriers with bronchiectasis and 300 083 controls with bronchiectasis but without a CF carrier diagnosis. We evaluated if CF carriers were more likely to be hospitalized for bronchiectasis. In addition, we examined if CF carriers were more likely to be infected with Pseudomonas aeruginosa or nontuberculous mycobacteria (NTM) or to have filled more antibiotic prescriptions. We considered regression models for incident and rate outcomes that controlled for age, sex, smoking status, and comorbidities. Results: The odds of hospitalization were almost 2.4 times higher (95% CI, 1.116-5.255) for CF carriers with bronchiectasis when compared with non-CF carriers with bronchiectasis. The estimated odds of being diagnosed with a Pseudomonas infection for CF carriers vs noncarriers was about 4.2 times higher (95% CI, 2.417-7.551) and 5.4 times higher (95% CI, 3.398-8.804) for being diagnosed with NTM. The rate of distinct antibiotic fill dates was estimated to be 2 times higher for carriers as compared with controls (95% CI, 1.735-2.333), and the rate ratio for the total number of days of antibiotics supplied was estimated as 2.8 (95% CI, 2.290-3.442). Conclusions: CF carriers with bronchiectasis required more hospitalizations and more frequent administration of antibiotics as compared with noncarriers. Given that CF carriers were also more likely to be diagnosed with Pseudomonas and NTM infections, CF carriers with bronchiectasis may have a phenotype more resembling CF-related bronchiectasis than non-CF bronchiectasis.

Does Implementation Matter? Associations Between Implementation of Maine's Anti- Bullying Law and Bullying Victimization Among High School Youth.

PURPOSE: To characterize the relationship between implementation of an antibullying law and bullying rates among high school youth. METHODS: School staff (administrators, counselors, and teachers) from public high schools in Maine completed a survey assessing: (1) the frequency with which they implemented 17 components of their district's antibullying policy as mandated by state law; and (2) confidence in implementing the law. Their responses were linked to data on bullying victimization among high school respondents to the Maine Integrated Youth Health Survey, which created a population-based dataset of 84 high schools with 29,818 student responses. RESULTS: Students in schools where administrators (adjusted odds ratio = 0.93; 95% CI: 0.89, 0.97) and counselors (adjusted odds ratio = 0.86; 95% CI: 0.81, 0.92) reported implementing more mandated components of the law experienced notable reductions in the odds of bullying, controlling for student-level characteristics (sex, race, grade) and for school-level bullying rates assessed prior to the passage of the law. With respect to specific implementation components, bullying was most consistently reduced in schools where staff reported increased referrals for counseling and other supports for targets of bullying and in schools where counselors and teachers were interviewed as part of bullying investigations. Students in schools where teachers reported increased confidence in implementing the antibullying law also had reduced odds of bullying. DISCUSSION: These data provide some of the first evidence that the efficacy of a state's antibullying law depends in part on the extent to which school personnel implement the law.

Diurnal temperature variation and the implications for diagnosis and infectious disease screening: a population-based study.

OBJECTIVES: Fevers have been used as a marker of disease for hundreds of years and are frequently used for disease screening. However, body temperature varies over the course of a day and across individual characteristics; such variation may limit the detection of febrile episodes complicating the diagnostic process. Our objective was to describe individual variation in diurnal temperature patterns during episodes of febrile activity using millions of recorded temperatures and evaluate the probability of recording a fever by sex and for different age groups. METHODS: We use timestamped deidentified temperature readings from thermometers across the US to construct illness episodes where continuous periods of activity in a single user included a febrile reading. We model the mean temperature recorded and probability of registering a fever across the course of a day using sinusoidal regression models while accounting for user age and sex. We then estimate the probability of recording a fever by time of day for children, working-age adults, and older adults. RESULTS: We find wide variation in body temperatures over the course of a day and across individual characteristics. The diurnal temperature pattern differed between men and women, and average temperatures declined for older age groups. The likelihood of detecting a fever varied widely by the time of day and by an individual's age or sex. CONCLUSIONS: Time of day and demographics should be considered when using body temperatures for diagnostic or screening purposes. Our results demonstrate the importance of follow-up thermometry readings if infectious diseases are suspected.

Recruitment of Row Crop Farmers into a Research Study to Assess Farm Hazards.

