Prognostic Value of Stress Myocardial Perfusion Imaging Across the Spectrum of Cardiovascular Risk.

BACKGROUND: Single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) is widely used to identify ischemia. There is limited research to evaluate if there is a risk threshold below which SPECT-MPI may not add significant prognostic value. METHODS: Between January 1, 2012, and December 31, 2018, individuals who underwent SPECT-MPI were stratified into four risk groups. The primary outcome was acute myocardial infarction (MI) or death. Multivariable Cox proportional hazards regression analysis was used to calculated HRs with 95% CIs. RESULTS: Among 48,845 patients (52.3% male, median age 67 years), 8.5% were low risk, 4.8% borderline risk, 18.1% intermediate risk, and 68.6% high risk based on the American College of Cardiology pooled cohort equation. Ischemia was more commonly detected in the high-risk cohort (19.4% in high-risk vs. 6.5% in low-risk). SPECT-MPI testing was associated with a significantly increased use of preventive medications such as statin therapy, regardless of stress test results. At a median follow-up of 4.2 years, there was no significant association between ischemia and death or MI in the low-risk cohort (adjusted HR 1.91, 95% CI 0.94-3.92) or the borderline-risk cohort (adjusted HR 1.58, 95% CI 0.79-3.15). Ischemia was associated with a higher risk of death or MI in the intermediate-risk (adjusted HR 1.57, 95% CI 1.24-1.99) and high-risk groups (adjusted HR 1.54, 95% CI 1.44-1.64). CONCLUSION: SPECT-MPI was less useful for risk stratification among low-risk patients due to their low event rates regardless of test result.

Exploring risk factors and their differences on suicidal ideation and suicide attempts among depressed adolescents based on decision tree model.

BACKGROUND: Suicide has been recognized as a major global public health issue. Depressed adolescents are more prone to experiencing it. We explore risk factors and their differences on suicidal ideation and suicide attempts to further enhance our understanding of suicidal behavior. METHODS: 2343 depressed adolescents aged 12-18 from 9 provinces/cities in China participated in this cross-sectional study. We utilized decision tree model, incorporating 32 factors encompassing participants' suicidal behavior. The feature importance of each factor was measured using Gini coefficients. RESULTS: The decision tree model demonstrated a good fit with high accuracy (SI = 0.86, SA = 0.85 and F-Score (SI = 0.85, SA = 0.83). The predictive importance of each factor varied between groups with suicidal ideation and with suicide attempts. The most significant risk factor in both groups was depression (SI = 16.7 %, SA = 19.8 %). However, factors such as academic stress (SI = 7.2 %, SA = 1.6 %), hopelessness (SI = 9.1 %, SA = 5.0 %), and age (SI = 7.1 %, SA = 3.2 %) were more closely associated with suicidal ideation than suicide attempts. Factors related to the schooling status (SI = 3.5 %, SA = 10.1 %), total years of education (SI = 2.6 %, SA = 8.6 %), and loneliness (SI = 2.3 %, SA = 7.4 %) were relatively more important in the suicide attempt stage compared to suicidal ideation. LIMITATIONS: The cross-sectional design limited the ability to capture changes in suicidal behavior among depressed adolescents over time. Possible bias may exist in the measurement of suicidal ideation. CONCLUSION: The relative importance of each risk factor for suicidal ideation and attempted suicide varies. These findings provide further empirical evidence for understanding suicide behavior. Targeted treatment measures should be taken for different stages of suicide in clinical interventions.

Mortality Outcomes in a Large Population with and without Covert Cerebrovascular Disease.

