Fatigue Inducing Resistance Training Produces Differences in Perceived Recovery Status and Session Rate of Perceived Exertion Responses

Psychophysiological tools have gained substantial traction as methods of assessing fatigue during exercise. Borg’s rate of perceived exertion (RPE) measures exertion levels of various modes of exercise, including resistance training. The perceived recovery status (PRS) scale is recognized as an effective tool when assessing recovery following fatiguing bouts of exercise. Previous PRS and RPE sprint training research, recognized PRS decline with concurrent sRPE increases. However, the relationship between PRS and sRPE during resistance training is unknown. PURPOSE: The aim of this study is to explore the relationship between PRS and sRPE within resistance training. METHODS: Fourteen resistance trained males (n = 7) and females (n = 7) participated in five resistance training sessions. Session 1 consisted of one-repetition maximum (1RM) testing of bench press (BP) and squat (SQ), and familiarization of PRS and sRPE. Sessions 2-5 involved a standardized dynamic warm up followed by four sets of SQ - three warm up sets (55, 65, 75% 1RM) and one working set of as many repetitions as possible (AMRAP) at 85% 1RM. A 10-minute rest period was allotted, followed by four sets of BP adhering to the 4 set protocol. Following a 5-minute rest period, participants completed 4 sets of 2-repetitions in reserve for three accessory lifts (barbell reverse lunge, overhead press, and bent-over row) performed in circuit training fashion (90s rest between circuits). In order, 72hrs, 48hrs, 24hrs, then 6hrs rest was assigned as between session recovery. Prior to each session PRS was recorded and 30 minutes after completion of each session sRPE was logged. PRS and sRPE were measured using a 2 (fatigue) x 4 (sets) repeated measures ANOVA. RESULTS: A significant main effect was revealed within PRS and sRPE (F(2.319, 60.287) = 8.050, p \u3c .001), as well as between PRS and sRPE across sessions (F(2.319, 60.287) = 14.803, p \u3c .001). Bonferroni post hoc adjustment revealed differences in sessions 1 and 2 (2.214(95% CI, 1.091 to 3.338), p \u3c .001), 1 and 3 (2.00 (95% CI, .328 to 3.672), p \u3c .013), 1 and 4 (3.571 (95% CI, 2.425 to 4.718), p \u3c .001), 2 & 4 (1.357 (95% CI, .273 to 2.441), p = .008), as well as 3 and 4 (1.571 (95% CI, .390 to 2.753), p = .005) PRS scores. Furthermore, a significant difference was recognized between PRS and sRPE of sessions 4 (-3.143 (95% CI, -4.456 to 2.192), p \u3c .001). CONCLUSION: These results support and mirror intermittent sprint training PRS and sRPE reports. Moreover, as PRS values decrease, due to fatiguing resistance training sessions, global levels of fatigue (sRPE) increased; thus, further illustrating the PRS scale as a valid metric of assessing pre-exercise recovery

Macronutrients for High and Low Injury Risk Collegiate Rodeo Athletes Compared to Recommended Dietary Allowances

Rodeo is a high-intensity, intermittent sport in nature unlike popular American sports. The production of empirical research outlining the physical demands and ideal training methods connected to rodeo and improving performance has not matched the rate of growth the sport of rodeo has experienced. Particularly regarding nutritional recommendations, limited research explains nutrition and its role in injury prevention and the process of recovery in rodeo athletes. PURPOSE: The purpose was to investigate the differences of macronutrients between high risk and low risk of injury in rodeo athletes compared to recommended daily allowances (RDA). METHODS: College rodeo athletes from a mid-size university in the southwest region were recruited to be a part of the study (n=150). Subjects completed a 3-day food record – 2 non-consecutive standard nutritional intake days and 1 unconventional day. Dietary intake records were input into Elizabeth Stewart Hands and Associates (ESHA) Food Processor Nutrition Analysis Software. Low and high-risk categorization was performed across nine college rodeo events. In accordance with previous literature outlying injury percentages (\u3e10 injuries; low-risk year). Subjects that competed in barrel racing, breakaway, and team roping were categorized as low injury risk athletes. Bull riding, saddle bronc, bareback, team roping, goat-tying, and steer wrestling were grouped as high-risk. The RDA macronutrient percentage recommendations (protein 25%, carbohydrates 55%, fats 20%) were utilized as comparative values. A paired sample t-test (p \u3c .05) was used to analyze the average macronutrients intake of rodeo athletes compared to recommended daily allowance (RDA) for high-risk and low-risk rodeo athletes. RESULTS: High-risk athletes’ average macronutrients were significantly different when compared to the RDA (Kcal pCONCLUSION: These data will be able to expose the surpluses and deficiencies of the dietary intake of the collegiate rodeo athletes. Low-risk rodeo athletes experienced overconsumption in fat and under consume the recommended number of kcals, protein and carbohydrates. High-risk athletes’ data showed under consumption in all areas explored. These data suggest for both adjustments should be made to address these deficiencies

