Trends and correlates in HIV viral load monitoring and viral suppression among adolescents and young adults in Dar es Salaam, Tanzania.

BACKGROUND: Adolescents and young adults (AYA) living with HIV have been shown to have lower rates of viral load testing and viral suppression as compared to older adults. We examined trends over time and predictors of HIV viral load monitoring and viral suppression among AYA in a large HIV treatment programme in Dar es Salaam, Tanzania. METHODS: We analysed longitudinal data of AYA aged 10-24 years initiated on antiretroviral therapy between January 2017 and October 2022. Trend models were used to assess changes in HIV viral load testing and viral suppression by calendar year. Generalised estimating equations were used to examine the relationship of sociodemographic and clinical factors with HIV viral load testing and viral suppression. RESULTS: Out of 15,759 AYA, the percentage of those who received a 6-month HIV viral load testing increased from 40.6% in 2017 to 64.7% in 2022 and, a notable annual increase of 5.6% (p < 0.001). A higher HIV viral load testing uptake was observed among 20- to 24-year-olds (87.7%) compared to 10- to 19-year-olds (80.2%) (p < 0.001). The likelihood of not receiving an HIV viral load test within 12 months of antiretroviral therapy initiation was higher among 10- to 19-year-olds (adjusted odds ratio [aOR] = 1.7; 95% confidence interval [CI] = 1.4-2.0), advanced HIV disease (aOR = 1.3; 95% CI = 1.12-1.53), normal nutrition status at enrolment aOR 2.6 (95% CI = 1.59-4.26) and initiation of non-nucleoside reverse transcriptase inhibitors regimen aOR 1.2 (95% CI = 1.08-1.34). The proportion of AYA with viral suppression increased from 83.0% in 2017 to 94.6% in 2022. Notably, the overall trend in viral suppression increased significantly at 2.4% annually. The risk of not achieving viral suppression was greater among 10- to 14-year-olds (aOR = 2; 95% CI = 1.75-2.43) and 15- to 19-year-olds (aOR = 1.4; 95% CI = 1.24-1.58) as compared to 20-24 years; being male (aOR = 1.16; 95% CI = 1.02-1.32); undernourished (aOR = 1.53; 95% CI = 1.17-1.99); in WHO Stage II (aOR = 1.16; 95% CI = 1.02-1.33) and III (aOR = 1.21; 95% CI = 1.03-1.42) and being on an non-nucleoside reverse transcriptase inhibitors regimen (aOR = 1.32; 95% CI = 1.18-1.48). CONCLUSION: HIV viral load testing uptake at 6 months of antiretroviral therapy initiation and viral suppression increased from 2017 to 2022; however, overall HIV viral load testing was suboptimal. Demographic and clinical characteristics can be used to identify AYA at greater risk for not having HIV viral load test and not achieving viral suppression.

Challenges and Opportunities with at-Home Blood Collection for HIV-1 Viral Load Monitoring among Sexual Minoritized Men who use Stimulants.

Sexually minoritized men (SMM) with HIV who use stimulants experience difficulties achieving and maintaining an undetectable viral load (VL). Home-based VL monitoring could augment HIV care by supporting interim, early identification of detectable VL. We describe implementation challenges associated with a home-collection device for laboratory-based VL testing among SMM with HIV who use stimulants. From March-May 2022, cisgender SMM with HIV reporting moderate-to-severe stimulant use disorder and suboptimal (< 90%) past-month antiretroviral therapy (ART) adherence were recruited via a consent-to-contact participant registry. Eligible men completed teleconference-based informed consent and were mailed a HemaSpot-HD blood collection device (volume capacity 160 µL; lower limit of detection 839 copies/mL) with detailed instructions for home blood self-collection and return shipment. Implementation process measures included estimated blood volume and VL quantification. Among 24 participants, 21 (88%) returned specimens with a median duration of 23 days (range: 10-71 days) between sending devices to participants and receiving specimens. Of these, 13/21 (62%) included enough blood (≥ 40 µL) for confidence in detectable/undetectable results; 10/13 (77%) had detectable VL, with 4/10 (40%) were quantifiable at ≥ 839 copies/mL. The remaining 8/21 had low blood volume (< 40 µL), but 3/8 (38%) still had detectable VL, with 1/3 (33%) quantifiable at ≥ 839 copies/mL. Home blood collection of ≥ 40 µL using HemaSpot-HD was feasible among this high-priority population, with > 50% having a VL detected. However, interim VL monitoring using HemaSpot-HD among those experiencing difficulties with ART adherence may be strengthened by building rapport via teleconferencing and providing detailed instructions to achieve adequate sample volume.