Farmers are at an elevated risk for injuries and are, therefore, highly sought after for research studies. However, their participation in research studies is low. We examine how characteristics of the farmer, farm location, and timing of recruitment contact impact the probability that farmers will engage and participate in a study of injuries and related farm hazards. Study data were obtained from the Farm Safety Study conducted at the University of Iowa between June 2019 and March 2020. We used recruitment data from participants enrolled using Farm Journal magazine subscription lists. Multinomial logistic regression was used for predictive modeling. Predictor variables included the time of day and the farm season in which phone contact for study recruitment was attempted, as well as the rurality of the farm. Two models were created to characterize screening and participation of farmers in the study. Farm season and time of day of the last recruitment call increased the likelihood of farmers being screened for study participation and completing the study. Specifically, contacting farmers during the growing season and during the daytime, regardless of farm rurality, resulted in higher probabilities of participation. Studies of agricultural injury may be more efficiently conducted, with higher participation responses, when circumstances of the recruitment call are considered. This work serves as a starting place for much-needed methodological research to identify factors that increase participation of farmers and farm workers in research studies.

Association between household opioid prescriptions and risk for overdose among family members not prescribed opioids.

BACKGROUND: Prescription opioids have contributed to the rise in opioid-related overdoses and deaths. The presence of opioids within households may increase the risk of overdose among family members who were not prescribed an opioid themselves. Larger quantities of opioids may further increase risk. OBJECTIVES: To determine the risk of opioid overdose among individuals who were not prescribed an opioid but were exposed to opioids prescribed to other family members in the household, and evaluate the risk in relation to the total morphine milligram equivalents (MMEs) present in the household. METHODS: We conducted a cohort study using a large database of commercial insurance claims from 2001 to 2021. For inclusion in the cohort, we identified individuals not prescribed an opioid in the prior 90 days from households with two or more family members, and determined the total MMEs prescribed to other family members. Individuals were stratified into monthly enrollment strata defined by household opioid exposure and other confounders. A generalized linear model was used to estimate incidence rate ratios (IRRs) for overdose. RESULTS: Overall, the incidence of overdose among enrollees in households where a family member was prescribed an opioid was 1.73 (95% confidence interval [CI]: 1.67-1.78) times greater than households without opioid prescriptions. The risk of overdose increased continuously with the level of potential MMEs in the household from an IRR of 1.23 (95% CI: 1.16-1.32) for 1-100 MMEs to 4.67 (95% CI: 4.18-5.22) for >12,000 MMEs. The risk of overdose associated with household opioid exposure was greatest for ages 1-2 years (IRR: 3.46 [95% CI: 2.98-4.01]) and 3-5 years (IRR: 3.31 [95% CI: 2.75-3.99]). CONCLUSIONS: The presence of opioids in a household significantly increases the risk of overdose among other family members who were not prescribed an opioid. Higher levels of MMEs, either in terms of opioid strength or quantity, were associated with increased levels of risk. Risk estimates may reflect accidental poisonings among younger family members.

Informing traffic enforcement leniency and discretion: Crash culpability and the effectiveness of written warnings versus citations.

OBJECTIVES: Deterrence of risky driving behavior is important for the prevention of crashes and injuries. Traffic law enforcement is a key strategy used to decrease risky driving, but there is little evidence on the deterrent effect of issuing warnings versus citations to drivers regarding the prevention of future crashes. The purpose of this study was to 1) investigate the difference between citations and written warnings in their association with future crash culpability and 2) investigate whether drivers who were issued written warnings or citations have different associations with future crash culpability likelihood than those without prior citations or written warnings. METHODS: Data for this study included Iowa Department of Transportation crash data for 2016 to 2019 linked to data from the Iowa Court Case Management System. A quasi-induced exposure method was used based on driver pairs involved in the same collision in which one driver was deemed culpable and one was non-culpable. Conditional logistic regression models were constructed to examine predictors of crash culpability. The main independent variable was traffic citation and warnings history categorized into moving warning, non-moving warning, moving citation, non-moving citation, or no citation or warning in the 30 days prior to the crash. RESULTS: The study sample included a total of 152,986 drivers. Among drivers with moving violations, previously cited drivers were more likely to be crash culpable than previously warned drivers (OR = 1.64, 95% CI = 1.29-2.08). Drivers with prior non-moving citations were less likely to be the culpable party in a crash than a driver who had no recent warnings or citations (OR = 0.72, 95% CI = 0.58-0.89). Drivers with prior warnings (moving or non-moving) did not appreciably differ in crash culpability relative to drivers who had not received any citations or warnings in the previous 30 days. CONCLUSIONS: Drivers with prior moving citations were more likely to be culpable in a future crash than drivers with prior moving warnings, which may relate to overall driving riskiness as opposed to effectiveness of citations in deterring risky driving behaviors. Results from this study also suggest that officer discretion was being appropriately applied by citing the riskiest drivers, while giving lower risk drivers warnings. Results from this study may be useful to support strengthening of state driver improvement programming.

