Despite the introduction of vaccination, there remains a need for pre-exposure prophylactic agents against SARS-CoV-2. Several patient groups are more vulnerable to SARS-CoV-2 infection by virtue of underlying health conditions, treatments received or suboptimal responses to vaccination.PROTECT-V is a platform trial testing pre-exposure prophylactic interventions against SARS-CoV-2 infection in vulnerable patient populations . Multiple agents can be evaluated across multiple vulnerable populations sharing placebo groups, with the option of adding additional treatments at later time points as these become available. The primary endpoint is symptomatic SARS-CoV-2 infection, and each agent will be independently evaluated in real time when the required number of events occurs. Presently, three agents are approved in the platform: intranasal niclosamide, nasal and inhaled ciclesonide and intravenous sotrovimab.Despite the introduction of vaccination, there remains a need for pre-exposure prophylactic agents against SARS-CoV-2. Several patient groups are more vulnerable to COVID-19 disease by virtue of underlying health conditions, treatments received or suboptimal responses to vaccination.ClinicalTrials.gov NCT04870333. EudraCT 2020-004144-28 The order of the items has been modified to group similar items .Unified sponsor and regulatory oversight.Single contract with participating sites for multiple interventions/populations.Statistical efficiency—depending on specific interventions/populations, it may be possible to use Bayesian analysis methods that allow adaptive borrowing of information across populations. This will mean in the case that there is a consistent effect across populations, the trial will have greater power to find significant differences for individual patient groups. Furthermore, placebo data may be able to be shared across arms during periods of concurrent recruitment.The PROTECT-V trial platform brings greater efficiency, running multiple sub-trials within one master protocol. The core components of the PROTECT-V trial platform include:Intranasal niclosamideInhaled and intranasal ciclesonideIntravenous sotrovimabAt present three agents are approved in the PROTECT-V platform:Specific information relevant to each of these agents is provided under sub-headings in each section of this manuscript.The primary aim of the trial is to determine if pre-exposure prophylactic treatment reduces the risk of confirmed, symptomatic SARS-CoV-2 infection in vulnerable immunosuppressed patients.Determine if pre-exposure prophylactic treatment increases the time to confirmed SARS-CoV-2 infection from the date of randomisation including incidental asymptomatic cases in vulnerable populationsDetermine the safety of prophylactic treatments in this patient populationDetermine if prophylactic treatment reduces mortality and severity of COVID-19 disease in the vulnerable populations taking part in the studyThe trial also aims to:PROTECT-V is a platform trial to test pre-exposure prophylactic interventions against SARS-CoV-2 infection in vulnerable patient populations at particularly high risk of COVID-19 and its complications, seeking to identify treatments that either prevent the disease from occurring or reduce the number of cases where the disease becomes serious or life-threatening. In PROTECT-V, multiple agents can be evaluated on the same platform across multiple vulnerable populations, with the option of adding additional treatments at later time points as these become available. The expectation is for as many sites as possible to recruit to all available trial interventions at any time; however, the platform structure and randomisation/data collection systems allow sites to open trial treatment arms according to their capacity.PROTECT-V will be conducted in a hospital setting. Potential participants will be identified via outpatient clinics and dialysis units. The niclosamide and ciclesonide arms will run in approximately 40 UK sites and the sotrovimab arm in 20–30 UK sites. A full list of recruiting study sites will be included in the final study report for each intervention. A parallel niclosamide arm of the PROTECT-V study will also be conducted in India. The George Institute for Global Health, India, will sponsor the PROTECT-V protocol in India. Trial medications and funding for the Indian arm of the study are provided by UNION Therapeutics. The overarching trial electronic case report form (eCRF), statistical support and trial committees will be provided by the UK PROTECT-V trial infrastructure. Data on patients recruited in India will be entered directly into the PROTECT-V study database, and cumulative data from the parallel trial will contribute to the overall sample size and primary endpoint events.Be aged 18 years or olderHave given written informed consentEnd-stage renal failure on dialysis—including in-centre haemodialysis, home haemodialysis and peritoneal dialysisKidney transplant recipient receiving at least one of the immunosuppressive medications listed in the protocolVasculitis (according to Chapel Hill Consensus Conference 2012 definitions) or systemic lupus erythematosus (SLE) receiving at least one immunosuppressive medicationGlomerulonephritis* receiving at least one immunosuppressive medicationBe a member of one of the following vulnerable patient populations:To be included in the trial, the participant must:*Glomerulonephritis includes prior histological confirmation of any of the following conditions—minimal change nephropathy, focal segmental glomerulosclerosis (FSGS), IgA nephropathy, primary membranous nephropathy, membranoproliferative glomerulonephritis or lupus nephritis.Inability to provide informed consent or to comply with trial proceduresCOVID-19 at time of enrolment—either positive SARS-CoV-2 swab ) or symptoms highly suggestive of COVID-19 infectionKnown chronic liver disease or hepatic dysfunction as evidenced by ALT or AST > 3× upper limit of the normal rangeAllergy or hypersensitivity to any of the active IMPs or to any of the excipients usedPregnant, trying to conceive, unwilling to use contraception or breastfeedingCurrent participation in another interventional prophylactic or vaccine trial* against COVID-19.The presence of any of the following will preclude participant inclusion:*Patients remain eligible for enrolment if they have received SARS-CoV-2 vaccination as part of routine care.Significant structural nasal disease in the opinion of the investigatorPrior participation in the niclosamide arm of the trial The following are additional exclusion criteria for the niclosamide arm:Additional exclusion criteria for the ciclesonide armSignificant structural nasal disease in the opinion of the investigatorPrior participation in the ciclesonide arm of the trial Currently taking inhaled corticosteroidsReceived a live vaccine within the last 14 daysTaking one of the following medications: systemic ketoconazole, itraconazole, ritanovir and nelfinavirThe following are additional exclusion criteria for the ciclesonide arm:Individuals receiving replacement normal human immunoglobulin (NHIg) for any cause of antibody deficiency are eligible regardless of antibody titre, although this will be measured at screening. An Anti-SARS-CoV-2 antibody assay result < 400 AU/mL is NOT required for eligibility in these patients. Antibody titres are unreliable in these patients and vary according to the batch of NHIg administered; timing since NHIg administration and the strict criteria for prescription of NHIg replacement therapy reflects the marked immune compromise of these individuals.Responses should be assessed at least 14 days after the participants’ most recent vaccination.Absent or suboptimal antibody response (defined by Roche Elecsys® Anti-SARS-CoV-2 antibody assay result < 400 AU/mL) to SARS-CoV-2 vaccination or infectionImmunodeficiency (primary and secondary immunodeficiencies)Any oncology, haematology-oncology or haematology patient who is currently receiving or has received chemotherapy or who is immunocompromised as a result of their disease or treatmentHave a diagnosis of an autoimmune/inflammatory disease currently receiving immunosuppression including those individuals currently on prednisolone ≥ 20 mg daily for at least 4 weeks. Those who have received rituximab or alemtuzumab within the last 12 months would also be eligibleSolid organ and haematopoietic stem cell transplant recipientsBe a member of an immunocompromised population, which includes but is not limited to those groups listed in the core protocol as well as the following:The following are additional inclusion criteria for the sotrovimab arm:The following are additional exclusion criteria for the sotrovimab arm:Antibody response to SARS-CoV-2 vaccination or infection above the pre-specified threshold, as measured by the central laboratory antibody assay If in the opinion of the PI it is not in the best interests of the participant to take part in the study—for example, due to limited life expectancy (≤ 12 months) due to pre-existing co-morbiditiesHistory of hypersensitivity reaction to sotrovimab, one of its excipients or any other monoclonal antibody targeting SARS-CoV-2History of receiving any monoclonal antibody targeting SARS-CoV-2 within the last 6 monthsAdmission to the hospital for acute, unplanned care at the time of randomisation or in the 2 weeks prior to screeningHistory of receiving chimeric antigen receptor T-cell (CAR-T) therapy less than 4 weeks prior to consenting to take part in the studyIn addition to the core exclusion criteria in the master protocol, the presence of any of the following will preclude participant inclusion:Consent will be obtained by the principal investigator at each trial site or by a suitably qualified and delegated health professional and member of the research team at each site.Explicit consent for the use of participant data and biological specimens is collected. Participants are asked to agree to the following statement on the consent form “I understand that de-identified information collected during my participation in the PROTECT-V trial may be used to support other, future ethically approved research studies, including research conducted by both commercial and non-commercial organizations in the UK and abroad, and that analysis of the samples may occur that involves DNA/RNA collected from my donated blood samples”. Making information and samples from trials available for further research helps maximise the benefit of conducting trials and allows other researchers to verify the results and avoid duplicating research. Any samples not used will be disposed of in accordance with the Human Tissue Authority codes of practice.Each intervention will have a matched placebo as a comparator.There are currently three separate interventions approved in PROTECT-V: intranasal niclosamide, intranasal and inhaled ciclesonide and intravenous sotrovimab.Niclosamide, a salicylic acid derivative, is a cheap and safe anti-helminthic medication on the World Health Organization’s List of Essential Medicines that has potent anti-SARS-CoV-2 activity in vitro. It emerged as the leading candidate for activity against SARS-CoV-2 in two separate library screens of existing approved drugs . FurtherAs oral niclosamide is poorly absorbed from the gut with low bioavailability, UNION therapeutics has developed a stable liquid formulation (UNI911). The PROTECT-V trial will administer 1% niclosamide ethanolamine solution via a nasal spray pump twice daily  and total daily dose of 5.6 mg niclosamide ethanolamine salt (4.7 mg free niclosamide acid) to maximise delivery of drug to the nasal and upper respiratory tract epithelia.Ciclesonide is an inhaled corticosteroid licenced for the treatment of asthma and allergic rhinitis that has been shown to possess in vitro anti-SARS-CoV-2 activity but has negligible systemic bioavailability even at higher doses . Class eThe proposed combination of prophylactic inhaled and intranasal ciclesonide will deliver early infection-modifying therapy covering the entire respiratory epithelium, critical in the early stages of COVID-19 . A 320-μSotrovimab is a recombinant human IgG1κ monoclonal antibody (mAb) derived from the parental mAb S309, a potent neutralising mAb directed against the spike protein of SARS-CoV-2 . SotroviP = 0.002 of disease progression leading to hospitalisation or death. The final analysis of 1057 patients showed all-cause