An all-inclusive model for predicting invasive bacterial infection in febrile infants age 7-60 days.

BACKGROUND: Invasive bacterial infections (IBIs) in febrile infants are rare but potentially devastating. We aimed to derive and validate a predictive model for IBI among febrile infants age 7-60 days. METHODS: Data were abstracted retrospectively from electronic records of 37 emergency departments (EDs) for infants with a measured temperature >=100.4 F who underwent an ED evaluation with blood and urine cultures. Models to predict IBI were developed and validated respectively using a random 80/20 dataset split, including 10-fold cross-validation. We used precision recall curves as the classification metric. RESULTS: Of 4411 eligible infants with a mean age of 37 days, 29% had characteristics that would likely have excluded them from existing risk stratification protocols. There were 196 patients with IBI (4.4%), including 43 (1.0%) with bacterial meningitis. Analytic approaches varied in performance characteristics (precision recall range 0.04-0.29, area under the curve range 0.5-0.84), with the XGBoost model demonstrating the best performance (0.29, 0.84). The five most important variables were serum white blood count, maximum temperature, absolute neutrophil count, absolute band count, and age in days. CONCLUSION: A machine learning model (XGBoost) demonstrated the best performance in predicting a rare outcome among febrile infants, including those excluded from existing algorithms. IMPACT: Several models for the risk stratification of febrile infants have been developed. There is a need for a preferred comprehensive model free from limitations and algorithm exclusions that accurately predicts IBIs. This is the first study to derive an all-inclusive predictive model for febrile infants aged 7-60 days in a community ED sample with IBI as a primary outcome. This machine learning model demonstrates potential for clinical utility in predicting IBI.

CA FIRST (California Febrile Infant Risk Stratification Tool) Algorithm Development in a Learning Health System.

Introduction There is considerable variation in the approach to infants presenting to the emergency department (ED) with fever. The authors' primary aim was to develop a robust set of algorithms using community ED data to inform modifications of broader clinical guidance. Methods The authors report the development of California Febrile Infant Risk Stratification Tool (CA FIRST) using key components of the Roseville Protocol (ROS) and American Academy of Pediatrics (AAP) Clinical Practice Guideline (CPG). Expanded guidance was derived using a retrospective analysis of a cohort of 3527 febrile infants aged 7-90 days presenting to any Kaiser Permanente Northern California ED between 2010 and 2019 who underwent a core febrile infant evaluation. Results Melding ROS and AAP CPG algorithms in infants 7-60 days old, CA FIRST Algorithms had comparable performance characteristics to ROS and AAP CPG. CA FIRST enhancements included guidance on febrile infants 61-90 days old, high-risk infants, infants with bronchiolitis, and infants who received immunizations within the prior 48 hours. This retrospective analysis revealed that of 235 febrile infants 22-90 days old with respiratory syncytial virus and 221 who had fever in the 48 hours following vaccination, there were no cases of invasive bacterial infection. Discussion CA FIRST is a set of 13 algorithms providing a thoughtful and flexible approach to the febrile infant while minimizing unnecessary interventions. Conclusions CA FIRST Algorithms empower clinicians to manage most febrile infants. Algorithms are being modified as new data become available, imparting useful and ever-current educational information within a learning health care system.

Factors Associated With Firearm Injury Among Pediatric Members of a Large Integrated Healthcare System.

BACKGROUND AND OBJECTIVES: Few studies have tested multiple socio-ecological risk factors assocated with firearm injury among pediatric populations and distinguished self-inflicted from non-self-inflicted injury. To address this gap, the current study examined demographic, individual psychosocial, and neighborhood variables as risk factors for firearm injury among a large cohort of children and adolescents. METHODS: Retrospective cohort study. Data were obtained from the electronic health records of a large integrated healthcare system. The cohort included children <18 years with at least one clinical encounter between January 1, 2010 and December 31, 2018. Poisson regression was used to examine demographic (age, gender, race and ethnicity, Medicaid status), psychosocial (depression, substance use disorder, medical comorbidities), and neighborhood education variables as potential risk factors for non-self-inflicted and self-inflicted firearm injuries. RESULTS: For non-self-inflicted injury, the highest relative risk was found for children age 12-17 years old compared to 0-5 year olds (RR = 37.57); other risk factors included male gender, Black and Hispanic race and ethnicity (compared to White race), being a Medicaid recipient, lower neighborhood education, and substance use disorder diagnosis. For self-inflicted injury, only age 12-17 years old and male gender were associated with increased risk. CONCLUSIONS: These results reinforce the established higher risk for firearm injury among adolescent males, highlight differences between self-inflicted and non-self-inflicted injuries, and the need to consider demographic, psychosocial, and neighborhood variables as risk factors to inform interventions aimed to reduce firearm injuries among children and adolescents.