Sex Specific Difference in Rate of Perceived Exertion During Fatigue Induced Resistance Training

While previously literature clearly articulates the OMNI Scale of Perceived Exertion (RPE) as a quality tool for identifying resistance training perceived difficulty, sex-specific RPE differences during fatigue induced resistance training still remain unclear. PURPOSE: The aim of the current investigation was to examine the difference in male and female intrasession and session RPE (sRPE) during fatiguing upper and lower body resistance exercise. METHODS: Fourteen resistance trained individuals (7 males, 7 females, age = 20.93 ± 1.54, height = 68.07 ± 4.16 cm, weight = 78.33 ± 12.86 kg) performed 5 sessions of resistance training. Session 1 involved familiarization of the RPE scales, anthropometric and skinfold measurements, and 1-repetition maximum (1RM) testing of barbell back squat (SQ) and barbell bench press (BP). Sessions 2-5 participants completed a dynamic warm up followed by 1 set of as many repetitions as possible (AMRAP) at 85% 1RM on SQ and BP, with 10 min rest between exercises. Intrasession RPE was recorded immediately after AMRAP set completion for SQ and BP. To simulate a typical resistance training routine, 4 sets of accessory lifts were performed following BP AMRAP sets. Session RPE was recorded 30 min after completion of each session. Between sessions rest incrementally declined (72, 48, 24, and 6 h) to elicit fatigue. A 2 (sex) x 2 (exercise) x 4 (session) mixed factorial ANOVA was employed to examine sex-specific responses to upper and lower body fatigue induced resistance training. A 2 (sex) x 4 (session) factorial ANOVA was used to assess sRPE sex differences. Alpha level set at p \u3c .05. RESULTS: There was no significant main effect or interaction revealed (F (2,27) = 4.467, p = .021). However, a medium effect size was established between sexes during session 1 squat average intrasession RPE (d= -0.33) and session 4 sRPE (d = -0.32). A large effect size was found between males and females in session 3 sRPE (d = -3.31). Intrasession RPE and sRPE were collapsed and female reported substantially lower sRPE than males (d = .49); however, a small magnitude (d = -.18) of difference or no difference was identified between sexes for intrasession RPE. CONCLUSION: In conclusion, these findings suggest that female possess greater fatigue resistance during lower body exercises when assessed utilizing intrasession RPE. Moreover, males and females differ in their perception of exertion as intersession recovery periods decline, illustrated by decreased sRPE reported by females upon completion of sessions 3 and 4 compared to men. These data also indicated intrasession RPE does not markedly vary between sexes; however, retrospectively (sRPE), females appear to be less effected by fatigue induced exercise or females’ recollection of difficulty diminished post exercise. In conclusion, RPE should be interpreted and utilized differently for males and females

Establishing a Predictive Equation for Anaerobic Capacity Utilizing the 300-yard Shuttle Field Test

Anaerobic capacity can be tested through the Running-based Anaerobic Sprint Test (RAST), Wingate test (gold standard), and the 300-yard shuttle. While each testing is recognized as a valid method of assessing anaerobic capacity, previous investigations found no significant correlation between Wingate test and time to completion of 300-yard shuttle test. The insignificant relationship found between the 300-yard shuttle times and the Wingate outputs insinuate a need for further research investigating the correlations between these two anaerobic tests. PURPOSE: The aim of this study was to determine the influence of 300-yard shuttle measures on anaerobic capacity obtained via the Wingate test. METHODS: Twenty-two Division I softball players (20.41 +1.50 yr) completed two anaerobic testing sessions. Session 1 consisted of the 30s all out Wingate test. Sessions 2 was completed 48 hours following session 1 and involved the performance of two 300-yard shuttle run tests separated with 5 minutes rest. The Wingate test data included: anaerobic peak power (PP), average power (AP), power drop (PD), power drop per second (PD/s), maximal speed (MS), and power at maximal speed (PMS). The recorded 300-yard shuttle measures were time and kinetic energy factor (K-factor) (new anaerobic variable) for both attempts, as well as average time and average K-factor. K-factor during the 300-yard shuttle was calculated by utilizing the mass of participants multiplied by speed (distance divided by time elapsed) squared. A backwards stepwise multiple linear regression was employed to examine the influence of 300-yard shuttle on anaerobic capacity measure obtained via Wingate test. RESULTS: Statistical analysis identified the second 300-yard shuttle attempt time (S300) predicting AP as the model of best fit, which S300 explaining 32.7% of the variance of AP; furthermore, generating the following predictive equation: AP = 9.91 – (.049 x S300). Secondly, 84.2% of the variance in PD was explained by Average K-factor (AKF), establishing PD = -.85 + (.098 x AKF) as a predictive equation. Lastly, AKF, also, predicted 84.3% of the variance in PD/s: PD/s = -.028 + (.003 x AKF). CONCLUSION: An aspect of these finding contradicted preview investigations, as the S300 was recognized as a significant predictor of AP, suggesting faster 300-yard shuttle performance may increase AP. The positive significant correlation between the AKF and Wingate PD and PD/s suggest higher AKF may influence greater measures of PD and PD/s. These finding appear to support that calculating K-factor provides a richer understanding of field tested (300-yard shuttle) anaerobic capacity

