Citations

AbstractIntroductionWe investigated the association of the area deprivation index (ADI) with cognitive decline, mild cognitive impairment (MCI), and dementia in older adults (≥50 years old). ADI is a neighborhood socioeconomic disadvantage measure assessed at the census block group level.MethodsThe study included 4699 participants, initially without dementia, with available ADI values for 2015 and at least one study visit in 2008 through 2018. Using logistic regression and Cox proportional hazards models with age as the time scale, we assessed the odds for MCI and the risk for dementia, respectively.ResultsIn cognitively unimpaired (CU) adults at baseline, the risk for progression to dementia increased for every decile increase in the ADI state ranking (hazard ratio = 1.06, 95% confidence interval (1.01–1.11), P = .01). Higher ADI values were associated with subtly faster cognitive decline.DiscussionIn older CU adults, higher baseline neighborhood socioeconomic deprivation levels were associated with progression to dementia and slightly faster cognitive decline.Highlights The study used area deprivation index, a composite freely available neighborhood deprivation measure. Higher levels of neighborhood deprivation were associated with greater mild cognitive impairment odds. Higher neighborhood deprivation levels were associated with higher dementia risk.

AbstractIntroductionAs knowledge about neurological examination findings in autosomal dominant Alzheimer disease (ADAD) is incomplete, we aimed to determine the frequency and significance of neurological examination findings in ADAD.MethodsFrequencies of neurological examination findings were compared between symptomatic mutation carriers and non mutation carriers from the Dominantly Inherited Alzheimer Network (DIAN) to define AD neurological examination findings. AD neurological examination findings were analyzed regarding frequency, association with and predictive value regarding cognitive decline, and association with brain atrophy in symptomatic mutation carriers.ResultsAD neurological examination findings included abnormal deep tendon reflexes, gait disturbance, pathological cranial nerve examination findings, tremor, abnormal finger to nose and heel to shin testing, and compromised motor strength. The frequency of AD neurological examination findings was 65.1%. Cross‐sectionally, mutation carriers with AD neurological examination findings showed a more than two‐fold faster cognitive decline and had greater parieto‐temporal atrophy, including hippocampal atrophy. Longitudinally, AD neurological examination findings predicted a significantly greater decline over time.DiscussionADAD features a distinct pattern of neurological examination findings that is useful to estimate prognosis and may inform clinical care and therapeutic trial designs.

Purpose To characterize the shoulder injuries experienced by baseball batters and position players (nonpitchers); to quantify the outcomes of these injuries with respect to time out of play, recurrence, and surgery rates; and to identify any injury patterns that are associated with worse outcomes. Methods Between 2011 and 2017, all Major League Baseball (MLB) and Minor League Baseball (MiLB) players who sustained shoulder injuries were identified using the MLB Health and Injury Tracking System (HITS). Injuries were included if they were sustained during baseball activity, resulted in at least 1 day missed (DM), and occurred in position players (nonpitchers). Results Over the study period, a total of 3,414 shoulder injuries occurred in batters, resulting in a sum of 68,808 DM and a mean of 22 DM per injury. Most injuries were a result of acute trauma (n = 2125; 62.2%) with throwing as the predominant activity (n = 1292; 38%). Rotator cuff strain/tears was the most common diagnosis (n = 790; 23.1%), and SLAP tears had the highest season‐ending rate (35.3%) and need for surgery (45.1%). There was a lower frequency of surgery (6.2% vs 9.2%; P = .002) and reinjury (2.03% vs 3.62%; P = .007) in the throwing shoulder vs the nonthrowing shoulder. There was an increased frequency of surgery for the front versus the back batting shoulder (8.2% vs 6.2%; P = .031) with similar DM (20.7 vs 22.2; P = .333) and return to play rates (94.0% vs 92.2%; P = .135). Conclusions During the 7‐season study period, there were a total of 3,414 shoulder injuries that resulted in nearly 70,000 days of out of play in professional baseball position players/batters (nonpitchers). Although pitchers were intentionally excluded from the analysis, throwing was still the most common mechanism of injury, and rotator cuff injuries were the most common injury. Labral tears were the most likely injury to be season ending and require surgery. Clinical Relevance This study is meant to help determine characteristics of shoulder injuries that occur in non‐pitchers by focusing on professional baseball batters and position players. This information could be helpful to sports medicine practitioners and shoulder specialists to better prognosticate injury recovery.

Abstract Aims Some artificial intelligence models applied in medical practice require ongoing retraining, introduce unintended racial bias, or have variable performance among different subgroups of patients. We assessed the real-world performance of the artificial intelligence-enhanced electrocardiogram to detect left ventricular systolic dysfunction with respect to multiple patient and electrocardiogram variables to determine the algorithm’s long-term efficacy and potential bias in the absence of retraining. Methods and results Electrocardiograms acquired in 2019 at Mayo Clinic in Minnesota, Arizona, and Florida with an echocardiogram performed within 14 days were analyzed (n = 44 986 unique patients). The area under the curve (AUC) was calculated to evaluate performance of the algorithm among age groups, racial and ethnic groups, patient encounter location, electrocardiogram features, and over time. The artificial intelligence-enhanced electrocardiogram to detect left ventricular systolic dysfunction had an AUC of 0.903 for the total cohort. Time series analysis of the model validated its temporal stability. Areas under the curve were similar for all racial and ethnic groups (0.90–0.92) with minimal performance difference between sexes. Patients with a ‘normal sinus rhythm’ electrocardiogram (n = 37 047) exhibited an AUC of 0.91. All other electrocardiogram features had areas under the curve between 0.79 and 0.91, with the lowest performance occurring in the left bundle branch block group (0.79). Conclusion The artificial intelligence-enhanced electrocardiogram to detect left ventricular systolic dysfunction is stable over time in the absence of retraining and robust with respect to multiple variables including time, patient race, and electrocardiogram features.