Covert cerebrovascular disease (CCD) is frequently reported on neuroimaging and associates with increased dementia and stroke risk. We aimed to determine how incidentally-discovered CCD during clinical neuroimaging in a large population associates with mortality. We screened CT and MRI reports of adults aged ≥50 in the Kaiser Permanente Southern California health system who underwent neuroimaging for a non-stroke clinical indication from 2009-2019. Natural language processing identified incidental covert brain infarcts (CBI) and/or white matter hyperintensities (WMH), grading WMH as mild/moderate/severe. Models adjusted for age, sex, ethnicity, multimorbidity, vascular risks, depression, exercise, and imaging modality. Of n=241,028, the mean age was 64.9 (SD=10.4); mean follow-up 4.46 years; 178,554 (74.1%) had CT; 62,474 (25.9%) had MRI; 11,328 (4.7%) had CBI; and 69,927 (29.0%) had WMH. The mortality rate per 1,000 person-years with CBI was 59.0 (95%CI 57.0-61.1); with WMH=46.5 (45.7-47.2); with neither=17.4 (17.1-17.7). In adjusted models, mortality risk associated with CBI was modified by age, e.g. HR 1.34 [1.21-1.48] at age 56.1 years vs HR 1.22 [1.17-1.28] at age 72 years. Mortality associated with WMH was modified by both age and imaging modality e.g., WMH on MRI at age 56.1 HR = 1.26 [1.18-1.35]; WMH on MRI at age 72 HR 1.15 [1.09-1.21]; WMH on CT at age 56.1 HR 1.41 [1.33-1.50]; WMH on CT at age 72 HR 1.28 [1.24-1.32], vs. patients without CBI or without WMH, respectively. Increasing WMH severity associated with higher mortality, e.g. mild WMH on MRI had adjusted HR=1.13 [1.06-1.20] while severe WMH on CT had HR=1.45 [1.33-1.59]. Incidentally-detected CBI and WMH on population-based clinical neuroimaging can predict higher mortality rates. We need treatments and healthcare planning for individuals with CCD.

Identification of recurrent atrial fibrillation using natural language processing applied to electronic health records.

AIMS: This study aimed to develop and apply natural language processing (NLP) algorithms to identify recurrent atrial fibrillation (AF) episodes following rhythm control therapy initiation using electronic health records (EHRs). METHODS AND RESULTS: We included adults with new-onset AF who initiated rhythm control therapies (ablation, cardioversion, or antiarrhythmic medication) within two US integrated healthcare delivery systems. A code-based algorithm identified potential AF recurrence using diagnosis and procedure codes. An automated NLP algorithm was developed and validated to capture AF recurrence from electrocardiograms, cardiac monitor reports, and clinical notes. Compared with the reference standard cases confirmed by physicians' adjudication, the F-scores, sensitivity, and specificity were all above 0.90 for the NLP algorithms at both sites. We applied the NLP and code-based algorithms to patients with incident AF (n = 22 970) during the 12 months after initiating rhythm control therapy. Applying the NLP algorithms, the percentages of patients with AF recurrence for sites 1 and 2 were 60.7% and 69.9% (ablation), 64.5% and 73.7% (cardioversion), and 49.6% and 55.5% (antiarrhythmic medication), respectively. In comparison, the percentages of patients with code-identified AF recurrence for sites 1 and 2 were 20.2% and 23.7% for ablation, 25.6% and 28.4% for cardioversion, and 20.0% and 27.5% for antiarrhythmic medication, respectively. CONCLUSION: When compared with a code-based approach alone, this study's high-performing automated NLP method identified significantly more patients with recurrent AF. The NLP algorithms could enable efficient evaluation of treatment effectiveness of AF therapies in large populations and help develop tailored interventions.

Emergency Department Cardiac Risk Stratification With High-Sensitivity vs Conventional Troponin HEART Pathway.