A comprehensive framework to estimate the frequency, duration, and risk factors for diagnostic delays using bootstrapping-based simulation methods.

BACKGROUND: The incidence of diagnostic delays is unknown for many diseases and specific healthcare settings. Many existing methods to identify diagnostic delays are resource intensive or difficult to apply to different diseases or settings. Administrative and other real-world data sources may offer the ability to better identify and study diagnostic delays for a range of diseases. METHODS: We propose a comprehensive framework to estimate the frequency of missed diagnostic opportunities for a given disease using real-world longitudinal data sources. We provide a conceptual model of the disease-diagnostic, data-generating process. We then propose a bootstrapping method to estimate measures of the frequency of missed diagnostic opportunities and duration of delays. This approach identifies diagnostic opportunities based on signs and symptoms occurring prior to an initial diagnosis, while accounting for expected patterns of healthcare that may appear as coincidental symptoms. Three different bootstrapping algorithms are described along with estimation procedures to implement the resampling. Finally, we apply our approach to the diseases of tuberculosis, acute myocardial infarction, and stroke to estimate the frequency and duration of diagnostic delays for these diseases. RESULTS: Using the IBM MarketScan Research databases from 2001 to 2017, we identified 2,073 cases of tuberculosis, 359,625 cases of AMI, and 367,768 cases of stroke. Depending on the simulation approach that was used, we estimated that 6.9-8.3% of patients with stroke, 16.0-21.3% of patients with AMI and 63.9-82.3% of patients with tuberculosis experienced a missed diagnostic opportunity. Similarly, we estimated that, on average, diagnostic delays lasted 6.7-7.6 days for stroke, 6.7-8.2 days for AMI, and 34.3-44.5 days for tuberculosis. Estimates for each of these measures was consistent with prior literature; however, specific estimates varied across the different simulation algorithms considered. CONCLUSIONS: Our approach can be easily applied to study diagnostic delays using longitudinal administrative data sources. Moreover, this general approach can be customized to fit a range of diseases to account for specific clinical characteristics of a given disease. We summarize how the choice of simulation algorithm may impact the resulting estimates and provide guidance on the statistical considerations for applying our approach to future studies.

The incidence, duration, risk factors, and age-based variation of missed opportunities to diagnose pertussis: A population-based cohort study.

OBJECTIVE: To estimate the incidence, duration and risk factors for diagnostic delays associated with pertussis. DESIGN: We used longitudinal retrospective insurance claims from the Marketscan Commercial Claims and Encounters, Medicare Supplemental (2001-2020), and Multi-State Medicaid (2014-2018) databases. SETTING: Inpatient, emergency department, and outpatient visits. PATIENTS: The study included patients diagnosed with pertussis (International Classification of Diseases [ICD] codes) and receipt of macrolide antibiotic treatment. METHODS: We estimated the number of visits with pertussis-related symptoms before diagnosis beyond that expected in the absence of diagnostic delays. Using a bootstrapping approach, we estimated the number of visits representing a delay, the number of missed diagnostic opportunities per patient, and the duration of delays. Results were stratified by age groups. We also used a logistic regression model to evaluate potential factors associated with delay. RESULTS: We identified 20,828 patients meeting inclusion criteria. On average, patients had almost 2 missed opportunities prior to diagnosis, and delay duration was 12 days. Across age groups, the percentage of patients experiencing a delay ranged from 29.7% to 37.6%. The duration of delays increased considerably with age from an average of 5.6 days for patients aged <2 years to 13.8 days for patients aged ≥18 years. Factors associated with increased risk of delays included emergency department visits, telehealth visits, and recent prescriptions for antibiotics not effective against pertussis. CONCLUSIONS: Diagnostic delays for pertussis are frequent. More work is needed to decrease diagnostic delays, especially among adults. Earlier case identification may play an important role in the response to outbreaks by facilitating treatment, isolation, and improved contact tracing.

