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Provisions for post-trial care {30} | Participants who achieve two successive negative liquid media cultures, the first of which is at or before week 08, with no positives to follow by the week 16 visit, will not receive further standard of care TB-treatment (continuation phase) according to national guidelines to complete 6 months of treatment. Their planned post-treatment follow-up visits at week 18, week 26, week 38 and week 52 will serve to determine whether they have achieved lasting cure. Participants who do not fulfil these criteria will receive standard of care TB-treatment according to national guidelines until week 26 at a government health facility. These participants will be invited to return for a follow-up visit at week 52 to determine their well-being and treatment outcome.Clinical trial insurance is obtained to compensate participants in case participating in this study causes any harm. | PMC10243693 | ||
Outcomes {12} | anaemia, TB, leukopenia, neuropathy, toxicities | ANAEMIA, LEUKOPENIA, NEUROPATHY, THROMBOCYTOPENIA, RECURRENT DISEASE, EVENT, SECONDARY | The primary safety outcome is the occurrence of oxazolidinone class toxicities defined as peripheral or optical neuropathy, incident leukopenia, anaemia or thrombocytopenia, or AEs in line with tyramine pressor response, all of grade 2 or higher, possibly, probably or definitely related to DZD. Participants will be evaluated for AEs on a regular basis during treatment and follow-up phase.The efficacy of DZD will be evaluated by measuring the change in mycobacterial load over time on treatment as quantified by time to positivity in BD BACTEC™ MGIT liquid culture described by non-linear mixed-effects methodology.A secondary endpoint is the proportion of participants who suffer relapse, defined as recurrent disease caused by a strain identical to the baseline isolate, within 12 months post randomization, out of participants completing 16 weeks of therapy and achieving sustained sputum culture conversion defined as two successive negative liquid media cultures at or before WK08, with no positives to follow by the week 16 visit. We will analyze this also by a time-to event analysis (time to recurrent TB, and to relapse). Pharmacokinetic endpoints are chosen to support the development of a population PK model for DZD. In addition, we will use non-compartmental analysis for DZD, BDQ, DLM and their main metabolites, and for MXF, to determine the area under the plasma concentration curve from 0 to 24 h on day 14, the observed maximum concentration, the time of maximum concentration and the minimum observed plasma concentration. Furthermore, the apparent oral clearance, apparent volume of distribution and terminal half-life will be determined for MOX only.Mycobacteriological Identification and Characterization Endpoint: • Isolates will be assessed for minimum inhibitory concentrations of BDQ, DLM, MXF, and DZD of the infecting strain, at baseline and on representative isolate(s) grown at or after WK08, if any.• In the case of recurrent disease, a comparison between bacterial strain causing recurrent disease, and the strain at baseline will be performed by whole genome sequencing, to discriminate relapse from re-infection. | PMC10243693 |
Participant timeline {13} | EVENTS, JENSEN | The timeline of the study (see Fig. Schedule of events. WK, week of treatment; MGIT, liquid media (BD mycobacterium growth indicator tube); LJ, Loewenstein - Jensen solid media; MBLA, molecular bacterial load assay; PK, pharmacokinetics; X, refers to all visits mentioned above; ZN, Ziehl-Neelsen stain; PG, pharmacogenomics
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Sample size {14} | Fifteen participants per arm with a total of 75 participants and a wide range of DZD doses (from 0mg to 800 mg BID) has been determined as an adequate sample size for population PK modelling, and for exposure-response modelling to detect a clinically meaningful dose-dependent relationship.Furthermore, the planned sample size of 15 participants per treatment group is in keeping with other trials of this type and accounts for the possibility of up to 3 drop-outs per group, which, based on previous studies of this type conducted at these sites, represents a conservative estimate of the expected drop-out rate.Previous Phase IIA (EBA) studies indicate that the between-participant standard deviation of logCFU can be approximately 0.2 [ | PMC10243693 | ||
Recruitment {15} | TB | RECRUITMENT, RECRUITMENT | Sites will place recruitment teams in government health clinics where TB diagnostics are offered. Participants who test positive will be informed about the trial and invited for screening.Recruitment can be improved by individual and community awareness of the study and/or TB in general, through public announcements through advertisements, posters and radio announcements and information leaflets distributed to healthcare providers for their participants with newly diagnosed TB. | PMC10243693 |
Assignment of interventions: allocation | PMC10243693 | |||
Sequence generation {16a} | The study will be a randomized, open-label trial. Randomization will be implemented after all screening results are available for participants who have given informed consent and who have been found eligible for participation.Participants will be allocated using the Internet-Based Randomization service system: RANDOMIZE.NET. Participant randomization will be stratified by a bacterial load in sputum as measured by GeneXpert, cycle threshold (≥ 16, < 16), site (five sites have been activated: The Aurum site, Clinical HIV Research Unit (CHRU), KCRI/KIDH, the Ifakara site and the NIMR-MMRC site), and HIV status (positive, negative). Each site will have its own account and the allocation result will be generated by the web system immediately based on a minimization randomization algorithm. The minimization algorithm allocates the participant to the treatment arm with the lowest allocation proportion and includes a probabilistic element so that the allocation is not deterministic. | PMC10243693 | ||
Concealment mechanism {16b} | The allocation sequence is generated by a web-based randomization system set up by the sponsor, with the investigator entering patient details. A minimization algorithm with a random element generates the treatment allocation; the random element prevents the investigator from knowing the allocation before the randomization process. | PMC10243693 | ||
