In a Cox regression survival analysis, the hazard ratio for breakthrough infection among patients with CDA compared to matched patients was 0.91 . Conclusions: COVID-19 vaccination is effective in patients with coeliac disease autoimmunity. Vaccine effectiveness was comparable to the reference population.Background: Data on COVID-19 vaccine effectiveness among patients with coeliac disease are currently lacking because patients with immune conditions were excluded from clinical trials. We used our coeliac disease autoimmunity (CDA) cohort to explore the effectiveness of the BNT162b2 mRNA COVID-19 vaccine in preventing SARS-CoV-2 infection among patients with CDA. Methods: This retrospective cohort study included patients with positive autoantibodies against tissue transglutaminase (tTG-IgA). In the primary analysis, the cohort included CDA patients who received two vaccine doses against COVID-19 and matched patients in a 1:3 ratio. Patients were divided into subgroups based on their positive tTG-IgA level at diagnosis and their current serology status. Results: The cohort included 5381 vaccinated patients with CDA and 14,939 matched vaccinated patients. The risk for breakthrough SARS-CoV-2 infection evaluated with Kaplan–Meier survival analysis via log-rank tests was similar between groups ( Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has caused over 300 million confirmed cases of COVID-19 globally and more than 5 million deaths as of January 2022 .Coeliac disease (CD) and CD autoimmunity (CDA) are immune-mediated conditions characterized by autoantibodies to tissue transglutaminase, affecting around 1% of the population worldwide with trends towards an increase in incidence in recent years ,6,7. PatCD has been associated with a decreased immune response to vaccination against the hepatitis B virus . StudiesFew studies have addressed the effect of the SARS-CoV-2 vaccine in patients with celiac disease . StudiesIn the present population-based controlled study, we aimed to explore the effectiveness of COVID-19 vaccination in preventing SARS-CoV-2 infection in patients with CDA, both for newly diagnosed patients and patients with an established diagnosis with and without serologic remission.We used the Maccabi Healthcare Services (MHS) comprehensive database, a 2.5-million-member state-mandated health fund in Israel. MHS is the second largest of the four nationwide health funds in Israel, of which citizens can choose their respective healthcare memberships. The Maccabi health fund members represent 26.7% of the population and share similar socio-demographic characteristics with the overall Israeli population. The fund has maintained a computerized database of electronic health records since 1993, containing extensive longitudinal data on a stable population .Additionally, the health fund has developed several computerized registries of major clinical conditions. These registries are continuously updated and detect relevant patients using pre-defined criteria .This retrospective cohort study included vaccinated patients age ≥ 12 years with CDA with a minimum of two BNT162b2 mRNA COVID-19 vaccine doses. Only patients registered in the MHS database for at least 12 months prior to the first vaccine dose (index date) were included. Patients with CDA were further stratified according to the degree of tTG IgA elevation, as described below.Individual matching was performed with a 1:3 ratio (patients with CDA to matched patients). Only patients without a record of tTG-IgA testing were considered for controls, and patients were matched based on birth year, sex, MHS branch , socioeconomic status (SES), and month of first vaccine dose. The SES was computed from patients’ residential areas and presented from low to high with a ranking system (1 as the lowest and 10 as the highest). Patients with a record of a prior positive polymerase chain reaction (PCR) result or those with a diagnosis of SARS-CoV-2 prior to the index date were excluded from this study. All patients were required to have at least two doses of the Pfizer vaccine with a minimum of 14 days follow-up after the second vaccination dose to ensure full vaccine effectiveness. The first vaccination date was used as the index date for this study for both those with CDA and their matched patients. PCR breakthrough infections post-second vaccination were recorded from 1 February 2021 until end of follow-up on 18 September 2021. Patients with CDA with an elevated tTG-IgA above ten times the upper limit of normal, described as patients with near-certain coeliac disease. This definition is based on the high positive predictive value of very high tTG-IgA levels .Patients with CDA with an elevated tTG-IgA followed by a subsequent normal tTG-IgA within two years pre-index date, where the subsequent normal test is at least one year since the first, described as patients with likely well-controlled coeliac disease.Patients with CDA with an elevated tTG-IgA followed by a subsequently elevated tTG-IgA within two years pre-index date, where the subsequent elevated test is at least one year since the first, described as patients with possibly not well-controlled coeliac disease.Newly diagnosed patients with CDA (a first elevated tTG-IgA test within a year from index date), described as patients with recently diagnosed coeliac disease autoimmunity.Patients in this study with CDA were stratified into four groups, compared to their matched patients, and then categorized as follows:Baseline characteristics described in this study include the matching parameters, such as age at index date, sex, SES, and the month of the first vaccine dose. Comorbidities at baseline from the MHS registries were also recorded, including diabetes, hypertension, cancer, cardiovascular disease (CARDIOVASCULAR DISEASE), chronic kidney disease (CKD), and immunosuppressed patients ,20,21. TThe primary outcome was to compare vaccine effectiveness against