hospitalisation or death was significantly reduced with sotrovimab (6/528 [1%]) vs placebo (30/529 [6%])  [The Phase II/III COVID-19 Monoclonal Antibody Efficacy Trial–Intent to Care Early (COMET-ICE) evaluated the efficacy and tolerability of 500 mg sotrovimab administered intravenously in high-risk non-hospitalised patients with mild to moderate COVID-19 infection . In a pro 0.50]) .90, respectively, when compared to the Wuhan reference strain. More recently, sotrovimab was found to neutralise Omicron BA.4, BA.5 and BA.2 to a similar extent [90 (for wild type and for variants with < 22-fold shift in potency) through 24 weeks, the primary endpoint was changed from 24 to 12 weeks to ensure the highest likelihood of demonstrating efficacy, particularly with the BA.2 variant predominance at the time.Sotrovimab targets a conserved epitope in the SARS-CoV-2 spike protein at a region that does not compete with the binding of the angiotensin-converting enzyme 2. However, pseudotype and live virus neutralisation data suggested reduced neutralisation of Omicron BA.1 and BA.2 confer a 3.5-fold and 35-fold shift in ECr extent . TherefoFuture prophylactic agents such as alternative monoclonal antibody therapies, antivirals or nasal or inhaled agents may be included within the platform.Participants will be withdrawn from the trial treatment at the discretion of the PI/CI if continuation in the trial is deemed to be against the participant’s best interest.Participants become pregnantParticipant is hospitalised for COVID-19 Participant experiences unacceptable drug reactionParticipant has not been followed up for more than 6 consecutive weeks  or for more than 12 consecutive weeks Treatment will be withdrawn if:Participants who have been withdrawn from the trial treatment and are experiencing ongoing toxicity will be followed up until the adverse reaction comes to its conclusion. In the event of a participant being withdrawn from the trial treatment, they will continue to receive the most appropriate standard of care treatment available under the guidance of their treating clinician. Following treatment withdrawal, at the final assessment, patients may be re-screened for consideration of enrolment (under a new subject identifier) into one of the other arms of the PROTECT-V trial platform.Specifically for the niclosamide arm, unacceptable drug reactions which may lead to the withdrawal of treatment include moderate/severe pain or severe burning/itching in the nose, spontaneous nose bleeding as a result of nasal ulceration or oedema which prevents breathing through the nose.No dose adjustment is required for any of the IMPs  even for those individuals with end-stage renal failure on dialysis.Participants being recruited to the PROTECT-V trial are clinically extremely vulnerable, and therefore, attendance for in-person hospital visits has been minimised where possible. For all IMPs, contact is made remotely with patients every 2 weeks for the duration of the trial. IMP will be collected by the participant during dialysis sessions or sent by courier to the participant to avoid the need for in-person study visits for medication re-supply. For niclosamide and ciclesonide, which need to be self-administered twice daily throughout the study period, participants are asked to complete medication diaries, which are then returned together with IMP containers, for compliance assessment at the final study visit. Specifically for the ciclesonide arm, an easy-to-use delivery method via an AeroChamber spacer and facemask with mouth breathing for the inhaled route and nose breathing for the intranasal route has been employed, which has previously been shown to improve adherence , 28.All standard-of-care medicines are to continue as per standard practice, including receipt of vaccines against SARS-CoV-2 as part of routine clinical care. Furthermore, should patients contract SARS-CoV-2 infection during the study, they are eligible to receive all standard-of-care treatments both in the hospital and in the community. Any treatment received will be recorded in the eCRFs.After the end of the trial, we will endeavour to make available to trial participants further supplies of the IMP in the event that the trial demonstrates benefit, but this cannot be guaranteed.Cambridge University Hospitals NHS Foundation Trust, as a member of the NHS Clinical Negligence Scheme for Trusts, will accept full financial liability for harm caused to participants in the clinical trial caused through the negligence of its employees and honorary contract holders. There are no specific arrangements for compensation should a participant be harmed through participation in the trial, but no one has acted negligently. The University of Cambridge will arrange insurance for negligent harm caused as a result of protocol design and for non-negligent harm arising through participation in the clinical trial in the UK. The George Institute India will arrange insurance in India.Confirmed SARS-CoV-2 Respiratory (cough ± sputum and shortness of breath)Constitutional Gastrointestinal One or more symptoms in keeping with COVID-19, including:The primary outcome for PROTECT-V is confirmed symptomatic SARS-CoV-2 infection during treatment defined as the presence of both:Time to confirmed SARS-CoV-2 infection from randomisation including asymptomatic casesSafety and all-cause mortalityHealthy carriers—confirmed SARS-CoV-2 infection, no symptomsVery mild symptoms, no limitationsMild, limitations on activitiesMild, hospitalised, no oxygen requirementModerate, hospitalised, oxygen via mask or nasal cannulaSevere, non-invasive ventilation or high-flow oxygenVery severe, intubation and mechanical ventilationCritical, ventilation and additional organ support (RRT/ECMO)DeathAdapted WHO ordinal scale Length of inpatient stayCommon COVID-19 complications Severity of COVID-19 disease (assessed by PI 28 days after the date of positive test)Secondary outcomes includeSpecifically for the sotrovimab arm, since the IMP is administered as a single infusion on day 1, the primary outcome will be reported at 12 weeks (85 ± 7 days) from the date of IMP administration. The following secondary outcomes will also be assessed: confirmed, symptomatic SARS-CoV-2 infection at 16 weeks (113 ± 7 days), 24 weeks (169 ± 7 days), 36 weeks (253 ±7 days) and 48 weeks (337 ± 7 days) from the date of IMP administration.The following is the trial flowchart Figs.  and 2 fo1Day 3 (24–72 h post-infusion) telephone call only necessary for lead-in cohorts2Day 4 (48–96 h post-infusion) in-person assessment will only be done for lead-in cohort one and will be a home-visitSince there is limited data on a 2000-mg dose of sotrovimab, there will be 3 leads in cohorts.Infusion and observation times will begin as per cohort 1 (see figure below). After 60 patients have been recruited, a safety analysis will be carried out assessing whether any participants had suffered from a severe infusion-related reaction (IRR) .Any severe IRR in cohort 1 will be reviewed by the independent Data Monitoring Committee (IDMC) to evaluate the IRR and make recommendations to the Trial Management Group (TMG) regarding whether to adjust the infusion time further, implement any other measures or delay progress to cohort 2. If no severe IRRs are noted from the first 60 patients recruited, and the day 4 routine haematological and biochemical assessments do not demonstrate any clinically significant abnormalities, then sites will be instructed to alter the IMP infusion time in line with cohort 2.After 60 patients have been recruited to cohort 2, data will be reviewed by the IDMC to evaluate the IRR and make recommendations to the TMG regarding whether to adjust the infusion time further, implement any other measures or delay progress to cohort 3. If there is no severe IRR, then sites will be instructed to alter the IMP infusion time in line with cohort 3.After 60 patients have been recruited to cohort 3, data will be reviewed by the IDMC to evaluate any IRR and make recommendations to the TMG regarding whether to adjust the infusion time further or implement any other measures. If there are no severe IRRs, then the infusion and observation times will remain as per cohort 3 for the remainder of the study.There will be no pause in recruitment whilst the safety analyses are being carried out between cohorts. Progression to the next cohort will not occur until the safety analysis has been reviewed by the IDMC.Infusion and observation timings for each lead-in cohort. IMP investigational medicinal product, IRR infusion-related reaction1Day 4 post-infusion, routine haematology and biochemistry results will also be used to inform this decision2Post-infusion observation period to remain at 60 minIt is planned to randomise subjects between the prophylactic treatment and placebo or the shared placebo group for patients randomised to more than one prophylactic treatment option. This was based on an estimated 6-month rate of confirmed symptomatic SARS-CoV-2 infection of approximately 15% in the placebo group and 10% in each treatment arm; this would correspond to a hazard ratio of 0.648. With a 0.045 significance level . Allowing for a 15% noncompliance, a total of approximately 1500 subjects would be required.The primary outcome measure is symptomatic SARS-CoV-2 infection at 12 weeks (85 ± 7 days) from the date of IMP administration. It is anticipated that there will be a reduction of 75% in symptomatic SARS-CoV-2 infection with sotrovimab treatment compared with the placebo arm. With the estimated symptomatic SARS-CoV-2 infection rate at 12 weeks around 2 to 3% in the placebo arm, the table below is a range of sample sizes using the Fisher’s exact test with a 5% significance level, 90% power and two-sided test to detect a 75% reduction. It is planned to recruit a minimum of 1760 participants.Due to significant uncertainty in the anticipated infection rate, the sample size assumption will be monitored and reviewed regularly by the independent Data Monitoring Committee (IDMC) (details are specified in the IDMC charter) in a blinded manner and sample size re-estimation may be considered under the recommendation of the IDMC.In March 2021, PROTECT-V was awarded UK Urgent Public Health Status as a nationally prioritised COVID-19 platform trial. The study was initially designed for renal patients, and a key eligibility criterion for the niclosamide and ciclesonide arms are that patients are a member of a renal disease patient population . At the time of the study set-up, it was unclear whether sufficient patients could be enrolled in the UK alone, and so a parallel niclosamide arm of the PROTECT-V study was opened in India with the George Institute for Global Health as sponsor for the PROTECT-V protocol in India. The overarching trial eCRF, statistical support and trial committees are provided by the UK PROTECT-V infrastructure and data on patients recruited in India are entered directly into the PROTECT-V study database, with cumulative data from the parallel trial contributing to the overall sample size and primary endpoint events.For the sotrovimab arm, the trial eligibility criteria were broadened to include any patient who had mounted a sub-optimal vaccine response either due to their underlying condition or treatment for the condition, thus opening the trial to patients including, but not limited to, the following disease areas—haematology, oncology, immunology, rheumatology and transplantation. In order to effectively expand recruitment into these patient groups, national leads have been appointed to drive recruitment across all centres for their allocated patient cohorts.https://www.sealedenvelope.com/) accessible via password-protected access. Randomisation is stratified by PROTECT-V disease sub-group, age and site using a stratified block randomisation method.Randomisation is carried out using a web-based randomisation system  a participant has been randomised to but not whether active or placebo drug has been assigned.https://www.sealedenvelope.com/).Eligible participants will be randomised by local investigators using the web-based randomisation system . As additional IMPs are added to the platform, the practicalities of blinding treatment and the need/availability of matched placebo will be evaluated on an individual basis. It may be necessary to restrict the number of IMPs in the platform if blinding is to be maintained. The IDMC will regularly review