Derivation and Validation of Generalized Sepsis-induced Acute Respiratory Failure Phenotypes Among Critically Ill Patients: A Retrospective Study.

Background: Septic patients who develop acute respiratory failure (ARF) requiring mechanical ventilation represent a heterogenous subgroup of critically ill patients with widely variable clinical characteristics. Identifying distinct phenotypes of these patients may reveal insights about the broader heterogeneity in the clinical course of sepsis. We aimed to derive novel phenotypes of sepsis-induced ARF using observational clinical data and investigate their generalizability across multi-ICU specialties, considering multi-organ dynamics. Methods: We performed a multi-center retrospective study of ICU patients with sepsis who required mechanical ventilation for ≥24 hours. Data from two different high-volume academic hospital systems were used as a derivation set with N=3,225 medical ICU (MICU) patients and a validation set with N=848 MICU patients. For the multi-ICU validation, we utilized retrospective data from two surgical ICUs at the same hospitals (N=1,577). Clinical data from 24 hours preceding intubation was used to derive distinct phenotypes using an explainable machine learning-based clustering model interpreted by clinical experts. Results: Four distinct ARF phenotypes were identified: A (severe multi-organ dysfunction (MOD) with a high likelihood of kidney injury and heart failure), B (severe hypoxemic respiratory failure [median P/F=123]), C (mild hypoxia [median P/F=240]), and D (severe MOD with a high likelihood of hepatic injury, coagulopathy, and lactic acidosis). Patients in each phenotype showed differences in clinical course and mortality rates despite similarities in demographics and admission co-morbidities. The phenotypes were reproduced in external validation utilizing an external MICU from second hospital and SICUs from both centers. Kaplan-Meier analysis showed significant difference in 28-day mortality across the phenotypes (p<0.01) and consistent across both centers. The phenotypes demonstrated differences in treatment effects associated with high positive end-expiratory pressure (PEEP) strategy. Conclusion: The phenotypes demonstrated unique patterns of organ injury and differences in clinical outcomes, which may help inform future research and clinical trial design for tailored management strategies.

Bigger calves from doing higher resistance training volume?

We compared the effects of different calf training weekly sets on muscle size changes. Sixty-one untrained young women performed a calf training program for 6 weeks, 3 d·wk-1, with differences in the resistance training volume. The participants were randomly assigned to 1 of the 3 groups: 6-SET, 9-SET, and 12-SET calf training weekly sets. The calf raise exercise was performed in sets of 15-20 repetitions maximum. The muscle thickness measurements of medial gastrocnemius (MG), lateral gastrocnemius (LG), and soleus (SOL) were taken via B-mode ultrasound. We used the sum of the three-muscle thickness as a proxy for the triceps surae (TSSUM). The 12-SET group elicited greater increases than 6-SET in LG (6-SET = +8.1% vs. 12-SET = +14.3%; P = 0.017), SOL (6-SET = +6.7% vs. 12-SET = +12.7%; P = 0.024), and TSSUM (6-SET = +6.9% vs. 12-SET = +12.0%; P = 0.005), but there was no significant difference in MG changes (6-SET = +6.6% vs. 12-SET = +9.9%; P = 0.067). There were no significant differences when comparing 9-SET vs. 6-SET and 12-SET (P ≥ 0.099). Although all groups experienced calf muscle hypertrophy, our results suggest that the higher dose range may optimize triceps surae muscle size gains.

The influence of microbial colonization on inflammatory versus pro-healing trajectories in combat extremity wounds.