Patient and Visit Characteristics Associated With Physical Restraint Use in the Emergency Department.

Objective Physical restraints are used in emergency departments (EDs) to address behavioral emergencies in situations in which less restrictive methods have failed. The objective of this study was to evaluate for associations between patient/visit characteristics and physical restraint use. Study Design This study was designed as a cross-sectional, retrospective study of all encounters at Kaiser Permanente Northern California EDs from January 1, 2016, to December 31, 2019, to evaluate differences in patient and visit characteristics between visits involving physical restraint use and those without. Methods Using electronic health record data, this study identified physical restraint use among ED encounters and extracted demographic, clinical, and facility characteristics. The authors calculated odds ratios for physical restraint placement, adjusting for patient and visit characteristics and accounting for within-patient clustering. Results Among 4,410,816 encounters (representing 1,791,673 patients), 6369 encounters (0.1%) involved physical restraint use among 5,554 patients (0.3%). Variables associated with the lowest odds of physical restraint included female sex, presentation to the ED in more recent years, and presence of intentional self-harm/suicidal ideation. Variables associated with the highest odds of physical restraint included higher visit acuity and weekend presentations to the ED. Discussion This study, which leveraged a large, diverse patient sample generalizable to the Northern California population, found several patient and visit characteristics associated with physical restraint use in the ED. Conclusion Results of this study may help identify patient groups and situational factors that are most likely to lead to physical restraint use and structural factors contributing to disparities in care, thereby informing interventions to reduce physical restraint use when possible.

Development and validation of the COVID-19 Hospitalized Patient Deterioration Index.

OBJECTIVES: To develop a COVID-19-specific deterioration index for hospitalized patients: the COVID Hospitalized Patient Deterioration Index (COVID-HDI). This index builds on the proprietary Epic Deterioration Index, which was not developed for predicting respiratory deterioration events among patients with COVID-19. STUDY DESIGN: A retrospective observational cohort was used to develop and validate the COVID-HDI model to predict respiratory deterioration or death among hospitalized patients with COVID-19. Deterioration events were defined as death or requiring high-flow oxygen, bilevel positive airway pressure, mechanical ventilation, or intensive-level care within 72 hours of run time. The sample included hospitalized patients with COVID-19 diagnoses or positive tests at Kaiser Permanente Southern California between May 3, 2020, and October 17, 2020. METHODS: Machine learning models and 118 candidate predictors were used to generate benchmark performance. Logit regression with least absolute shrinkage and selection operator and physician input were used to finalize the model. Split-sample cross-validation was used to train and test the model. RESULTS: The area under the receiver operating curve was 0.83. COVID-HDI identifies patients at low risk (negative predictive value [NPV] > 98.5%) and borderline low risk (NPV > 95%) of an event. Of all patients, 74% were identified as being at low or borderline low risk at some point during their hospitalization and could be considered for discharge with or without home monitoring. A high-risk group with a positive predictive value of 51% included 12% of patients. Model performance remained high in a recent cohort of patients. CONCLUSIONS: COVID-HDI is a parsimonious, well-calibrated, and accurate model that may support clinical decision-making around discharge and escalation of care.

Using AAP Guidelines for Managing Febrile Infants Without C-Reactive Protein and Procalcitonin.