SARS-CoV-2 infection (regardless of symptoms) in both CDA patients and controls. Cases were defined by at least 1 positive SARS-CoV-2 polymerase chain reaction (PCR) test recorded in the MHS computerized database. All such testing in MHS members is recorded centrally.Baseline characteristics were evaluated and comparative analyses were performed, namely, descriptive statistics presented as mean values (standard deviation (±SD)) and frequencies per parameter between coeliac and matched patients. The Mann–Whitney test was used to evaluate age and Pearson’s chi-squared test was used for discrete variables such as sex, SES, vaccination month, and comorbidities. Kaplan–Meier survival analyses were performed to evaluate time to breakthrough infection with SARS-CoV-2, defined as a positive PCR result 14 days post second vaccination date. Patients with CDA and their matched patients were compared via the log-rank test. Multivariate Cox regression analyses were also conducted where the independent variable was a PCR outcome event. The covariates entered in the models include comorbidities listed in Primary analysis—whole cohortIn this study, 7083 patients with CDA were identified in the MHS database with two confirmed COVID-19 vaccination doses and no prior record of a positive PCR test. After matching, there were 5381 patients with CDA matched to 14,939 patients without any record of tTG-IgA testing. The mean age in years for the CDA and matched patients was 33.38 (standard deviation (SD) ± 17.78) and 33.93 (SD ± 17.68), respectively. There were 3476 (64.6%) females in the whole cohort.The CDA and matched patients included in the study predominantly received their first vaccination in December 2020 (37.1% and 37.5%) or January 2021 (31.1% and 31.8%). SES was also similar in both groups, where most patients were of high socioeconomic status (64.3% and 64.9%). Among the whole CDA cohort, the mean time from the first positive tTG-IgA was 6.73 years (SD ± 4.42). p < 0.05). Additionally, BMI differed between groups such that there were more overweight individuals in the CDA group (53.1%) compared to the matched patients (44.5%).The patients with CDA and matched patients differed in certain comorbidities, where we observed differences in patients with diabetes, hypertension, cancer, cardiovascular disease, and immunosuppression  to evaluate time to breakthrough SARS-CoV-2 infection, where there was no observed statistical difference between groups . The Cox regression survival analysis (p = 0.29). The Cox regression survival analysis (p = 0.3). The Cox regression survival analysis (p = 098). The Cox regression survival analysis  and their matched patients (n = 8923) is presented in analysis  demonstranalysis  demonstranalysis  demonstranalysis  demonstrIn this population-based study of all patients with at least two doses of COVID-19 vaccination with CDA in our health organization, we found that vaccine effectiveness is similar in CDA patients compared to matched patients. The effectiveness was evaluated across several subgroups of CDA patients, including newly diagnosed patients, and was similar in all groups. Patients with tTG-IgA above ten times the normal upper limit represent patients with near-coeliac disease as this cut-off represents a very high positive predictive value for villous atrophy and, in the proper clinical setting, is considered high enough for diagnosis without a biopsy in children and possibly in adults ,23,24,25To the best of our knowledge, there are no published studies to date regarding vaccine effectiveness for COVID-19 in coeliac disease patients. Vaccine effectiveness in the general population was high in clinical trials and in real-world settings in several different statistical models. In patients with specific comorbidities, the results are conflicting and are related to the comorbidity and immune-modifying drugs in use. Dagan et al. showed slightly decreased vaccine effectiveness in patients with multiple coexisting conditions such as hypertension and diabetes . ChodickThe fact that we did not observe any difference in vaccine effectiveness despite a significantly higher proportion of patients with comorbidities and immunosuppression in the CDA group further strengthens our findings that CDA is not associated with decreased effectiveness of mRNA COVID-19 vaccines. Our findings are supported by two studies that looked at the humoral response in patients with celiac disease. In the study by Ibsen et al. , there wThe main strength of our study is our validated CDA cohort based on tTG-IgA performed in one national central laboratory and our centralized database on COVID-19 vaccination and breakthrough infections, allowing us to follow this large cohort accurately over time. In addition, the extended follow-up that lasted eight months included the third and fourth waves of the pandemic in Israel, dominated by the Alpha and Delta variants, respectively ,31, whicThis study has limitations relating to our structured database, which lacks information on pathological reports. Therefore, we focused on coeliac disease autoimmunity rather than coeliac disease. While acknowledging that CDA is not necessarily coeliac disease, it does represent the broad spectrum of autoimmunity to gluten peptides. This study was conducted prior to the Omicron surge and therefore cannot conclude on ongoing immunity against the Omicron variant. Patients with CDA differed from matched patients in BMI, diabetes, hypertension, and cancer proportion. These characteristics are risk factors for more severe COVID-19 but not for breakthrough infections. In conclusion, to the best of our knowledge, this is one of the first reports of real-world COVID-19 vaccine effectiveness in patients with CDA. The overall vaccine effectiveness was excellent and comparable to the reference population. Future studies should focus on long-term vaccine effectiveness and safety over time in patients with coeliac disease.