A combination of improved body armor, medical transportation, and treatment has led to the increased survival of warfighters from combat extremity injuries predominantly caused by blasts in modern conflicts. Despite advances, a high rate of complications such as wound infections, wound failure, amputations, and a decreased quality of life exist. To study the molecular underpinnings of wound failure, wound tissue biopsies from combat extremity injuries had RNA extracted and sequenced. Wounds were classified by colonization (colonized vs. non-colonized) and outcome (healed vs. failed) status. Differences in gene expression were investigated between timepoints at a gene level, and longitudinally by multi-gene networks, inferred proportions of immune cells, and expression of healing-related functions. Differences between wound outcomes in colonized wounds were more apparent than in non-colonized wounds. Colonized/healed wounds appeared able to mount an adaptive immune response to infection and progress beyond the inflammatory stage of healing, while colonized/failed wounds did not. Although, both colonized and non-colonized failed wounds showed increasing inferred immune and inflammatory programs, non-colonized/failed wounds progressed beyond the inflammatory stage, suggesting different mechanisms of failure dependent on colonization status. Overall, these data reveal gene expression profile differences in healing wounds that may be utilized to improve clinical treatment paradigms.

ClotCatcher: a novel natural language model to accurately adjudicate venous thromboembolism from radiology reports.

INTRODUCTION: Accurate identification of venous thromboembolism (VTE) is critical to develop replicable epidemiological studies and rigorous predictions models. Traditionally, VTE studies have relied on international classification of diseases (ICD) codes which are inaccurate - leading to misclassification bias. Here, we developed ClotCatcher, a novel deep learning model that uses natural language processing to detect VTE from radiology reports. METHODS: Radiology reports to detect VTE were obtained from patients admitted to Emory University Hospital (EUH) and Grady Memorial Hospital (GMH). Data augmentation was performed using the Google PEGASUS paraphraser. This data was then used to fine-tune ClotCatcher, a novel deep learning model. ClotCatcher was validated on both the EUH dataset alone and GMH dataset alone. RESULTS: The dataset contained 1358 studies from EUH and 915 studies from GMH (n = 2273). The dataset contained 1506 ultrasound studies with 528 (35.1%) studies positive for VTE, and 767 CT studies with 91 (11.9%) positive for VTE. When validated on the EUH dataset, ClotCatcher performed best (AUC = 0.980) when trained on both EUH and GMH dataset without paraphrasing. When validated on the GMH dataset, ClotCatcher performed best (AUC = 0.995) when trained on both EUH and GMH dataset with paraphrasing. CONCLUSION: ClotCatcher, a novel deep learning model with data augmentation rapidly and accurately adjudicated the presence of VTE from radiology reports. Applying ClotCatcher to large databases would allow for rapid and accurate adjudication of incident VTE. This would reduce misclassification bias and form the foundation for future studies to estimate individual risk for patient to develop incident VTE.

Targeted metagenomic assessment reflects critical colonization in battlefield injuries.

IMPORTANCE: Microbial contamination in combat wounds can lead to opportunistic infections and adverse outcomes. However, current microbiological detection has a limited ability to capture microbial functional genes. This work describes the application of targeted metagenomic sequencing to profile wound bioburden and capture relevant wound-associated signatures for clinical utility. Ultimately, the ability to detect such signatures will help guide clinical decisions regarding wound care and management and aid in the prediction of wound outcomes.

Acute Effects of a Practical Blood Flow Restriction Device During Swimming Exercise.

Purpose: The present study aimed to analyze: 1) the reliability of the tissue saturation index (TSI) and ratings of perceived discomfort (RPD) responses wearing a neoprene practical cuff (PrC), comparing with the responses from traditional (TrC) pneumatic cuffs (study I); 2) the effects of PrC on metabolic (blood lactate concentration, BLC), perceptual (rate of perceived effort, RPE) and kinematic responses at sub-maximal swimming velocities (study II). Methods: Study I; 1) PrC test-retest at rest and during swimming ergometer exercise; 2) BFR at rest with TrC inflated to different percentages of the minimum arterial occlusion pressure (MAOP; 60, 80, 100, 120 and 140%). Test-retest reliability of TSI and RPD was assessed by the intraclass correlation coefficient (ICC) and comparisons among conditions were analyzed by one-way repeated-measures ANOVA. Study II; 1) 50, 200 and 400 m swimming performances; 2) sub-maximal incremental swimming protocol with and without PrC. Two-way repeated measures ANOVA was used to compare all variables during sub-maximal velocities. Results: TSI (ICC = 0.81; 95%CI 0.62-0.91) and RPD (ICC = 0.97; 95%CI 0.94-0.99) were reliable under restricted exercise using PrC. TSI during restricted exercise was lower (p <.001) compared to unrestricted exercise (6.8 ± 6.1% vs. 21.6 ± 8.2% of physiological normalization). PrC showed higher BLC only at or above 91% of critical velocity (p < .03), while stroke rate and RPE were higher (p < .005), and stroke length was lower (p < .03) during all swimming velocities. Conclusion: This easy-to-handle and affordable practical BFR device increased physiological stress at sub-maximal efforts which could be an additional training tool for swimmers.

