Carter, Rickey E.

The timing and magnitude of sex differences in athletic performance during early human development, prior to adulthood, is unknown. Objective To compare swimming velocity of boys and girls for all Olympic‐length freestyle swimming events to determine the age of divergence in swimming performance. Methods We collected the all‐time top 100 U.S. freestyle swimming performance times of boys and girls age 5 to 18 years for the 50m to 1500m events. Results Swimming performance improved with increasing age for boys and girls ( p <0.001) until reaching a plateau, which initiated at a younger age for girls (15 years) than boys (17 years; sex×age; p <0.001). Prior to age 10, the top 5 swimming records for girls were 3% faster than the top boys ( p <0.001). For the 10 th –50 th places, however, there were no sex‐related differences in swimming performance prior to age 10 ( p =0.227). For both the top 5 and 10 th –50 th places, the sex difference in performance increased from age 10 (top 5, 2.5%; 10 th –50 th places, 1.0%) until age 17 (top 5, 7.6%; 10 th –50 th places, 8.0%). For all places, the sex difference in performance at age 18 was larger for sprint events (9.6%; 50–200m) than endurance events (7.1%; 400–1500m; p <0.001). Additionally, the sex‐related difference in performance increased across age and US ranking from 2.4% for 1 st place to 4.3% for 100 th place ( p <0.001), indicating less depth of performance in girls than boys. However, annual participation was ~20% higher in girls than boys for all ages ( p <0.001). Conclusion The top 5 girls demonstrated faster swimming velocities and the 10 th –50 th place girls demonstrated similar swimming velocities than boys (until ~10 years). After age 10, however, boys demonstrated increasingly faster swimming velocities than girls until 17 years. Collectively, these data suggest girls are faster, or at least not slower, than boys prior to the performance‐enhancing effects of puberty. Support or Funding Information This study was supported by the National Institutes of Health R‐35‐HL139854‐02 (MJJ), HL139854‐02S1 (AJC), 5T32DK007352‐40 (JWS), and the Mayo Foundation. Elite swimming performance. Mean swimming velocity from 5 to 18 years of the top 100 fastest US boys (blue circles) and girls (red triangles) for the 50, 100, 200, 400, 800 and 1500m freestyle swimming distances. Figure 1 Sex differences in performance of the top 5 places. The primary plot (heat map) displays the sex differences in swimming velocity (% boy’s swimming velocity) of the top 5 US rankings in each freestyle event distance and age, negative values (red) indicate faster performance of girls. The top displays the mean sex difference across age, and the right plot displays the mean sex difference across swimming event distance. Figure 2

Background Artificial Intelligent Virtual Assistants (AIVA) is a segment of artificial intelligence that is rapidly developing. However, its utilization to address patients' frequently asked questions remains unexplored. Methods We developed an AIVA to answer questions related to 10 frequent topics asked by plastic surgery patients in our institution. Between July 27, 2018, and August 10 of 2018, we recruited subjects with administrative positions at our health care institution to chat with the virtual assistant. They asked, with their own words, 1 question for each topic and filled out a satisfaction questionnaire. Postsurvey analysis of questions and answers allowed assessment of the virtual assistant's accuracy. Results Thirty participants completed the survey. The majority was female (70%), and the mean age was 27.76 years (SD, 8.68 [19–51] years). The overall accuracy of the plastic surgery AIVA was 92.3% (277/294 questions), and participants considered the answer correct in 83.3% of the time (250/294 answers). Most of the participants considered the AIVA easy to use, answered adequately, and could be helpful for patients. However, when asked if this technology could replace a human assistant, they stayed neutral.

New Findings What is the central question of this study? Are sex difference in the central airways present in healthy paediatric patients? What is the main finding and its importance? In patients ≤12 years we found no sex differences in central airway luminal area. After 14 years, the males had significantly larger central airway luminal areas than the females. The sex differences were minimized, but preserved when correcting for height. Luminal area is the main determinant of airway resistance and our finding could help explain sex differences in pulmonary system limitations to exercise in paediatric patients. Abstract Cross‐sectional airway area is the main determinant of resistance to airflow in the respiratory system. In paediatric patients (<18 years), previous evidence for sex differences in cross‐sectional airway area was limited to patients with history of pulmonary disease or cadaveric studies with small numbers of subjects. These studies either only report tracheal data and do not include a range of ages or correct for height. Therefore, we sought to assess sex differences in airway luminal area utilizing paediatric patients of varying ages and no history of respiratory disease. Using three‐dimensional reconstructions from high‐resolution computed tomography scans, we retrospectively assessed the cross‐sectional airway area in healthy paediatric females ( n = 97) and males ( n = 128) over a range of ages (1–17 years). The areas of the trachea, left main bronchus, left upper lobe, left lower lobe, right main bronchus, intermediate bronchus and right upper lobe were measured at three discrete points by a blinded investigator. No differences between the sexes were noted in the cross‐sectional areas of the youngest (ages 1–12 years) patients ( P > 0.05). However, in patients ≥14 years the cross‐sectional areas were larger in the males compared to females in most airway sites. For instance, the cross‐sectional size of the trachea was 25% (218 ± 44 vs . 163 ± 24 mm 2 , P < 0.01) larger in males vs . females among ages 13–17 years. When accounting for height, these sex differences in airway areas were attenuated, but persisted. Our results indicate that sex differences in paediatric airway cross‐sectional area manifest after age ≥14 years and are independent of height.