Semi-supervised learning with flexible threshold for non-intrusive load monitoring.

Non-intrusive load monitoring (NILM) can obtain fine-grained power consumption information for individual appliances within the user without installing additional hardware sensors. With the rapid development of the deep learning model, many methods have been utilized to address NILM problems and have achieved enhanced appliance identification performance. However, supervised learning models require a substantial volume of annotated data to function effectively, which is time-consuming, laborious, and difficult to implement in real scenarios. In this paper, we propose a novel semi-supervised learning method that combines consistency regularization and pseudo-labels to help identification of appliances with limited labeled data and an abundance of unlabeled data. In addition, given the different learning difficulties of various appliance categories, for example, feature learning is more difficult for multi-state appliances than two-state appliances, the thresholds employed for different appliances are adjusted in a flexible way at each time step so that the informative unlabeled data and their pseudo-labels can be delivered. Experiments have been conducted on publicly available datasets, and the results indicate that the proposed method attains superior appliance identification performance compared to cutting-edge methods.

Bridging the Gap Between Training and Competition in Elite Rink Hockey: A Pilot Study.

BACKGROUND: Monitoring training load and competition load is crucial for evaluating and improving athlete performance. This study proposes an applied approach to characterize and classify the training task specificity in relation to competition in a top-level rink hockey team, considering external and internal load from training tasks and competition. HYPOTHESIS: Training tasks and game demands have significant dose-response differences, and exercises can be classified successfully based on their physiological and biomechanical demands. STUDY DESIGN: Cross-sectional study. LEVEL OF EVIDENCE: Level 5. METHODS: Ten elite-level male rink hockey players participated in this study. Players were monitored on 6 different task categories during 8 training sessions and 2 official games. A linear mixed model with random intercepts was used to compare training tasks and competition load, accounting for individual repeated measures. A 2-step cluster analysis was performed to classify the training tasks and games based on physiological and biomechanical load, employing log-likelihood as the distance measure and Schwartz's Bayesian criterion. RESULTS: Average heartrate , maximum heartrate, and high-speed skating (18.1-30 km/h) were the best physiological load predictors, while the most effective biomechanical load predictors were impacts [8-10] g(n), decelerations [-10 to -3]m/s²(n), and accelerations [3-10]m/s²(n). Different physiological and biomechanical responses were verified between training tasks and match demands. A 4-quadrant efforts assessment for each task category revealed that training tasks used by the team in the analysis presented lower biomechanical and physiological load demands than competition. CONCLUSION: Training tasks failed to adequately replicate the specific demands of competition, especially regarding high mechanical stress, such as the absence of high-intensity impacts and decelerations. CLINICAL RELEVANCE: This method of classification of training tasks may allow coaches to understand further the specificity and contribution of each task to competition demands, consequently improving the capacity of load management and the preparedness and readiness of players for competition.

External Load Evaluation in Elite Futsal: Influence of Match Results and Game Location with IMU Technology.

The purpose of this study was to assess the external load demands in futsal, considering both home and away matches and their outcomes, in order to plan microcycles throughout the season based on the external load of each match. The external load of 10 players from a First Division team in the Spanish Futsal League was recorded throughout 15 official matches in the first half of the league championship. The players' external load was monitored using OLIVER devices. To analyse the influence of the match outcome and location on the external load, a univariate general linear model (GLM) analysis was conducted with Bonferroni post hoc. There are no differences between the variables neither comparing results nor location factors, except for accelerations of 2 to 3 m/s2 (m) per minute and the number of accelerations of 2 to 3 m/s2 per minute, reporting higher value winnings at home than away (p < 0.05). The location and results are not factors that influence on external load in futsal matches, except the number and distance performed in accelerations and distance covered at a low to medium speed. These findings are important for planning microcycles and providing the appropriate dosage to each player to achieve optimal performance in matches.

Frequency and intensity of maximal and submaximal demanding scenarios in U19 professional soccer players.