BACKGROUND AND OBJECTIVES: In 2021, the American Academy of Pediatrics (AAP) published the Clinical Practice Guideline (CPG) for management of well-appearing, febrile infants 8 to 60 days old. For older infants, the guideline relies on several inflammatory markers, including tests not rapidly available in many settings like C-reactive protein (CRP) and procalcitonin (PCT). This study describes the performance of the AAP CPG for detecting invasive bacterial infections (IBI) without using CRP and PCT. METHODS: This retrospective cohort study included infants aged 8 to 60 days old presenting to Kaiser Permanente Northern California emergency departments between 2010 and 2019 with temperatures ≥38°C who met AAP CPG inclusion criteria and underwent complete blood counts, blood cultures, and urinalyses. Performance characteristics for detecting IBI were calculated for each age group. RESULTS: Among 1433 eligible infants, there were 57 (4.0%) bacteremia and 9 (0.6%) bacterial meningitis cases. Using absolute neutrophil count >5200/mm3 and temperature >38.5°C as inflammatory markers, 3 (5%) infants with IBI were misidentified. Sensitivities and specificities for detecting infants with IBIs in each age group were: 8 to 21 days: 100% (95% confidence interval [CI] 83.9%-100%) and 0% (95% CI 0%-1.4%); 22 to 28 days: 88.9% (95% CI 51.8%-99.7%) and 40.4% (95% CI 33.2%- 48.1%); and 29 to 60 days: 93.3% (95% CI 77.9%-99.2%) and 32.1% (95% CI 29.1%- 35.3%). Invasive interventions were recommended for 100% of infants aged 8 to 21 days; 58% to 100% of infants aged 22 to 28 days; and 0% to 69% of infants aged 29 to 60 days. CONCLUSIONS: When CRP and PCT are not available, the AAP CPG detected IBI in young, febrile infants with high sensitivity but low specificity.

Social risks and social needs in a health insurance exchange sample: a longitudinal evaluation of utilization.

BACKGROUND: Health systems are increasingly attempting to intervene on social adversity as a strategy to improve health care outcomes. To inform health system efforts to screen for social adversity, we sought to explore the stability of social risk and interest in assistance over time and to evaluate whether the social risk was associated with subsequent healthcare utilization. METHODS: We surveyed Kaiser Permanente members receiving subsidies from the healthcare exchange in Southern California to assess their social risk and desire for assistance using the Accountable Health Communities instrument. A subset of initial respondents was randomized to be re-surveyed at either three or six months later. RESULTS: A total of 228 participants completed the survey at both time points. Social risks were moderate to strongly stable across three and six months (Kappa range = .59-.89); however, social adversity profiles that included participants' desire for assistance were more labile (3-month Kappa = .52; 95% CI = .41-.64 & 6-month Kappa = .48; 95% CI = .36-.6). Only housing-related social risks were associated with an increase in acute care (emergency, urgent care) six months after initial screening; no other associations between social risk and utilization were observed. CONCLUSIONS: This study suggests that screening for social risk may be appropriate at intervals of six months, or perhaps longer, but that assessing desire for assistance may need to occur more frequently. Housing risks were associated with increases in acute care. Health systems may need to engage in screening and referral to resources to improve overall care and ultimately patient total health.

The impact of stay-at-home orders on the rate of emergency department child maltreatment diagnoses.

BACKGROUND: There is limited data regarding the rates and severity of child maltreatment in medical settings during the COVID-19 pandemic, and the reports are somewhat contradictory. OBJECTIVE: To examine the rates of emergency department (ED) child maltreatment (CM) diagnosis before and after the California statewide stay-at-home order, as well as potential disparities by age, gender, race/ethnicity, and Medicaid status. METHODS: A retrospective pre-post interrupted time series was conducted using data from the electronic health records of children (<18 years) with at least one emergency department visit between January 1, 2019 and September 30, 2021. Enactment of the stay-at-home order in California, March 2020 was used to determine a change in trend of rates of diagnosis of CM in the ED. RESULTS: Overall the study included 407,228 pediatric ED visits. There was a significant change in the percentage of CM visits immediately after the stay-at-home order, followed by small month to month decreases returning to near pre-stay-at-home order levels. This significant increase was driven by higher risk for children <4 years old. The increased rate of CM in the first month after the stay-at-home order was also elevated for female, Black, and Hispanic children. CONCLUSIONS: Our results indicated the rates of CM diagnoses in the ED doubled after the March 2020 stay-at-home order in California. Additionally, our findings suggest that some children may be at higher risk than others, which supports the importance of social safety nets for children in times of national emergency.

