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BACKGROUND:International Classification of Diseases (ICD) codes utilized for congenital heart defect (CHD) case identification in datasets have substantial false-positive (FP) rates. Incorporating machine learning (ML) algorithms following case selection by ICD codes may improve the accuracy of CHD identification, enhancing surveillance efforts. METHODS:Traditional ML methods were applied to four encounter-level datasets, 2010-2019, for 3334 patients with validated diagnoses and with at least one CHD ICD code identified. A 5-fold cross-validation approach was applied to the dataset to determine the set of overlapping important features best classifying CHD cases. Training and testing combinations were explored to determine the approach yielding the most accurate CHD classification. RESULTS:CHD ICD positive predictive values (PPVs) by site ranged from 53.2% to 84.0%. The ML algorithm achieved a PPV of 95% (1273/1340) for the four-site dataset with a false-negative (FN) rate of 33% (639/1912) by choosing an operating point prioritizing PPV from the PPV-FN rate curve. XGBoost reduced 2105 Clinical Classification Software (CCS) features to 137 that identified those with true-positive (TP) CHD and false-positive FP classification. CONCLUSION:Applying ML algorithms following case selection by CHD-related ICD codes improved the accuracy of identifying TP true-positive CHD cases.
This population-based cohort study examines the appropriateness of antibiotic prescribing in South Carolina via aggregated pharmacy claims data matched with diagnosis codes from medical claims. Inappropriate antibiotic prescribing decreased from 30.2% in 2012 to 22.6% in 2017 (P < 0.001) and was more common in adults >40 years old.
Invasive mosquito species play an important role in transmitting pathogens that cause diseases in humans and animals around the world. In the last decade, arboviral pathogens transmitted by invasive mosquito species have increased substantially in the southeastern region of the USA ("the Southeast"). Early detection of invasive mosquitoes is an important component of an integrated mosquito management (IMM) plan. To determine the capacity of the southern region of the USA to conduct invasive mosquito surveillance, the Mosquito Biodiversity Enhancement and Control of Non-native Species (BEACONS) working group conducted a survey in 2021 in seven US southern states: Alabama, Florida, Georgia, Louisiana, Mississippi, North Carolina, and South Carolina. A total of 348 mosquito control agencies were contacted, and of those, 90 agencies (26%) responded. Here we report the results about the status of an IMM program and the techniques used for mosquito and pathogen surveillance in the Southeast. Results reveal several gaps in surveillance for invasive mosquito species, compromising the ability for early detection and rapid response. Further, we identified a lack of arbovirus testing, which could result in inadequate arboviral risk assessment and may increase the risk of human and livestock to acquire arboviral infections. This survey data can assist decision makers at the county, regional, and state levels to ameliorate gaps in surveillance capacity in the Southeast.
BACKGROUND:We provide updated crude and adjusted prevalence estimates of major birth defects in the United States for the period 2016-2020. METHODS:Data were collected from 13 US population-based surveillance programs that used active or a combination of active and passive case ascertainment methods to collect all birth outcomes. These data were used to calculate pooled prevalence estimates and national prevalence estimates adjusted for maternal race/ethnicity for all conditions, and maternal age for trisomies and gastroschisis. Prevalence was compared to previously published national estimates from 1999 to 2014. RESULTS:Adjusted national prevalence estimates per 10,000 live births ranged from 0.63 for common truncus to 18.65 for clubfoot. Temporal changes were observed for several birth defects, including increases in the prevalence of atrioventricular septal defect, tetralogy of Fallot, omphalocele, trisomy 18, and trisomy 21 (Down syndrome) and decreases in the prevalence of anencephaly, common truncus, transposition of the great arteries, and cleft lip with and without cleft palate. CONCLUSION:This study provides updated national estimates of selected major birth defects in the United States. These data can be used for continued temporal monitoring of birth defects prevalence. Increases and decreases in prevalence since 1999 observed in this study warrant further investigation.
BACKGROUND:One in four South Carolinians lives in a county along a nearly 200-mile stretch of Interstate 95 (I-95). Stretching from North Carolina to Georgia, this region is among the most rural, economically depressed, and racially/ethnically diverse in the state. Research is needed to identify social factors contributing to adverse health outcomes along the I-95 corridor, guide interventions, and establish a baseline for measuring progress. This study assessed social determinants of health in counties in South Carolina's I-95 corridor relative to the rest of the state. METHOD:Data for South Carolina's 46 counties were extracted from the Centers for Disease Control and Prevention Minority Health Social Vulnerability Index (SVI), which grouped 34 census variables into six themes: socioeconomic status, household composition and disability, minority status and language, housing type and transportation, health care infrastructure, and medical vulnerability. Each theme was ranked from 0 (least vulnerable) to 1 (most vulnerable). Measures between regions were compared using the Wilcoxon-Mann-Whitney test. RESULTS:Compared with counties outside the I-95 corridor (n = 29), counties in the corridor (n = 17) scored higher on socioeconomic status vulnerability (.67 and .82, respectively) and medical vulnerability (.65 and .79, respectively). No statistically significant differences were found across other themes. CONCLUSION:Identifying social determinants of health in South Carolina's I-95 corridor is a crucial first step toward alleviating health disparities in this region. Interventions and policies should be developed in collaboration with local stakeholders to address distal social factors that create and reinforce health disparities.