A clinically-guided unsupervised clustering approach to recommend symptoms of disease associated with diagnostic opportunities.

OBJECTIVES: A first step in studying diagnostic delays is to select the signs, symptoms and alternative diseases that represent missed diagnostic opportunities. Because this step is labor intensive requiring exhaustive literature reviews, we developed machine learning approaches to mine administrative data sources and recommend conditions for consideration. We propose a methodological approach to find diagnostic codes that exhibit known patterns of diagnostic delays and apply this to the diseases of tuberculosis and appendicitis. METHODS: We used the IBM MarketScan Research Databases, and consider the initial symptoms of cough before tuberculosis and abdominal pain before appendicitis. We analyze diagnosis codes during healthcare visits before the index diagnosis, and use k-means clustering to recommend conditions that exhibit similar trends to the initial symptoms provided. We evaluate the clinical plausibility of the recommended conditions and the corresponding number of possible diagnostic delays based on these diseases. RESULTS: For both diseases of interest, the clustering approach suggested a large number of clinically-plausible conditions to consider (e.g., fever, hemoptysis, and pneumonia before tuberculosis). The recommended conditions had a high degree of precision in terms of clinical plausibility: >70% for tuberculosis and >90% for appendicitis. Including these additional clinically-plausible conditions resulted in more than twice the number of possible diagnostic delays identified. CONCLUSIONS: Our approach can mine administrative datasets to detect patterns of diagnostic delay and help investigators avoid under-identifying potential missed diagnostic opportunities. In addition, the methods we describe can be used to discover less-common presentations of diseases that are frequently misdiagnosed.

Development of a Checklist to Identify Injury Hazards on Row Crop Farms in the Midwestern United States.

Agriculture is among the most dangerous industries in the U.S., yet routine surveillance of injury hazards is not currently being conducted on a national level. The objectives of this study were to describe a new tool, called the Hazard Assessment Checklist (HAC), to identify and characterize farm hazards that increase injury risk to farmers and farm workers, and (2) report the inter-rater reliability of the new tool when administered on row-crop farms in Iowa. Based on a literature review and a consensus of expert opinion, the HAC included hazards related to self-propelled vehicles, powered portable implements, fixed machinery and equipment, farm buildings and structures, fall risks, and portable equipment associated with fall risk. A scoring metric indicating the extent of compliance with recommended safety guidelines and standards was developed for each item of the HAC, which included compliant, minimal improvement needed, substantial improvement needed, and not compliant. Inter-rater reliability was assessed from data collected by research staff on 52 row crop farms in Iowa. Cohen's weighted Kappa values demonstrated high inter-rater reliability, ranging between 0.86 and 0.94, for all HAC sections. The HAC can be completed in 1.5-2 hours on each farm and requires about three hours of training, two hours of which are spent in field training. The ability to monitor injury-related hazards over time using an empirically driven tool will contribute significantly to injury prevention efforts in an industry with consistently high rates of fatal and nonfatal injury.

Should we throw the book at 'em? Charge combinations and conviction rates among alcohol-influenced drivers involved in motorcycle crashes.

INTRODUCTION: Motorcycle fatality rates are increasing, and impaired driving is a major contributing factor. Impaired driving laws are a main component of state efforts to reduce drunk driving, but motorcycle crash charge and conviction outcomes have yet to be studied. The purpose of this study was to evaluate driver charge and conviction outcomes following alcohol-related motorcycle crashes. METHODS: Data for this study were drawn from Iowa crash, charge, and conviction data from 2011 to 2018. The study sample included 480 alcohol-influenced drivers (428 motorcyclists and 52 other vehicle drivers) involved in motorcycle crashes. Driver crash-related charges were categorized by type: Alcohol, Moving Violations, and Administrative/Miscellaneous. Factors associated with convictions were determined and estimated with multivariable logistic regression models. The main factor of interest was charge combination. RESULTS: Over three-quarters (78.5%) of the 480 alcohol-influenced drivers in crashes received any charge type and 68.1% received an alcohol-related charge. Among drivers with any charge, 88.6% were convicted, and among drivers with alcohol charges, 87.2% were convicted on an alcohol charge. After adjusting for BAC, drivers with a combination of Alcohol, Administrative, and Moving Violation charges had more than three times the odds of conviction of any charge compared to drivers with alcohol only charges (OR = 3.21, 95% CI = 1.00-10.26). However, charge combinations had little impact on alcohol-related convictions. CONCLUSIONS: Convictions were more likely when the impaired driver was charged with multiple types of offenses than with a single offense. An increased variety of charges was not associated with greater rates of conviction on alcohol-specific charges, which had high conviction rates overall. PRACTICAL APPLICATIONS: Law enforcement officers should be informed that lesser infractions impact driver conviction outcomes in alcohol-related crashes and procedures for issuing charges should be evaluated to assure equitable enforcement and to hold drivers accountable for unsafe driving behaviors.