Central role for neurally dysregulated IL-17A in dynamic networks of systemic and local inflammation in combat casualties.

Dynamic Network Analysis (DyNA) and Dynamic Hypergraphs (DyHyp) were used to define protein-level inflammatory networks at the local (wound effluent) and systemic circulation (serum) levels from 140 active-duty, injured service members (59 with TBI and 81 non-TBI). Interleukin (IL)-17A was the only biomarker elevated significantly in both serum and effluent in TBI vs. non-TBI casualties, and the mediator with the most DyNA connections in TBI wounds. DyNA combining serum and effluent data to define cross-compartment correlations suggested that IL-17A bridges local and systemic circulation at late time points. DyHyp suggested that systemic IL-17A upregulation in TBI patients was associated with tumor necrosis factor-α, while IL-17A downregulation in non-TBI patients was associated with interferon-γ. Correlation analysis suggested differential upregulation of pathogenic Th17 cells, non-pathogenic Th17 cells, and memory/effector T cells. This was associated with reduced procalcitonin in both effluent and serum of TBI patients, in support of an antibacterial effect of Th17 cells in TBI patients. Dysregulation of Th17 responses following TBI may drive cross-compartment inflammation following combat injury, counteracting wound infection at the cost of elevated systemic inflammation.

Entre o medo e a esperança: um estudo sobre os usos e sentidos do treinamento cerebral no Brasil / Between fear and hope: a study on the uses and meanings of brain training in Brazil

O presente trabalho tem como objeto de análise os usos e sentidos das práticas de treinamento cerebral na realidade brasileira. Este tipo de treinamento, também chamado de treinamento cognitivo e ginástica cerebral, diz respeito à prática guiada de determinados exercícios e jogos com o objetivo de preservar ou melhorar as habilidades cognitivas e/ou a cognição como um todo. O objetivo central deste trabalho é mapear e analisar os sentidos atribuídos pelas empresas de treinamento cerebral e seus clientes às próprias atividades de treinamento cerebral. Para atingir tal objetivo realizamos a análise de conteúdo de dois conjuntos de dados: a) informações textuais dos sites oficiais das três franquias de treinamento cerebral existentes no Brasil (Supera, Super Cérebro e Ginástica do Cérebro) assim como das principais plataformas virtuais brasileiras (Supera Online, NeuroForma, Afinando o Cérebro e Mente Turbinada); b) transcrições de entrevistas semiestruturadas com dez clientes destas empresas, com idades entre 22 e 87 anos, e que praticavam regulamente tais atividades. Após analisarmos o conteúdo dos sites e das entrevistas pudemos observar que os sentidos do treinamento cerebral se relacionam, para os clientes, a uma série de medos e esperanças ­ e também à busca por diversão e sociabilidade. Dentre os medos destaca-se aquele relacionado à possibilidade de desenvolver a doença de Alzheimer ou algum outro quadro demencial que prejudique suas funções cognitivas e os levem a perder a autonomia e se tornarem dependentes de outras pessoas. Por outro lado, a busca por atividades de treinamento cerebral se relaciona também à esperança de reverter ou interromper o "declínio cognitivo" e de evitar, assim, o desenvolvimento de uma demência. As empresas, por sua vez, fomentam em seus clientes e potenciais clientes, através dos seus sites publicitários, diferentes formas de esperança, em especial a esperança de um futuro com capacidade cognitiva nas diversas etapas da vida. É possível dizer que o que há em comum entre aquilo que é vendido pelas empresas e aquilo que é comprado por seus clientes é a esperança. Apontamos, por fim, para as técnicas de treinamento cerebral como tecnologias da esperança, devido ao fato de serem utilizadas pelas empresas do ramo para fomentarem em seus clientes e potenciais clientes a crença de que é possível agir no presente de forma a preservar e aprimorar as habilidades cognitivas, a prevenir doenças como o Alzheimer e a prolongar o tempo de vida com saúde, autonomia e independência... (AU)