the event rate in individual placebo arms to ensure they are comparable.Unblinding must only occur in exceptional circumstances when knowledge of the actual treatment is essential for further management of a participant and/or their safety. If the treating clinician deems unblinding to be necessary, the web-based randomisation system can be used by designated local investigators to unblind. The allocation will be sent by email to the treating clinician and the unblinding notification without allocation should be printed and retained within the investigator site file. An email stating that an unblinding has taken place will be automatically sent to the coordination team and CI for oversight purposes. Unless it is necessary for the safety of the participant, the actual allocation must not be disclosed to the participant or other site personnel, either verbally or by any written correspondence.Data will be captured using eCRFs and entered directly into a web-based system either by the site team or directly by patients for the symptom checkers in the niclosamide and ciclesonide arms beyond week 6. Sequential eCRF entry is dictated by the data portal to limit errors in the timeline of the trial procedures. For example, eligibility must be confirmed before the randomisation data can be entered, and the follow-up eCRFs are not available until the randomisation data has been entered. Follow-up visits that have specific date windows are checked to be within the specified window. Forms entered into the database are also tracked by the central data manager to flag any outstanding expected forms and ensure that the trial timeline of data collection is adhered to.UKHSA (formerly PHE): Data received from the UKHSA will be transferred to the secure data hosting server (SDHS), and SARS-CoV-2 infection data received will be cross-checked with the primary endpoint data provided by the sites.SAEs will be reported using the standard trials unit SAE form. Only relevant fields are entered in the trial databaseSARS-CoV-2 antibody samples : results will not be entered directly into the database, but a csv file generated which will be passed directly to the statistician for analysisSARS-CoV-2 antibody samples for the sotrovimab arm—samples are processed in real time at the Clinical Immunology Service laboratories in the University of Birmingham Clinical Immunology Service laboratory using the CE marked Roche Elecsys® Anti-SARS-CoV-2 assay (Product code: 09203079190). Screening results are released to site investigators to allow confirmation of eligibility and randomisation. Subsequent measures will be entered into a csv file and passed directly to the statistician for analysis.Data will also be obtained from the following sources:The study has been designed to minimise patient visits to the hospital during the pandemic. For those participants who withdraw from treatment, but provide consent for ongoing data linkage with UKHSA, data on the occurrence of SARS-CoV-2 infection will be collected  and will be reported enabling an ITT analysis for SARS-CoV-2 infection .Data will be entered at the site into an eCRF which will be anonymised. All trial data in the eCRF must be extracted from and be consistent with the relevant source documents.Confirmation that the trial endpoint form is completedDocumentation of a positive SARS-CoV-2 test result by either PCR or lateral flow test. Source data as follows: UKHSA or photographic evidenceCross check primary endpoint form with a symptom checker to ensure symptoms are reported on bothConfirmation that the event has occurred whilst receiving or having received IMPOne hundred per cent of variables used to define the primary endpoint and safety data will undergo a cleaning process. For the primary endpoint, symptomatic SARS-CoV-2 infection, the following checks are in place:Study participants will provide explicit consent to the use of identifiable data for the purposes of the conduct of the study. Personal identifiable data (PID) will be stored separately from anonymised study data on a secure server hosted within the University of Cambridge School of Clinical Medicine Secure Data Hosting Service. PID will be accessible to the PROTECT-V trial team within the Cambridge Clinical Trials Unit, monitors, auditors and inspectors as required. It is necessary to (1) perform validation of NHS numbers and linkage to routinely collected datasets  and (2) generate datasets with participant details for mail merge creation of questionnaires, and is therefore imperative to the conduct of the study.In view of the pragmatic study design, and aim to minimise study visits, the serum for measurement of antibody titres will only be collected at baseline and the final study visit. The samples will be processed in batch.Where possible, serum, plasma, PBMC, DNA and RNA samples  will be collected at the day 1 infusion of IMP and in those subjects that develop SARS-CoV-2 infection 28 days later. Additionally, saliva samples will be collected at the Cambridge and Birmingham sites. These samples will be shipped immediately for centrally processing at the University of Cambridge or the University of Birmingham and appropriately stored for future analyses including but not confined to B and T cell immunophenotyping, functional B and T cell assays, anti-cytokine assays, evaluation of the role of mucosal immunity and neutrophil function analyses.The following populations will be defined for efficacy and safety analyses for each of the prophylactic interventions.Intent-to-treat population (ITT) is defined as all participants randomised between the prophylactic intervention and placebo, regardless of whether they actually received trial treatment. The treatment group will be analysed as randomised.The modified ITT (mITT) population is defined as all participants randomised who received at least one dose of trial treatment. The treatment group will be analysed as randomised at baseline.The safety population comprises all participants randomised between the prophylactic intervention and the placebo and having received at least one dose of trial treatment. The treatment group will be analysed as treated.The primary outcome measure, symptomatic SARS-CoV-2 infection by either PCR or lateral flow test, will be compared between each prophylactic treatment and the randomised placebo groups in the ITT population using a Cox proportional hazards model, considering adjustment for fixed effects with age, sex, ethnicity, patient population and known high-risk pre-existing conditions.The hazard ratio will be determined and statistical significance will be declared using a 2-sided alpha-level of 0.045 . There is no need to use a multiplicity adjustment for the treatment arms as these are considered independent comparisons. A 95% confidence interval for the hazard ratio from the Cox model will be provided. The estimand properties of the primary and sensitivity analyses of the primary endpoint will be detailed in the statistical analysis plan.For the secondary outcome measure of time-to-confirmed SARS-Cov-2 infection (either by PCR or LFT) in the ITT population, the analysis will use a Cox proportional hazards model as described for the primary outcome measure. The median, 25th and 75th percentile and 95% Cis for time to confirmed SARS-CoV-2 infection (either by PCR or LFT) will be provided. The severity scale of COVID-19 disease will be compared using a proportional odds model for all SARS-CoV-2-infected participants. Length of inpatient stay will be compared using the Fine and Gray approach with discharge alive as an event of interest and hospital death as a competing event for all hospitalised participants. Common COVID-19 complications for all SARS-CoV-2-infected participants in the ITT population will be analysed using the standard chi-square test. The comparisons on secondary outcome measures will be compared according to a pre-specified hierarchal order.α-level of 5%), that is, to test the following hypotheses:H0: there is no treatment difference between sotrovimab and placebo in the proportion of patients who develop symptomatic SARS-CoV-2 infection vs. H1: there is a treatment difference between sotrovimab and placebo in the proportion of patients who develop symptomatic SARS-CoV-2 infection.The primary efficacy analysis of this trial will be a logistic regression analysis for the difference in the distribution of symptomatic SARS-CoV-2 infection at 12 weeks between the sotrovimab group and the placebo group  will be presented. The disease sub-group and age at randomisation will be adjusted for as fixed effects in the analyses.Primary efficacy analyses will be performed according to ITT in participants who have received any IMP. The analyses will be performed when all patients randomised have been in the trial for 12 weeks or up to 4 weeks post the date of the last confirmed positive SARS-CoV-2 result to allow for symptom collection, for those cases that occur between week 8 and week 12. If the statistical significance at a 2-sided 0.05 level is established for the primary efficacy outcome measure, a hierarchical testing procedure will be applied to the key secondary efficacy outcome measures at a 2-sided 0.05 significance level. The order of testing sequence for key secondary outcome measures is (1) confirmed, symptomatic SARS-CoV-2 infection at 16 weeks (113 ± 7 days) from the date of IMP administration; (2) confirmed, symptomatic SARS-CoV-2 infection at 24 weeks (169 ± 7 days) from the date of IMP administration; (3) confirmed, symptomatic SARS-CoV-2 infection at 36 weeks (253 ± 7 days) from the date of IMP administration; and (4) confirmed, symptomatic COVID-19 infection at 48 weeks (337 ± 7 days) from the date of IMP administration. Further detail will be documented in the statistical analysis plan (SAP).SAEs for all treatment arms will be reported using the preferred term MedDRA system according to treatment group. For the niclosamide and ciclesonide arms, adverse events will be collected via the fortnightly symptom checkers that are completed. Data on infusion reactions, AEs up until day 29 and laboratory parameters, graded according to DAIDS categorisation will be presented for the sotrovimab arm. Also for the sotrovimab arm, data on adverse events of special interest (AESIs) will be collected throughout the study period. These are detailed in the trial protocol.The primary outcome measure, symptomatic SARS-CoV-2 infection by either PCR or lateral flow test, will be compared between each prophylactic treatment and the randomised placebo groups in the ITT population using a Cox proportional hazards model, considering adjustment for fixed effects with age, sex, ethnicity, patient population and known high-risk pre-existing conditions.The hazard ratio will be determined and statistical significance will be declared using a 2-sided alpha-level of 0.045 . There is no need to use a multiplicity adjustment for the treatment arms as these are considered independent comparisons. A 95% confidence interval for the hazard ratio from the Cox model will be provided. The estimand properties of the primary and sensitivity analyses of the primary endpoint will be detailed in the statistical analysis plan.For the secondary outcome measure of time-to-confirmed SARS-Cov-2 infection (either by PCR or LFT) in the ITT population, the analysis will use a Cox proportional hazards model as described for the primary outcome measure. The median, 25th and 75th percentile and 95% Cis for time to confirmed SARS-CoV-2 infection (either by PCR or LFT) will be provided. The severity scale of COVID-19 disease will be compared using a proportional odds model for all SARS-CoV-2-infected participants. Length of inpatient stay will be compared using the Fine and Gray approach with discharge alive as an event of interest and hospital death as a competing event for all hospitalised participants. Common COVID-19 complications for all SARS-CoV-2-infected participants in the ITT population will be analysed using the standard chi-square test. The comparisons on secondary outcome measures will be compared according to a pre-specified hierarchal order.