Association of Appendicitis Incidence With Warmer Weather Independent of Season.

Importance: Acute appendicitis is a common cause of abdominal pain and the most common reason for emergency surgery in several countries. Increased cases during summer months have been reported. Objective: To investigate the incidence of acute appendicitis by considering local temperature patterns in geographic regions with different climate over several years. Design, Setting, and Participants: This cohort study used insurance claims data from the MarketScan Commercial Claims and Encounters Database and the Medicare Supplemental and Coordination of Benefits Database from January 1, 2001, to December 31, 2017. The cohort included individuals at risk for appendicitis who were enrolled in US insurance plans that contribute data to the MarketScan databases. Cases of appendicitis in the inpatient, outpatient, and emergency department settings were identified using International Classification of Diseases, Ninth Revision, Clinical Modification or International Statistical Classification of Diseases, Tenth Revision, Clinical Modification diagnosis codes. Local weather data were obtained for individuals living in a metropolitan statistical area (MSA) from the Integrated Surface Database. Associations were characterized using a fixed-effects generalized linear model based on a negative binomial distribution. The model was adjusted for age, sex, and day of week and included fixed effects for year and MSA. The generalized linear model was fit with a piecewise linear model by searching each 0.56 °C in temperature for change points. To further isolate the role of temperature, observed temperature was replaced with the expected temperature and the deviation of the observed temperature from the expected temperature for a given city on a given day of year. Data were analyzed from October 1, 2021, to July 31, 2022. Main Outcomes and Measures: The primary outcome was the daily number of appendicitis cases in a given city stratified by age and sex, with mean temperature in the MSA over the previous 7 days as the independent variable. Results: A total of 450 723 744 person-years at risk and 689 917 patients with appendicitis (mean [SD] age, 35 [18] years; 347 473 male [50.4%] individuals) were included. Every 5.56 °C increase in temperature was associated with a 1.3% increase in the incidence of appendicitis (incidence rate ratio [IRR], 1.01; 95% CI, 1.01-1.02) when temperatures were 10.56 °C or lower and a 2.9% increase in incidence (IRR, 1.03; 95% CI, 1.03-1.03) for temperatures higher than 10.56 °C. In terms of temperature deviations, a higher-than-expected temperature increase greater than 5.56 °C was associated with a 3.3% (95% CI, 1.0%-5.7%) increase in the incidence of appendicitis compared with days with near-0 deviations. Conclusions and Relevance: Results of this cohort study observed seasonality in the incidence of appendicitis and found an association between increased incidence and warmer weather. These results could help elucidate the mechanism of appendicitis.

Understanding the Prodromal Period of Necrotizing Soft Tissue Infections of the Genitalia (Fournier's Gangrene) and the Incidence, Duration, and Risk Factors Associated With Potential Missed Opportunities for an Earlier Diagnosis: A Population-based Longitudinal Study.