Can an automated prognostic model embedded in the electronic medical record help prevent hospital-acquired venous thromboembolism (HA-VTE) among hospitalized children and adolescents?In this randomized clinical trial that included 17 427 pediatric hospitalizations, 58 patients (0.7%) in the control group and 77 (0.9%) in the intervention group developed HA-VTE, a non–statistically significant difference. Recommendations to initiate thromboprophylaxis were followed only 25.8% of the time.Despite use of an accurate and validated prognostic model for HA-VTE, there was substantial reluctance by primary clinical teams to initiate thromboprophylaxis as recommended; in this context, HA-VTE rates between the control and intervention groups were not different. This randomized clinical trial evaluates whether the use of a previously validated prognostic model for hospital-acquired venous thromboembolism (HA-VTE) reduces pediatric inpatient rates of HA-VTE. Rates of hospital-acquired venous thromboembolism (HA-VTE) are increasing among pediatric patients. Identifying at-risk patients for whom prophylactic interventions should be considered remains challenging.To determine whether use of a previously validated HA-VTE prognostic model, together with pediatric hematologist review, could reduce pediatric inpatient rates of HA-VTE.This pragmatic randomized clinical trial was performed from November 2, 2020, through January 31, 2022, at a single-center academic children’s hospital . All pediatric hospital admissions (aged <22 years) under inpatient status were included and randomized.All patients had an HA-VTE probability automatically calculated daily, which was visible to the hematology research team for patients in the intervention group. Patients with an elevated risk (predicted probability ≥2.5%) underwent additional medical record review by the research team to determine eligibility for thromboprophylaxis.The primary outcome was rate of HA-VTE. Secondary outcomes included rates of prophylactic anticoagulation and anticoagulation-associated bleeding events.P = .10). Recommendations to initiate thromboprophylaxis were accepted by primary clinical teams 25.8% of the time . Minor bleeding events were rare among patients who received anticoagulation (3 of 74 [4.1%]), and no major bleeding events were observed during the study period. Among patients randomized to the control group, the model exhibited high discrimination accuracy .A total of 17 427 hospitalizations met eligibility criteria, were randomized, and were included in the primary analysis: patients had a median (IQR) age of 1.7 (0 to 11.1) years; there were 9143 (52.5%) female patients and 8284 (47.5%) male patients, and there were 445 (2.6%) Asian patients, 2739 (15.9%) Black patients, and 11 752 (67.4%) White patients. The 2 groups were evenly balanced in number (8717 in the intervention group and 8710 in the control group) and patient characteristics. A total of 58 patients (0.7%) in the control group and 77 (0.9%) in the intervention group developed HA-VTE (risk difference: 2.2 per 1000 patients; 95% CI, −0.4 to 4.8 per 1000 patients; In this randomized clinical trial of the use of a HA-VTE prognostic model to reduce pediatric inpatient rates of HA-VTE, despite the use of an accurate and validated prognostic model for HA-VTE, there was substantial reluctance by primary clinical teams to initiate thromboprophylaxis as recommended. In this context, rates of HA-VTE between the control and intervention groups were not different. Future research is needed to identify improved strategies for prevention of HA-VTE and to overcome clinician concerns regarding thromboprophylaxis.NCT04574895ClinicalTrials.gov Identifier:  Prior studies have sought to identify risk factors and develop prognostic models to assist in risk stratification,7 although many of these models are limited to specific patient subgroups and are not broadly applicable across all pediatric patients.10 Furthermore, to our knowledge, these models have not been prospectively assessed to determine their impact on patient outcomes in randomized controlled trials.Hospital-acquired venous thromboembolism (HA-VTE) is an increasing cause of morbidity and mortality among pediatric patients,13 we previously developed and validated a prognostic model to identify general pediatric inpatients with elevated risk for developing HA-VTE.14 The model uses data available upon admission to estimate the probability of HA-VTE for each patient, which is updated every 24 hours as new data become available during hospitalization. For ease of use, the model is incorporated into the electronic medical record (EMR), such that variables are extracted and the predicted probability is calculated automatically without any need for clinician input of clinical or laboratory information. To assess the model’s impact on patient outcomes by identifying at-risk patients within a large general pediatric inpatient population, we conducted a randomized clinical trial using the HA-VTE prognostic model along with targeted hematology review of patients with elevated risk to determine whether the combination could decrease pediatric HA-VTE rates compared with usual care at our medical center.Knowing that prognostic models have been shown to better identify patients at elevated risk for HA-VTE than physician judgment alone,15 The trial was approved by the Vanderbilt University Medical Center Human Research Protections Program with waiver of informed consent due to minimal risk to participants and impracticality of obtaining informed consent from all admissions. The trial was registered with ClinicalTrials.gov prior to initiation of patient enrollment on September 28, 2020. The date of first patient enrollment was November 2, 2020; date of study completion, January 31, 2022; dates of data extraction and analysis, March 15, 2022, to February 17, 2023. Trial data were obtained