Importance: Patients presenting to the emergency department with chest pain are routinely risk stratified for major adverse cardiac events using the HEART (History, Electrocardiogram, Age, Risk factors, and Troponin) score pathway, which incorporates clinical features, risk factors, electrocardiography findings, and initial serum troponin testing. A new HEART pathway incorporating high-sensitivity troponin level may improve risk stratification among patients with possible acute myocardial infarction (AMI). Objective: To compare health outcomes and resource use among emergency department patients undergoing cardiac risk stratification with a HEART pathway using conventional vs high-sensitivity serum troponin. Design, Setting, and Participants: This multicenter pre-post cohort study was conducted between January 1 and September 6, 2021, at 16 Kaiser Permanente Southern California hospitals during uptake of a high-sensitivity serum troponin assay and included 17 384 adult patients who presented to an emergency department with chest pain and were risk stratified with a HEART pathway based on conventional troponin or high-sensitivity troponin. Exposures: A HEART pathway incorporating either conventional or high-sensitivity serum troponin was used to stratify study groups for risk of major adverse cardiac events within 30 days. Main Outcomes and Measures: The primary outcome was detection of AMI in the emergency department and within 30 days. Results: Of the 17 384 patients (median age, 58 years [IQR, 45-69 years]; 9767 women [56.2%]), 12 440 (71.6%) were risk stratified with a HEART pathway based on conventional troponin, and 4944 (28.4%) were risk stratified with a HEART pathway based on high-sensitivity troponin. Detection of AMI within 30 days was higher for the high-sensitivity troponin group than the conventional troponin group (288 [5.8%] vs 545 [4.4%]; P < .001), while the 30-day all-cause mortality rate was unchanged (16 [0.3%] vs 50 [0.4%]; P = .50). In the emergency department, 228 of 4944 patients (4.6%) in the high-sensitivity troponin group received a diagnosis of AMI compared with 251 of 12 440 patients (2.0%) in the conventional troponin group (P < .001). Among those who did not receive a diagnosis of AMI in the emergency department, an additional 60 patients (1.2%) in the high-sensitivity troponin group and 294 (2.4%) in the conventional troponin group (P < .001) received a diagnosis within 30 days. Patients in the high-sensitivity troponin group had lower rates of health care use compared with the conventional troponin group, including admission (605 [12.2%] vs 1862 [15.0%]; P < .001), stress testing within 7 days (506 [10.2%] vs 1591 [12.8%]; P < .001), and coronary revascularization within 30 days (51 [1.0%] vs 244 [2.0%]; P < .001). Conclusions and Relevance: This multicenter pre-post cohort study suggests that a new HEART pathway incorporating high-sensitivity troponin may improve detection of AMI and decrease resource use among emergency department patients with chest pain.

Stratifying future stroke risk with incidentally-discovered white matter disease severity and covert brain infarct site.

BACKGROUND: Covert cerebrovascular disease (CCD) includes white matter disease (WMD) and covert brain infarction (CBI). Incidentally-discovered CCD is associated with increased risk of subsequent symptomatic stroke. However, it is unknown whether the severity of WMD or the location of CBI predicts risk. OBJECTIVES: To examine the association of incidentally-discovered WMD severity and CBI location with risk of subsequent symptomatic stroke. METHOD: This retrospective cohort study includes patients 50 years old in the Kaiser Permanente Southern California health system who received neuroimaging for a non-stroke indication between 2009-2019. Incidental CBI and WMD were identified via natural language processing of the neuroimage report, and WMD severity was classified into grades. RESULTS: 261,960 patients received neuroimaging; 78,555 (30.0%) were identified to have incidental WMD, and 12,857 (4.9%) to have incidental CBI. Increasing WMD severity is associated with increased incidence rate of future stroke. However, the stroke incidence rate in CT-identified WMD is higher at each level of severity compared to rates in MRI-identified WMD. Patients with mild WMD via CT have a stroke incidence rate of 24.9 per 1,000 person-years, similar to that of patients with severe WMD via MRI. Among incidentally-discovered CBI patients with a determined CBI location, 97.9% are subcortical rather than cortical infarcts. CBI confers a similar risk of future stroke, whether cortical or subcortical, or whether MRI- or CT-detected. CONCLUSIONS: Increasing severity of incidental WMD is associated with an increased risk of future symptomatic stroke, dependent on the imaging modality. Subcortical and cortical CBI conferred similar risks.

Stratifying Future Stroke Risk with Incidentally Discovered White Matter Disease Severity and Covert Brain Infarct Site.