Clinical management and outcomes for febrile infants 29-60 days evaluated in community emergency departments.

Objective: Describe emergency department (ED) management and patient outcomes for febrile infants 29-60 days of age who received a lumbar puncture (LP), with focus on timing of antibiotics and type of physician performing LP. Methods: Retrospective observational study of 35 California EDs from January 1, 2010 through December 31, 2019. Primary analysis was among patients with successful LP and primary outcome was hospital length of stay (LOS). Logistic regression analysis included variables associated with LOS of at least 2 days. Secondary outcomes were bacterial meningitis, hospital admission, length of antibiotics, and readmission. Results: Among 2569 febrile infants (median age 39 days), 667 underwent successful LP and 633 received intravenous antibiotics. Most infants (n = 559, 88.3%) had their LP before intravenous antibiotic administration. Pediatricians performed 54% of LPs and emergency physicians 34%. Sixteen infants (0.6% of 2569) were diagnosed with bacterial meningitis, and none died. Five hundred and fifty-eight (88%) infants receiving an LP were hospitalized. Among patients receiving an LP and antibiotics (n = 633), 6.5% were readmitted within 30 days. Patients receiving antibiotics before LP had a longer length of antibiotics (+ 7.9 hours, 95% confidence interval [CI] 3.8-13.4). Primary analysis found no association between timing of antibiotics and LOS (odds ratio [OR] 0.67, 95% CI 0.34-1.30), but shorter LOS when emergency physicians performed the LP (OR 0.66, 95% CI 0.45-0.97). Conclusions: Febrile infants in the ED had no deaths and few cases of bacterial meningitis. In community EDs, where a pediatrician is often not available, successful LP by emergency physician was associated with reduced inpatient LOS.

Opioid and Naloxone Prescribing Following Insertion of Prompts in the Electronic Health Record to Encourage Compliance With California State Opioid Law.

Importance: Opioid addiction or dependency is a serious crisis in the US that affects public health as well as social and economic welfare. The State of California passed Assembly Bill (AB) 2760 in 2018 that mandates the coprescription of naloxone and opioids for patients with a high overdose risk. Objective: To assess whether the AB 2760-based electronic prompts were associated with increased naloxone orders for opioid users and reduced opioid prescribing when integrated into the practitioner workflow. Design, Setting, and Participants: This cohort study used interrupted time series mixed models to evaluate data obtained from the regional integrated health care system Kaiser Permanente Southern California (KPSC) from January 1, 2018, to December 31, 2019. Clinician participants were continuously employed at KPSC during the study period and ordered an opioid analgesic for eligible patients in 2018. Patient participants were KPSC members aged 18 years or older who received an opioid analgesic prescription during the study period. A series of AB 2760-based electronic prompts were integrated into the KPSC electronic health record system on December 27, 2018. The prompts are triggered or activated when 1 or more opioid prescribing conditions, defined in the AB 2760, are met at outpatient visits. Data were analyzed from January 8, 2021, to September 15, 2021. Exposures: Assembly Bill 2760-based electronic prompts for outpatient opioid prescriptions in the electronic health record system. Main Outcomes and Measures: Primary outcomes were changes in outpatient naloxone order rates among patients who were prescribed opioids and changes in outpatient opioid prescribing rates. Secondary outcomes were total morphine milligram equivalents (MMEs) ordered per prescriber-month, prompts-targeted objectives, and unintended consequences. Risk for opioid abuse among 3 types of patients was also assessed. Results: The 6515 eligible clinicians (mean [SD] age, 45.9 [9.43] years; 3604 men [55.3%]) included in the study served 500 711 unique patients in 1 903 289 outpatient encounters (mean [SD] age, 60.4 [15.67] years; 1 121 004 women [58.9%]) in which an opioid analgesic was prescribed. Naloxone order rate increased from 2.0% in December 2018 to 13.2% in January 2019 and then continued to increase to 27.1% in December 2019. Outpatient opioid prescribing rates decreased by 15.1% (rate ratio [RR], 0.85; 95% CI, 0.83-0.87) per prescriber-month when the electronic prompts were implemented. The postimplementation trend increased by 0.7% per prescriber-month (RR, 1.01; 95% CI, 1.01-1.01); the overall trend was still decreasing. The total MMEs per prescriber-month decreased by 7.8% (RR, 0.92; 95% CI, 0.89-0.96) after implementation of the prompts. The postimplementation trend tapered off. Other safe opioid prescribing measures also improved after implementation (decreases in concomitant muscle relaxants orders [RR, 0.94; 95% CI, 0.89-1.00], initial [RR, 0.86; 0.83-0.89] and renewal [RR, 0.65; 95% CI, 0.62-0.69] opioid orders, and long-term high-dose orders [RR, 0.96; 95% CI, 0.94-0.98]). Conclusions and Relevance: This study found an association between implementation of AB 2760-based prompts and increased naloxone order rate; improved opioid prescribing measures (ie, decreased concomitant muscle relaxants orders, initial and renewal opioid orders, and long-term high-dose orders), except monthly median MMEs; and reduced opioid prescribing. The findings suggest that opioid overdose risks can be mitigated by encouraging safe prescribing habits.