The main goal of the present doctoral thesis is to analyze the uses and meanings of the practices of cerebral training in Brazil. This type of training, also known as cognitive training and cerebral gymnastics, is related to the guided practice of specific exercises and games to preserve or improve cognitive skills and/or cognition in general. The main objective of this work is to map and analyze the definitions attributed to cerebral training companies and their clients to their brain training activities. To achieve this goal, we analyzed two groups of data: a) textual information available on the official websites of three Brazilian franchises focused on brain training (Super, Super Cérebro e Ginástica do Cérebro), as well the leading Brazilian virtual platforms (Supera Online, NeuroForma, Afinando o Cérebro e Mente Turbinada); b) transcriptions of semi-structured interviews with ten regular consumers of these companies, ages from 22 to 87 years. After analyzing the contents available on the websites and interviews, we could observe that the aims of brain training are connected. Besides the search for fun and sociability on the client's side, there are a series of fears and hopes. Among fears, we could stand out as the ones connected to the possibility of developing a future Alzheimer's disease or any other type of dementia state that could harm their cognitive functions and, consequently, lead them to lose their autonomy and become dependent on others. On the other hand, the search for brain gymnastic activities is related to the hope to revert or interrupt the "cognitive decline" and avoid the development of dementia. However, on their side, the companies encourage their clients and potential clients, through their advertising websites, different ways to trigger their hopes, especially the hope of a future when they develop cognitive capacities in different parts of their lives. We could claim that what connects the message released and these types of products, bought and sold, is hope. We finally point out that the techniques of brain training are technologies of hope since the companies of the field use them to foment their clients and potential clients the belief that it is possible to achieve, in the present, some preservation and improvement of cognitive skills, to prevent some diseases as Alzheimer and to lengthen their life expectancy healthily, enjoying autonomy and independence...(AU)

Modeling the expenditure and reconstitution of distance above critical speed during two swimming interval training sessions.

In swimming, the speed-time relationship provides the critical speed (CS) and the maximum distance that can be performed above CS (D'). During intermittent severe intensity exercise, a complete D' depletion coincides with task failure, while a sub-CS intensity is required for D' reconstitution. Therefore, determining the balance D' remaining at any time during intermittent exercise (D'BAL) could improve training prescription. This study aimed to 1) test the D'BAL model for swimming; 2) determine an equation to estimate the time constant of the reconstitution of D' (τD'); and 3) verify if τD' is constant during two interval training sessions with the same work intensity and duration and recovery intensity, but different recovery duration. Thirteen swimmers determined CS and D' and performed two high-intensity interval sessions at a constant speed, with repetitions fixed at 50 m. The duration of passive recovery was based on the work/relief ratio of 2:1 (T2:1) and 4:1 (T4:1). There was a high variability between sessions for τD' (coefficient of variation of 306%). When τD' determined for T2:1 was applied in T4:1 and vice versa, the D'BAL model was inconsistent to predict the time to exhaustion (coefficient of variation of 29 and 28%). No linear or nonlinear relationships were found between τD' and CS, possibly due to the high within-subject variability of τD'. These findings suggest that τD' is not constant during two high-intensity interval sessions with the same recovery intensity. Therefore, the current D'BAL model was inconsistent to track D' responses for swimming sessions tested herein.

Metagenomic features of bioburden serve as outcome indicators in combat extremity wounds.