PURPOSE: The purpose of this paper was to investigate patterns of health care utilization leading up to diagnosis of necrotizing soft tissue infections of the genitalia and to identify risk factors associated with potential diagnostic delay. MATERIALS AND METHODS: IBM MarketScan Research Databases (2001-2020) were used to identify index cases of necrotizing soft tissue infections of the genitalia. We identified health care visits for symptomatically similar diagnoses (eg, penile swelling, cellulitis) that occurred prior to necrotizing soft tissue infections of the genitalia diagnosis. A change-point analysis identified the window before diagnosis where diagnostic opportunities first appeared. A simulation model estimated the likelihood symptomatically similar diagnosis visits represented a missed opportunity for earlier diagnosis. Patient and provider characteristics were evaluated for their associations with delay. RESULTS: We identified 8,098 patients with necrotizing soft tissue infections of the genitalia, in which 4,032 (50%) had a symptomatically similar diagnosis visit in the 21-day diagnostic window, most commonly for "non-infectious urologic abnormalities" (eg, genital swelling; 64%): 46% received antibiotics; 16% saw a urologist. Models estimated that 5,096 of the symptomatically similar diagnosis visits (63%) represented diagnostic delay (mean duration 6.2 days; mean missed opportunities 1.8). Risk factors for delay included urinary tract infection history (OR 2.1) and morbid obesity (OR 1.6). Visits to more than 1 health care provider/location in a 24-hour period significantly decreased delay risk. CONCLUSIONS: Nearly 50% of insured patients who undergo debridement for, or die from, necrotizing soft tissue infections of the genitalia will present to a medical provider with a symptomatically similar diagnosis suggestive of early disease development. Many of these visits likely represent diagnostic delay. Efforts to minimize logistic and cognitive biases in this rare condition may lead to improved outcomes if they lead to earlier interventions.

Frequency and Duration of, and Risk Factors for, Diagnostic Delays Associated with Histoplasmosis.

Histoplasmosis is often confused with other diseases leading to diagnostic delays. We estimated the incidence, length of, and risk factors for, diagnostic delays associated with histoplasmosis. Using data from IBM Marketscan, 2001-2017, we found all patients with a histoplasmosis diagnosis. We calculated the number of visits that occurred prior to the histoplasmosis diagnosis and the number of visits with symptomatically similar diagnoses (SSDs). Next, we estimated the number of visits that represented a delay using a simulation-based approach. We also computed the number of potential opportunities for diagnosis that were missed for each patient and the length of time between the first opportunity and the diagnosis. Finally, we identified risk factors for diagnostic delays using a logistic regression model. The number of SSD-related visits increased significantly in the 97 days prior to the histoplasmosis diagnosis. During this period, 97.4% of patients had a visit, and 90.1% had at least one SSD visit. We estimate that 82.9% of patients with histoplasmosis experienced at least one missed diagnostic opportunity. The average delay was 39.5 days with an average of 4.0 missed opportunities. Risk factors for diagnostic delays included prior antibiotic use, history of other pulmonary diseases, and emergency department and outpatient visits, especially during weekends. New diagnostic approaches for histoplasmosis are needed.

The Rapid Reduction of Infection-Related Visits and Antibiotic Use Among People With Cystic Fibrosis After Starting Elexacaftor-Tezacaftor-Ivacaftor.

BACKGROUND: People with cystic fibrosis (CF) routinely suffer from recurrent sinopulmonary infections. Such infections require frequent courses of antimicrobials and often involve multidrug-resistant organisms. The goal of this study was to identify real-world evidence for the effectiveness of elexacaftor-tezacaftor-ivacaftor (ELX/TEZ/IVA) in decreasing infection-related visits and antimicrobial use in people with CF. METHODS: Using IBM MarketScan data, we identified 389 enrollees with CF who began taking ELX/TEZ/IVA before 1 December 2019 and were enrolled from 1 July 2019 to 14 March 2020. We also identified a comparison population who did not begin ELX/TEZ/IVA during the study period. We compared the following outcomes in the 15 weeks before and after medication initiation: total healthcare visits, inpatient visits, infection-related visits, and antimicrobial prescriptions. We analyzed outcomes using both a case-crossover analysis and a difference-in-differences analysis, to control for underlying trends. RESULTS: For the case-crossover analysis, ELX/TEZ/IVA initiation was associated with the following changes over a 15-week period: change in overall healthcare visit dates, -2.5 (95% confidence interval, -3.31 to -1.7); change in inpatient admissions, -0.16 (-.22 to -.10); change in infection-related visit dates, -0.62 (-.93 to -.31); and change in antibiotic prescriptions, -0.78 (-1.03 to -.54). Results from the difference-in-differences approach were similar. CONCLUSIONS: We show a rapid reduction in infection-related visits and antimicrobial use among people with CF after starting a therapy that was not explicitly designed to treat infections. Currently, there are >30 000 people living with CF in the United States alone. Given that this therapy is effective for approximately 90% of people with CF, the impact on respiratory infections and antimicrobial use may be substantial.

Associations between body mass index and body composition measures in a birth cohort.