Social Risk Factors and Desire for Assistance Among Patients Receiving Subsidized Health Care Insurance in a US-Based Integrated Delivery System.

PURPOSE: Because social conditions such as food insecurity and housing instability shape health outcomes, health systems are increasingly screening for and addressing patients' social risks. This study documented the prevalence of social risks and examined the desire for assistance in addressing those risks in a US-based integrated delivery system. METHODS: A survey was administered to Kaiser Permanente members on subsidized exchange health insurance plans (2018-2019). The survey included questions about 4 domains of social risks, desire for help, and attitudes. We conducted a descriptive analysis and estimated multivariate modified Poisson regression models. RESULTS: Of 438 participants, 212 (48%) reported at least 1 social risk factor. Housing instability was the most common (70%) factor reported. Members with social risks reported more discomfort being screened for social risks (14.2% vs 5.4%; P = .002) than those without risks, although 90% of participants believed that health systems should assist in addressing social risks. Among those with 1-2 social risks, however, only 27% desired assistance. Non-Hispanic Black participants who reported a social risk were more than twice as likely to desire assistance compared with non-Hispanic White participants (adjusted relative risk [RR] 2.2; 95% CI, 1.3-3.8). CONCLUSIONS: Athough most survey participants believed health systems have a role in addressing social risks, a minority of those reporting a risk wanted assistance and reported more discomfort being screened for risk factors than those without risks. Health systems should work to increase the comfort of patients in reporting risks, explore how to successfully assist them when desired, and offer resources to address these risks outside the health care sector.VISUAL ABSTRACT.

Healthcare Utilization Among Patients Diagnosed with COVID-19 in a Large Integrated Health System.

BACKGROUND: The demands for healthcare resources following a COVID-19 diagnosis are substantial, but not currently quantified. OBJECTIVE: To describe trends in healthcare utilization within 180 days for patients diagnosed with COVID-19 and identify patient factors associated with increased healthcare use. DESIGN: Observational cohort study. PATIENTS: A total of 64,011 patients with a test-confirmed COVID-19 diagnosis from March to September 2020 in a large integrated healthcare system in Southern California. MAIN MEASURES: Overall healthcare utilization during the 180 days following COVID-19 diagnosis, as well as encounter types and reasons for visits during the first 30 days. Poisson regression was used to identify patient factors associated with higher utilization. Analyses were performed separately for patients who were and were not hospitalized for COVID-19. KEY RESULTS: Healthcare utilization was about twice as high for hospitalized patients compared to non-hospitalized patients in all time periods. The average number of visits was highest in the first 30 days (hospitalized: 12.3 visits/30 person-days; non-hospitalized: 6.6) and gradually decreased over time. In the first 30 days, the majority of healthcare visits were telehealth encounters (hospitalized: 9.0 visits; non-hospitalized: 5.6 visits), and the most prevalent reasons for visits were COVID-related diagnoses, COVID-related symptoms, and respiratory-related conditions. For hospitalized patients, older age (≥65: RR 1.27, 95% CI 1.15-1.41), female gender (RR 1.07, 95% CI 1.05-1.09), and higher BMI (≥40: RR 1.07, 95% CI 1.03-1.10) were associated with higher total utilization. For non-hospitalized patients, older age, female gender, higher BMI, non-white race/ethnicity, former smoking, and greater number of pre-existing comorbidities were all associated with increased utilization. CONCLUSIONS: Patients with COVID-19 seek healthcare frequently within 30 days of diagnosis, placing high demands on health systems. Identifying ways to support patients diagnosed with COVID-19 while adequately providing the usual recommended care to our communities will be important as we recover from the pandemic.