Implementation {16c} | The web-based randomization system has been set up by the sponsor statistician on the Internet-Based Randomization service system: RANDOMIZE.NET. Participants will be enrolled by the allocated study staff (investigator). After all screening results are available and eligibility is proven, the investigator will request a treatment allocation from the system for the individual participant in question. Allocation concealment will be granted by the inbuilt random element. | PMC10243693 | ||
Assignment of interventions: blinding | PMC10243693 | |||
Who will be blinded {17a} | RECURRENT DISEASE | The personnel assessing participants’ outcomes, like the microbiology laboratory staff or the sponsor medical expert discussing the possibility of recurrent disease, will remain blinded to treatment assignment throughout the whole study in order to ensure unbiased assessment of efficacy endpoints, in attribution of AE causality and expectedness, and in discussion on management with site staff. This is laid down in the trial protocol and associated documents; and data fields from the study database that show treatment assignment, will not be shared with those persons before formal database lock. The data analyst will not be blinded, which is required for composing unblinded reports to the DSMB. | PMC10243693 | |
Procedure for unblinding if needed {17b} | EVENT | In the unlikely event that unblinding is necessary in the interest of participants’ safety and well-being throughout the study for sponsor, sponsor medical expert and other blinded staff, this will be requested from the unblinded statisticians and documented. | PMC10243693 | |
Data collection and management | PMC10243693 | |||
Plans for assessment and collection of outcomes {18a} | TTD | For this study, a data management group created a predefined data base. On a weekly basis, the sponsor receives data reports for review, including listings of blood results for the safety management of the participants. These listings help to identify and to act upon weaknesses in data capture but also quality. Further, this group will send queries to the responsible site in case data has been entered incorrectly or is missing. Several manuals (e.g. lab manual, manual of procedure for clinical assessment of the participants, including “red flags” for discussion with the sponsor medical expert, PK manual) exist to promote data quality. A site initiation visit will be conducted prior to study start to train assessors and a re-training will be conducted in case changes of the protocol occur.Further, time to detection (TTD) is a measurement of bacterial load in the liquid culture BD MGIT system. In order to reduce variability, we will collect two sputum samples per weekly visit and inoculate a MGIT culture from each sample. | PMC10243693 | |
Plans to promote participant retention and complete follow-up {18b} | The process of promoting retention will begin at consent by building a trusting relationship between the participant and the clinical team, as participants are more likely to adhere to study schedules if they know from the outset what they are agreeing to. The study team will collect participants’ demographic information including mobile phone contact(s) and physical address. Using the study visit calculator, participants whose scheduled visits are due will be contacted telephonically prior to the appointment, and a text message will be sent to them a day prior to the appointment as a reminder. Regular review of participants´ communication logs will be done to assist in identifying study participants who potentially may pose to be a retention challenge or loss to follow-up. Re-emphasis on the importance of adhering to study visits and procedures will be conducted on these participants. The study team will also ensure each visit is done according to its scheduled time-point and visit-specific window period with aid of the study visit calculator. The use of these retention tools will help reinforce participant and study staff relationship assisting in study compliance and ensuring a positive study experience. Ensuring compensation for travel expenses and for the time lost during attendance as well as contacting them on special occasions such as Christmas, New Year, or similar culturally appropriate festivals where feasible, might help further to promote participant retention. The inclusion of participants’ representatives in the Community Advisory Board/Institutional meetings where study updates will be presented will also serve to reinforce adherence, retention and complete follow-up of the study participants. Tracing information will be documented in the communication log and information on discontinuation or deviation will be recorded in the participants file notes. | PMC10243693 | ||
Data management {19} | ICH | Electronic case report forms (eCRF) will be created for each participant and all study data collected will be entered into the eCRF. Some data may still be captured entirely or partially on paper source documents and will manually be entered into the eCRF. Accuracy and completeness of the data will be checked by monitoring visits at each site, and by pre-programmed edit checks that will flag out of range values.Risk-based monitoring will be carried out according to the The sponsor will provide a framework for maintenance of quality in performance and reporting of laboratory procedures.The study database will be locked after the data has been monitored by the sponsor and all queries issued through data cleaning activities have been completed and resolutions documented.Essential documents will be retained until at least 2 years after the last approval of a marketing application in the International Conference on Harmonization (ICH) region and until there are no pending or contemplated marketing applications in an ICH region or at least 2 years have elapsed since the formal discontinuation of clinical development of the investigational product, or for not less than 10 years after trial completion, whichever is longer.These documents should be retained for a longer period, however, if required by the applicable regulatory requirements or by an agreement with the sponsor. It is the responsibility of the sponsor to inform the investigator/institution as to when these documents no longer need to be retained. | PMC10243693 | |