α-level of 5%), that is, to test the following hypotheses:H0: there is no treatment difference between sotrovimab and placebo in the proportion of patients who develop symptomatic SARS-CoV-2 infection vs. H1: there is a treatment difference between sotrovimab and placebo in the proportion of patients who develop symptomatic SARS-CoV-2 infection.The primary efficacy analysis of this trial will be a logistic regression analysis for the difference in the distribution of symptomatic SARS-CoV-2 infection at 12 weeks between the sotrovimab group and the placebo group  will be presented. The disease sub-group and age at randomisation will be adjusted for as fixed effects in the analyses.Primary efficacy analyses will be performed according to ITT in participants who have received any IMP. The analyses will be performed when all patients randomised have been in the trial for 12 weeks or up to 4 weeks post the date of the last confirmed positive SARS-CoV-2 result to allow for symptom collection, for those cases that occur between week 8 and week 12. If the statistical significance at a 2-sided 0.05 level is established for the primary efficacy outcome measure, a hierarchical testing procedure will be applied to the key secondary efficacy outcome measures at a 2-sided 0.05 significance level. The order of testing sequence for key secondary outcome measures is (1) confirmed, symptomatic SARS-CoV-2 infection at 16 weeks (113 ± 7 days) from the date of IMP administration; (2) confirmed, symptomatic SARS-CoV-2 infection at 24 weeks (169 ± 7 days) from the date of IMP administration; (3) confirmed, symptomatic SARS-CoV-2 infection at 36 weeks (253 ± 7 days) from the date of IMP administration; and (4) confirmed, symptomatic COVID-19 infection at 48 weeks (337 ± 7 days) from the date of IMP administration. Further detail will be documented in the statistical analysis plan (SAP).SAEs for all treatment arms will be reported using the preferred term MedDRA system according to treatment group. For the niclosamide and ciclesonide arms, adverse events will be collected via the fortnightly symptom checkers that are completed. Data on infusion reactions, AEs up until day 29 and laboratory parameters, graded according to DAIDS categorisation will be presented for the sotrovimab arm. Also for the sotrovimab arm, data on adverse events of special interest (AESIs) will be collected throughout the study period. These are detailed in the trial protocol.If the rate of unacceptable toxicity in the niclosamide or ciclesonide arm is over 20%, that is, the estimated lower limit of a 95% confidence interval is greater than 20%. In general, local intolerance should only be regarded as an unacceptable toxicity if the event fulfils the criteria for a serious adverse event or is severe.If the incidence of moderate/severe adverse events/symptoms is 15% more in the niclosamide or ciclesonide arm with a minimum of 200 participants in each arm at a significance level of 0.05.The study will be reviewed every 2 months by the IDMC for safety, combined primary outcome measure event rate and making a recommendation for performing efficacy analyses. Should there be sufficient evidence of a difference in the primary outcome measure between the niclosamide arm and the matched placebo arm at one planned interim analysis, the IDMC may consider recommending early termination of the study. As a guide to the IDMC, considering the total duration of the study is around 1 year, a maximum of two formal interim analyses, based on the number of primary endpoint events, are to be performed using a Lan-DeMets error-spending approach corresponding to symmetric 2-sided O’Brien-Fleming boundaries. The study will only be stopped earlier if there is sufficient evidence of benefit using the O’Brien-Fleming boundaries, that is, the value of the test statistic crosses the O’Brien-Fleming boundary of the beneficial effect of niclosamide. As a potential pivotal study, it is not planned to stop the study for futility. The study will be stopped early if there are any safety concerns based on the recommendation of the IDMC and the approval from the Trial Steering Committee (TSC). As guidance, the study might be stopped early for safety concernsAn independent Data Monitoring Committee (IDMC) will review the data, by treatment group on the safety of patients in the trial. The IDMC will meet approximately every 2 months until the end of the trial. In addition, during the initial three lead-in cohort period and prior to the final infusion time being established, the IDMC will review severe infusion-related reaction (IRR) events whenever they are observed and have additional meetings as required.There are no plans to stop the trial early for efficacy, and therefore, no interim analyses for efficacy or futility. Efficacy data, by treatment arm, will therefore not be routinely provided. The IDMC can request efficacy data, by treatment group, confidentially from the Trial Steering Committee (TSC) if changes to the protocol are considered, and these data are required by the IDMC in order to reach decisions about the ongoing risk/benefit to patients in the trial. If efficacy data are reviewed, a Haybittle-Peto boundary may be used. Full details will be given in the IDMC charter.Details will be documented in the statistical analysis plan.Details will be documented in the statistical analysis plan.The full protocol is available on the study website and is submitted as supplementary material with this manuscript. Participant-level data and statistical code will be shared with the relevant industry partner.The TMG will meet at least weekly during the initial set-up, and then at least two weekly face to face or by teleconference to oversee the running of the trial thereafter. TMG members will review SAEs which have occurred in the trial. If there are specific safety concerns, these may be raised with the TSC and IDMC. TMG members will include co-investigators, the trial statistician, trial pharmacist, trial coordinator(s) and data manager(s) at the Cambridge Clinical Trials Unit (CCTU).The TSC is responsible for the review of the trial and related activities at regular intervals. The TSC also provides overall supervision for the trial, to ensure that it is conducted in accordance with the protocol and GCP and to provide advice through its independent chairman. The committee will aim to convene at regular intervals to review the data and discuss the recommendations from the IDMC. The details of the TSC are set out in the PROTECT-V Trial Steering Committee Charter.The Independent Data Monitoring Committee (IDMC) comprises an unblinded independent group, as defined in the PROTECT-V Data Monitoring Committee Charter document, which defines the role of the IDMC. The IDMC is responsible for the review of all safety data and meets regularly whilst the trial is ongoing, from opening to recruitment until the final visit of the last participant.All adverse events (AEs) are recorded from the point of informed consent regardless of whether a participant has yet received a medicinal product. Individual adverse events are evaluated by the local site investigator for the evaluation of their seriousness and any relationship between the investigational medicinal product(s) and/or concomitant therapy and the adverse event . All expected adverse reactions (ARs) are listed in the latest MHRA-approved version of the specified reference safety information (RSI), and this must be used when making a determination as to the expectedness of the adverse reaction. If the adverse reaction meets the criteria for seriousness, this must be reported to the sponsor within 24 h of the investigator becoming aware of the event.All AEs and ARs, which are new or significantly worse since commencing the trial, should be recorded on the symptom checker questionnaire in the eCRF and sent to the trial coordination centre within 1 month of the investigator becoming aware of the event.All AEs (serious and non-serious) are reported until day 29 of the study as these are most likely to be potentially related to the study drug. Data regarding any AE reported prior to day 29 will be gathered until the resolution of the AE. The population that will take part in this study are multi-morbid and suffer from numerous fluctuating chronic symptoms. Recording all symptoms as possible AEs beyond day 29 would likely lead to an inability to identify any meaningful trends in the AE analysis.Hypersensitivity reactions (including skin reactions and bronchospasm) at any time after IMP infusionInfusion-related reactions within 24 h after IMP infusion Beyond day 29, all SAEs and AESIs (whether serious or non-serious) will continue to be gathered until the final study visit on week 48 or day 337. AESIs have been defined based on potential risks associated with the mAb class of therapeutics administered via intravenous infusion and the data available from the COMET-ICE study, and include the following:Antibody-dependent enhancement (ADE) of disease in those who reach the primary end-point will be assessedNo formal audits on behalf of the sponsor are planned, but should a monitoring visit or audit be requested, investigators must make the trial documentation and source data available to the auditor or sponsor’s representative.Protocol amendments must be reviewed and agreement received from the sponsor for all proposed amendments prior to submission to the REC and/or MHRA. The only circumstance in which an amendment may be initiated prior to REC and/or MHRA approval is where the change is necessary to eliminate apparent, immediate risks to the participants (urgent safety measures). In this case, the accrual of new participants will be halted until the REC and/or MHRA approval has been obtained.All correspondence with the REC will be retained in the trial master file/investigator site file. A complete list of all protocol amendments will be included in the final clinical study report for each arm of the platform.On completion of each intervention of the trial, the data will be analysed and tabulated, and an intervention-specific final trial report prepared. The results of this trial may be initially disseminated via a press release and then subsequently published and presented at scientific meetings. The results will be summarised in an easily accessible format for patients.These arms are event-driven, and these arms will close when the required number of symptomatic SARS-CoV-2 infections have been observed. At common close-out, all participants still receiving IMP will be instructed to stop, and a final safety assessment will be conducted 4–6 weeks later. Analyses will be conducted once all study visits are complete.The analysis of the primary outcome measure will be performed when all randomised patients have completed week 12 or up to 4 weeks post the date of the last confirmed positive SARS-CoV-2 result to allow for symptom collection, for those cases that occur between week 8 and week 12. The efficacy on key secondary outcome measure analyses will be performed when there are a sufficient number of patients that have completed week 16, week 24, week 36 and week 48 (or up to 4 weeks post the date of last confirmed positive SARS-CoV-2 result), using a hierarchical testing procedure. The details will be documented in the statistical analysis plan.Despite the development of vaccination against SARS-CoV-2 infection transforming the lives of the majority of the population in the pandemic, sub-optimal vaccine responses and vulnerability to SARS-CoV-2 infection remain a major issue for a broad range of immunocompromised individuals. There is an ongoing unmet need for pre-exposure prophylactic strategies for these patients to reduce hospitalisation and death.https://www.ecdc.europa.eu/en/covid-19/high-risk-groups)This study initially commenced in renal patients only, as in the first wave of infection in April 2020, individuals requiring renal replacement therapy suffered particularly poor outcomes. However, with the vaccine roll out, and sub-optimal vaccine responses becoming apparent across a range of conditions, the patient population eligibility criteria were broadened to include not just renal patients, but also immunology, haematology oncology, rheumatology and organ transplant recipients—any individual with a sub-optimal vaccine response . Approvals have been in place to add ciclesonide to the platform from May 2021, but it has not been possible to secure a drug supply for the whole trial. The sotrovimab arm opened in August 2022 . As of 31 October 2022, 68 patients have been randomised. Recruitment is expected to complete by Q3 2023. The study investigators are actively scanning emerging data on future potential agents to be trialled in the platform.