Sex-Specific Pre-Session PRS Difference between Bouts of Fatiguing Resistance Training

The perceived recovery status (PRS) scale, a valid psychophysiological tool, provides a scalar representation of varying levels of an individualized recovery status before or during various modes of exercise. Previous investigations recognize females as more fatigue resilient, quantified via the PRS scale, than males during repeated sprint performance. To the best of our knowledge, no investigations have examined the sex-specific PRS responses during multi-session resistance training. PURPOSE: The purpose of this study was to compare male and female PRS scores for multi-session fatiguing resistance training with incremental decline intersession recovery periods. METHODS: Subjects consisted of 14 trained males (n = 7) and females (n = 7) that participated in five resistance training sessions. Session 1 consisted of one repetition maximum (1RM) testing for barbell back squat (SQ) and barbell bench press (BP); additionally, during session 1, subjects were given standardized instructions explaining how to interpret the PRS scale (familiarization). PRS was collected prior to each training session. Seventy-two hours after session 1, participants completed a standardized dynamic warm up, followed by a comprehensive, fatiguing resistance training session that began with 3 sets of 55%, 65%, and 75% 1RM, followed by 1 set of as many repetitions as possible (AMRAP) at 85% 1RM for SQ. Ten minutes of recovery was provided upon completion of SQ, before completing the same 4 set routine for BP. Upon 5-minute rest, participants completed 4 set of 2 repetitions in reserve (RIR) for barbell reverse lunge, barbell shoulder press, and barbell bent-over row in circuit format with 90 seconds rest between circuits. In order, 72hrs, 48hrs, 24hrs, and 6hrs rest periods were assigned as intersession recovery. A 2 (sex) x 4 (session) mixed factorial ANOVA was used to determine the sex-specific responses to resistance training. RESULTS: No significant main effect was revealed between males and females PRS scores across sets. However, a statistically significant main effect of PRS scores was illustrated across sets [F (2.323, 27.875) =19.363, pCONCLUSION: These results suggest males and females globally recover similarly from fatigue induced resistance training. However, these data also suggest optimal intersession recovery duration may differ between the sexes – males reported significantly less recovered 48hr after training (between set 2 and 3), while female recovery decline after 48hr was an insignificant change; thus, aligning with previous reports of greater fatigue resilience appearing in females versus males

The Relationship between 60-yard sprint, 30-yard sprint, Standardized Base Stealing Sprint, and Offensive Baseball Performance