Confidentiality {27} | In the trial database and forms, participants will only be identified by a participant identification number, consisting of six figures, which represent the respective site and the enrollment number of the participant. The corresponding participant identification log will be kept in a securely locked separate trial site file, that only delegated staff will have access to. All participants´ records and laboratory specimen displaying names or addresses will be kept confidential in a secure storage area at the sites. The trial database will be encrypted, stored on secure servers with regular back-up, and access control. | PMC10243693 | ||
Plans for collection, laboratory evaluation and storage of biological specimens for genetic or molecular analysis in this trial/future use {33} | Genetic blood samples, stored for future testing, will be labelled using anonymous codes. Results of any genetic tests will not be disclosed to anybody not involved with the study. | PMC10243693 | ||
Statistical methods | PMC10243693 | |||
Statistical methods for primary and secondary outcomes {20a} | TTP | TTP | To establish an exposure-response model for DZD, the change in liquid culture MGIT time to positivity (TTP) will be modelled and linked to derived PK metrics. The model for TTP will be based on a previously develop and published model, linking a latent variable describing the decline in bacterial load to a model of probability of detection in MGIT (handling negative samples) and a time-to-event model for TTP [ | PMC10243693 |
Interim analyses {21b} | The data management and safety board (DSMB) will act as an advisory capacity to the Trial Steering Committee (TSC), to safeguard the interest of trial participants and to review the results of the interim analyses. It will also provide the TSC with recommendations on the continuation, premature closure of the trial or of single experimental treatment arms or extension of the study. The DSMB will meet at least every 6 months and more often if needed. | PMC10243693 | ||
Methods for additional analyses (e.g. subgroup analyses) {20b} | death, TTP | REGRESSION, TTP | Descriptive summary statistics, such a mean/median of the time to culture conversion will be tabulated. Proportion of participants achieving culture conversion at each time point during treatment will be summarized.A Cox regression model will be used to compare each arm with different DZD doses to the background regimen without DZD, censoring for death and loss to follow-up, to estimate the hazard ratio. The analysis will be adjusted for the baseline cultures using time to positivity (TTP) at the time of screening and enrolment. Demographic and clinical characteristics, such as gender, age, race, BMI, HIV status, smoking, and alcohol usage, will also be adjusted in sensitivity analyses. | PMC10243693 |
Methods in analysis to handle protocol non-adherence and any statistical methods to handle missing data {20c} | SECONDARY | The primary analysis population is the intent-to-treat (ITT) analysis population. The ITT analysis population will consist of all randomized patients in the groups to which they were randomly assigned, and who have taken at least one dose of study treatment.A secondary analysis will be of the adequate adherence (AA) analysis population. The AA analysis population will be the same as the ITT population with the following patients excluded: randomized patients not meeting the eligibility criteria; patients having missed 10 or more doses of their allocated treatment in the first 16 weeks of their treatment.All safety analyses will use the safety analysis population: the safety analysis population will be defined as all patients who received any dose of study medication.After entering the study data into the eCRFs, programmed database checks will raise automatic queries in case of any identified inconsistencies or incompleteness of the data. Further completeness and consistency checks will be performed by data management and any resulting queries will be sent through the database query system so as to leave an audit trail. | PMC10243693 | |
Plans to give access to the full protocol, participant level-data and statistical code {31c} | TB | The PanACEA consortium intends to make the protocol and dataset available, e.g. via the TB PACTS TB trials database. | PMC10243693 | |
Oversight and monitoring | PMC10243693 | |||
Composition of the coordinating centre and trial steering committee {5d} | TSC | The TSC will be composed of at least 3 voting members, including a representative of the sponsor, the coordinator of the PanACEA consortium and an independent clinician.The role of the TSC is to provide overall supervision of the trial and ensure that the trial is conducted in accordance with Good Clinical Practice and Good Clinical Laboratory Practice principles. TSC meetings will be held on an ad hoc basis throughout the trial from first-participant-in to last-participant-out to evaluate participants’ safety. The TSC will formally report to the Sponsor. TSC specifics will be detailed and justified in the TSC charter. | PMC10243693 | |
Composition of the data monitoring committee, its role and reporting structure {21a} | TB | The DSMB will consist of five members: a clinician with experience in treatment for drug-sensitive and MDR-TB, an epidemiologist, a pharmacologist, a statistician and a TB laboratory science expert. The DSMB will be installed to safeguard the interest of trial participants and include an element of expert advice that is independent of the sponsor and the principal investigators. Further, the DSMB will review data and will make recommendations to the TSC to stop single arms or the whole trial if trial participation is an undue risk to participants. | PMC10243693 | |
Adverse event reporting and harms {22} | ADVERSE EVENT | All participants will be instructed during informed consent to report at any time any occurrence of AEs to the investigator. In addition, AEs will be solicited at every scheduled visit. The severity of AEs will be classified following the U.S. National Institutes of Health Common Terminology for Adverse Events 5.0 (CTCAE), available online at In this study, in order to prevent a false signal that might be due to a change in heart rate between assessments, a higher grade QTcF prolongation is defined as a combination of QTcF prolongation from baseline with an elevated absolute value, not a prolongation alone.