This study examined the frequency of the most demanding scenarios (MDS) during official soccer matches using rolling averages over 1, 5, and 10 min. Forty-two Under-19 players from different positions (central defenders, full-backs, central midfielders, wide midfielders, offensive midfielders, and forwards) were monitored across 27 matches using GPS to track distance covered, high-speed running, sprint distance, accelerations, and decelerations. Intensity thresholds were established based on percentiles (0-25, 25-50, 50-75, 75-100, and ≥100). The main findings suggest that: (i) Peak Demands occur in less than 1% of all time windows and variables for all positions; (ii) Most efforts occur below peak demands, with around 95% for high-speed running and sprint distance, and 85% for accelerations, decelerations, and total distance; (iii) Significant differences in intensity distributions were found between positions, particularly at medium-low and high intensities. Regarding training prescription, relying solely on MDS may be limited, highlighting the need to supplement MDS with other metrics for a comprehensive understanding of match demands. This approach ensures better-informed training programs for soccer players.

The occurrence of peak demand events during soccer matches is infrequent. Therefore, understanding the frequency of efforts below the intensity threshold of the most demanding passages for each playing position and across various analysed variables and periods is of utmost importance.MDS might not be enough for effective soccer training planning. Complementing with additional metrics like GPS, tactical analysis, physiological data and psychological factors is essential for a comprehensive understanding of the game's demands and tailored training programmes.

A Critical Comparison of Shape Sensing Algorithms: The Calibration Matrix Method versus iFEM.

Two shape-sensing algorithms, the calibration matrix (CM) method and the inverse Finite Element Method (iFEM), were compared on their ability to accurately reconstruct displacements, strains, and loads and on their computational efficiency. CM reconstructs deformation through a linear combination of known load cases using the sensor data measured for each of these known load cases and the sensor data measured for the actual load case. iFEM reconstructs deformation by minimizing a least-squares error functional based on the difference between the measured and numerical values for displacement and/or strain. In this study, CM is covered in detail to determine the applicability and practicality of the method. The CM results for several benchmark problems from the literature were compared to the iFEM results. In addition, a representative aerospace structure consisting of a twisted and tapered blade with a NACA 6412 cross-sectional profile was evaluated using quadratic hexahedral solid elements with reduced integration. Both methods assumed linear elastic material conditions and used discrete displacement sensors, strain sensors, or a combination of both to reconstruct the full displacement and strain fields. In our study, surface-mounted and distributed sensors throughout the volume of the structure were considered. This comparative study was performed to support the growing demand for load monitoring, specifically for applications where the sensor data is obtained from discrete and irregularly distributed points on the structure. In this study, the CM method was shown to achieve greater accuracy than iFEM. Averaged over all the load cases examined, the CM algorithm achieved average displacement and strain errors of less than 0.01%, whereas the iFEM algorithm had an average displacement error of 21% and an average strain error of 99%. In addition, CM also achieved equal or better computational efficiency than iFEM after initial set-up, with similar first solution times and faster repeat solution times by a factor of approximately 100, for hundreds to thousands of sensors.

Predicting daily recovery during long-term endurance training using machine learning analysis.

PURPOSE: The aim of this study was to determine if machine learning models could predict the perceived morning recovery status (AM PRS) and daily change in heart rate variability (HRV change) of endurance athletes based on training, dietary intake, sleep, HRV, and subjective well-being measures. METHODS: Self-selected nutrition intake, exercise training, sleep habits, HRV, and subjective well-being of 43 endurance athletes ranging from professional to recreationally trained were monitored daily for 12 weeks (3572 days of tracking). Global and individualized models were constructed using machine learning techniques, with the single best algorithm chosen for each model. The model performance was compared with a baseline intercept-only model. RESULTS: Prediction error (root mean square error [RMSE]) was lower than baseline for the group models (11.8 vs. 14.1 and 0.22 vs. 0.29 for AM PRS and HRV change, respectively). At the individual level, prediction accuracy outperformed the baseline model but varied greatly across participants (RMSE range 5.5-23.6 and 0.05-0.44 for AM PRS and HRV change, respectively). CONCLUSION: At the group level, daily recovery measures can be predicted based on commonly measured variables, with a small subset of variables providing most of the predictive power. However, at the individual level, the key variables may vary, and additional data may be needed to improve the prediction accuracy.