In proof-of-concept experiments, gas sensing was demonstrated by monitoring the real-time spectral response of the phase-shifted grating to glycerol vapor flowing through its sealed cavity. We believe that the phase-shifted grating-based terahertz resonant gas sensor can open new opportunities in the monitoring of gaseous analytes.The development of low-cost sensing devices with high compactness, flexibility, and robustness is of significance for practical applications of optical gas sensing. In this work, we propose a waveguide-based resonant gas sensor operating in the terahertz frequency band. It features micro-encapsulated two-wire plasmonic waveguides and a phase-shifted waveguide Bragg grating (WBG). The modular semi-sealed structure ensures the controllable and efficient interaction between terahertz radiation and gaseous analytes of small quantities. WBG built by superimposing periodical features on one wire shows high reflection and a low transmission coefficient within the grating stopband. Phase-shifted grating is developed by inserting a Fabry–Perot cavity in the form of a straight waveguide section inside the uniform gratings. Its spectral response is optimized for sensing by tailoring the cavity length and the number of grating periods. Gas sensor operating around 140 GHz, featuring a sensitivity of 144 GHz/RIU to the variation in the gas refractive index, with resolution of 7 × 10 An increasing demand for the monitoring of air quality has promoted the development of high-performance gas sensing devices operating on various chemical and physical principles such as optical, calorimetric, chromatographic, acoustic, as well as electrochemical ,2,3,4,5.It is, therefore, important to investigate the integrated resonant structures, particularly in the THz band, capable of reducing the size of sensor systems, compared to the free-space systems, without sacrificing sensitivity. One way to achieve this is by using hollow core waveguides filled with gaseous analytes to perform broadband molecular vibration absorption spectroscopy. Such waveguides operate using various guidance principles  and offer high field–analyte overlap ,20,21,22Alternatively, a THz waveguide-based sensor of relatively short length can be designed using various resonant elements in their structures  and two−5 RIU is estimated from the 10 MHz resolution of our spectrometer. Finally, using a continuous-wave (CW) THz spectroscopy system, we experimentally demonstrate the real-time detection of glycerol vapors from an electronic cigarette as an analyte. Namely, when replacing dry air with glycerol vapor in the cavity of a phase-shifted grating module, a shift in the sensor resonant frequency (transmission peak) of ~50 MHz reveals an RI difference of ~3.5 × 10−4 RIU.In this work, we propose a real-time resonant THz gas sensor based on phase-shifted waveguide Bragg grating (WBG). At the core of this device is a broadband two-wire plasmonic waveguide formed by metalizing polymer cylinders that are encapsulated within a closed polymer cage. The gaseous analyte flows inside the cage and in the air gap of a two-wire plasmonic waveguide. WBG is formed by a periodic conical pattern imprinted onto one of the cylinders of a two-wire waveguide and is optimized to feature a spectrally broad stopband. Finally, the phase-shifted grating is formed by inserting a Fabry–Perot cavity in the form of a uniform waveguide section in the middle of WBG. The cavity length and the number of grating periods should be chosen to support a single spectrally narrow transmission peak within a broad WBG stopband. The THz spectral response of phase-shifted gratings is then studied for different lengths of a cavity and different refractive indices of gaseous analyte that are filling the semi-sealed cavity. By tracking the position of the transmission peak, our sensor sensitivity near 0.14 THz is found to be ~14.5 GHz/mm for changes in the cavity length, and ~144 GHz/RIU for changes in the analyte RI . A theoretical sensing resolution of ~7 × 10Different from the most reported optical gas sensors whose delicate structures are realized using costly infrastructures , the proposed gas sensor on a centimeter-scale THz waveguide can be rapidly manufactured using the emerging 3D printing technology with precision and robustness. Owing to the ubiquitous availability of hardware as well as the compact modular design that integrates various crucial elements, we believe that this sensor confronts a lower threshold for entering into production and less challenging engineering problems for operation in practical applications.Unlike the conventional two-wire metallic waveguides ,33, the Additionally, the integration of the plasmonic terahertz waveguide and semi-sealed cavity promises the controllable interaction between the supported THz surface plasmon polariton wave and the gaseous analyte flowing through. However, as refractive indices  for most gases are close to one, it is challenging to detect the difference between them, thus necessitating the use of long interaction distances (long gas cells) to accumulate sufficient phase differential between different analytes. In contrast, by using resonant devices like a Fabry–Perot cavity , we can fold the optical path to realize much smaller devices.Experimentally, we find that the two-wire WBGs featuring a sequence of end-to-end connected truncated cones on one wire was an optimal design that can be printed reliably with high precision and without supports, using a tabletop stereolithography 3D printer  with a thickness of tens of micrometers. In experiments, the addition of such a THz transparent material led to negligible changes in the transmission spectra of this module. To couple with the free-space THz beam for characterization, this module was placed between two 3 cm long featureless two-wire waveguide sections which support broadband operation. The assembled waveguide component was then fitted with conical horn antenna and placed inside the THz spectroscopy setup  [centerυ, similarly to what is shown in The numerical simulations of the independent phase-shifted grating module predict that the spectral position of a transmission peak is linear with the gaseous analyte RI with the corresponding sensitivity of 144 GHz/RIU see a. Given 0−4 RIU) . In expe−4 compared to that of dry air. Highly consistent experimental results were obtained in each measurement of this sensor. Owing to its compact integrated structure and insensitivity to the environment change, this two-wire waveguide-based sensor can find its practical applications in gas sensing by simply replacing the external infrastructure for gas delivery  bandwidth in the middle of a WBG stopband was realized by using a ~2.75 mm long cavity flanked on both sides by two seven-period WBGs with a Q-factor of ~39. The theoretical sensitivity of the peak spectral position to changes in the RI of gaseous analytes inside the 2.5 cm long phase-shifted WBG is estimated to be 144 GHz/RIU. The response of our sensor to glycerol vapor flow at low concentrations was then verified in a proof-of-concept time-resolved experiment, which reliably detected the displacement of dry air by glycerol vapor with a resultant RI change of ~3.5 × 10For future work, we note that higher sensitivity sensor designs are readily achievable by moving the sensor operational frequency to higher frequencies , while a


Experimental and numerical analyses of eight in-plane restrained slabs (1425 mm (length) × 475 mm (width) × 150 mm (thickness)) reinforced with glass fiber-reinforced polymer (GFRP) bars are reported in this paper. The test slabs were installed into a rig, that provided 855 kN/mm in-plane stiffness and rotational stiffness. The effective depths of the reinforcement in the slabs varied from 75 mm to 150 mm, and the amount of reinforcement changed from 0 to 1.2% with 8, 12, and 16 mm bar diameters. A comparison of the service and ultimate limit state behavior of the tested one-way spanning slabs shows that a different design approach is necessary for GFRP-reinforced in-plane restrained slabs that demonstrate compressive membrane action behavior. Design codes based on yield line theory, which considers simply supported and rotationally restrained slabs, are not sufficient to predict the ultimate limit state behavior of restrained GFRP-reinforced slabs. Tests reported a higher failure load for GFRP-reinforced slabs by a factor of 2, which was further validated by numerical models. The experimental investigation was validated by a numerical analysis, and the acceptability of the model was further confirmed by consistent results obtained by analyzing in-plane restrained slab data from the literature. Bridge deck slabs exposed to extreme environmental conditions deteriorate due to steel corrosion. Extensive corrosion caused by de-icing salts and corrosive environments have raised concerns about the service life of steel-reinforced deck slabs and other steel-reinforced structures . ConsideReplacing steel with corrosion-resistant reinforcement such as stainless steel or fiber-reinforced polymer (FRP) bars in concrete structures can be beneficial. Strong fibers, durability, and lightweight are the attractive features of FRP bars. The initial cost, brittleness, low stiffness of some fibers, and inflexibility once produced were found to be the major disadvantages . AlthougThe application of FRP reinforcement in concrete structures has been studied extensively. In the early 1990s, studies ,11,12 foIt can reduce the amount of reinforcement used in deck slabs ,30,31,37The designer can focus on the serviceability limit state requirements as the ultimate limit state is governed by CMA-induced concrete crushing failure. Therefore, for GFRP-reinforced slabs, explicit design for failure criteria is not necessary.When a slab is restrained for in-plane expansion, the compressive membrane action phenomenon influences the serviceability and ultimate limit state behavior of the concrete slab. Compressive membrane action (CMA) in short-span-reinforced concrete slabs has been extensively discussed in the literature ,31,32,33Although the benefits of CMA have been discussed for over 100 years, designers still have a limited understanding of empirical design methods as they are insufficiently explored in major design codes ,38,39,40The study presented in this paper experimentally and numerically investigate the behavior of in-plane restrained GFRP-reinforced slabs and provides a basis for consideration of CMA in design approach of FRP-reinforced flexural elements.The test specimens were compared for their serviceability and ultimate limit state behavior changing various reinforcement parameters. The test slabs