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Frequency and plans for auditing trial conduct {23} | The sponsor has created an audit plan that includes three audits performed by qualified auditors of partner institutions in the PanACEA consortium that take on trial-related responsibilities, and of subcontractors. | PMC10243693 | ||
Plans for communicating important protocol amendments to relevant parties (e.g. trial participants, ethical committees) {25} | Protocol amendments, after being fully approved by applicable ethics committees and regulatory agencies, will be transmitted to investigators and a protocol amendment training will be performed and documented. | PMC10243693 | ||
Dissemination plans {31a} | TB | Trial outcomes will be important for TB participants and their treating healthcare providers. The results of this trial will be disseminated via scientific publications through high-impact, international, peer-reviewed journals and through scientific conferences; open access schemes will be used. | PMC10243693 | |
Discussion | hypoxemia, infection | INFECTION | The occurrence of COVID-19 during trial preparation affected IMP production, and COVID-19 in trial participants may generate false safety signals if attributed to the trial drugs. Therefore, we included guidance on COVID-19 testing based on symptoms or hypoxemia into the trial-specific manuals and discussed preventive infection control measures with the study sties. Furthermore, to enable on-site monitoring during international lockdowns, we contracted local monitors instead of relying on international travel. | PMC10243693 |
Trial status | RECRUITMENT | At the time of writing this publication, the protocol version 2.1 was used in South Africa and protocol version 2.0 in Tanzania. Recruitment started at the end of October 2021 and is expected to end in Q3 2022.
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Acknowledgements | TB, Alphonce | BRUCE, FRANCIS, DAWSON | The authors would like to acknowledge the members of the data safety monitoring board (Prof. Robert Horsburgh Jr., Prof Andrew Nunn, Prof. Gary Maartens, Prof. Jae-Joon Yim, Dr Ndeky Maria Oriyo),We are grateful to Prof. Kelly Dooley, Vanderbilt University, for invaluable support during study design and conduct, Prof. Eric Nuermberger, Dr. Kerstin Walter and Dr. Christoph Hoelscher for support during the generation of this study and the Global TB Alliance for their research programme that we and others are building on.Further, we would like to acknowledge the team from Tecro Reserach for invaluable data management, and Erina Pretorius and her team at FHI for clinical monitoring support.The authors would also like to acknowledge The Pan African Consortium for the Evaluation of Anti-tuberculosis Antibiotics (PanACEA), which comprises of the following individuals and institutions:Medical Centre of the University of Munich, Munich, Germany (Norbert Heinrich, Michael Hoelscher, Larissa Hoffmann, Alexa Dierig, Krista Stoycheva, Wandini Lutchmun, Julia Dreisbach, Petra Gross - Demel); University of St Andrews, St Andrews, United Kingdom (Derek Sloan, Wilber Sabiiti, Stephen Gillespie); Radboud University Nijmegen Medical Center, Nijmegen, the Netherlands (Lindsey te Brake, Elin Svensson, Rob Aarnoutse, Martin Boeree); UCL Centre for Clinical Microbiology, University College of London, London, UK (Anna Bateson, Robert Hunt, Timothy McHugh, Leticia Muraro Wildner, Priya Solanki); University of California San Francisco (Patrick Phillips, Xue Gong), MRC Clinical Trials Unit at UCL, London, UK (Angela Crook); University of Cape Town, Cape Town, South Africa (Rodney Dawson, Kim Narunsky); University of Stellenbosch, Cape Town, South Africa (Andreas Diacon, Veronique de Jager, Sven Friedrich); University of the Witwatersrand, Johannesburg, South Africa (Ian Sanne, Mohammed Rassool); The Aurum Institute, Johannesburg, South Africa (Gavin Churchyard, Modulakgotla Sebe, Heeran Makkan, Lucia Mokaba, Namhla Madikizela, John Mdluli, Jane Sithole, Robert Wallis, Trevor Beattie); NIMR-Mbeya Medical Research Centre, Mbeya, Tanzania (Nyanda Elias Ntinginya, Chacha Mangu, Christina Manyama, Issa Sabi, Gabriel Rojas-Ponce, Bariki Mtafya, Lilian F. Minja); Ifakara Health Institute, Dar es Salaam, Tanzania (Francis Mhimbira, Benno Mbeya, Tresphory Zumba, Mohamed Sasamalo); Swiss Tropical and Public Health Institute, Basel, Switzerland, University of Basel, Basel, Switzerland (Klaus Reither, Levan Jugheli) ; Kilimanjaro Clinical Research Institute, Moshi, Tanzania (Noel Sam, Gibson Kibiki, Hadija Semvua, Stellah Mpagama, Alphonce Liyoyo); Centre de Recherches Médicales de Lambaréné, Gabon (Bayode Romeo Adegbite, Ayola Akim Adegnika, Martin Peter Grobusch); Amsterdam University Medical Centers (Martin P. Grobusch, Bayode Romeo Adegbite),; Makerere University, Kampala, Uganda (Bruce Kirenga), Instituto Nacional de Saúde, Marracuene, Mozambique (Celso Khosa, Isabel Timana), College of Medicine, Blantyre, Malawi (Mariott Nliwasa, Madalo Mukoka). | PMC10243693 |
Authors’ contributions {31b} | MH, RA | The study design was conceptualized by NH, ES, MH, and LG. Funding and study drug is made available by YLC and LG. The study protocol was written by SS, NH, AD, AJM, ES, LtB, RA, YLC, LG, and MH. The study is set up and conducted by AD, SS, LH, AJM, LtB, RA, MB, TMcH, LMW, LTM, NN, MS, AL, RSW, MS, FAM, BM, LG, YLC, and NH. Statistical input and analyses are performed by PP and XG. The manuscript was written by AD, LG, and NH. All authors read and approved the final manuscript.Authorship of the final will include the sponsor LegoChem Biosciences, and African, European and US-based members of the PanACEA consortium who participated in trial design, protocol writing, trial preparation, conduct, monitoring, oversight, data analysis, PK-PD modelling and manuscript writing, among others. | PMC10243693 | |