Loading or Unloading? This Is the Question! A Multi-Season Study in Professional Football Players.

This study examined the impact of training load periodization on neuromuscular readiness in elite football players using the Locomotor Efficiency Index (LEI) as a measure of performance optimization. Throughout the 2021/22 and 2022/23 seasons, 106 elite male players (age: 19.5 ± 3.9 years) from an Italian professional football club were monitored using Global Positioning Systems (GPS) external load data. The LEI was derived from a machine learning model, specifically random forest regression, which compared predicted and actual PlayerLoad™ values to evaluate neuromuscular efficiency. Players were categorized by weekly LEI into three readiness states: bad, normal, and good. Analysis focused on the variation in weekly LEI relative to weekly load percentage variation (large decrease, moderate decrease, no variation, moderate increase, large increase), which included total distance, high-speed distance (above 25.2 km/h), and mechanical load, defined as the sum of accelerations and decelerations. Statistical analysis showed significant differences only with variations in total distance and mechanical load. Specifically, reducing weekly loads improved LEI in players in lower readiness states, while maintaining or slightly increasing loads promoted optimal readiness. This approach enables coaches to tailor training prescriptions more effectively, optimizing workload and recovery to sustain player performance throughout a demanding season.

Changing how the third 95 is counted: suitable indicators for measuring U = U with findings from Taiwan.

INTRODUCTION: The World Health Organisation has implemented multiple HIV prevention policies and strived to achieve the 90-90-90 goal by 2020, achieving the 95-95-95 goal by 2030, which refers to 95% of patients living with HIV knowing their HIV status, 95% of patients living with HIV receiving continual care and medication, and 95% of patients living with HIV exhibiting viral suppression. However, how to measure the status of viral suppression varies, and it is hard to indicate the quality of HIV care. The study aimed to examine the long-term viral load suppression in these cases and explore potential factors affecting the control of long-term viral load. METHODS: This study analyzed viral load testing data from HIV patients who are still alive during the period from notification up to 2019-2020. Three indicators were calculated, including durable viral suppression, Viremia copy-years, and Viral load > 1,500 copies/ml, to assess the differences between them. RESULTS: Among the 27,706 cases included in the study, the proportion of persistent viral load suppression was 87%, with 4% having viral loads exceeding 1,500 copies/ml. The average duration from notification to viral load suppression was 154 days, and the geometric mean of annual viral replication was 90 copies*years/ml. Regarding the last available viral load measurement, 96% of cases had an undetectable viral load. However, we observed that 9.3% of cases, while having an undetectable viral load for their last measurement, did not show consistent long-term viral load suppression. An analysis of factors associated with non-persistent viral load suppression revealed higher risk in younger age groups, individuals with an educational level of high school or below, injection drug users, cases from the eastern region, those seeking care at regional hospitals, cases with drug resistance data, individuals with lower healthcare continuity, and those with an initial CD4 count below 350 during the study period. CONCLUSIONS: The recommendation is to combine it with the indicator of sustained viral load suppression for a more accurate assessment of the risk of HIV transmission within the infected community.

The Autoregulation Rest-Redistribution Training Method Mitigates Sex Differences in Neuromuscular and Perceived Fatigue During Resistance Training.

PURPOSE: To examine the sex differences in performance and perceived fatigue during resistance training prescribed using traditional (TRA) and autoregulation rest-redistribution training (ARRT) approaches. METHODS: Twelve resistance-trained men and 12 women completed 2 sessions including the bench-press exercise matched for load (75% of 1-repetition maximum), volume (24 repetitions), and total rest (240 s). Sessions were performed in a counterbalanced randomized design with TRA consisting of 3 sets of 8 repetitions with 120-second interset rest and ARRT employing a personalized combination of clusters, repetitions per cluster, and between-clusters rest regulated with a 20% velocity-loss threshold. The effects of TRA and ARRT on velocity loss, unilateral isometric peak force, and rating of fatigue (ROF) were compared between sexes. RESULTS: The velocity loss was generally lower during ARRT compared with TRA (-0.47% [0.11%]), with velocity loss being mitigated by ARRT to a greater extent among males compared with females (-0.37% [0.15%]). A smaller unilateral isometric peak force decline was observed after ARRT than TRA among males compared with females (-38.4 [8.4] N). Lower ROF after ARRT than TRA was found among males compared to females (-1.97 [0.55] AU). Additionally, males reported greater ROF than females across both conditions (1.92 [0.53] AU), and ARRT resulted in lower ROF than TRA overall (-0.83 [0.39] AU). CONCLUSIONS: The ARRT approach resulted in decreased velocity loss, peak force impairment, and ROF compared with TRA in both sexes. However, male subjects exhibited more pronounced acute within-session benefits from the ARRT method.