BACKGROUND: Covert cerebrovascular disease (CCD) includes white matter disease (WMD) and covert brain infarction (CBI). Incidentally discovered CCD is associated with increased risk of subsequent symptomatic stroke. However, it is unknown whether the severity of WMD or the location of CBI predicts risk. OBJECTIVES: The aim of this study was to examine the association of incidentally discovered WMD severity and CBI location with risk of subsequent symptomatic stroke. METHOD: This retrospective cohort study includes patients aged ≥50 years old in the Kaiser Permanente Southern California health system who received neuroimaging for a nonstroke indication between 2009 and 2019. Incidental CBI and WMD were identified via natural language processing of the neuroimage report, and WMD severity was classified into grades. RESULTS: A total of 261,960 patients received neuroimaging; 78,555 patients (30.0%) were identified to have incidental WMD and 12,857 patients (4.9%) to have incidental CBI. Increasing WMD severity is associated with an increased incidence rate of future stroke. However, the stroke incidence rate in CT-identified WMD is higher at each level of severity compared to rates in MRI-identified WMD. Patients with mild WMD via CT have a stroke incidence rate of 24.9 per 1,000 person-years, similar to that of patients with severe WMD via MRI. Among incidentally discovered CBI patients with a determined CBI location, 97.9% are subcortical rather than cortical infarcts. CBI confers a similar risk of future stroke, whether cortical or subcortical or whether MRI- or CT-detected. CONCLUSIONS: Increasing severity of incidental WMD is associated with an increased risk of future symptomatic stroke, dependent on the imaging modality. Subcortical and cortical CBI conferred similar risks.

Investigating Tetanus, Diphtheria, Acellular Pertussis Vaccination During Pregnancy and Risk of Congenital Anomalies.

INTRODUCTION: This observational retrospective matched cohort study evaluated the safety of a prenatal tetanus, diphtheria, acellular pertussis (Tdap) vaccination, Boostrix. We previously reported on the risk of maternal and neonatal outcomes; here we report on the risk of congenital anomalies in infants at birth through 6 months of age. METHODS: The study included pregnant Kaiser Permanente Southern California members. Women who received the Tdap vaccine on or after the 27th week of pregnancy between January 2018 and January 2019 were matched to women who were pregnant between January 2012 and December 2014 and were not vaccinated with Tdap during pregnancy. Unadjusted and adjusted relative risks (aRRs) with 95% confidence intervals were estimated by Poisson regression. Quantitative secular trend analyses, from 2011 to 2017, were conducted on congenital anomalies with a statistically significant aRR > 1. RESULTS: The analysis consisted of 16,350 and 16,088 live-born infants in the Tdap-exposed and unexposed cohorts, respectively. Of the 14 congenital anomaly body systems evaluated, 8 (eye, ear/face/neck, respiratory, upper gastrointestinal, genital, renal, musculoskeletal, integument) had statistically significant elevated aRRs, with point estimates ranging from 1.17 to 2.02. The observed elevated aRRs were consistent with their respective secular increases over time. CONCLUSION: Cautious interpretation of these findings is warranted as these increases may have resulted from improved identification and diagnosis. Furthermore, the biological plausibility of an association between maternal vaccine exposure in the third trimester of pregnancy and birth defects is low. The overall study findings support the safety of maternal immunization with Boostrix during the third trimester of pregnancy. TRIAL REGISTRATION: ClinicalTrials.gov identifier, NCT03463577.

Association of Incidentally Discovered Covert Cerebrovascular Disease Identified Using Natural Language Processing and Future Dementia.