Funding {4} | TB, Infection | INFECTION | Open Access funding enabled and organized by Projekt DEAL. The study is funded by LegoChem Biosciences, Inc, and conducted under the umbrella of PanACEA, the PanAfrican Consortium for the Evaluation of anti-TB Antibiotics, which receives funding through the European and Developing Countries Clinical Trials Partnership (EDCTP, grant number TRIA2015-1102 PanACEA), the German Ministry for Education and Research (BMBF, grant number 01KA1701), and the German Center for Infection Research (DZIF). PanACEA is a not-for-profit consortium with the goal of shortening the treatment regimen of drug-sensitive TB. | PMC10243693 |
Availability of data and materials {29} | All parties conducting the trial will have access to the final trial dataset. | PMC10243693 | ||
Declarations | PMC10243693 | |||
Ethics approval and consent to participate {24} | This study protocol was approved by the Ethic committee of the Ludwig-Maximilians-University of Munich, Germany and by applicable ethics committees of the trial sites. These include:South African Health Products and Regulatory Authority, Arcadia, South AfricaHuman Research Ethics committee, University of the Witwatersrand (Ref 200910B)Medical Research Coordinating Committee Tanzania (Ref NIMR/HQ/R.8a/Vol.IX/3649)Mbeya Medical Research and Ethics review committee, Mbeya, Tanzania (Ref SZEC-2439/R.A./V.1/105)Institutional Review Board, Ifakara Health Institute, Dar es Salaam, Tanzania (Ref IHI/IRB/AMM/ No: 11-2021)Kilimanjaro Christian Medical College Research Ethics and Review Committee (CRERC), Moshi, TanzaniaWritten informed consent will be obtained from each participant or its legal guardian. The informed consent is available from the corresponding author on request. | PMC10243693 | ||
Consent for publication {32} | “Informed consent forms” of the study may be provided by the corresponding author upon reasonable request. | PMC10243693 | ||
Competing interests {28} | All authors except LG and YLC report receiving research funding from LegoChem Biosciences to their institutions. LG receives compensation as a consultant. YLC is an employee of LegoChem Biosciences. Further, the authors would like to report receiving delamanid (Deltyba®) free of charge, from Otsuka Novel Products GmbH. | PMC10243693 | ||
References | PMC10243693 | |||
Introduction | Across the literature, training interventions that have attempted to reduce hamstring strain injury (HSI) incidence, have aimed to mitigate the influence of the modifiable risk factors of HSI (i.e., eccentric hamstring strength and bicep femoris long head (BFCurrently, the NHE has been a key focus of training research by observing its effect on one or more of the modifiable risk factors of HSI (i.e., eccentric strength, muscle architecture) [As a result of the continued low compliance of NHE training, a natural progression of practice and research is to investigate the possibility of training that could be more agreeable or available for both athletes and coaches. One example could be sprint training, as it has been hypothesised there could be a similar imposed demand of fascicle lengthening (i.e. eccentric muscle action), while coinciding with the maximal activation patterns during the swing phase [To date, two studies have observed the effects of a sprint-based training on the modifiable risk factors for HSI [Improvements in athletic performance (e.g., strength, sprinting and jumping) are also a key if not the primary consideration when programming for athletes. It is well documented that sprint-based training can improve athletic tasks [The purpose of the present study was to determine the effect of a short-term (seven-week) intervention with supplemental sprint or NHE, imbedded within an ecologically valid training programme (group 1. Control training (CT) vs group 2. CT plus NHE vs group 3. CT plus sprinting), on the magnitude of adaptations to the modifiable risk factors, i.e., BF | PMC9980768 | ||
Materials and methods | An intervention study design was employed for the present study ( | PMC9980768 | ||
Schematic diagram of pre-testing, seven-week intervention and post-testing. | PMC9980768 | |||
Participants | 38 collegiate athletes who participated in regular team sports (football, futsal, rugby union, rugby league, ice hockey, American football, basketball, netball). All participants reported competing across a range of competitive levels from university (collegiate) to semi-professional level sports participation. Participants playing season varied between either pre- or in-season. All participants were required to have a history of resistance-based training, including the NHE, regularly (minimum of once/week) applied within the previous 6 months. All participants reported having between 1–2 years of sprint or running based technical coaching which had been delivered during sport-based training. All participants were required to be free from injury and not had a previous HSI in the past 6 months. Participants were randomly allocated to the three training groups using a random number generator; Nordic | PMC9980768 | ||
Lower limb resistance training programe, including sets x reps and estimated one repetition maximum percentages, performed by the control and intervention groups across the seven-week training intervention. | In conjunction to the control resistance training programme, the intervention groups were prescribed either additional sprint or NHE training at the start or end of each training session ( | PMC9980768 | ||