Automated interpretation of stress echocardiography reports using natural language processing.

Aims: Stress echocardiography (SE) findings and interpretations are commonly documented in free-text reports. Reusing SE results requires laborious manual reviews. This study aimed to develop and validate an automated method for abstracting SE reports in a large cohort. Methods and results: This study included adult patients who had SE within 30 days of their emergency department visit for suspected acute coronary syndrome in a large integrated healthcare system. An automated natural language processing (NLP) algorithm was developed to abstract SE reports and classify overall SE results into normal, non-diagnostic, infarction, and ischaemia categories. Randomly selected reports (n = 140) were double-blindly reviewed by cardiologists to perform criterion validity of the NLP algorithm. Construct validity was tested on the entire cohort using abstracted SE data and additional clinical variables. The NLP algorithm abstracted 6346 consecutive SE reports. Cardiologists had good agreements on the overall SE results on the 140 reports: Kappa (0.83) and intraclass correlation coefficient (0.89). The NLP algorithm achieved 98.6% specificity and negative predictive value, 95.7% sensitivity, positive predictive value, and F-score on the overall SE results and near-perfect scores on ischaemia findings. The 30-day acute myocardial infarction or death outcomes were highest among patients with ischaemia (5.0%), followed by infarction (1.4%), non-diagnostic (0.8%), and normal (0.3%) results. We found substantial variations in the format and quality of SE reports, even within the same institution. Conclusions: Natural language processing is an accurate and efficient method for abstracting unstructured SE reports. This approach creates new opportunities for research, public health measures, and care improvement.

Injuries Associated With Subsequent Child Maltreatment Diagnosis: By Age, Race, Gender, and Medicaid Status.

This study examined injuries that may precede a child maltreatment (CM) diagnosis, by age, race/ethnicity, gender, and Medicaid status using a retrospective case-control design among child members of a large integrated healthcare system (N = 9152 participants, n = 4576 case). Injury categories based on diagnosis codes from medical visits were bruising, fractures, lacerations, head injury, burns, falls, and unspecified injury. Results showed that all injury categories were significant predictors of a subsequent CM diagnosis, but only for children < 3 years old. Specifically, fracture and head injury were the highest risk for a subsequent CM diagnosis. All injury types were significant predictors of maltreatment diagnosis for Hispanic children < 3 years, which was not the case for the other race/ethnicities. Overall, these findings suggest that all types of injury within these specific categories should have a more thorough assessment for possible abuse for children under 3 years. This work can inform the development of clinical decision support tools to aid healthcare providers in detecting abusive injuries.

Does Hospital Admission/Observation for Chest Pain Improve Patient Outcomes after Emergency Department Evaluation for Suspected Acute Coronary Syndrome?