from our institution’s EMR, including sociodemographic characteristics, medical history, and outcomes identified from International Classification of Diseases, Ninth Revision (ICD-9) and International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) codes and medication orders (CONSORT) reporting guidelines.The Children’s Likelihood of Thrombosis (CLOT) trial was an unblinded, pragmatic randomized clinical trial conducted at Monroe Carell Jr Children’s Hospital at Vanderbilt (MCJCHV) at Vanderbilt University Medical Center in Nashville, Tennessee.n orders . This reEligible participants were younger than 22 years and were admitted to a pediatric unit  at MCJCHV during the study period. Patients admitted under observation status, same-day surgery, or other admission categories were not eligible unless their status was changed to inpatient. Patients who were discharged or had a diagnosis of HA-VTE prior to randomization were excluded. Enrolled patients who were discharged from the hospital and subsequently readmitted during the study period remained eligible and were rerandomized. The primary analysis included all admissions during the study period, while a secondary sensitivity analysis included only the first admission for each patient.Upon inpatient admission orders being placed by the treating clinicians, eligible patients were randomized by an Epic BestPractice Advisory that ran in the background and was not seen by clinicians. The advisory programmatically generated a random binary value to determine whether the patient was assigned to the control group or intervention group. The group to which each patient was assigned was saved for that admission encounter and then extracted into a daily report.The study principal investigator and the pediatric hematologists (S.C.W. and A.P.W.) who reviewed patients with elevated risk were unblinded to the intervention. Assignment to the intervention or control group was concealed for all other study personnel. Group assignments remained concealed from the biostatistics team and safety monitoring committee until primary data analysis was complete. The principal investigator was not responsible for diagnosing HA-VTE.14 on admission and daily thereafter , a 2-sample Fisher exact test achieves 80% power to detect an absolute risk reduction from 10 per 1000 in the control group to 5.95 per 1000 in the intervention group with a type I error rate of 5%.Primary analyses compared the intervention and control groups and were conducted by modified intention to treat, with the modification that randomized patients who already initiated thromboprophylaxis on the first day of their hospitalization were excluded. Secondary as-treated analyses were also conducted, considering whether treatment recommendations were followed by the primary clinical team. As-treated analyses were limited to the strata of patients with elevated risk of developing HA-VTE (predicted probability ≥2.5%), with comparisons between patients randomized to the control group, randomized to the intervention but treatment recommendations were not followed, and randomized to the intervention and treatment recommendations were followed.P < .05 (obtained from Pearson χ2 test) indicated statistical significance. Secondary subgroup analyses were performed by patient age, patient sex, patient race and ethnicity, admission type , and risk of VTE at admission (predicted probability <2.5% or ≥2.5%). As-treated analyses were performed using logistic regression models that adjusted for the highest predicted probability of HA-VTE prior to diagnosis. Secondary and subgroup analyses were conducted without corrections for multiple comparisons and were therefore considered exploratory. Interim safety analyses were conducted every 6 months and reported to the safety monitoring committee, for which outcome rates were presented with group assignments concealed and without between-group statistical comparisons; therefore, no predetermined stopping rules were used. Performance of the prognostic model was summarized using the C statistic, sensitivity, and specificity; due to the potential for the model-guided intervention to impact outcomes for patients in the intervention group, these summaries were obtained for the control group only. All statistical analyses were prespecified and performed using reproducible research methods in R version 4.2.1 , including the R packages Hmisc and rms.Sociodemographic characteristics (including race and ethnicity as reported by patients and recorded in the EMR) and baseline clinical characteristics were summarized using standard descriptive statistics. Race and ethnicity were included to ensure the model performed consistently across all groups. The proportion of patients diagnosed with HA-VTE (primary outcome) and the proportion of patients who received prophylactic anticoagulation (secondary outcome) were compared between the intervention and control groups using unadjusted risk differences with 95% CIs. We did not specify a priori any adjustment variables to include in multivariable models, and no variable exhibited a clinically meaningful imbalance between the intervention and control groups. For the primary outcome, a 2-sided C statistic, 0.799; 95% CI, 0.725-0.856; sensitivity, 0.86; 95% CI, 0.75 to 0.94; specificity, 0.90; 95% CI, 0.89 to 0.90)   experienced HA-VTE; among the 8717 hospitalizations in the intervention group, 77 (0.9%) experienced HA-VTE  . The locSecondary sensitivity analyses limited to the first admission during the study period, for which 7127 patients were randomized to the control group and 7120 were randomized to the intervention group, provided similar results  and those without elevated risk : those randomized to the control group , randomized to the intervention but treatment recommendations were not followed (9 of 213 [4.2%]), and randomized to the intervention and treatment recommendations were followed (7 of 74 [9.5%]) . The medOnce patients were initiated on prophylactic anticoagulation per the research team recommendations, they were followed up via medical record review and regular discussions with the primary team to assess for bleeding. Only intervention group patients receiving anticoagulation had bleeding scores tracked and captured due to the real-time nature of the study design. Three patients developed minor bleeding: 1 developed minor oropharyngeal bleeding , 1 developed hemoptysis , and 1 developed bleeding from procedure sites . All 3 patients had resolution of the bleeding upon cessation of anticoagulation. No patients developed major bleeding events during the study .5 and improving outcomes in pediatric patients identified to be at risk for HA-VTE has been challenging.13 The innovative study design of the CLOT trial used an automated EMR-based clinical decision support tool to calculate the probability of a patient developing HA-VTE and included integration into the EMR for key functions, including automated patient-level randomization, which led to large, well-balanced groups; automated implementation of the prognostic model to easily identify at-risk patients; and automated data extraction, which facilitated daily updates as patients’ clinical scenario evolved. The HA-VTE prognostic model has been shown to accurately identify at-risk patients in derivation and validation cohorts14 as well as among patients included in this trial; however, incorporating the model into routine clinical practice did not decrease HA-VTE rates. We postulate that this is chiefly due to low rates of thromboprophylaxis being initiated when recommended. Additionally, the study did not identify any episodes of severe bleeding in patients who received thromboprophylaxis.The development of pediatric HA-VTE is associated with longer hospital stays, increased medical costs, and subsequent medical complications,18 and the safety work performed during this trial demonstrate that it is unlikely that appropriately recommended prophylactic anticoagulation will increase an individual’s risk for significant bleeding. Further work is planned to identify potential barriers as well as to optimize the implementation of incorporating the model into clinical practice, with the hope of improving acceptance of the hematology recommendations during future trials.We hypothesize that the intervention’s primary lack of success in decreasing HA-VTE rates was due to low rates of thromboprophylaxis acceptance when recommended. Multiple clinical teams cited their concern that initiating pharmacologic prophylaxis would increase their patient’s risk of bleeding; however, prior literature19 This could contribute to the overall lack of change in HA-VTE rates despite an increased number of patients who received thromboprophylaxis in the intervention group. In addition, by identifying patients with elevated risk, primary teams may have been motivated to make nonpharmacologic changes to decrease a patient’s risk for HA-VTE, such as removing a CVL sooner or using increased mobilization, rather than initiating pharmacologic prophylaxis. While these nonpharmacologic interventions may have decreased a patient’s risk for HA-VTE, this risk reduction is unable to be quantified and likely contributes to the lack of difference in HA-VTE rates seen in the study.Other reasons that the intervention may have been unsuccessful include potentially ineffective dosing of thromboprophylaxis. During the study period, we recommended standard weight- and age-based prophylaxis dosing of unfractionated heparin and low-molecular-weight heparin for elevated risk patients deemed clinically safe for pharmacologic prophylaxis; however, recent data have emerged suggesting that HA-VTE associated with a central venous line (CVL) in patients with a history of HA-VTE may be prevented more effectively by using higher doses of pharmacologic prophylaxis.C statistic values compared with the original model.14 Using a pediatric hematologist to make the thromboprophylaxis recommendations as well as notifying the clinical teams of these recommendations allowed clinician concerns to be discussed directly. Clinicians and clinical teams often voiced strong acceptance or opposition to thromboprophylaxis recommendations; thus, using patient-level randomization avoided clinician or unit-dependent biases. The study also demonstrates the feasibility of performing a large-scale randomized trial without the need for significant external funding. Using readily available data that updates frequently to identify at-risk patients within a large general population that may benefit from subspecialist expertise without the need for clinical identification of risk can hopefully reduce the number of patients who experience potentially preventable complications.Despite the observed lack of efficacy in this study, strengths of the study include its originality as, to our knowledge, the first large pediatric study to demonstrate the use of a randomization tool integrated into the EMR to provide unbiased, automated randomization for more 17 000 patients. Furthermore, the model was updated with new EMR information daily throughout each patient’s admission, which may contribute to the slightly different We acknowledge the following limitations. First, although randomization and calculation of HA-VTE risk was automated in the EMR, subsequent manual review by the study team was only performed on weekdays; therefore, patients were randomized to the intervention who had elevated risk but were not reviewed. These patients were included in the intervention group in the primary intention-to-treat analysis but were not included in the as-treated analysis; both analyses failed to show benefit of the intervention. Second, while this study was only performed at a single site, we have successfully demonstrated the ability of an automated prognostic model incorporated into the EMR to