used one type of concrete mix design to keep the concrete strength parameter unchanged. Position of the reinforcement, namely either conventional two layers or single mid depth reinforcement; amount of reinforcement, spacing between reinforcement bars are the main reinforcement parameters considered.The tests programme observed serviceability and ultimate limit state behavior of GFRP-reinforced in-plane restrained slabs. Experimentally tested slabs were modelled using commercially available nonlinear finite element analysis tool to further evaluate the behavior of in-plane restrained slabs. It can be seen from the test results that the nonlinear finite element analysis tool can predict the ultimate failure load of the test slabs and a further evaluation of the model using the data obtained from the literature validate the usability of the model for in-plane restrained slabs.2. The concrete mix was consistent for all test slabs and typical of that used in bridge decks. The mix design used in this study was based on the concrete mix used in previous research [ck was estimated for nonlinear finite element analysis using BS EN 1992 [ck,cube .Eight in-plane restrained full scale slabs (1425 mm (length) × 475 mm (width) × 150 mm (thickness)) reinforced with glass-fiber-reinforced-polymer (GFRP) bars were constructed using high-strength concrete and tested for service and ultimate load state behavior. The test slabs were constructed using a concrete mix with a target cube compressive strength of 65 N/mmresearch . Concret EN 1992 , which c2 and 67,400 N/mm2, respectively, for the GFRP bars.Commercially available GFRP bars were used for the tests. The bars were tested for tensile strength and modulus of elasticity using the test methods suggested by ASTM D3916  with theThe test variables were reinforcement percentage, spacing between bars, effective depth, and bar diameter, as detailed in cf′—compressive strength of the concrete, fE—modulus of elasticity of the GFRP, cuε—ultimate strain in the concrete, fuf—design tensile strength of the FRP, and β1—0.65.Reinforcement amounts of 0, 0.15, 0.60, and 1.2% were selected to investigate the influence of reinforcement percentage in GFRP-reinforced restrained slabs. A lower level of 0.15% was chosen according to the lower limit allowed for a slab by BS EN 1992 . It shouβ1—0.70  used to measure deflection is shown in Load was applied through a 25 mm × 475 mm plate attached to a stiff beam and bedded on a soft board that prevented any stress concentration. The applied load represented part of an axle load and gives a more onerous representation of the wheel load on a one-way spanning slab as the slab strip would have only a portion of the whole wheel load acting on it. A similar loading method employed to study the flexural behavior of the slabs under flexural conditions can be found in the literature ,46.Two service loads equivalent to one-third of the predicted ultimate flexural load were applied initially. The service loads were held for 5 min and unloaded to allow for maximum recovery. Then, the slabs were loaded incrementally by 5 kN steps until failure and data were recorded for each 5 kN increment. The deflection of the slab, in-plane expansion of the frame and strain on the GFRP bars were recorded at each increment of the load.GFRP bars demonstrate a low modulus of elasticity and rupture failure. Therefore, the serviceability behavior of the slabs such as deflection, crack width expansion, and reinforcement stress at service load level and failure mode are discussed in this paper with great interest. The peak load at failure and failure mode are also compared.Load versus mid-span deflection is shown in Once a crack is formed in the tension zone, the behavior of the concrete slabs was influenced either by the position and the stiffness of the reinforcement or the stiffness of the membrane arch due to the in-plane restraints. All the double-reinforced slabs, independent of the amount of reinforcement, showed similar load versus deflection behavior up to 200 kN. The deflection values of the test slabs are compared in The higher stiffness and lower deflection of the unreinforced slab compared to the single mid-depth-reinforced slabs can be attributed in part to the higher concrete compressive strength compared to other slabs. All the test slabs were tested using the same frame with identical in-plane stiffness. Therefore, lower deflection in two-layer-reinforced slabs can be attributed to the reinforcement position, which provided better control of the crack-width expansion as noticed in the restrained slabs. The tests demonstrate that the conventional two layers of reinforcement is necessary to satisfy the deflection limit criteria. Independent of the amount of reinforcement, all the test slabs with two layers of reinforcement satisfy the deflection limits.Two types of crack pattern were observed during the tests on GFRP-reinforced slabs. Two-layer-reinforced concrete slabs showed one type of crack pattern and 0.6% single mid-depth-reinforced and unreinforced slabs showed another type of crack pattern. Only three cracks were noticed in unreinforced and single mid-depth-reinforced slabs a,b. The In addition to the primary crack on the soffit, a few additional cracks were noticed at the soffit parallel to the first crack at higher load levels in two-layer-reinforced c,d slabsDesign codes such as Eurocode restrict the crack widths to less than 0.3 mm for steel-reinforced concrete structures. However, considering the corrosion-resistant nature of GFRP bars, the Canadian code  recommenOur observations of the crack patterns and crack width expansion suggest that the conventional two-layer reinforcement method can control the rapid development of the depth and width  of the cCrack width exceeded 0.5 mm for the 0.15% GFRP-reinforced slab with the conventional two layers at 150 kN. The results show that two layers of 0.6% GFRP reinforcement is required to meet the recommended service behavior in concrete slabs. Maximum crack widths for 0.6% two-layer-reinforced slabs were below 0.33 mm at 150 kN, which was just above the allowable crack width for steel-reinforced structures and well within the allowable 0.5 mm crack width for FRP-reinforced structures.2 for GFRP bars  demonstrate stress below 95.48 N/mm2. The stress on GFRP bars is influenced by the crack width, as is discussed in the literature [Due to the creep rupture failure of FRP materials, the service load level stress on GFRP bars is limited to 20% of the design tensile stress, as given in Table 7.4.1 of ACI 440.1R [The higher reinforcement stress in the 0.15% GFRP-reinforced slab and 0.6% single mid-depth-reinforced slab (G-0.6%-12 mm-125-M) can be attributed to the lower amount of reinforcement in 0.15% GFRP-reinforced slabs and the reduction in the availability of depth for flexural capacity in slab G-0.6%-12 mm-125-M due to mid-depth reinforcement.The test slabs demonstrated good strength that was in excess of the maximum EC1  service A commercially available DIsplacement ANAlyser (DIANA)  finite eThe total strain fixed crack model was adopted for numerical analysis. Linear tensile stiffening was assumed for the post-peak tensile behavior. The Thorenfeldt  compress2, and the non-linear plastic property was 682 N/mm2 of yield/rupture stress. An ideal plastic condition was considered, although FRP is brittle in nature. This was due to the limited availability of brittle models in the analysis code. However, the slab tests showed that the reinforcement stress was within the maximum rupture stress due to the influence of CMA. Therefore, the plastic characteristic of the reinforcement material considered has a negligible influence on the behavior.FRP reinforcement was modelled with elastic and Von Mises plastic material models. A fully bonded criterion was chosen for the bond slip behavior in the slabs. The linear elastic property of the steel reinforcement was its modulus of elasticity of 67,400 N/mmSaatci and Vecchio  recommenIn this analysis, a regular Newton—Raphson method was used for the iteration. The stiffness matrix of the system is calculated at the end of each iteration step. This could reduce the number of iterations required to reach convergence. However, as this method updates the stiffness matrix for each step, this would require more time to analyze.Among the available four convergence norms, including force norm, displacement norm, energy norm, and residual norm, this analysis used energy norm to determine the convergence. A convergence tolerance ratio of 0.001 was selected based on a few preliminary analyses performed with nonlinear models. It has been found that the selected tolerance ratio provides acceptable accuracy, and thus it was used for the nonlinear investigation carried out on the test slabs investigated in this paper.T) and estimated failure load (PFEM) using NLFEA shows good agreement between the two.In the tested slab system, the slabs were clamped into a steel frame . The fraChristiansen  compared2 and 100 N/mm2. Two different stiffness values were used, and two different reinforcement positions were investigated.Lahlouh and Waldron  investigTaylor and Mullin  tested sT) and NLFEA predictions (PFEA) show a good correlation. A comparison of the test results with the NLFEA predictions for the slabs tested by the authors is shown in It can be seen from Compressive membrane action in in-plane restrained slabs has been under investigation for a considerable time. However, in-depth studies on the subject are limited only to steel-reinforced slabs. Understanding compressive membrane action in reinforced concrete slabs can benefit the construction of flexural members by reducing the amount of reinforcement , replaciThe experimental investigation carried out on seven in-plane restrained GFRP-reinforced concrete slabs and one unreinforced slab shows that in-plane restrained slabs demonstrate far more strength compared to the required wheel load of 150 kN, including unreinforced slabs, and the failure load was 80–100% higher than the flexural strengths predicted by design guidelines . The incA comparison of the deflection, crack width expansion, and stress of GFRP bars indicated that GFRP reinforcement in restrained slabs is required to control crack width, deflection, and reinforcement stress in the service limit state. The conventional two layers of reinforcement show acceptable deflection limits compared to single-mid-depth-reinforced slabs. Although a single mid-depth reinforcement was demonstrated to be sufficient for steel-reinforced in-plane restrained slabs, the same cannot be extended to GFRP-reinforced slabs due to the lower modulus of elasticity of GFRP bars. Test slabs reinforced with two layers of 0.6% GFRP reinforcement or higher satisfy both the service and ultimate limit state requirements. A 0.6% GFRP bar is a direct replacement for steel with GFRP bars being on an equal volume basis as recommended by the NI specifications  and CD 3NLFEA carried out on GFRP-reinforced concrete slabs demonstrates that the proposed model satisfactorily predicts the behavior of in-plane restrained GFRP-reinforced concrete slabs. The comparison shown in (1)As has been seen in steel-reinforced concrete in-plane restrained slabs, GFRP-reinforced in-plane restrained slabs also demonstrate the influence of compressive membrane action at the service and ultimate limit state. The strength capacities shown by in-plane restrained GFRP-reinforced and unreinforced slabs above the flexural strengths predicted by design codes. All the test slabs show strength far more than the required wheel load of 150 kN including unreinforced slab. The failure load was 80–100% higher than the flexural strengths predicted by Eurocode and ACI 440.1R. The increased failure load of restrained slabs and the strength of unreinforced slab can be attributed to the compressive membrane action which is not considered in many design codes to determine strength of in-plane restrained reinforced concrete slabs.