Battlefield injury management requires specialized care, and wound infection is a frequent complication. Challenges related to characterizing relevant pathogens further complicates treatment. Applying metagenomics to wounds offers a comprehensive path toward assessing microbial genomic fingerprints and could indicate prognostic variables for future decision support tools. Wound specimens from combat-injured U.S. service members, obtained during surgical debridements before delayed wound closure, were subjected to whole metagenome analysis and targeted enrichment of antimicrobial resistance genes. Results did not indicate a singular, common microbial metagenomic profile for wound failure, instead reflecting a complex microenvironment with varying bioburden diversity across outcomes. Genus-level Pseudomonas detection was associated with wound failure at all surgeries. A logistic regression model was fit to the presence and absence of antimicrobial resistance classes to assess associations with nosocomial pathogens. A. baumannii detection was associated with detection of genomic signatures for resistance to trimethoprim, aminoglycosides, bacitracin, and polymyxin. Machine learning classifiers were applied to identify wound and microbial variables associated with outcome. Feature importance rankings averaged across models indicated the variables with the largest effects on predicting wound outcome, including an increase in P. putida sequence reads. These results describe the microbial genomic determinants in combat wound bioburden and demonstrate metagenomic investigation as a comprehensive tool for providing information toward aiding treatment of combat-related injuries.

Cellular microRNAs correlate with clinical parameters in multiple injury patients.

INTRODUCTION: The pathophysiology of the inflammatory response after major trauma is complex, and the magnitude correlates with severity of tissue injury and outcomes. Study of infection-mediated immune pathways has demonstrated that cellular microRNAs may modulate the inflammatory response. The authors hypothesize that the expression of microRNAs would correlate to complicated recoveries in polytrauma patients (PtPs). METHODS: Polytrauma patients enrolled in the prospective observational Tissue and Data Acquisition Protocol with Injury Severity Score of >15 were selected for this study. Polytrauma patients were divided into complicated recoveries and uncomplicated recovery groups. Polytrauma patients' blood samples were obtained at the time of admission (T0). Established biomarkers of systemic inflammation, including cytokines and chemokines, were measured using multiplexed Luminex-based methods, and novel microRNAs were measured in plasma samples using multiplex RNA hybridization. RESULTS: Polytrauma patients (n = 180) had high Injury Severity Score (26 [20-34]) and complicated recovery rate of 33%. MicroRNAs were lower in PtPs at T0 compared with healthy controls, and bivariate analysis demonstrated that variations of microRNAs correlated with age, race, comorbidities, venous thromboembolism, pulmonary complications, complicated recovery, and mortality. Positive correlations were noted between microRNAs and interleukin 10, vascular endothelial growth factor, Acute Physiology and Chronic Health Evaluation, and Sequential Organ Failure Assessment scores. Multivariable Lasso regression analysis of predictors of complicated recovery based on microRNAs, cytokines, and chemokines revealed that miR-21-3p and monocyte chemoattractant protein-1 were predictive of complicated recovery with an area under the curve of 0.78. CONCLUSION: Systemic microRNAs were associated with poor outcomes in PtPs, and results are consistent with previously described trends in critically ill patients. These early biomarkers of inflammation might provide predictive utility in early complicated recovery diagnosis and prognosis. Because of their potential to regulate immune responses, microRNAs may provide therapeutic targets for immunomodulation. LEVEL OF EVIDENCE: Diagnostic Tests/Criteria; Level II.

A-Mode Ultrasound Reliability in Fat and Muscle Thickness Measurement.