Background Covert cerebrovascular disease (CCD) has been shown to be associated with dementia in population-based studies with magnetic resonance imaging (MRI) screening, but dementia risk associated with incidentally discovered CCD is not known. Methods and Results Individuals aged ≥50 years enrolled in the Kaiser Permanente Southern California health system receiving head computed tomography (CT) or MRI for nonstroke indications from 2009 to 2019, without prior ischemic stroke/transient ischemic attack, dementia/Alzheimer disease, or visit reason/scan indication suggestive of cognitive decline or stroke were included. Natural language processing identified incidentally discovered covert brain infarction (id-CBI) and white matter disease (id-WMD) on the neuroimage report; white matter disease was characterized as mild, moderate, severe, or undetermined. We estimated risk of dementia associated with id-CBI and id-WMD. Among 241 050 qualified individuals, natural language processing identified 69 931 (29.0%) with id-WMD and 11 328 (4.7%) with id-CBI. Dementia incidence rates (per 1000 person-years) were 23.5 (95% CI, 22.9-24.0) for patients with id-WMD, 29.4 (95% CI, 27.9-31.0) with id-CBI, and 6.0 (95% CI, 5.8-6.2) without id-CCD. The association of id-WMD with future dementia was stronger in younger (aged <70 years) versus older (aged ≥70 years) patients and for CT- versus MRI-discovered lesions. For patients with versus without id-WMD on CT, the adjusted HR was 2.87 (95% CI, 2.58-3.19) for older and 1.87 (95% CI, 1.79-1.95) for younger patients. For patients with versus without id-WMD on MRI, the adjusted HR for dementia risk was 2.28 (95% CI, 1.99-2.62) for older and 1.48 (95% CI, 1.32-1.66) for younger patients. The adjusted HR for id-CBI was 2.02 (95% CI, 1.70-2.41) for older and 1.22 (95% CI, 1.15-1.30) for younger patients for either modality. Dementia risk was strongly correlated with id-WMD severity; adjusted HRs compared with patients who were negative for id-WMD by MRI ranged from 1.41 (95% CI, 1.25-1.60) for those with mild disease on MRI to 4.11 (95% CI, 3.58-4.72) for those with severe disease on CT. Conclusions Incidentally discovered CCD is common and associated with a high risk of dementia, representing an opportunity for prevention. The association is strengthened when discovered at younger age, by increasing id-WMD severity, and when id-WMD is detected by CT scan rather than MRI.

[The correlation between sperm DNA damage and IVF-ET clinical pregnancy outcomes in different BMI population with normal routine semen examination].

OBJECTIVE: To analyze the correlation between sperm DFI, HDS and IVF-ET pregnancy outcomes in different BMI populations with normal routine semen examination. METHODS: The clinical data of 199 cycles of IVF-ET were retrospectively analyzed. Sperm chromatin structure analysis based on flow cytometry was used to detect sperm DFI and HDS. The correlation between sperm DFI, HDS and pregnancy outcome of IVF-ET were analyzed. RESULTS: The sperm DFI was negatively correlated with IVF-ET pregnancy in overweight (24.0 kg/m2≤BMI<28.0 kg/m2) population (OR=0.935, P=0.043). In the normal BMI group (18.5 kg/m2≤BMI < 24.0 kg/m2), the clinical pregnancy outcome of IVF-ET was not significantly correlated with sperm DFI, and was negatively correlated with male age (OR=0.744, P=0.020). In the obese population (BMI ≥ 28.0 kg/m2) , there was no significant correlation between the clinical pregnancy outcome of IVF-ET and sperm DNA fragmentation index (DFI) , but a negative correlation with male BMI (OR = 0.779, P = 0.043). CONCLUSION: The male BMI affected the correlation between sperm DFI and IVF-ET pregnancy outcomes: ①Sperm DFI was only associated with IVF-ET clinical pregnancy outcome in the overweight population; ② In normal BMI and obese populations, male age and male BMI were important factors affecting IVF-ET clinical pregnancy outcome respectively; ③No correlation was found between sperm HDS and IVF-ET pregnancy outcomes.

Association between prenatal exposure to ambient ozone, birth weight, and macrosomia in healthy women.

Studies have shown that prenatal ozone exposure is associated with an increased risk of adverse pregnancy outcomes, among which abnormal birth weight is a detrimental factor for diseases in adulthood, but the association between birth weight and ozone is inconclusive. Herein, we conducted this study by enrolling 407 couples of pregnant women and collected their demographical materials, their exposure to ambient ozone was assessed according to the place of their residence. The hourly monitored ozone was first averaged to the daily level, then monthly and whole-gestationally levels. After adjusting confounders, we processed a multivariate generalized addictive analysis to predict the association between prenatal ozone exposure and birth weight. We also divided the cohort into two categories according to whether the infant met the standard of macrosomia, and the occurrence of macrosomia was studied via univariate and multivariate logistic regression analyses as extreme conditions of the effects of ozone exposure on birth weight. We found that the ground-level ozone in Jinan changed with temperature periodically, higher in summer and lower in winter. Over the past 8 years from 2014, the ambient ozone increased by 1.74 µg/m3 per year. Of the 407 singleton-pregnant women, 21 infants were diagnosed with macrosomia. After adjusting confounders, we found that each unit increase in prenatal ozone exposure caused 8.80% [ORozone90%CI: 0.912 (0.850, 0.978)] decreased risk of macrosomia, but the splined ambient ozone exposure data was not statistically associated with birth weight, which is probably due to the limited sample size. In conclusion, prenatal ozone exposure is associated with decreased risk of macrosomia but is weakly linked to birth weight.