The published literature on cervicovaginal cytology includes fewer than ten reported cases of Cokeromyces recurvatus identified in Pap test samples. We report a unique case of an asymptomatic 27-year-old female with persistent gynecologic tract colonization by C. recurvatus in which distinctive fungal microorganisms were identified in three samples collected over three consecutive years.

The rates of diabetes throughout the world are rising rapidly, impacting nearly every country. New research is focused on better ways to monitor and treat this disease. Breath acetone levels have been defined as a biomarker for diabetes. The development of a method to monitor and diagnose diabetes utilizing breath acetone levels would provide a fast, easy, and non-invasive treatment option. An ideal material for point-of-care diabetes management would need to have a high response to acetone, high acetone selectivity, low interference from humidity, and be able to operate at room temperature. Chemiresistive gas sensors are a promising method for sensing breath acetone due to their simple fabrication and easy operation. Certain semiconductor materials in chemiresistive sensors can react to acetone in the air and produce changes in resistance that can be correlated with acetone levels. While these materials have been developed and show strong responses to acetone with good selectivity, most of them must operate at high temperatures (compared to RT), causing high power consumption, unstable device operation, and complex device design. In this paper, we systematically studied a series of 2-dimensional MXene-based nanocomposites as the sensing materials in chemiresistive sensors to detect 2.86 ppm of acetone at room temperature. Most of them showed great sensitivity and selectivity for acetone. In particular, the 1D/2D CrWO/Ti3C2 nanocomposite showed the best sensing response to acetone: nine times higher sensitivity than 1D KWO nanowires. To determine the sensing selectivity, a CrWO/Ti3C2 nanocomposite-based sensor was exposed to various common vapors in human breath. The result revealed that it has excellent selectivity for acetone, and far lower responses to other vapors. All these preliminary results indicate that this material is a promising candidate for the creation of a point-of-care diabetes management device.

In America, Black adults are 30% more likely to die from cardiovascular disease (CVD) compared to White adults, and more than half of this racial disparity in CVD‐related mortality may be attributed to the substantially greater prevalence of high blood pressure (BP) in Black adults. Furthermore, compared to White adults with hypertension, Black adults with hypertension are less likely to exhibit a nocturnal reduction in BP (i.e., “dipping”). Importantly, non‐dipping BP is associated with target organ damage and increased CVD risk. However, it is unclear whether young and apparently healthy Black adults exhibit reduced BP dipping compared to their White peers. PURPOSE Therefore, the purpose of this preliminary investigation was to determine whether there are racial differences in BP dipping using ambulatory BP monitoring (ABPM), including 24‐hour‐, daytime‐, and nighttime‐BP, in young and apparently healthy Black and White adults. METHODS We obtained clinical BP and 24‐hour ABPM readings in 10 self‐identified White adults (5M/5F; age: 21.6±4.4 yrs; BMI: 23.8±2.9 kg/m 2 ; Mean±SD) and 7 self‐identified Black adults (3M/4F; age: 21.7±3.5 yrs; BMI: 25.1±2.8 kg/m 2 ). The ABPM monitors were programmed to record BP every 20 and 30 minutes during each participants daytime‐ and nighttime‐period, respectively. True daytime‐ and nighttime‐BP periods were adjusted during analysis based upon participant activity logs. We defined “non‐dipping” as a failure to achieve a dipping ratio of <0.90 (night‐to‐day BP ratio). BP data were compared using independent t‐tests and the Fisher’s exact test was used to compare dipping frequency between races (α=0.05). RESULTS Clinically measured BP (systolic/diastolic) was not different (P>0.05) between White (117±9/67±6 mmHg) and Black (124±12/70±9 mmHg) adults. There was also no difference (P>0.05) in 24‐hour‐BP between White (117±11/66±7 mmHg) and Black (114±14/63±7 mmHg) adults. Likewise, daytime‐BP was not different (P>0.05) between White (122±12/71±8 mmHg) and Black (116±14/66±8 mmHg) participants, nor was there a difference in nighttime‐BP (P>0.05) between White (102±9/51±4 mmHg) and Black (105±13/54±7 mmHg) adults. However, systolic BP dipping was attenuated (P=0.04) in Black (0.90±0.05) compared to White (0.84±0.07) adults. Non‐dipping of systolic BP was observed in 5 of 7 Black participants and 2 of 10 White participants (P=0.06). Diastolic BP dipping in Black adults was 0.79±0.06 and White adults was 0.73±0.09 (P=0.05). Non‐dipping of diastolic BP was observed in 1 of 7 Black participants and 1 of 10 White participants (P=1.00). CONCLUSIONS These preliminary data suggest that despite similar clinical and 24‐hour ambulatory BP compared to White adults, young and apparently healthy Black adults exhibit impaired BP dipping, which may contribute to increased likelihood of CVD.