Additional training performed by the NHE or sprint intervention groups across the seven-week training intervention, including sets x reps. | The study aimed to control for any other resistance training performed by the participants, advising that outside the prescribed programme no further lower-limb resistance training could be performed. Only an individual’s sport-specific and upper body resistance training was permitted. | PMC9980768 | ||
Data collection | PMC9980768 | |||
Bicep femoris long head muscle architecture | All testing commenced with resting US imaging of the BFTo collect the ultrasound images, a layer of conductive gel was placed across the linear array probe; the probe was then placed on the skin over the scanning site and aligned longitudinally to the BF and perpendicular to the skin. During collection of the ultrasound images, care was taken to ensure minimal pressure was applied to the skin, as a larger application of pressure distort images leading to temporarily elongated muscle fascicles. The assessor manipulated the orientation of the probe slightly if the superficial and intermediate aponeuroses were not parallel. These methods are consistent to those used previously [ | PMC9980768 | ||
Countermovement jump | Following muscle architecture assessment, participants performed a standardised dynamic warm-up consisting of body weight squats, forward and reverse lunges, submaximal squat jumps and CMJs. Three maximal effort CMJs, with a one-minute rest between trials was assessed using a Kistler force platform, sampling at 1000 Hz, with data collected via Bioware 5.11 software (type 9286AA, Kistler Instruments Inc. Amherst, NY, USA). Participants were instructed to stand still for the initial one second of data collection [ | PMC9980768 | ||
Eccentric hamstring strength | The assessment of eccentric knee flexor strength was performed using the Nordbord device (Vald Performance, Newstead, Australia), which has been used in the literature previously [ | PMC9980768 | ||
Lower limb maximal strength | For the isometric mid-thigh pull (IMTP), the procedures and guidelines previously described were used [ | PMC9980768 | ||
Sprinting | Prior to completing the sprint assessment, two 20 m practice sprints at 50- and 75% of perceived maximum intensity, which also served as a brief familiarisation period. Three maximum effort trials of the 20 m sprint were performed, with brief rest periods of two minutes prescribed between trials. Instructions were provided to participants to initiate the sprint from a stationary two-point, split start and to perform a maximal effort throughout the full 20 m [ | PMC9980768 | ||
Data analysis | PMC9980768 | |||
Bicep femoris architectural digitization | All sonograms were analysed off-line with Image J version 1.52 software (National Institute of Health, Bethesda, MD, USA). Images were first calibrated to the known field of view (10-cm), then for each image a fascicle of interest was identified. Finally, muscle thickness, pennation angle, observed FL and distance between fascicle end-point and super-fascial aponeurosis were measured three times within each image, to enable complete FL estimation using a previously established reliable linear equation [Where L is the observable fascicle length, h is the perpendicular distance between the superficial aponeurosis and the fascicles visible end point and | PMC9980768 | ||
Force-time analysis | Raw force-time data for the CMJ, IMTP and NHE was analysed in Microsoft Excel (Excel 2016, Microsoft, Washington, USA). For the CMJ, velocity of centre of mass at take-off was determined as a measure of performance (take-off velocity) [For the IMTP, peak absolute and relative net force was determined as the maximum forces recorded from the whole force-time curve during the IMTP trials [For the NHE, consistent with the IMTP, peak force was determined as the maximum forces recorded from the whole force-time curve. Movement onset was determined as the point when the force increased above a 5 N absolute threshold, whereas the movement was finished when the vertical force decreased below a 5 N absolute threshold. Total and active impulse were determined by integrating the whole force-time curve and the active portion of the force-time curve (movement onset-finish), respectively. Mean force was determined as the average force across the active portion of the force-time curve. Time to peak force was determined as the time between movement onset and peak force, while repetition time was determined as the time between movement onset and movement finish.The mean performance of the trials for each assessment was used for further analysis. | PMC9980768 | ||
Reliability and measurement error | A subsample performed two PRE-testing sessions (n = 24), to determine the between-session reliability and measurement of each variable of interest. All data was first tested using the Shapiro-Wilk test to check if it satisfied parametric assumptions. A two-way random-effects model intraclass correlation coefficient (ICC) and coefficient of variation (CV) with corresponding 95% CI, was used to determine the relative and absolute, respectively. The ICC values were interpreted based on the upper and lower bound CI as (<0.50) poor, (0.5–0.74) moderate, (0.75–0.90) good and (>0.90) excellent [The standard error of measurement (SEM) and smallest detectable difference (SDD) for each variable were calculated to establish measurement error scores. The SEM was calculated using the following Formula [The SDD was calculated using the following established Formula [As test-retest reliability and measurement error was established for all variables of interest, any observed changes in performance that exceed the associated measurement error would likely be ‘true’ changes. | PMC9980768 | ||