ABSTRACT: Ribeiro, G, de Aguiar, RA, Penteado, R, Lisbôa, FD, Raimundo, JAG, Loch, T, Meira, Â, Turnes, T, and Caputo, F. A-mode ultrasound reliability in fat and muscle thickness measurement. J Strength Cond Res 36(6): 1610-1617, 2022-This study aimed to verify the reliability of the BodyMetrix portable A-mode ultrasound in measuring fat and muscle tissue thickness. Thirty physically active men participated in daily body composition evaluations. The evaluations comprised 2 techniques: (a) graphic technique (GTBM), which measured the fat thickness at 9 body sites (abdomen, axillary, biceps brachii, calf, chest, subscapular, suprailiac, thigh, and triceps brachii), and (b) imaging technique (ITBM), which simultaneously measured the fat and muscle thickness of 6 body surfaces (abdomen, biceps brachii, chest, thigh, trapezius, and triceps brachii). Regarding GTBM, relative reliability was moderate to excellent (intraclass correlation coefficient [ICC]: 0.81-0.98), whereas absolute reliability was acceptable for abdomen, calf, chest, subscapular, suprailiac, and triceps brachii (coefficient of variation [CV]: 6.9-8.8%) but high for axillary, biceps brachii, and thigh (CV: 12.0-17.4%) in measuring fat thicknesses. Concerning ITBM, relative reliability was good to excellent (ICC: 0.93-0.99 and 0.90-0.98), whereas absolute reliability was acceptable (CV: 3.0-9.2% and 3.5-5.9%) in measuring fat and muscle thickness, respectively. These findings suggest that the, GTBM was only reliable in measuring fat thickness of abdomen, calf, chest, subscapular, suprailiac, and triceps brachii, whereas ITBM was reliable in measuring both fat and muscle thickness in all regions, but showed better reliability values in measuring muscle than fat thickness.

Viral Micro-RNAs Are Detected in the Early Systemic Response to Injury and Are Associated With Outcomes in Polytrauma Patients.

OBJECTIVES: To evaluate early activation of latent viruses in polytrauma patients and consider prognostic value of viral micro-RNAs in these patients. DESIGN: This was a subset analysis from a prospectively collected multicenter trauma database. Blood samples were obtained upon admission to the trauma bay (T0), and trauma metrics and recovery data were collected. SETTING: Two civilian Level 1 Trauma Centers and one Military Treatment Facility. PATIENTS: Adult polytrauma patients with Injury Severity Scores greater than or equal to 16 and available T0 plasma samples were included in this study. Patients with ICU admission greater than 14 days, mechanical ventilation greater than 7 days, or mortality within 28 days were considered to have a complicated recovery. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Polytrauma patients (n = 180) were identified, and complicated recovery was noted in 33%. Plasma samples from T0 underwent reverse transcriptase-quantitative polymerase chain reaction analysis for Kaposi's sarcoma-associated herpesvirus micro-RNAs (miR-K12_10b and miRK-12-12) and Epstein-Barr virus-associated micro-RNA (miR-BHRF-1), as well as Luminex multiplex array analysis for established mediators of inflammation. Ninety-eight percent of polytrauma patients were found to have detectable Kaposi's sarcoma-associated herpesvirus and Epstein-Barr virus micro-RNAs at T0, whereas healthy controls demonstrated 0% and 100% detection rate for Kaposi's sarcoma-associated herpesvirus and Epstein-Barr virus, respectively. Univariate analysis revealed associations between viral micro-RNAs and polytrauma patients' age, race, and postinjury complications. Multivariate least absolute shrinkage and selection operator analysis of clinical variables and systemic biomarkers at T0 revealed that interleukin-10 was the strongest predictor of all viral micro-RNAs. Multivariate least absolute shrinkage and selection operator analysis of systemic biomarkers as predictors of complicated recovery at T0 demonstrated that miR-BHRF-1, miR-K12-12, monocyte chemoattractant protein-1, and hepatocyte growth factor were independent predictors of complicated recovery with a model complicated recovery prediction area under the curve of 0.81. CONCLUSIONS: Viral micro-RNAs were detected within hours of injury and correlated with poor outcomes in polytrauma patients. Our findings suggest that transcription of viral micro-RNAs occurs early in the response to trauma and may be associated with the biological processes involved in polytrauma-induced complicated recovery.

Effects of Time of Day on Race Splits, Kinematics, and Blood Lactate During a 50-m Front Crawl Performance.