(2)The unreinforced slab was tested and compared to demonstrate the real strength of in-plane restrained slabs. The comparison between unreinforced restrained slab and GFRP-reinforced restrained slabs shows that the strength can almost exclusively be achieved through arching action. This shows the influence of compressive membrane action in restrained slabs and the necessity to adopt arching action for consideration while designing in-plane restrained GFRP-reinforced concrete slabs.(3)GFRP-reinforced in-plane restrained slabs that satisfy the conditions for compressive membrane action as described in CD 360 , accepta(4)Although the unreinforced slab, the slabs reinforced with a single mid depth reinforcement and two layer 0.15% GFRP reinforcement show strength excess of a wheel load, they fail to satisfy serviceability requirements at maximum wheel load of 150kN. These deficits to satisfy serviceability criteria shall be attributed to the lower amount of reinforcement and the position of reinforcement.(5)NLFEA carried out on tested slabs and numerical analysis of data obtained from the literature clearly indicate the ability of nonlinear finite element models to predict the behavior of restrained slabs and the influence of compressive membrane action. Therefore, it is appropriate to adopt necessary modifications in design codes to incorporate the benefits of compressive membrane action that can significantly benefit GFRP/FRP-reinforced in-plane restrained slabs.The following conclusions can be drawn at the end of the study:The study reported in this paper evaluated the behavior of GFRP-reinforced in-plane restrained slabs. This investigated the influence of the reinforcement percentage, reinforcement spacing and reinforcement position. However, it is important to study the influence of concrete strength on GFRP-reinforced in-plane restrained slabs. It is also important to analyze the behavior of in-plane restrained slabs reinforced with more than balanced amount of reinforcement and under cyclic loading conditions.


Over the past decade, the use of deep learning has been widely increasing in the medical image diagnosis field. Deep learning-based methods’ (DLMs) performance strongly relies on training data. Therefore, researchers often focus on collecting as much data as possible from different medical facilities or developing approaches to avoid the impact of inter-category imbalance (ICI), which means a difference in data quantity among categories. However, due to the ICI within each medical facility, medical data are often isolated and acquired in different settings among medical facilities, known as the issue of intra-source imbalance (ISI) characteristic. This imbalance also impacts the performance of DLMs but receives negligible attention. In this study, we study the impact of the ISI on DLMs by comparison of the version of a deep learning model that was trained separately by an intra-source imbalanced chest X-ray (CXR) dataset and an intra-source balanced CXR dataset for COVID-19 diagnosis. The finding is that using the intra-source imbalanced dataset causes a serious training bias, although the dataset has a good inter-category balance. In contrast, the deep learning model performed a reliable diagnosis when trained on the intra-source balanced dataset. Therefore, our study reports clear evidence that the intra-source balance is vital for training data to minimize the risk of poor performance of DLMs. The polymerase chain reaction (PCR) test is the gold standard2 for detecting SARS-CoV-2 nowadays. Nevertheless, PCR testing is time-consuming and laborious, and it is also suffering from the high cost3.The severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) causes the Coronavirus disease 2019 (COVID-19) that has been widely spread worldwide and continues to have a devastating effect on the health and life of the global population4. The CXR imaging is often part of the standard procedure for patients with respiratory complaints, and it is reported that some patients showed abnormalities in the CXR images before they eventually test positive for COVID-19 with the PCR test4. Moreover, all the rapid triaging, availability, accessibility, and portability of CXR imaging indicated that it could be a preliminary tool for COVID-19 screening. Nonetheless, one of the biggest bottlenecks of CXR screening is the need for experts to diagnose from the CXR images because the radiological signatures can be subtle.As one of the essential complements to PCR testing, chest X-ray (CXR) imaging has also demonstrated its effectiveness in current diagnosis5 and they can aid image diagnosis in the lung areas that is not easy even for the experts6. The success made by DLMs encouraged researchers to develop deep learning-based computer-aided diagnostic (CAD) systems that can aid radiologists in screening COVID-19 more rapidly and accurately11. Brunese et al.7 applied VGG-16 model for COVID-19 detection from CXR images. Hemdan et al.8 proposed an original COVIDX-Net framework to assist radiologists to automatically diagnose COVID-19 in CXR images. Kundu et al.9 proposed an ET-NET for a more sensitive computer tomography scan based COVID-19 detection. Saha et al.10 proposed a GraphCovidNet to deal with classification of COVID-19 or any other kind of pneumonia patients from healthy people in screening. Wang et al.11 also proposed the new architecture of deep learning model named COVID-Net for COVID-19 detection in CXR images. In these previous studies, the deep learning models could achieve high performance on COVID-19 detection.The deep learning-based methods (DLMs) can actually enhance the diagnosis performance by radiologists12. The cause is that deep learning models lack transparency and explainability; it is difficult to know and understand how the model made a prediction, and the inner workings remain opaque to the outside observer13. Without a sufficient understanding of the machine-made prediction, it becomes very complicated to detect errors in models’ performance13, i.e., training bias caused by mislabeled training data, especially for medical applications. Therefore, the reliability of deep learning models remains a concern.Although the deep learning models can achieve high performance on COVID-19 detection, the lack of accepted theoretical explanation remains the fundamental problem of deep learning, i.e., the black-box problem14 proposed a region-of-interest (ROI) hide-and-seek protocol. As shown in Fig. 15 was utilized to visualize which parts of the CXR images were focused on by the deep learning models. The experiment results showed that the deep learning models even could achieve high performance using the lungs-removed images, and the focused locations were outside the lung regions when deep learning models made a COVID-19 prediction. Results in this study14 indicated the deep learning models are unreliable in terms of medical findings because the image features contributing to COVID-19 classification exist outside the lung regions, which is unexpected for a lung-based illness14.For assessing the reliability of deep learning models used for COVID-19 detection in CXR images, Sadre et al.14 mentioned that the unreliability of DLMs might be explained via data characteristics, because the previous studies collected as much data as possible from different medical facilities to develop DLMs for the urgent pandemic. The inter-category imbalance (ICI), i.e., the difference in data quantity among categories, belongs among such data characteristics, and its impact on DLMs has attracted much attention from researchers17. At the same time, there are few investigations for intra-source imbalance (ISI), which means the ICI within the data collected from each medical facility. Therefore, to demonstrate the unreliable performance shown in the previous study14 is related to the ISI, we organized two different COVID-19 datasets and analyzed how the ISI affects DLMs’ performance. The both datasets consist of positive and negative categories, and they are well-balanced between the two categories. The data sources differ between the two datasets (see Table 19. In another dataset (BIMCV), positive and negative CXR images were collected from a single medical facility. The ROI hide-and-seek protocol was implemented on the two datasets to investigate the effect of the ISI on the deep learning models. Then, to evaluate the reliability of the deep learning models trained by each dataset, we made a cross-dataset test, which refers to training a deep learning model on one dataset and testing it on another dataset. Finally, we analyzed the relationship between the unreliability and the ISI according to the experimental results.The study14. Then, we introduce the materials and methods for clarifying the relationship between the unreliability and the ISI. Finally, we summarized and analyzed the experimental results.The outline of this paper is as follows. Firstly, we discuss the unreliability of deep learning models in terms of medical findings, as shown in the previous study20, and the intra-source balanced dataset is BIMCV dataset22. As shown in Table 21 only provided positive images, and RSNA dataset23 only provided negative images for the Qata-COV19 dataset. The two datasets are both well balanced between positive and negative to avoid the influence of ICI. Since Qata-COV19 contains positive images not only from BIMCV but also