Development of Parkinson Disease and Its Relationship with Incidentally Discovered White Matter Disease and Covert Brain Infarction in a Real-World Cohort.

OBJECTIVE: This study aimed to examine the relationship between covert cerebrovascular disease, comprised of covert brain infarction and white matter disease, discovered incidentally in routine care, and subsequent Parkinson disease. METHODS: Patients were ≥50 years and received neuroimaging for non-stroke indications in the Kaiser Permanente Southern California system from 2009 to 2019. Natural language processing identified incidentally discovered covert brain infarction and white matter disease and classified white matter disease severity. The Parkinson disease outcome was defined as 2 ICD diagnosis codes. RESULTS: 230,062 patients were included (median follow-up 3.72 years). A total of 1,941 Parkinson disease cases were identified (median time-to-event 2.35 years). Natural language processing identified covert cerebrovascular disease in 70,592 (30.7%) patients, 10,622 (4.6%) with covert brain infarction and 65,814 (28.6%) with white matter disease. After adjustment for known risk factors, white matter disease was associated with Parkinson disease (hazard ratio 1.67 [95%CI, 1.44, 1.93] for patients <70 years and 1.33 [1.18, 1.50] for those ≥70 years). Greater severity of white matter disease was associated with increased incidence of Parkinson disease(/1,000 person-years), from 1.52 (1.43, 1.61) in patients without white matter disease to 4.90 (3.86, 6.13) in those with severe disease. Findings were robust when more specific definitions of Parkinson disease were used. Covert brain infarction was not associated with Parkinson disease (adjusted hazard ratio = 1.05 [0.88, 1.24]). INTERPRETATION: Incidentally discovered white matter disease was associated with subsequent Parkinson disease, an association strengthened with younger age and increased white matter disease severity. Incidentally discovered covert brain infarction did not appear to be associated with subsequent Parkinson disease. ANN NEUROL 2022;92:620-630.

Identifying Cases of Shoulder Injury Related to Vaccine Administration (SIRVA) in the United States: Development and Validation of a Natural Language Processing Method.

BACKGROUND: Shoulder injury related to vaccine administration (SIRVA) accounts for more than half of all claims received by the National Vaccine Injury Compensation Program. However, due to the difficulty of finding SIRVA cases in large health care databases, population-based studies are scarce. OBJECTIVE: The goal of the research was to develop a natural language processing (NLP) method to identify SIRVA cases from clinical notes. METHODS: We conducted the study among members of a large integrated health care organization who were vaccinated between April 1, 2016, and December 31, 2017, and had subsequent diagnosis codes indicative of shoulder injury. Based on a training data set with a chart review reference standard of 164 cases, we developed an NLP algorithm to extract shoulder disorder information, including prior vaccination, anatomic location, temporality and causality. The algorithm identified 3 groups of positive SIRVA cases (definite, probable, and possible) based on the strength of evidence. We compared NLP results to a chart review reference standard of 100 vaccinated cases. We then applied the final automated NLP algorithm to a broader cohort of vaccinated persons with a shoulder injury diagnosis code and performed manual chart confirmation on a random sample of NLP-identified definite cases and all NLP-identified probable and possible cases. RESULTS: In the validation sample, the NLP algorithm had 100% accuracy for identifying 4 SIRVA cases and 96 cases without SIRVA. In the broader cohort of 53,585 vaccinations, the NLP algorithm identified 291 definite, 124 probable, and 52 possible SIRVA cases. The chart-confirmation rates for these groups were 95.5% (278/291), 67.7% (84/124), and 17.3% (9/52), respectively. CONCLUSIONS: The algorithm performed with high sensitivity and reasonable specificity in identifying positive SIRVA cases. The NLP algorithm can potentially be used in future population-based studies to identify this rare adverse event, avoiding labor-intensive chart review validation.