Pre to post intervention changes | Data obtained at pre was taken forward to perform comparisons at post training, as parametric assumptions were met for all measures using the Shapiro-Wilk test, between- pre and post in the modifiable risk factors (BFAll statistical analyses performed using SPSS software (version 25; SPSS Inc. Chicago, IL, USA) with the alpha level set at | PMC9980768 | ||
Results | PMC9980768 | |||
Reliability and measurement error | Between session reliability and measurement error for all variables of interest are presented in | PMC9980768 | ||
Pre- to Post-intervention changes | At pre-testing, there were trivial non-significant differences observed between all groups for bicep femoris fascicle length and eccentric hamstring strength measures (Hedge’s | PMC9980768 | ||
Body mass | Trivial increases (g <0.34) in body mass were observed across all groups from PRE to POST ( | PMC9980768 | ||
Pairwise comparisons of body mass for all training groups. | PMC9980768 | |||
Bicep femoris fascicle length | A non-significant time×training interaction was observed for absolute and relative BF | PMC9980768 | ||
Gardner-Altman estimation plots identifying Pre- and Post-intervention individual changes for absolute bicep femoris fascicle length and Hedge’s | PMC9980768 | |||
Gardner-Altman estimation plots identifying Pre- and Post-intervention individual changes for relative bicep femoris fascicle length and Hedge’s | PMC9980768 | |||
Pairwise comparisons of Bicep femoris fascicle length for all training groups. | PMC9980768 | |||
Eccentric hamstring strength | Peak and relative peak force demonstrated a significant time×training interaction ( | PMC9980768 | ||
Gardner-Altman estimation plots identifying Pre- and Post-intervention individual changes for peak eccentric hamstring force and Hedge’s | PMC9980768 | |||
Gardner-Altman estimation plots identifying Pre- and Post-intervention individual changes for relative peak eccentric hamstring force and Hedge’s | PMC9980768 | |||
Pairwise comparisons of eccentric hamstring measures for all training groups. | PMC9980768 | |||
Countermovement jump | A non-significant time×training interaction was observed for take-off velocity and jump momentum (p = 0.834 & 0.518, respectively). Pairwise comparisons, revealed small increases ( | PMC9980768 | ||
Gardner-Altman estimation plots identifying Pre- and Post-intervention individual changes for take-off velocity and Hedge’s | PMC9980768 | |||
Gardner-Altman estimation plots identifying Pre- and Post-intervention individual changes for jump momentum and Hedge’s g effect size with the 95% CI indicated by the ends of the vertical error bar. | PMC9980768 | |||
Pairwise comparisons of countermovement jump measures for all training groups. | All other CMJ variables; countermovement time, displacement, and peak braking force, showed non-significant time×training interaction, with trivial differences from PRE to POST for all training groups. | PMC9980768 | ||
Isometric mid-thigh pull | For peak absolute and relative net force attained from the IMTP assessment, a significant time×training interaction was observed ( | PMC9980768 | ||
Gardner-Altman estimation plots identifying Pre- and Post-intervention individual changes for peak net force and Hedge’s | PMC9980768 | |||
Gardner-Altman estimation plots identifying Pre- and Post-intervention individual changes for peak net relative force and Hedge’s | PMC9980768 | |||
Pairwise comparisons of peak net IMTP force for all training groups. | * = significant increase | PMC9980768 | ||
Sprinting | Non-significant time×training interactions were observed for sprint and Nordic training groups for 0-10-, 0-20- and 10–20 m ( | PMC9980768 | ||
Gardner-Altman estimation plots identifying Pre- and Post-intervention individual changes for 0-10m sprint time and Hedge’s | PMC9980768 | |||
Gardner-Altman estimation plots identifying Pre- and Post-intervention individual changes for 0-20m sprint time and Hedge’s | PMC9980768 | |||
Gardner-Altman estimation plots identifying Pre- and Post-intervention individual changes for 10-20m sprint time and Hedge’s | PMC9980768 | |||
Pairwise comparisons of sprint measures between Nordic and sprint training groups. | RPE | No significant group×time interactions was observed for RPE ( | PMC9980768 | |
Mean (±95%CI) Rating of perceived exertion measured using a numeric scale (1–10) for the Nordic hamstring exercise, Sprint and control groups. | DOMS | The average DOMS reported ( | PMC9980768 | |
Mean (±95%CI) 24-hr post soreness measured using a numeric pain rating scale (1–10) for the Nordic hamstring exercise, Sprint, and control groups. | PMC9980768 | |||
Discussion | The results of the present study demonstrate that a multi-modal approach to hamstring training is highly effective in increasing both the modifiable risk factors of HSI (eccentric hamstring strength and BF | PMC9980768 | ||
Modifiable risk factors | The results of the present study identified meaningful increases (i.e., >SDD) for the modifiable risk factors (absolute and relative BFThe observed changes seen within the present study for BFConsistent with previous training interventions, absolute and relative eccentric hamstring strength was increased across all training groups [With regards to other modalities used within this study (i.e. sprint and hip dominant traditional exercise), the present study found a greater change in eccentric hamstring strength than Freeman, Young [ | PMC9980768 | ||