Unknown appliances detection for non-intrusive load monitoring based on vision transformer with an additional detection head.

Non-intrusive load monitoring (NILM) offers precise insights into equipment-level energy consumption by analyzing current and voltage data from residential smart meters, thus emerging as a potential strategy for demand-side management in power systems. However, a prevalent limitation in current NILM techniques is the presupposition of a known inventory of household appliances, an assumption that often becomes impractical due to the regular introduction of new appliances by consumers. To address this challenge, our approach integrates a vision transformer network with an additional detection head (ViTD), utilizing V-I trajectory images. Initially, the ViT model is trained to classify known appliances. Subsequently, an additional detection head is incorporated to manipulate the embedded features, encouraging the formation of distinct, compact class centers for the known appliance categories. During testing, samples are identified as either known or unknown appliances based on their proximity to these class centers. We utilize two public datasets, PLAID and WHITED, to demonstrate the effectiveness and superiority of our proposed method.

Learning-Based Non-Intrusive Electric Load Monitoring for Smart Energy Management.

State-of-the-art smart cities have been calling for economic but efficient energy management over a large-scale network, especially for the electric power system. It is a critical issue to monitor, analyze, and control electric loads of all users in the system. In this study, a non-intrusive load monitoring method was designed for smart power management using computer vision techniques popular in artificial intelligence. First of all, one-dimensional current signals are mapped onto two-dimensional color feature images using signal transforms (including the wavelet transform and discrete Fourier transform) and Gramian Angular Field (GAF) methods. Second, a deep neural network with multi-scale feature extraction and attention mechanism is proposed to recognize all electrical loads from the color feature images. Third, a cloud-based approach was designed for the non-intrusive monitoring of all users, thereby saving energy costs during power system control. Experimental results on both public and private datasets demonstrate that the method achieves superior performances compared to its peers, and thus supports efficient energy management over a large-scale Internet of Things network.

Analytical and Clinical Performance of the NeuMoDx™ Platform for Cytomegalovirus and Epstein-Barr Virus Viral Load Testing.

DNA assays for viral load (VL) monitoring are key tools in the management of immunocompromised patients with cytomegalovirus (CMV) or Epstein-Barr virus (EBV) infection. In this study, the analytical and clinical performances of the NeuMoDx™ CMV and EBV Quant Assays were compared with artus CMV and EBV QS-RGQ Kits in a primary hospital testing laboratory. Patient plasma samples previously tested using artus kits were randomly selected for testing by NeuMoDx assays. The NeuMoDx CMV Quant Assay and artus CMV QS-RGQ Kit limits of detection (LoDs) are 20.0 IU/mL and 69.7 IU/mL, respectively; 33/75 (44.0%) samples had CMV DNA levels above the LoD of both assays. The Pearson correlation coefficient was 0.9503; 20 samples (60.6%) had lower NeuMoDx CMV quantification values versus the artus kit. The LoD of the NeuMoDx EBV Quant Assay and artus EBV QS-RGQ Kit are 200 IU/mL and 22.29 IU/mL, respectively; 16/75 (21.3%) samples had EBV DNA levels above the LoD of both assays. The Pearson correlation coefficient was 0.8990. EBV quantification values with the NeuMoDx assay were higher versus the artus kit in 15 samples (93.8%). In conclusion, NeuMoDx CMV and EBV Quant Assays are sensitive and accurate tools for CMV and EBV DNA VL quantification.

Impact of Maternal Viral Suppression on Growth Patterns for HIV-Exposed Uninfected Infants in Kenya.