Risk Factors for Silent Brain Infarcts and White Matter Disease in a Real-World Cohort Identified by Natural Language Processing.

OBJECTIVE: To assess the frequency of silent brain infarcts (SBIs) and white matter disease (WMD) and associations with stroke risk factors (RFs) in a real-world population. PATIENTS AND METHODS: This was an observational study of patients 50 years or older in the Kaiser Permanente Southern California health system from January 1, 2009, through June 30, 2019, with head computed tomography or magnetic resonance imaging for nonstroke indications and no history of stroke, transient ischemic attack, or dementia. A natural language processing (NLP) algorithm was applied to the electronic health record to identify individuals with reported SBIs or WMD. Multivariable Poisson regression estimated risk ratios of demographic characteristics, RFs, and scan modality on the presence of SBIs or WMD. RESULTS: Among 262,875 individuals, the NLP identified 13,154 (5.0%) with SBIs and 78,330 (29.8%) with WMD. Stroke RFs were highly prevalent. Advanced age was strongly associated with increased risk of SBIs (adjusted relative risks [aRRs], 1.90, 3.23, and 4.72 for those aged in their 60s, 70s, and ≥80s compared with those in their 50s) and increased risk of WMD (aRRs, 1.79, 3.02, and 4.53 for those aged in their 60s, 70s, and ≥80s compared with those in their 50s). Magnetic resonance imaging was associated with a reduced risk of SBIs (aRR, 0.87; 95% CI, 0.83 to 0.91) and an increased risk of WMD (aRR, 2.86; 95% CI, 2.83 to 2.90). Stroke RFs had modest associations with increased risk of SBIs or WMD. CONCLUSION: An NLP algorithm can identify a large cohort of patients with incidentally discovered SBIs and WMD. Advanced age is strongly associated with incidentally discovered SBIs and WMD.

Cardiorespiratory Fitness and Mortality in Patients Aged 60 to 90 Years.

Chronological age alone does not fully reflect a patient's prognosis. We sought to assess the association of cardiorespiratory fitness (quantified by METs) with all-cause mortality among patients aged 60 to 90 years. This retrospective study included patients who underwent exercise treadmill testing at an integrated healthcare system from 2011 to 2019. Patients were categorized into age groups: 60 to <70 years, 70 to <80 years, and 80 to 90 years; and cardiorespiratory fitness level: low (<5 METs), moderate (5 to 10 METs), and high fitness (>10 METs). Mean follow-up was 3.5 years. A total of 40,520 patients were included (mean age 67.7 ± 4.7 years, 48.6% women). Of whom, 27,021 were 60 to <70 years old (66.7%); 12,638 70 to <80 years old (31.2%); and 1,861 80 to 90 years old (4.6%). There were 3,494 patients categorized as low (8.6%), 21,863 as moderate (54%), and 15,163 as high fitness (37.4%). Low fitness level was independently associated with lower survival (hazard ratio [HR] 1.61, 95% confidence interval [CI] 1.15 to 2.24). Using age 60 to 70 group with high fitness level as reference, the age 80 to 90 group with high fitness level had better survival than their younger counterparts with low fitness level (age 80 to 90 years high fitness level: HR 2.9, 95% CI 1.2 to 7.2; age 60 to 70 years low fitness level: HR 4.3, 95% CI 3.1 to 5.9; age 70 to 80 years low fitness level: HR 6.8, 95% CI 5.2 to 8.9) on adjusted analysis. In conclusion, higher cardiorespiratory fitness is associated with better survival. Patients >80 years old with high fitness level have comparable or even better survival than their younger counterparts with submoderate fitness levels. Chronological age alone should not be the only factor when considering prognosis.

Risk for Shoulder Conditions After Vaccination: A Population-Based Study Using Real-World Data.