BACKGROUND: Associations among body composition measures have been limited to cross-sectional analyses of different subjects. We identified cross-sectional relationships between body mass index (BMI) and other body composition measures and predicted body composition measures from BMI throughout childhood and adolescence. METHODS: BMI was calculated and % body fat (%BF), fat mass index (FMI), and fat-free mass index (FFMI) were measured using dual-energy x-ray absorptiometry at ages 5, 9, 11, 13, 15, and 17 years in a birth cohort (n = 629). Sex-specific body composition measures were calculated for BMI-for-age percentiles; associations between BMI and body composition measures were characterized; and body composition measures were predicted from BMI. RESULTS: %BF, FMI, and FFMI generally increased with BMI-for-age percentiles at each age. Correlations between BMI and %BF or FMI were generally higher at BMI-for-age percentiles ≥95% than for lower BMI-for-age percentiles. Correlations between BMI and FFMI were generally higher for participants at very low and very high BMI-for-age percentiles than at moderate BMI-for-age percentiles. Age- and sex-specific predictions from BMI are provided for %BF, FM, and FFMI. CONCLUSIONS: Sex-specific body composition measures throughout childhood and adolescence are presented. BMI is a better indicator of adiposity at higher than at lower BMI values. IMPACT: Sex-specific body composition measures throughout childhood and adolescence are described. % BF, FMI, and FFMI generally increased with BMI-for-age percentiles for both sexes throughout childhood and adolescence. BMI is a better indicator of adiposity at higher BMI levels than at lower BMI values throughout childhood and adolescence.

Incidence, Duration, and Risk Factors Associated With Missed Opportunities to Diagnose Herpes Simplex Encephalitis: A Population-Based Longitudinal Study.

BACKGROUND: Delays in diagnosing herpes simplex encephalitis (HSE) are associated with increased morbidity and mortality. The purpose of this paper is to determine the frequency and duration of diagnostic delays for HSE and risk factors for diagnostic delays. METHODS: Using data from the IBM Marketscan Databases, 2001-2017, we performed a retrospective cohort study of patients with HSE. We estimated the number of visits with HSE-related symptoms before diagnosis that would be expected to occur in the absence of delays and compared this estimate to the observed pattern of visits. Next, we used a simulation-based approach to compute the number of visits representing a delay, the number of missed diagnostic opportunities per case patient, and the duration of delays. We also investigated potential risk factors for delays. RESULTS: We identified 2667 patients diagnosed with HSE. We estimated 45.9% (95% confidence interval [CI], 43.6%-48.1%) of patients experienced at least 1 missed opportunity; 21.9% (95% CI, 17.3%-26.3%) of these patients had delays lasting >7 days. Risk factors for delays included being seen only in the emergency department, age <65, or a history of sinusitis or schizophrenia. CONCLUSIONS: Many patients with HSE experience multiple missed diagnostic opportunities before diagnosis.

Comparative Effectiveness of Parent-Based Interventions to Support Injured Children.

OBJECTIVES: A comparative effectiveness trial tested 2 parent-based interventions in improving the psychosocial recovery of hospitalized injured children: (1) Link for Injured Kids (Link), a program of psychological first aid in which parents are taught motivational interviewing and stress-screening skills, and (2) Trauma Education, based on an informational booklet about trauma and its impacts and resources. METHODS: A randomized controlled trial was conducted in 4 children's hospitals in the Midwestern United States. Children aged 10 to 17 years admitted for an unintentional injury and a parent were recruited and randomly assigned to Link or Trauma Education. Parents and children completed questionnaires at baseline, 6 weeks, 3 months, and 6 months posthospitalization. Using an intent-to-treat analysis, changes in child-reported posttraumatic stress symptoms, depression, quality of life, and child behaviors were compared between intervention groups. RESULTS: Of 795 injured children, 314 children and their parents were enrolled into the study (40%). Link and Trauma Education was associated with improved symptoms of posttraumatic stress, depression, and pediatric quality of life at similar rates over time. However, unlike those in Trauma Education, children in the Link group had notable improvement of child emotional behaviors and mild improvement of conduct and peer behaviors. Compared with Trauma Education, Link was also associated with improved peer behaviors in rural children. CONCLUSION: Although children in both programs had reduced posttrauma symptoms over time, Link children, whose parents were trained in communication and referral skills, exhibited a greater reduction in problem behaviors.