Accurate identification of patients with cirrhosis is important for research using administrative databases. We aimed to examine the accuracy of several major ICD-10 codes for cirrhosis diagnosis in a large and diverse patient cohort; there is little existing research on this topic. Using data from 3396 patients with chronic liver disease (hepatitis B, C or non-alcoholic fatty liver disease) from one university and several community medical centers, we calculated sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the receiver operating characteristic curve (AUROC) for several major ICD-10 codes for cirrhosis, which was verified by individual chart review. We performed a secondary validation in a general cohort of 1560 randomly selected patients. While each of the individual study ICD-10 codes were specific (98.08 - 100%), none of the codes were sufficiently sensitive (0.27 - 55.70%). PPVs were high in the chronic liver disease cohort (88.41 - 100%) but lower in the general population (55.53 - 66.76%). The AUROC for having at least one code was higher (0.79) than any code alone (0.50 - 0.65). Individual ICD-10 codes are suboptimal for identifying patients with cirrhosis in the general patient population. We recommend conditioning ICD-10 code searches with a chronic liver disease diagnosis code and/or combining diagnostic codes to maximize performance. Individual ICD-10 codes are suboptimal for identifying patients with cirrhosis in the general patient population. We recommend conditioning ICD-10 code searches with a chronic liver disease diagnosis code and/or combining diagnostic codes to maximize performance. To examine the physiological, muscle-damage, endocrine, and immune responses to a modified soccer-simulation protocol to include technical and jumping activities characteristic of match play (the Technical Soccer-Specific Aerobic Field Test; T-SAFT90). Eighteen university players (age23 [2]y, stature175 [5]cm, body mass 74 [11]kg) performed the 90-minute protocol, with acute physiological responses monitored via heart rate, ratings of perceived exertion (6-20 scale), and body mass changes. Creatine kinase, myoglobin, cortisol, and leukocyte subset concentrations were measured at baseline, immediately (0h), and 24 hours post T-SAFT90. T-SAFT90 incurred an average heart rate equivalent to 87% (5%) of maximum, 16 (2)a.u. ratings of perceived exertion, and a 1.5% (1.0%) body mass deficit. Moderate to large proliferation of leukocyte subsets (P ≤ .01; leukocytes 6.4-fold; neutrophils 5.5-fold; lymphocytes 2.0-fold) and increases in cortisol (2.3-fold) were observed at 0 hours (effect size = 1.13-3.52), each returning to baseline by 24 hours (P > .45; effect size = 0.05-0.50). Myoglobin peaked immediately post T-SAFT90 (4.8-fold), whereas creatine kinase (24h 6.0-fold) showed a delayed time course (both P ≤ .001; very large effects; effect size = 2.66 and 3.43, respectively). The magnitude and time course of the physiological, immune, endocrine, and muscle-damage markers observed during and following T-SAFT90 are similar to values reported in match-play literature, demonstrating external validity of the simulation. The magnitude and time course of the physiological, immune, endocrine, and muscle-damage markers observed during and following T-SAFT90 are similar to values reported in match-play literature, demonstrating external validity of the simulation. To compare the metabolic cost of paddling on different commercially available kayak ergometers using a standardized kayak incremental exercise protocol. Six male sprint kayak athletes undertook an incremental exercise protocol on 3 different kayak ergometers utilizing a randomized counterbalanced pair-matched design. Mean maximal aerobic power on the WEBA ergometer (265 [14]W) was significantly higher than on the Dansprint (238 [9]W) and KayakPro® (247 [21]W, P < .01, effect size [ES] = 0.80). https://www.selleckchem.com/products/kpt-8602.html At the fifth stage, absolute oxygen consumption on the WEBA (3.82 [0.25]L·min-1) was significantly lower (P < 0.05, ES = 0.20) than KayakProand Dansprint (4.10 [0.28] and 4.08 [0.27]L·min-1, respectively). Blood lactate concentration response at the sixth stage was significantly lower for the WEBA (3.5 [0.8]mmol·L-1), compared with KayakProand Dansprint (5.4 [1.2] and 5.6 [1.5] mmol·L-1, P = .012, ES = 0.20). Stroke rate was significantly higher, without any effect of pacing during the submaximal stages for d against a first principle device, it is necessary to consider calibration of various drag settings, due to their impact on stroke rate. Further research should explore the relationship between drag settings and stroke rate. To examine the within- and between-sexes physical performance, well-being, and neuromuscular function responses across a 4-day international touch rugby (Touch) tournament. Twenty-one males and 20 females completed measures of well-being (fatigue, soreness, sleep, mood, and stress) and neuromuscular function (countermovement jump height, peak power output, and peak force) during a 4-day tournament with internal, external, and perceptual loads recorded for all matches. Relative and absolute total, low-intensity (females), and high-intensity distance were lower on day 3 (males and females) (effect size [ES] = -0.37 to -0.71) compared with day 1. Mean heart rate was possibly to most likely lower during the tournament (except day 2 males; ES = -0.36 to -0.74), whereas rating of perceived exertion-training load was consistently higher in females (ES = 0.02 to 0.83). The change in mean fatigue, soreness, and overall well-being was unclear to most likely lower (ES = -0.33 to -1.90) across the tournament for boessary. To examine the impact of workload volume during training sessions and games on subsequent sleep duration and sleep quality in basketball players. Seven semiprofessional male basketball players were monitored across preseason and in-season phases to determine training session and game workloads, sleep duration, and sleep quality. Training and game data were collected via accelerometers, heart-rate monitors, and rating of perceived exertion (RPE) and reported as PlayerLoad™ (PL), summated heart-rate zones, and session RPE (sRPE). Sleep duration and sleep quality were measured using wrist-worn activity monitors in conjunction with self-report sleep diaries. For daily training sessions and games, all workload data were independently sorted into tertiles representing low, medium, and high workload volumes. Sleep measures following low, medium, and high workloads and control nights (no training/games) were compared using linear mixed models. Sleep onset time was significantly later following medium and high PL and sRPE game workloads compared with control nights (P < .