BACKGROUND: Although shoulder conditions have been reported as an adverse event after intramuscular vaccination in the deltoid muscle, epidemiologic data on shoulder conditions after vaccination are limited. OBJECTIVE: To estimate the risk for shoulder conditions after vaccination and assess possible risk factors. DESIGN: Retrospective cohort study. SETTING: Kaiser Permanente Southern California, a large integrated health care organization. PARTICIPANTS: Kaiser Permanente Southern California members aged 3 years or older who had an intramuscular vaccination administered in the deltoid muscle between 1 April 2016 and 31 December 2017. MEASUREMENTS: A natural language processing (NLP) algorithm was used to identify potential shoulder conditions among vaccinated persons with shoulder disorder diagnosis codes. All NLP-identified cases were manually chart confirmed on the basis of our case definition. The characteristics of vaccinated persons with and without shoulder conditions were compared. RESULTS: Among 3 758 764 administered vaccinations, 371 cases of shoulder condition were identified, with an estimated incidence of 0.99 (95% CI, 0.89 to 1.09) per 10 000 vaccinations. The incidence was 1.22 (CI, 1.10 to 1.35) for the adult (aged ≥18 years) and 0.05 (CI, 0.02 to 0.14) for the pediatric (aged 3 to 17 years) vaccinated populations. In the adult vaccinated population, advanced age, female sex, an increased number of outpatient visits in the 6 months before vaccination, lower Charlson Comorbidity Index, and pneumococcal conjugate vaccine were associated with a higher risk for shoulder conditions. Among influenza vaccines, quadrivalent vaccines were associated with an increased risk for shoulder conditions. Simultaneous administration of vaccines was associated with a higher risk for shoulder conditions among elderly persons. LIMITATION: Generalizability to other health care settings, use of administrative data, and residual confounding. CONCLUSION: These population-based data suggest a small absolute risk for shoulder conditions after vaccination. Given the high burden of shoulder conditions, clinicians should pay attention to any factors that may further increase risks. PRIMARY FUNDING SOURCE: Centers for Disease Control and Prevention.

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.

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.

The Probability of Lung Cancer in Patients With Incidentally Detected Pulmonary Nodules: Clinical Characteristics and Accuracy of Prediction Models.

BACKGROUND: The frequency of cancer and accuracy of prediction models have not been studied in large, population-based samples of patients with incidental pulmonary nodules measuring > 8 mm in diameter. RESEARCH QUESTIONS: How does the frequency of cancer vary by size and smoking history among patients with incidental nodules? How accurate are two widely used models for identifying cancer in these patients? STUDY DESIGN AND METHODS: We assembled a retrospective cohort of individuals with incidental nodules measuring > 8 mm in diameter identified by chest CT imaging between 2006 and 2016. We used a validated natural language processing algorithm to identify nodules and their characteristics by scanning the text of dictated radiology reports. We reported patient and nodule characteristics stratified by the presence or absence of a lung cancer diagnosis within 27 months of nodule identification and estimated the area under the receiver operating characteristic curve (AUC) to compare the accuracy of the Mayo Clinic and Brock models for identifying cancer. RESULTS: The sample included 23,780 individuals with a nodule measuring > 8 mm, including 2,356 patients (9.9%) with a lung cancer diagnosis within 27 months of nodule identification. Cancer was diagnosed in 5.4% of never smokers, 12.2% of former smokers, and 17.7% of current smokers. Cancer was diagnosed in 5.7% of patients with nodules measuring 9 to 15 mm, 12.1% of patients with nodules > 15 to 20 mm, and 18.4% of patients with nodules > 20 to 30 mm. In the full sample, the Mayo Clinic model (AUC, 0.747; 95% CI, 0.737-0.757) was more accurate than the Brock model (AUC, 0.713; 95% CI, 0.702-0.724; P < .0001). When restricted to ever smokers, the Mayo Clinic model was still more accurate. Both models overestimated the probability of cancer. INTERPRETATION: Almost 10% of patients with an incidental pulmonary nodule measuring > 8 mm in diameter will receive a lung cancer diagnosis. Existing prediction models have only fair accuracy and overestimate the probability of cancer.

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.