Background. Currently, no surveillance guidelines for hepatocellular carcinoma (HCC) recurrence after liver transplantation (LT) exist. In this retrospective, multicenter study, we have investigated the role of surveillance imaging on postrecurrence outcomes. Methods. Patients with recurrent HCC after LT from 2002 to 2016 were reviewed from 3 transplant centers (University of California San Francisco, Mayo Clinic Florida, and University of Toronto). For this study, we proposed the term cumulative exposure to surveillance (CETS) as a way to define the cumulative sum of all the protected intervals that each surveillance test provides. In our analysis, CETS has been treated as a continuous variable in months. Results. Two hundred twenty-three patients from 3 centers had recurrent HCC post-LT. The median follow-up was 31.3 months, and median time to recurrence was 13.3 months. Increasing CETS was associated with improved postrecurrence survival (hazard ratio, 0.94; P < 0.01) as was treatment of recurrence with resection or ablation (hazard ratio, 0.31; P < 0.001). An receiver operating characteristic curve (area under the curve, 0.64) for CETS covariate showed that 252 days of coverage (or 3 surveillance scans) within the first 24 months provided the highest probability for aggressive postrecurrence treatment. Conclusions. In this review of 223 patients with post-LT HCC recurrence, we found that increasing CETS does lead to improved postrecurrence survival as well as a higher probability for aggressive recurrence treatment. We found that 252 days of monitoring (ie, 3 surveillance scans) in the first 24 months was associated with the ability to offer potentially curative treatment.

AbstractBackgroundThe accurate separation of undifferentiated wide complex tachycardias (WCTs) into ventricular tachycardia (VT) or supraventricular wide complex tachycardia (SWCT) using conventional, manually‐applied 12‐lead electrocardiogram (ECG) interpretation methods is difficult.PurposeWe sought to devise a new WCT differentiation method that operates solely on automated measurements routinely provided by computerized ECG interpretation software.MethodsIn a two‐part analysis, we developed and validated a logistic regression model (ie, VT Prediction Model) that utilizes routinely available computerized measurements derived from patients' paired WCT and baseline ECGs.ResultsThe derivation cohort consisted of 601 paired WCT (273 VT, 328 SWCT) and baseline ECGs from 421 patients. The VT Prediction Model, composed of WCT QRS duration (ms) (P < .0001), QRS duration change (ms) (P < .0001), QRS axis change (°) (P < .0001) and T axis change (°) (P < .0001), yielded effective VT and SWCT differentiation (area under the curve [AUC]: 0.924; confidence interval [CI]: 0.903‐0.944) for the derivation cohort. The validation cohort comprised 241 paired WCT (97 VT, 144 SWCT) and baseline ECGs from 177 patients. The VT Prediction Model's implementation on the validation cohort yielded effective WCT differentiation (AUC: 0.900; CI: 0.862‐0.939) with overall accuracy, sensitivity, and specificity of 85.0%, 80.4%, and 88.2%, respectively.ConclusionThe VT Prediction Model is an example of how readily available ECG measurements may be used to distinguish VT and SWCT effectively. Further study is needed to develop and refine newer WCT differentiation approaches that utilize computerized measurements provided by ECG interpretation software.

Abstract Aims Increases in extravascular lung water (EVLW) during exercise contribute to symptoms, morbidity, and mortality in patients with heart failure and preserved ejection fraction (HFpEF), but the mechanisms leading to pulmonary congestion during exercise are not well-understood. Methods and results Compensated, ambulatory patients with HFpEF (n = 61) underwent invasive haemodynamic exercise testing using high-fidelity micromanometers with simultaneous lung ultrasound, echocardiography, and expired gas analysis at rest and during submaximal exercise. The presence or absence of EVLW was determined by lung ultrasound to evaluate for sonographic B-line artefacts. An increase in EVLW during exercise was observed in 33 patients (HFpEFLW+, 54%), while 28 (46%) did not develop EVLW (HFpEFLW−). Resting left ventricular function was similar in the groups, but right ventricular (RV) dysfunction was two-fold more common in HFpEFLW+ (64 vs. 31%), with lower RV systolic velocity and RV fractional area change. As compared to HFpEFLW−, the HFpEFLW+ group displayed higher pulmonary capillary wedge pressure (PCWP), higher pulmonary artery (PA) pressures, worse RV-PA coupling, and higher right atrial (RA) pressures during exercise, with increased haemoconcentration indicating greater loss of water from the vascular space. The development of lung congestion during exercise was significantly associated with elevations in PCWP and RA pressure as well as impairments in RV-PA coupling (area under the curve values 0.76–0.84). Conclusion Over half of stable outpatients with HFpEF develop increases in interstitial lung water, even during submaximal exercise. The acute development of lung congestion is correlated with increases in pulmonary capillary hydrostatic pressure that favours fluid filtration, and systemic venous hypertension due to altered RV-PA coupling, which may interfere with fluid clearance. Clinical trial registration NCT02885636.