accurately identify patients at elevated risk, which we are actively working to expand to additional academic children’s hospitals, which may have different baseline rates of HA-VTE due to demographic variability and different strategies for pharmacologic thromboprophylaxis, mobilization, and CVL removal.In this randomized clinical trial evaluating the use of a real-time, prognostic model to reduce rates of HA-VTE in hospitalized children and adolescents, the automated, EMR-integrated model functioned well to estimate risk of pediatric inpatients developing HA-VTE and did not demonstrate an increased risk of bleeding, but overall acceptance of the recommendations from the hematology research team was low and use of the model in this context did not improve patient outcomes. Moving forward, we are considering additional ways to assess the success of future studies, including the use of quality improvement metrics such as aim statements, plan-do-study-act cycles, and run charts, in addition to more traditional research mechanisms to identify the best strategies to prevent pediatric HA-VTEs. Overall, we anticipate optimizing anticoagulation dosing and overcoming barriers to implementation and adoption of the HA-VTE model in clinical practice to be the most important next steps.


This research examined the cost-effectiveness of adding empagliflozin to standard of care (SoC) compared with SoC alone for treatment of heart failure with reduced ejection fraction (HFrEF) from the perspective of healthcare payers in the United Kingdom (UK), Spain and France.A lifetime Markov cohort model was developed to simulate patients’ progression through health states based on Kansas City Cardiomyopathy Questionnaire Clinical Summary Score. The model predicted risk of death, hospitalisation for worsening heart failure (HHF), treatment-related adverse events, and treatment discontinuation each monthly cycle. Clinical inputs and utilities were derived from EMPEROR-Reduced trial data, supplemented by published literature and national costing databases. Costs (2021 pound sterling/euro) and quality-adjusted life-years (QALYs) were discounted annually for the UK (3.5%), Spain (3.0%) and France (2.5%).In the UK, Spain and France, empagliflozin plus SoC yielded additional QALYs  at higher cost  than SoC alone, yielding incremental cost-effectiveness ratios of £6152/QALY, €7736/QALY and €5511/QALY, respectively. Reduced HHF incidence provided most cost offsets for empagliflozin plus SoC. Similar results were obtained for a range of subgroups and sensitivity analyses. Probabilistic sensitivity results indicated empagliflozin plus SoC remained cost-effective vs. SoC at willingness-to-pay thresholds of £20,000/QALY, €20,000/QALY and €30,000/QALY in 79.6%, 75.5% and 97.3% of model runs for the UK, Spain and France, respectively.Empagliflozin added to SoC leads to health benefits for patients with HFrEF and is a cost-effective treatment option for payers in multiple European countries .The online version contains supplementary material available at 10.1007/s10198-022-01555-6. Heart failure (HF) is characterised by frequent hospitalisations and significantly diminished life expectancy and health-related quality of life (HRQoL), imposing a significant humanistic and economic burden in Europe and internationally . While rHF with reduced ejection fraction  comprises approximately half or more of HF cases . As per ®) vs. placebo, both in addition to background standard of care (SoC), demonstrating a 25%  reduction in the primary composite outcome of CV death or first HHF and 30%  reduction in total HHF [Recent large-scale clinical trials (DAPA-HF and EMPEROR-Reduced) have shown the effects of sodium–glucose cotransporter-2 inhibitors (SGLT2i) (dapagliflozin and empagliflozin) on reducing the risk of cardiovascular (CV) death or HHF in patients with HFrEF , 10. EMPExamining the economic implications of these clinical results is essential to assist decision-makers in making judicious use of scarce healthcare resources, because this facilitates understanding of the trade-offs that ensue when introducing a novel health intervention that may improve clinical outcomes for patients, but may also increase expenditures for local healthcare systems. The establishment of dedicated institutions and frameworks for the assessment of new health technologies in each jurisdiction included in this study attests to the widespread recognition of the importance of formal economic evaluation as a tool for supporting such decisions –14. Acco®-based lifetime Markov cohort model with monthly cycles comparing empagliflozin plus SoC vs. SoC alone was developed to simulate patients’ progression through health states based on the Kansas City Cardiomyopathy Questionnaire (KCCQ) Clinical Summary Score  KCCQ-CSS state, regress to a higher (better) KCCQ-CSS state, or die, and could experience HHF or treatment-related adverse events (AEs) as transient events while in a KCCQ-CSS state. The model monitored patients’ HRQoL and resource use over time as they transitioned between health states and independently tracked CV- and non-CV-related deaths. Treatment was assumed to impact patient outcomes by reducing the risk of mortality and HHF and influencing the likelihood of transitions between KCCQ-CSS health states, further modifying the risk of model events and driving accrual of both costs and quality-adjusted life-years (QALYs).Modelled SoC therapies represented treatments patients in the EMPEROR-Reduced trial received, including diuretics, inhibitors of the renin–angiotensin system and neprilysin, beta-blockers, mineralocorticoid receptor antagonists, and cardiac devices (when indicated). Similar to the trial, where termination of therapy could result from exposure to AEs, non-adherence, or other causes, the model assumed patients for whom SoC was complemented by empagliflozin gradually discontinued empagliflozin therapy over time, after