Background and Objective: Children born to mothers living with human immunodeficiency virus (HIV) are at risk for poor health outcomes but data characterizing these associations are limited. Our objective was to determine the impact of maternal viral suppression on growth patterns and malnutrition for infants who are HIV-exposed but uninfected (HEU). Methods: We conducted a retrospective cohort analysis of clinical data for infants who were HEU and their mothers (September 2015 - March 2019) in Kenya. Infants were stratified based on maternal viral suppression status (≥ or <1000 copies/mL); t-tests were used to compare groups. Growth indicators were evaluated with Chi-square, Fisher's exact, and area under the curve. Moderate-to-severe underweight status, stunting, and wasting were defined by weight-for-age (WFA), height-for-age (HFA), and weight-for-height (WFH), z-scores ≤2, and were used to define malnutrition. Multivariate logistic regression analyses were performed to evaluate potential associations with malnutrition indicators between WFH and HFA. Results: Among 674 infants who were HEU, 48.7% were male and 85.0% had mothers who were virally suppressed. The median age at first and last clinic visits was 1.5 and 16.4 months, respectively. WFA and HFA z-scores over time differed by sex, and WFA and HFA differed based on maternal viral suppression (P < 0.05). Male infants had higher adjusted odds for stunted status, and as children aged, they had slightly increased odds of becoming underweight or stunted. Maternal viral suppression and timing of maternal antiretroviral therapy initiation in relation to the prevention of vertical transmission (PVT) enrollment did not significantly affect malnutrition indicators. Conclusion and Global Health Implications: Maternal viral suppression status was not associated with increased odds of more severe malnutrition indicators in children who were HEU. However, overall growth patterns over time, measured by z-scores of growth indicators, did differ based on maternal viral suppression status, and to a lesser degree, by gender.

Non-Intrusive Load Identification Based on Retrainable Siamese Network.

Non-intrusive load monitoring (NILM) can identify each electrical load and its operating state in a household by using the voltage and current data measured at a single point on the bus, thereby behaving as a key technology for smart grid construction and effective energy consumption. The existing NILM methods mainly focus on the identification of pre-trained loads, which can achieve high identification accuracy and satisfying outcomes. However, unknown load identification is rarely involved among those methods and the scalability of NILM is still a crucial problem at the current stage. In light of this, we have proposed a non-intrusive load identification method based on a Siamese network, which can be retrained after the detection of an unknown load to increase the identification accuracy for unknown loads. The proposed Siamese network comprises a fixed convolutional neural network (CNN) and two retrainable back propagation (BP) networks. When an unknown load is detected, the low-dimensional features of its voltage-current (V-I) trajectory are extracted by using the fixed CNN model, and the BP networks are retrained online. The finetuning of BP network parameters through retraining can improve the representation ability of the network model; thus, a high accuracy of unknown load identification can be achieved by updating the Siamese network in real time. The public WHITED and PLAID datasets are used for the validation of the proposed method. Finally, the practicality and scalability of the method are demonstrated using a real-house environment test to prove the ability of online retraining on an embedded Linux system with STM32MP1 as the core.

Early HIV viral suppression associated with subsequent 12-month treatment success among people living with HIV in South Africa.

BACKGROUND: We analyzed the STREAM (Simplifying HIV TREAtment and Monitoring) study to determine risk factors associated with HIV viraemia and poor retention 18 months after initiation of antiretroviral therapy (ART). METHODS: The STREAM study was an open-label randomized controlled trial in Durban, South Africa, that enrolled 390 people living with HIV presenting for their first HIV viral load measurement ~6 months after ART initiation. We used modified Poisson regression with robust standard errors to describe associations between baseline characteristics and three HIV outcomes 18 months after ART initiation: HIV viraemia (>50 copies/mL), poor retention in HIV care, and a composite outcome of poor retention in care and/or HIV viraemia. RESULTS: Approximately 18 months after ART initiation, 45 (11.5%) participants were no longer retained in care and 43 (11.8%) had viraemia. People with CD4 counts <200 and those with viraemia 6 months after ART initiation were significantly more likely to have viraemia 18 months after ART initiation (adjusted relative risk [aRR] 4.0; 95% confidence interval [CI] 2.1-7.5 and aRR 5.5; 95% CI 3.3-9.0, respectively). People who did not disclose their HIV status and had viraemia after ART initiation were more likely to not be retained in care 12 months later (aRR 2.6; 95% CI 1.1-6.1 and aRR 2.2; 95% CI 1.0-4.8). People with a CD4 count <200 and those with viraemia were more likely to not achieve the composite outcome 18 months after ART initiation. CONCLUSIONS: Viraemia after ART initiation was the strongest predictor of subsequent viraemia and poor care retention. Understanding early indicators can help target our interventions to better engage people who may be more likely to experience persistent viraemia or disengage from HIV care.