ABSTRACT: Lisbôa, FD, Raimundo, JAG, Pereira, GS, Ribeiro, G, de Aguiar, RA, and Caputo, F. Effects of time of day on race splits, kinematics, and blood lactate during a 50-m front crawl performance. J Strength Cond Res 35(3): 819-825, 2021-This study aimed to investigate the performance, race splits, metabolic, and stroke parameters during 2 successive 50-m front crawl under conditions simulating a competition. Eleven competitive male swimmers (20 ± 3 years, 182 ± 5 cm, and 77 ± 5 kg) performed 2 successive 50-m front crawl trials in a 50-m swimming pool at 10 am and 5 pm. Block time (tB), 15-m performance (t.15-m), and 50-m performance (t.50-m) were measured. Velocity (V), stroke rate (SR), stroke length (SL), and stroke index (SI) were measured at 3 time points during the trials. Pre-trial and post-trial blood samples were taken to determine blood lactate accumulation (Δ[Lac]). For t.50-m, the relative difference between 10 am and 5 pm reached 0.1% (p = 0.7; effect size [ES] = 0.02). Furthermore, no differences in tB (p = 0.12; ES = -0.28) and t.15-m (p = 0.39; ES = -0.16) were observed between periods. Both V (p = 0.11; ES = -0.14) and SI (p = 0.16; ES = 0.15) were also similar. Higher values of SR were recorded at 10 am (p = 0.03; ES = -0.32), whereas the morning values of SL were lower (p = 0.04; ES = 0.3). Δ[Lac] was not significantly different between periods (p = 0.07; ES = -0.27). Although time of the day did not impact performance in 2 successive 50-m front crawl performances, different stroke parameters profiles were observed during these trials. This may help coaches design specific warm-up exercises to enhance performance at different times of the day.

The effects of predictive trials on critical stroke rate and critical swimming speed.

BACKGROUND: Critical swimming speed (CSS) and critical stroke rate (CSR) have important practical applications in evaluating endurance capacity and stroke parameters. The CSS and CSR are determined from the linear regression between two or more performance times with the respective predictive distance or "number of stroke cycles," respectively. It is already known that CSS is dependent on the number and duration of the predictive trials chosen, and performance times ranging from 2 to 12 min have been recommended. However, the effects of predictive trials on the CSR have not been reported. It was hypothesized that CSS and CSR determined by different predictive trials lasting 2 to 12 min would elicit similar values. Therefore, the purpose of the present study was to determine the impact of different combinations of predictive trials lasting 2 to 12 min on both CSR and CSS. METHODS: Thirteen swimmers performed three fixed-distance (200, 400, and 800 m) performances. All possible combinations of CSR and CSS with two (CSR200-400/CSS200-400, CSR200-800/CSS200-800, CSR400-800/CSS400-800) and three (CSR200-400-800/CSS200-400-800) trials were determined. RESULTS: No significant differences were found between CSR and CSS determined with different predictive distance tests. In addition, CSR200-800 and CSS200-800 showed the lowest coefficient of variation and highest intraclass correlation coefficients with CSR200-400-800 and CSS200-400-800, respectively. CONCLUSIONS: This study demonstrated that CSR and CSS were not statistically different when determined with different predictive trials located within the recommended durations of 2-12 min. Nevertheless, CSR200-800 and CSS200-800 exhibited the best consistency with CSR200-400-800 and CSS200-400-800, respectively.

Clinical risk factors and inflammatory biomarkers of post-traumatic acute kidney injury in combat patients.