BACKGROUND: Chest pain is the top reason for hospitalization/observation in the USA, but it is unclear if this strategy improves patient outcomes. OBJECTIVE: The objective of this study was to compare 30-day outcomes for patients admitted versus discharged after a negative emergency department (ED) evaluation for suspected acute coronary syndrome. DESIGN: A retrospective, multi-site, cohort study of adult encounters with chest pain presenting to one of 13 Kaiser Permanente Southern California EDs between January 1, 2015, and December 1, 2017. Instrumental variable analysis was used to mitigate potential confounding by unobserved factors. PATIENTS: All adult patients presenting to an ED with chest pain, in whom an acute myocardial infarction was not diagnosed in the ED, were included. MAIN MEASURES: The primary outcome was 30-day acute myocardial infarction or all-cause mortality, and secondary outcomes included 30-day revascularization and major adverse cardiac events. KEY RESULTS: In total, 77,652 patient encounters were included in the study (n=11,026 admitted, 14.2%). Three hundred twenty-two (0.4%) had an acute myocardial infarction (n=193, 0.2%) or death (n=137, 0.2%) within 30 days of ED visit (1.5% hospitalized versus 0.2% discharged). Very few (0.3%) patients underwent coronary revascularization within 30 days (0.7% hospitalized versus 0.2% discharged). Instrumental variable analysis found no adjusted differences in 30-day patient outcomes between the hospitalized cohort and those discharged (risk reduction 0.002, 95% CI -0.002 to 0.007). Similarly, there were no differences in coronary revascularization (risk reduction 0.003, 95% CI -0.002 to 0.007). CONCLUSION: Among ED patients with chest pain not diagnosed with an acute myocardial infarction, risk of major adverse cardiac events is quite low, and there does not appear to be any benefit in 30-day outcomes for those admitted or observed in the hospital compared to those discharged with outpatient follow-up.

Automated abstraction of myocardial perfusion imaging reports using natural language processing.

BACKGROUND: Findings and interpretations of myocardial perfusion imaging (MPI) studies are documented in free-text MPI reports. MPI results are essential for research, but manual review is prohibitively time consuming. This study aimed to develop and validate an automated method to abstract MPI reports. METHODS: We developed a natural language processing (NLP) algorithm to abstract MPI reports. Randomly selected reports were double-blindly reviewed by two cardiologists to validate the NLP algorithm. Secondary analyses were performed to describe patient outcomes based on abstracted-MPI results on 16,957 MPI tests from adult patients evaluated for suspected ACS. RESULTS: The NLP algorithm achieved high sensitivity (96.7%) and specificity (98.9%) on the MPI categorical results and had a similar degree of agreement compared to the physician reviewers. Patients with abnormal MPI results had higher rates of 30-day acute myocardial infarction or death compared to patients with normal results. We identified issues related to the quality of the reports that not only affect communication with referring physicians but also challenges for automated abstraction. CONCLUSION: NLP is an accurate and efficient strategy to abstract results from the free-text MPI reports. Our findings will facilitate future research to understand the benefits of MPI studies but requires validation in other settings.

Are Mental Health and Substance Use Disorders Risk Factors for Missed Acute Myocardial Infarction Diagnoses Among Chest Pain or Dyspnea Encounters in the Emergency Department?

STUDY OBJECTIVE: To assess if having a mental health and/or substance use disorder is associated with a missed acute myocardial infarction diagnosis in the emergency department (ED). METHODS: This was a retrospective cohort analysis (2009 to 2017) of adult ED encounters at Kaiser Permanente Southern California. We used the validated symptom-disease pair analysis of diagnostic error methodological approach to "look back" and "look forward" and identify missed acute myocardial infarctions within 30 days of a treat-and-release ED visit. We use adjusted logistic regression to report the odds of missed acute myocardial infarction among patients with a history of mental health and/or substance use disorders. RESULTS: The look-back analysis identified 44,473 acute myocardial infarction hospital encounters; 574 (1.3%) diagnoses were missed. The odds of missed diagnoses were higher in patients with mental health disorders (odds ratio [OR] 1.48, 95% confidence interval [CI] 1.23 to 1.77) but not in those with substance abuse disorders (OR 1.22, 95% CI 0.91 to 1.62). The highest risk was observed in those with co-occurring disorders (OR 1.90, 95% CI 1.30 to 2.76). The look-forward analysis identified 325,088 chest pain/dyspnea ED encounters; 508 (0.2%) were missed acute myocardial infarctions. No significant associations of missed acute myocardial infarction were revealed in either group (mental health disorder: OR 0.92, 95% CI 0.71 to 1.18; substance use disorder: OR 1.22, 95% CI 0.80 to 1.85). CONCLUSION: The look-back analysis identified patients with mental illness at increased risk of missed acute myocardial infarction diagnosis, with the highest risk observed in those with a history of comorbid substance abuse. Having substance use disorders alone did not increase this risk in either cohort. The look-forward analysis revealed challenges in prospectively identifying high-risk patients to target for improvement.