Testing variations between starters and substitute players in terms of total distance, high-speed running, and sprinting distance: a descriptive study on professional male soccer players.

The purpose of this study was three-fold: (i) to compare total distance, high-speed running (HSR) distance, and sprint distance covered per 5-minute epoch by players acting as both starters and substitutes; (ii) to compare the locomotor demands between the moments the players entered the match (45-60, 60-75 and 75-90 minutes); and (iii) to compare the locomotor demands of the players between the variations of the within- and between-playing positions. Twenty-one male professional soccer players competing in the Professional Premier League of one of the European countries were observed over sixteen official matches. The players were monitored during all matches using a Global Navigation Satellite System. The measures collected were total distance (TD; m), distance in HSR, sprint distance, HSR, and sprint counts. Considering the comparisons between the splits over the second half of match play, a significant difference between the starters and the substitutes was observed only for sprint distance in the 90-95 minute split (Z = -2.023; p = 0.043). Moreover, no substantial differences were found between the moment the substitute player entered the match regarding total distance (H = 2.650; p = 0.266), HSR distance (H = 1.738; p = 0.419), and sprint distance (H = 0.048; p = 0.976). However, the comparison of between-playing positions revealed considerable differences in total distance (H = 29.246; p < 0.001), and HSR distance (H = 12.153; p = 0.002) covered by the players acting as starters. In contrast, for substitute players, such differences were reported in HSR distance (H = 27.892; p < 0.001) and sprint distance (H = 15.879; p < 0.001). In conclusion, this study suggests that acting as a starter or a substitute does not significantly affect the intensity of effort except during the last periods of match play. However, the contextual factor of performing in a specific playing position plays a significant role both for starters and substitutes.

Assessment of the performance of the plasma separation card for HIV-1 viral load monitoring in South Africa.

Scaling up of newer innovations that address the limitations of the dried blood spot and the logistics of plasma monitoring is needed. We employed a multi-site, cross-sectional assessment of the plasma separation card (PSC) on blood specimens collected from all consenting adults, assenting young and pediatric patients living with HIV from 10 primary healthcare clinics in South Africa. Venous blood for EDTA-plasma samples was collected and analyzed according to the standard of care assay, while collected capillary blood for the PSC samples was analyzed using the Roche COBAS AmpliPrep/Cobas TaqMan (CAP/CTM) HIV-1 Test at the National Reference laboratories. McNemar tests assessed the differences in concordance between the centrifuged plasma and dried plasma spots. The usability of PSC by blood spotting, PSC preparation, and pre-analytical work was assessed by collecting seven-point Likert-scale data from healthcare and laboratory workers. We enrolled 538 patients, mostly adults [n = 515, 95.7% (95% CI: 93.7%-97.1%)] and females [n = 322, 64.2% (95% CI: 60.0%-68.1%)]. Overall, 536 paired samples were collected using both PSC- and EDTA-plasma diagnostics, and 502 paired PSC- and EDTA-plasma samples assessed. Concordance between the paired samples was obtained for 446 samples. Analysis of these 446 paired samples at 1,000 copies per milliliter threshold yielded an overall sensitivity of 87.5% [95% CI: 73.2%-95.8%] and specificity of 99.3% [95% CI: 97.9%-99.8%]. Laboratory staff reported technical difficulties in most tasks. The usability of the PSC by healthcare workers was favorable. For policymakers to consider PSC scale-up for viral load monitoring, technical challenges around using PSC at the clinic and laboratory level need to be addressed. IMPORTANCE: Findings from this manuscript emphasize the reliability of the plasma separation card (PSC), a novel diagnostic method that can be implemented in healthcare facilities in resource-constrained settings. The agreement of the PSC with the standard of care EDTA plasma for viral load monitoring is high. Since the findings showed that these tests were highly specific, we recommend a scale-up of PSC in South Africa for diagnosis of treatment failure.