which they received SoC alone until death or the model horizon expired.The model structure was the same for the UK, Spain and France, although some inputs used to inform each analysis were country-specific (Supplementary Appendix Section S1). Direct medical costs consisted of expenditures related to drug acquisition, clinical event management, and disease management. Utilities were accrued based on time spent in each KCCQ-CSS state, adjusted for disutilities associated with HHF and AEs. Future costs and benefits were discounted at annual rates of 3.5%, 3.0% and 2.5% for the UK , Spain  and Fran2, and 20% were receiving an angiotensin receptor–neprilysin inhibitor (ARNi) as part of SoC.The modelled cohort was representative of patients in the EMPEROR-Reduced trial . Patient2) and utilisation or non-utilisation of ARNi.The model was equipped to perform a range of pre-specified subgroup analyses based on patient age at baseline (< 65 vs. ≥ 65 years), presence or absence of T2D, eGFR  or progression (descent) of disease through KCCQ-CSS quartiles. KCCQ-CSS quartiles were used to ensure sufficient granularity in predicting movement between health states and were constructed in such a way as to ensure enough patient data for robust statistical analysis . Treatment-specific monthly transition probabilities between quartiles were computed based on transition count data. Independent transition matrices were developed based on the first three months of follow-up in EMPEROR-Reduced, from month 4 to 8, and from month 9 onwards, recognising inflection points observed in the data (Supplementary Appendix Section S3). Transition probabilities were assumed to be equivalent for all patient subgroups.Parametric survival analysis of EMPEROR-Reduced trial data was conducted to estimate time to empagliflozin treatment discontinuation , with time-varying KCCQ-CSS as covariates ; alternative distributions were considered in sensitivity analyses. Discontinuation from empagliflozin was assumed to result in a treatment effect on event risks, costs, and utilities similar to SoC alone. This is a conservative assumption, to the extent it implies the treatment effect of empagliflozin dissipates immediately upon discontinuation, which may not be true in practice. However, event risks for patients who discontinue empagliflozin will remain lower than for patients who only ever received SoC, due to differences in how patients are distributed across health states. These distributions enter the predictive risk equations for HHF and all-cause and CV death, and differences among them, which persist even after discontinuing treatment with empagliflozin, will result in sustained divergence in risk profiles between interventions.Risk of first and subsequent HHF was estimated using a Poisson regression model fitted to patient-level EMPEROR-Reduced data with generalised estimating equations to account for the repeated measures on patients (Supplementary Appendix Section S2), including treatment allocation and time-varying KCCQ-CSS health states as covariates (Supplementary Appendix Section S3). Being on treatment with empagliflozin plus SoC or residing in higher KCCQ-CSS quartiles was associated with lower risk of HHF.The model captured AEs experienced by patients in the EMPEROR-Reduced trial, including urinary tract infection, genital mycotic infection, acute renal failure, hepatic injury, volume depletion, hypotension, hypoglycaemic events and bone fracture. Patients were subject to ongoing risk of experiencing AEs, estimated from the trial data (Supplementary Appendix Section S4). A constant hazard was assumed for each AE.Parametric survival analyses were undertaken using the complete EMPEROR-Reduced dataset to capture all-cause and CV death as a function of treatment and time-varying KCCQ-CSS, both during and beyond the trial duration. Distributions chosen for all-cause and CV death (Weibull) were selected from potential distributions based on goodness of fit and clinical plausibility of long-term projections; alternative distributions were considered in sensitivity analyses. Details regarding the statistical methodology and results of the parametric survival analyses are presented in Supplementary Appendices Sections S2 and S3, respectively.The model independently tracked CV and non-CV deaths; whereas CV death was dictated by the corresponding predictive risk equation (see above), non-CV death was calculated as (a) the difference between parametric fits for all-cause and CV death or (b) the difference between rates of age- and sex-specific all-cause mortality predicted from country-specific life tables –24 and rThe model applied utility scores ranging from 0 (death) to 1  to capture the effect of disease severity and clinical events on HRQoL. QALYs accrued during each model cycle, calculated as the difference between KCCQ-CSS health state utilities, and utility decrements attributable to transient events, including HHF and AEs  would not be higher than this level. The model did not apply further adjustments to account for cohort ageing due to comparatively brief life expectancy for patients with HFrEF.Direct reimbursable medical care costs were expressed in appropriate national currencies (i.e. 2021 British pounds for the UK and 2021 Euros for Spain and France), with adjustments for inflation. The model included costs associated with drug acquisition, management of clinical events, and disease management, sourced from local costing databases and published literature, as appropriate  and the Official Journal in France . For each SoC HF medication class, costs of individual therapies were used to compute an average cost, assuming treatments within each class were uniformly distributed (UK and Spain) or based on local market share (France). Then, the drug cost of SoC was computed as a weighted average cost based on these values and utilisation of HF medication classes at baseline in the empagliflozin