The Effectiveness of Neuromuscular Warmups for Lower Extremity Injury Prevention in Basketball: A Systematic Review.

BACKGROUND: Neuromuscular warmups have gained increasing attention as a means of preventing sports-related injuries, but data on effectiveness in basketball are sparse. The objective of this systematic review was to evaluate evidence of the effectiveness of neuromuscular warmup-based strategies for preventing lower extremity injuries among basketball athletes. METHODS: PubMed and Cochrane Library databases were searched in February 2019. Studies were included if they were English-language randomized controlled, non-randomized comparative, or prospective cohort trials, tested neuromuscular and/or balance-focused warmup interventions among basketball players, and assessed at least one type of lower extremity injury as a primary outcome. Criteria developed by the USPSTF were used to appraise study quality, and GRADE was used to appraise the body of evidence for each outcome. Due to heterogeneity in the included studies, meta-analyses could not be performed. RESULTS: In total, 825 titles and abstracts were identified. Of the 13 studies which met inclusion criteria for this review, five were balance interventions (3 randomized controlled trials) and eight were multicomponent interventions involving multiple categories of dynamic neuromuscular warmup (5 randomized controlled trials). Authors of four of the studies were contacted to obtain outcome data specific to basketball athletes. Basketball specific results from the studies suggest significant protective effects for the following lower extremity injuries: ankle injuries (significant in 4 out of the 9 studies that assessed this outcome); ACL injuries (2 of 4 studies); knee injuries generally (1 of 5 studies); and overall lower extremity injuries (5 of 7 studies). All but one of the non-significant results were directionally favorable. Evidence was moderate for the effect of multicomponent interventions on lower extremity injuries generally. For all other outcomes, and for balance-based interventions, the quality of evidence was rated as low. CONCLUSION: Overall, the evidence is supportive of neuromuscular warmups for lower extremity injury prevention among basketball players. However, most studies are underpowered, some used lower-quality research study designs, and outcome and exposure definitions varied. Due to the nature of the study designs, effects could not be attributed to specific intervention components. More research is needed to identify the most effective bundle of warmup activities.

High School Basketball Coach and Player Perspectives on Warm-Up Routines and Lower Extremity Injuries.

BACKGROUND: While participation in sports-related activities results in improved health outcomes, high school athletes are at risk for lower extremity injuries, especially ankle, knee, and thigh injuries. Efforts to promote the adoption and implementation of evidence-driven approaches to reduce injury risk among school-aged athletes are needed. However, there is limited research regarding the perceived barriers, facilitators, and adherence factors that may influence the successful implementation of effective warm-up routines among this population. METHODS: We conducted a qualitative study using semi-structured interviews and focus groups to assess high school basketball coach and player current practices, knowledge, and perspectives about warm-ups and lower-extremity injuries (LEIs). We interviewed coaches (n = 12) and players (n = 30) from May to October 2019. Participants were recruited from public high schools in a joint school district in Southern California. Multiple coders employed thematic analysis of the data using validated methods. RESULTS: Coaches and players reported regular engagement (e.g., daily) in warm-up routines, but the time dedicated (range 5-45 min), types of exercises, and order varied substantially. Players often co-lead the warm-up practice with the coach or assistant coach. Despite regular engagement in warm-up, players and coaches report multiple challenges, including (1) limited time and space to warm-up effectively at games, (2) a perception that young players are not prone to injury, (3) competing demands for coaches' time during practice, and (4) coaches' lack of knowledge. Coaches and players perceive that warming up before practice will result in fewer injuries, and many players are motivated to warm up as a result of their personal injury experience; however, they desire guidance on the ideal exercises for preventing injury and training on the proper form for each exercise. CONCLUSIONS: Regular involvement in basketball warm-up routines is common among high school teams, but the methods and time dedicated to these practices varied. Players and coaches are eager for more information on warm-up programs shown to reduce LEIs.