Background: Sex and age have long been known to affect the ECG. Several biologic variables and anatomic factors may contribute to sex and age-related differences on the ECG. We hypothesized that a convolutional neural network (CNN) could be trained through a process called deep learning to predict a person’s age and self-reported sex using only 12-lead ECG signals. We further hypothesized that discrepancies between CNN-predicted age and chronological age may serve as a physiological measure of health. Methods: We trained CNNs using 10-second samples of 12-lead ECG signals from 499 727 patients to predict sex and age. The networks were tested on a separate cohort of 275 056 patients. Subsequently, 100 randomly selected patients with multiple ECGs over the course of decades were identified to assess within-individual accuracy of CNN age estimation. Results: Of 275 056 patients tested, 52% were males and mean age was 58.6±16.2 years. For sex classification, the model obtained 90.4% classification accuracy with an area under the curve of 0.97 in the independent test data. Age was estimated as a continuous variable with an average error of 6.9±5.6 years (R-squared =0.7). Among 100 patients with multiple ECGs over the course of at least 2 decades of life, most patients (51%) had an average error between real age and CNN-predicted age of <7 years. Major factors seen among patients with a CNN-predicted age that exceeded chronologic age by >7 years included: low ejection fraction, hypertension, and coronary disease ( P <0.01). In the 27% of patients where correlation was >0.8 between CNN-predicted and chronologic age, no incident events occurred over follow-up (33±12 years). Conclusions: Applying artificial intelligence to the ECG allows prediction of patient sex and estimation of age. The ability of an artificial intelligence algorithm to determine physiological age, with further validation, may serve as a measure of overall health.

AbstractBackground and ObjectivesConclusive evidence in favor of neoadjuvant therapy for those with non‐metastatic pancreatic ductal adenocarcinoma (PDAC) is still lacking. The objective of this study was to evaluate the survival benefit of neoadjuvant therapy vs upfront surgery for patients with non‐metastatic PDAC.MethodsThe study involved 565 patients undergoing neoadjuvant therapy or upfront surgery as the primary treatment for PDAC. Propensity score matching was performed between the neoadjuvant therapy group (NAT group) and the upfront surgery group (UFS group) using 20 clinical variables at diagnosis. Overall survival and surgical pathology were compared between the two treatment groups on an intent‐to‐treat basis.ResultsIn the matched cohort, the NAT group (n = 91) had a longer median overall survival than the UFS group (n = 91) (23.1 months vs 18.5 months, P = .043). The rate of patients undergoing surgical resection was lower in the NAT group (58% vs 80%, P = .001). Regarding surgical pathology, the NAT group had smaller tumor size (2.8 cm vs 4.0 cm, P = .001), lower incidence of positive surgical margins (8% vs 30%, P < .002), and less lymph node metastasis (45% vs 78%, P < .001).ConclusionsThe strategy of neoadjuvant therapy before surgical resection appears to offer pathologic effect and survival benefit for the patients presenting with non‐metastatic PDAC.

While the triple tracer isotope dilution method has enabled accurate estimation of carbohydrate turnover after a mixed meal, use of the simple carbohydrate glucose as the carbohydrate source limits its translational applicability to everyday meals that typically contain complex carbohydrates. Hence, utilizing the natural enrichment of [13C]polysaccharide in commercially available grains, we devised a novel tracer method to measure postprandial complex carbohydrate turnover and indices of insulin action and β-cell function and compared the parameters to those obtained after a simple carbohydrate containing mixed meal. We studied healthy volunteers after either rice ( n = 8) or sorghum ( n = 8) and glucose ( n = 16) containing mixed meals and modified the triple tracer technique to calculate carbohydrate turnover. All meals were matched for calories and macronutrient composition. Rates of meal glucose appearance (2,658 ± 736 vs. 4,487 ± 909 μM·kg−1·2 h−1), endogenous glucose production (−835 ± 283 vs. −1,123 ± 323 μM·kg−1·2 h−1) and glucose disappearance (1,829 ± 807 vs. 3,606 ± 839 μM·kg−1·2 h−1) differed ( P < 0.01) between complex and simple carbohydrate containing meals, respectively. Interestingly, there were significant increase in indices of insulin sensitivity (32.5 ± 3.5 vs. 25.6 ± 3.2 10−5(dl·kg−1·min−2)/pM, P = 0.006) and β-cell responsivity (disposition index: 1,817 ± 234 vs. 1,236 ± 159 10−14(dl·kg−1·min−2)/pM, P < 0.005) with complex than simple carbohydrate meals. We present a novel triple tracer approach to estimate postprandial turnover of complex carbohydrate containing mixed meals. We also report higher insulin sensitivity and β-cell responsivity with complex than with simple carbohydrates in mixed meals of identical calorie and macronutrient compositions in healthy adults.