BACKGROUND: Post-traumatic acute kidney injury has occurred in every major military conflict since its initial description during World War II. To ensure the proper treatment of combat casualties, early detection is critical. This study therefore aimed to investigate combat-related post-traumatic acute kidney injury in recent military conflicts, used machine learning algorithms to identify clinical and biomarker variables associated with the development of post-traumatic acute kidney injury, and evaluated the effects of post-traumatic acute kidney injury on wound healing and nosocomial infection. METHODS: We conducted a retrospective clinical cohort review of 73 critically injured US military service members who sustained major combat-related extremity wounds and had collected injury characteristics, assayed serum and tissue biopsy samples for the expression of protein and messenger ribonucleic acid biomarkers. Bivariate analyses and random forest recursive feature elimination classification algorithms were used to identify associated injury characteristics and biomarker variables. RESULTS: The incidence of post-traumatic acute kidney injury was 20.5%. Of that, 86% recovered baseline renal function and only 2 (15%) of the acute kidney injury group required renal replacement therapy. Random forest recursive feature elimination algorithms were able to estimate post-traumatic acute kidney injury with the area under the curve of 0.93, sensitivity of 0.91, and specificity of 0.91. Post-traumatic acute kidney injury was associated with injury severity score, serum epidermal growth factor, and tissue activin A type receptor 1, matrix metallopeptidase 10, and X-C motif chemokine ligand 1 expression. Patients with post-traumatic acute kidney injury exhibited poor wound healing and increased incidence of nosocomial infections. CONCLUSION: The occurrence of acute kidney injury in combat casualties may be estimated using injury characteristics and serum and tissue biomarkers. External validations of these models are necessary to generalize for all trauma patients.

Correction to: Advanced Modeling to Predict Pneumonia in Combat Trauma Patients.

In the original article, the units indicated on the y-axes of Fig. 3 are incorrectly labelled. The correct label is pg/mL. Following is the corrected Fig. 3.

Advanced Modeling to Predict Pneumonia in Combat Trauma Patients.

BACKGROUND: Tools to assist clinicians in predicting pneumonia could lead to a significant decline in morbidity. Therefore, we sought to develop a model in combat trauma patients for identifying those at highest risk of pneumonia. METHODS: This was a retrospective study of 73 primarily blast-injured casualties with combat extremity wounds. Binary classification models for pneumonia prediction were developed with measurements of injury severity from the Abbreviated Injury Scale (AIS), transfusion blood products received before arrival at Walter Reed National Military Medical Center (WRNMMC), and serum protein levels. Predictive models were generated with leave-one-out-cross-validation using the variable selection method of backward elimination (BE) and the machine learning algorithms of random forests (RF) and logistic regression (LR). BE was attempted with two predictor sets: (1) all variables and (2) serum proteins alone. RESULTS: Incidence of pneumonia was 12% (n = 9). Different variable sets were produced by BE when considering all variables and just serum proteins alone. BE selected the variables ISS, AIS chest, and cryoprecipitate within the first 24 h following injury for the first predictor set 1 and FGF-basic, IL-2R, and IL-6 for predictor set 2. Using both variable sets, a RF was generated with AUCs of 0.95 and 0.87-both higher than LR algorithms. CONCLUSION: Advanced modeling allowed for the identification of clinical and biomarker data predictive of pneumonia in a cohort of predominantly blast-injured combat trauma patients. The generalizability of the models developed here will require an external validation dataset.

Utilizing Precision Medicine to Estimate Timing for Surgical Closure of Traumatic Extremity Wounds.

BACKGROUND: Both the frequency and high complication rates associated with extremity wounds in recent military conflicts have highlighted the need for clinical decision support tools (CDST) to decrease time to wound closure and wound failure rates. METHODS: Machine learning was used to estimate both successful wound closure (based on penultimate debridement biomarker data) and the necessary number of surgical debridements (based on presentation biomarkers) in 73 service members treated according to military guidelines based on clinical data and the local/systemic level of 32 cytokines. Models were trained to estimate successful closure including an additional 8 of 80 civilian patients with similar injury patterns. Previous analysis has demonstrated the potential to reduce the number of operative debridements by 2, with resulting decreases in ICU and hospital LOS, while decreasing the rate of wound failure. RESULTS: Analysis showed similar cytokine responses when civilians followed a military-like treatment schedule with surgical debridements every 24 to 72 hours. A model estimating successful closure had AUC of 0.89. Model performance in civilians degraded when these had a debridement interval > 72 hours (73 of the 80 civilians). A separate model estimating the number of debridements required to achieve successful closure had a multiclass AUC of 0.81. CONCLUSION: CDSTs can be developed using biologically compatible civilian and military populations as cytokine response is highly influenced by surgical treatment. Our CDSTs may help identify who may require serial debridements versus early closure, and precisely when traumatic wounds should optimally be closed.