from other medical facilities, the two dataset have different sizes. Examples of positive and negative images in each dataset are shown in Fig. In this study, we used two CXR datasets collected from various public COVID-19 databases to investigate how the ISI of training data impacts the deep learning models for the COVID-19 diagnosis. The intra-source imbalanced dataset is Qata-COV19 datasetIn our study, the two datasets were used to clarify the influence of the ISI on the reliability of deep learning models. All the images were resized to mentclass2pt{minim14 on the Qata-COV19 dataset and the BIMCV dataset and trained and tested the VGG-16 model33 on the original datasets and the modified datasets separately.As in Fig. 14 to generate datasets. In this step, we used a pre-trained U-Net model14 to segment the lung regions from the original images .To evaluate the performance of the deep learning models, we utilized a receiver operating characteristics (ROC) curve14. These results confirm the high risk of obtaining an unreliable deep learning model. As shown in Fig. As in Fig. As shown in Fig. 37, which uses different portions of the data to train and test a model on different iterations, in the comparison experiments and the cross-dataset test. Cross-validation is a statistical technique for testing the performance of deep learning models that can help to avoid selecting bias.To demonstrate the statistical significance of the experiments, we utilized cross-validation38 of the ROC curves by maximizing sensitivity (True Positive Rate) plus specificity (True Negative Rate). The model trained by the original images and the lungs-boxed-out images from Qata-COV19 dataset both achieved more than 0.99 accuracy on the cut-off points. On the other hand, the model trained by the original images and the lungs-boxed-out images from BIMCV dataset achieved 0.68 and 0.55 accuracy on the cut-off points, respectively.To demonstrate the effect of lung regions on the deep learning performance, we ran a 5-folder cross-validation to compare the impact of lung regions when using Qata-COV19 dataset and BIMCV dataset. In the cross-validation, original images and lungs-boxed-out images were used to train and test a VGG-16 model separately. We compared the mean cross-validated ROC curves and 95% confidence intervals. As shown in Fig. We also ran a 5-folder cross-validation for the cross-dataset test by using the original images from BIMCV and Qata-COV19 datasets. Based on the results of the cross-validation, the ROC curves and the 95% confidence intervals are given in Fig. 39 method to visualize the basis of the predictions made by the VGG-16 models in the cross-dataset test. The LIME method can generate a readily interpretable model which is locally close to the deep learning model and highlight areas inside input images that contribute to predictions. We selected top-5 areas which contribute the most in the LIME results as the explanations for predictions.To provide intuitive explanations for the unreliable performance of the model trained on the Qata-COV19 dataset, we utilized Local Interpretable Model-agnostic Explanations (LIME)Figure 14.The VGG-16 model performed well even when lung regions were hidden when using the Qata-COV19 dataset. This result shows the same unreliable performance as shown in the previous studyThe performance degraded when lung regions were hidden from the CXR images when using the BIMCV dataset. In particular, the ROC curve suggested nearly no capacity for classification when lung regions were boxed out. It demonstrated that the classification of CXR images in the BIMCV dataset relies on the features representing COVID-19 characteristics in lung regions, and the deep learning models are more reliable when using intra-source balanced datasets.The model trained by the Qata-COV19 dataset showed nearly no capacity to classify the CXR images in the BIMCV dataset because the AUC value was about 0.5. Moreover, according to the sensitivity and specificity, all images from BIMCV were classified into the COVID-19 positive class. It is suggested that the model learned the features representing data characteristics of BIMCV from the positive images in the training step, so that the negative images from the BIMCV dataset were also classified into positive class in the test step. It revealed that when using intra-source imbalanced datasets, the prediction bases are the features representing each data source characteristics, but not the features representing COVID-19 characteristics, so the ISI can lead to an unreliable performance of deep learning models. Especially, as shown in the cross-dataset test, the model trained by intra-source imbalanced datasets can be totally unable to make a diagnosis for other datasets.The model trained by the BIMCV dataset achieved a relatively high performance when testing on the Qata-COV19 dataset, which indicated it had better generalizability.Many previous studies19 used the Qata-COV19 dataset to train and test deep learning models and obtained high performance on the test subset, but few of them discussed about the reliability and generalizability. Our study revealed a risk of training bias when using such an intra-source imbalanced dataset, so researchers should raise their concerns about the intra-source balance when collecting training data to minimize the risk of unreliability.Our study reveals that the ISI of training data can lead to an unreliable performance of deep learning models. The analysis of the comparative experiment and the cross-dataset test are as follows:We report that the intra-source imbalance of training data leads to the unreliability of deep learning methods by re-implementing the ROI hide-and-seek protocol on two differently collected CXR datasets. Using a cross-dataset test, we show that the model trained by intra-source imbalanced datasets might classify images based on the features characterizing data sources; hence, it lacks the capability to diagnose other datasets. As emphasized in the introduction, for the urgent COVID-19 pandemic, many previous studies collected as much data as possible from different medical facilities to train deep networks, but without enough validation. They might lack clinical applicability because of the intra-source imbalance of the training data. Our study reveals the risk of unreliability when using intra-source imbalanced datasets in deep learning methods, not only for COVID-19 classification but also for other medical applications. Therefore, when developing deep learning methods, we should ensure the intra-source balance of the datasets before they are applied to train deep learning models.


To report the technique and outcome of ultrasound-guided percutaneous access to the superior mesenteric vein (SMV) for balloon-assisted portal vein recanalization–transjugular intrahepatic portosystemic shunt (PVR-TIPS) in a patient with chronic portal venous and splenic vein occlusion.A 51-year-old, non-cirrhotic patient with severe portal hypertension was admitted for PVR-TIPS. Neither splenic nor hepatic access was feasible due to chronic portal and splenic vein occlusion. Percutaneous ultrasound-guided direct puncture of the SMV was performed to obtain access for balloon-assisted PVR-TIPS. The transmesenteric approach in combination with a balloon puncture technique for PVR-TIPS was successful, and no immediate complications were observed post-procedure. The subsequent follow-up exams showed patent TIPS and SMV without signs of intraabdominal hemorrhage.Percutaneous ultrasound-guided superior mesenteric vein access for balloon-assisted PVR-TIPS is a feasible option in cases where hepatic or splenic access is not. Portal vein thrombosis (PVT) can result in chronic occlusion of the portal vein (PV) , which m2) with no history of hepatic cirrhosis or malignoma presented with chronic occlusion of the PV in the setting of essential thrombocythemia. Pre-interventional imaging presented an occlusion of the intrahepatic and extrahepatic PV as well as the splenic vein (SV). The PV, which could only be delineated in strands, was cavernously transformed. Dilated esophageal and gastric portosystemic collaterals, splenomegaly and ascites were evident signs of portal hypertension  that was free of intestinal superimposition, (II) where the vein was large enough for the insertion of a sheath and (III) that was distant enough to avoid an obstruction of the origin of the PV by the sheath. The percutaneous puncture was performed under ultrasound-guided puncture of the branch using a 4-Fr micro-puncture set . No intestine was punctured. Subsequently, a 4-Fr sheath  was introduced.After initial imaging of the occluded PV/SV and the extensive cavernous transformation Fig. , passageIn order to establish through and through access (Archimedean access), the balloon catheter was pulled into the direction of the SMV sheath, but the wire could not be retrieved due to severe kinking within the balloon and eventually broke. The distal end of the wire was secured through the sheath. The 4-Fr sheath in the SMV was replaced by a 6-Fr sheath and a 6-Fr multi snare catheter  was inserted to snare the wire. Nonetheless, the proximal end of the wire could not be retrieved, and the wire had to be removed via the jugular access. Now with the 6F sheath in place the maneuver was repeated using another balloon catheter  positioned in the right hepatic vein and inflated as fluoroscopic target. Direct TIPS needle-guided puncture of the balloon was performed without complications, and a 0.035 wire  was used to successfully achieve through and through access.Following this, sequential widening of the TIPS tract and portal vein was performed using 6 mm and 8 mm balloons . Subsequent implantation of a 7/2 VIATORR endoprosthesis, which needed to be extended to the caval vein by a second 7/2 VIATORR endoprosthesis as a stent-in-stent  was performed. The final angiography showed a swift contrast outflow via the TIPS as well as a significant caliber reduction of the collaterals  liver parenchyma . EspeciaThis case study is reporting on one patient only; thus our results and assumptions must be taken with great caution. However, in contrast to the previously published case reports, we inserted a sheath with a larger lumen (6-Fr) in the SMV  . In our To conclude, percutaneous trans-mesenteric access is a feasible alternative to perform PVR-TIPS with preliminary favorable clinical success and safety. Furthermore, the combination of SMV access and balloon assisted shunt placement is a new addition to the portfolio in this often technically demanding intervention. Nonetheless, further studies should evaluate long-term safety and clinical outcome of this novel procedure.