Athletic performance | Meaningful increases in CMJ take-off velocity were observed for all training groups. The increase in take-off velocity, would also represent an increased jump height, although the smaller measurement error observed with take-off velocity means the increases observed are less likely to be an effect of random error. It should be noted however, that the control group had the largest increase in CMJ take-off velocity, although the magnitude of increases was similar between groups. The addition of sprinting or NHE had less of an effect on jumping than the control training programme, suggesting the benefits to performance came from the conventional resistance program including the RDL. Non-significant changes were observed within mean propulsion force for the sprint and control training groups; however, all three training groups had a small increase in mean propulsion force to a similar magnitude, with the sprint training group having the greatest magnitude of adaptation. However, on an individual basis within the NHE training group, all bar one individual, which was within SEM, had a positive and meaningful increase within mean propulsion force. Whereas for both the sprint and control the individual response was mixed. This indicates that the NHE potentially led to an increased force generating capacity during hip extension [The control group had non-meaningful (<SDD) increase in absolute and relative peak net force attained during the IMTP, with a trivial and non-significant increase for absolute peak net force and small, significant increase in relative peak net force. Both NHE and sprint intervention groups, had meaningful (>SDD), significant and small increases in both absolute and relative peak net force. The sprint training group had the largest positive increase in both absolute and relative peak net force, 34.71- and 35.73%, respectively. Followed by the NHE training group had large positive increases in both absolute and relative peak net force, 22.28- and 22.46%, respectively. The observed increases in the sprint training group could be the result of increased potential of increase motor unit activation, increase passive tension of the muscle-tendon complex and improved cross bridge mechanics [The NHE and sprint training groups had meaningful and significant decreases in 0–10 m, 0–20 m, and 10–20 m sprint times. Across all sprint times, the sprint training group achieved the greatest decreases in comparison to the NHE training group. Although the differences cannot be entirely attributed to the NHE or sprint training, due to the accompanying resistance training programme [ | PMC9980768 | ||
Compliance | The present study was highly effective at increasing both modifiable risk factors of HSI (eccentric hamstring strength of BF | PMC9980768 | ||
Limitations | The present study is not without its limitations; firstly, although all participants reported participation in regular sport (predominantly team sport); competitive level, season, positional demands could have influenced the adaptations. This meant that individuals would have been exposed to a variety of external running and training loads, which could have all influenced the individual responses observed during the intervention [The application of the training intervention could have been improved with appropriate feedback or technical modification. Real time visual feedback has been previously shown to increase mean eccentric peak force in the NHE within athletes [Finally, due to track unavailability, the control group was not able to perform any sprint assessments, this means that the conclusions made about the effect of sprint and NHE training upon improvement in sprint ability should be taken with caution. As the effect of the standardised training programme were not identified, as it would be expected increases in strength (i.e., IMTP peak net force), through the periodized resistance training programme could also transfer to sprint performance. | PMC9980768 | ||
Conclusions | The present study set out to determine the effect of a short-term training intervention with supplemental sprint or NHE, imbedded within an ecologically valid lower limb training programme, on the magnitude of adaptations to the modifiable risk factors of HSI, BF | PMC9980768 | ||
Supporting information | (XLSX)Click here for additional data file. | PMC9980768 | ||
Key Points | PMC10638655 | |||
Question | DISORDER | Does social contagion affect adoption of the practice of emergency department initiation of buprenorphine for opioid use disorder? | PMC10638655 | |
Findings | SECONDARY | In this secondary analysis of a multicenter, cluster-randomized trial of 5 health care systems and 1026 clinicians, including attending physicians, residents, and advanced practice practitioners, the number of interactions with another clinician initiating buprenorphine in the emergency department had a dose-dependent association with self-adoption of the practice. The primary trial intervention, health care system, and clinician type were also associated with practice adoption. | PMC10638655 | |
Meaning | opioid use disorder | SECONDARY, INTERACTION | Interaction with other clinicians initiating buprenorphine was associated with increased likelihood of self-adoption, suggesting that there may be a role for social factors in practice uptake.This secondary analysis of a cluster randomized trial examines the factors, including social contagion, associated with the adoption of the practice of emergency department (ED) initiation of buprenorphine for patients with opioid use disorder. | PMC10638655 |
Importance | EMERGENCY | Emergency department (ED) initiation of buprenorphine is safe and effective but underutilized in practice. Understanding the factors affecting adoption of this practice could inform more effective interventions. | PMC10638655 | |
Objective | opioid use disorder | To quantify the factors, including social contagion, associated with the adoption of the practice of ED initiation of buprenorphine for patients with opioid use disorder. | PMC10638655 |
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