Athletic performance testing protocols strive to accurately predicting or gain better understanding of an athlete’s performance within a particular sport or game. Regarding baseball, Wolfe and colleagues (2012) examined the predictive validity of the 60-yard shuttle run on pitching performance and concluded that strikeouts and innings pitched were significantly related to elevated kinetic energy factors of pitchers obtained from the shuttle run performance. Concerning for baseball position players, the 60-yard sprint (60YS) is traditionally utilized to showcase “baseball speed”, with minimal empirical evident supporting predictability to baseball specific performance outcomes. PURPOSE: The aim of the current investigation was to have examine the relationship between 60YS and offensive baseball performance outcomes, as well as the 30-yard sprint (30YS) test, and newly created standardized 1st to 2nd sprint (STS) test relationship to offensive baseball performance outcomes. METHODS: Division I baseball position players (n = 17; height: 180.92 ± 5.61 cm; weight: 82.1 ± 11.12 kg) performed three sprinting tests: 60YS, 30YS, and STS. Each test was recorded using the Brower Timing Gate System, with sprint time recorded in second. All testing was completed prior to the first game of the team’s college baseball season. Offensive baseball performance measures were recorded throughout 61 regular season games. The following baseball performance data was collected from the university’s official NCAA game performance website: total stolen bases (SB), stole base attempts (AT), stolen base percentage (SBP), at bats (AB), hits (H), doubles (DB), triples (TR), homeruns (HR), runs (R), base-on-balls (BB), hit by pitch (HBP), on base percentage (OBP), slugging percentage (SLP), touched bases (TB), runs batted in (RBI), and batting average (AVE). Pearson’s product-moment correlation (p \u3c .05) was employed to examine the correlation between sprint tests and offensive baseball performance. RESULTS: The statistical analysis revealed significant correlations between STS (p = .002, r = -.762), 30 yd sprint (p = .048, r = -.556), and 60 yd sprint (p = .038, r = -.578) and SB. Additionally, a significant correlation was identified between OBP and STS (p = .022, r = -.625), 30YS (p = .027, r = -.609), and 60YS (p = .020, r = -.633). Aside from these two baseball performance metrics, 30YS and 60YS had no significant correlation with baseball performance. However, STS, additionally, significantly (p \u3c .05) correlated with AT, AB, H, TR, HR, R, BB, SLP, TB, RBI, and AVE. CONCLUSION: The STS, 30YS, and 60YS had a significant relationship with offensive baseball performance. However, the results of 30YS and 60YS only correlated with two offensive measures, while STS had a significant correlation with all but 3 offensive performance metrics. These findings suggest STS may be a more relevant measure for predicting offensive baseball performance than the traditional 30YS and 60YS tests

Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat

Correction to: Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

The original version of this article unfortunately contained a mistake

Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat

Differences in Assistance Exercise Volume-Load Prescription during Fatigue Induced Resistance Training

The common purpose of assistance lift application within resistance training is to prevent injury of sport-specific predisposed musculature by strengthening a specific muscle or muscle group. The integration of assistance exercises within standard resistance training is frequently observed, showcasing a high ecological validity of assistance exercises. However, specific prescription of assistance exercises has received little empirical examination. PURPOSE: Therefore, the purpose of the current investigation was to examine changes in assistance lift performance due to fatigue induced resistance training. METHODS: Fourteen resistance trained individuals (male = 7, female = 7, age = 20.93 ± 1.54, ht = 68.07 ± 4.16 cm, wt = 78.33 ± 12.86 kg) participated in 5 resistance training sessions. Session 1 consisted of anthropometric and skinfold testing, one repetition maximum (1RM) testing for barbell back squat (SQ) and barbell bench press (BP), and familiarization of assistance lifts. Session 2-5, involved a standardized dynamic warm up and a comprehensive resistance training session comprising 3 sets of 5 repetitions at 55%, 65%, and 75% 1RM, followed by 1 repetition maximum set at 85% 1RM for SQ and BP, ten minutes passive rest between exercises. Upon 5-minute rest, participants completed 4 sets of 2 repetitions-in-reserve for 3 assistance exercises (barbell reverse lunge [RL], barbell shoulder press [SP], and barbell bent-over row [BR]) in circuit format with 90s rest between circuits. Weight lifted and repetitions completed were recorded and combined as volume-load for each assistance lift. Total session volume-load was the sum of volume-load of all assistance exercises. In order, 72, 48, 24, and 6 h rest periods were assigned as between session recovery intentionally decreasing in time to elicit fatigue. A 3 (exercise) x 4 (session) mixed factorial ANOVA was used to determine difference in assistance lift volume-load. RESULTS: Due to the data violating assumptions of sphericity (p \u3c .001) ANOVA test statistics are estimated using the Greenhouse-Geisser method. There is a significant main effect for assistance exercise volume-load (p \u3c .001). There is no significant interaction between session volume-load (p = .846). Bonferroni post hoc expressed significant differences between all assistance exercises within all sessions, except, RL and SP during session 2 (p = .476) and RL and SP during session 4 (p = .130). CONCLUSION: These data suggest assistance exercises are inherently different and exercise specific prescriptions should be established for assistance lifts. While there was no significant interaction, Cohen\u27s d analysis indicated a medium effect size between cumulative session volume-load of session 1 and session 3 (d = .28), as well as session 1 and session 4 (d = .29). These magnitudinal differences support assistance lift prescription modulation based on fatigue. Furthermore, research examining load, volume, and intensity prescriptions necessitates further investigation to ensure resistance training prescriptions adhere to the principle of specificity