plus SoC and SoC arms of EMPEROR-Reduced. Finally, a cost associated with each treatment regimen  was computed. Indicated strength and dosage for each drug were based on summaries of product characteristics. The cost of empagliflozin 10 mg was incurred until treatment discontinuation, whereas expenditures associated with SoC accrued until death or the model horizon expired. Detailed examples of the steps involved in the calculation of treatment costs are presented in Supplementary Appendix Section S6.The model assumed that patients receiving implantable cardioverter defibrillators and cardiac resynchronisation therapy had these devices installed prior to entry, and, accordingly, the analysis excludes expenditures associated with the devices or their implantation. In addition, it was assumed patients entering the model were already receiving appropriately titrated doses of SoC therapies, such that the stable maintenance dosage for each SoC treatment could be applied.Expenses for managing clinical events  were obtained from national databases or published literature and modelled as one-off costs. The model assumed no cost for non-CV death. For AEs, these were calculated with reference to the distribution of visit types (i.e. outpatient or inpatient), reflecting their typical severity, and corresponding costs.HF-related disease management expenditures accrued each cycle and were assumed similar across KCCQ-CSS quartiles, reflecting utilisation rates and local costs associated with primary care, cardiologist visits, and accident and emergency referrals.Validation steps included assessment of face validity, technical validity, predictive validity, and cross-validity. Thorough evaluation of face validity and technical validity was supported by an independent modelling expert using the TECHnical VERification checklist (TECH-VER) . MeanwhiTo assess the applicability and generalisability of this study to clinical practice in each jurisdiction, baseline characteristics and observed event rates for EMPEROR-Reduced participants were compared with data collected from recent real-world studies involving patients with HFrEF, including Incidence, Prevalence, and resoUrce utiLiSation of hEart failure in England (PULSE), the FREnch Survey on Heart Failure (FRESH), and published analyses undertaken using a large Spanish administrative database , 33; theThe base-case analysis predicted absolute and incremental lifetime cumulative events per 100 PYs, life-years (LY), QALYs and costs with empagliflozin plus SoC vs. SoC alone for the EMPEROR-Reduced trial intent-to-treat (ITT) population. Additionally, the model synthesised results for incremental costs and QALYs to compute the ICER for empagliflozin plus SoC vs. SoC alone. The ICERs for each setting were compared with country-specific, willingness-to-pay (WTP) thresholds—£20,000/QALY for the UK , €20,000Scenarios were run for pre-specified subgroups that were considered clinically and/or economically meaningful (outlined above). Deterministic sensitivity analyses (DSA) were performed using plausible ranges or alternative values for key inputs  to test the robustness of model results to changes in the parameters. A probabilistic sensitivity analysis (PSA) was conducted using distributions reflecting parameter uncertainties, producing 1000 pairs of incremental effectiveness and cost estimates. The parameters for sensitivity analyses are provided in Supplementary Appendix Sections S9 and S10.Empagliflozin plus SoC was associated with fewer HHFs, CV deaths, non-CV deaths and specific AEs  vs. SoC alone in all three country settings over a lifetime horizon , €4073–€13,520 in Spain  and from €4123–€11,810 in France , reinforcing the base-case results. Eliminating the effect of treatment on HHF was the most influential parameter, increasing the ICER in each jurisdiction. That was followed by empagliflozin cost per pack (− 20 to + 20%) and discount rate for cost  in the UK; drug costing source  and empagliflozin cost per pack (− 20 to + 20%) in Spain; and empagliflozin cost per pack (− 20 to + 20%) and discount rate for cost  in France , €20,000/QALY (Spain) and €30,000/QALY (France) were 79.6%, 75.5% and 97.3%, respectively  and drove further differences in the risk of HHF and mortality. Operating through these channels, empagliflozin plus SoC resulted in lower rates of HHF or CV death compared with SoC alone, culminating in additional LYs and higher QALYs. Utilising empagliflozin alongside SoC also produced higher monthly drug acquisition costs, and greater life expectancy vs. SoC which further increased lifetime expenditures for medication, as well as for disease management. These were partially offset by cost-savings from reduced incidence of clinical events, especially HHF. ICERs capturing the trade-offs between increased clinical benefits and higher lifetime costs fall well below accepted WTP thresholds in each jurisdiction, demonstrating that empagliflozin plus SoC was highly cost-effective compared with SoC alone. These findings were broadly supported by results from a series of comprehensive scenario and sensitivity analyses.The modelling approach adopted in this analysis was consistent with a recently published economic evaluation in HFrEF for the SGLT2i dapagliflozin added to SoC . This moThis model has several strengths. First, it accurately reproduced the EMPEROR-Reduced trial results over the median trial follow-up period of 16 months. Second, health status was quantified using the KCCQ-CSS , a prognostically important, patient-reported measure of health status which is considered more reliable than physician-reported NYHA classification . KCCQ-CSThe model was also subject to limitations. First, EMPEROR-Reduced collected relatively short-term data, as is typical for a randomised controlled trial. Accordingly, long-term outcomes based on this trial data were extrapolated and are therefore prone to uncertainty. However, sensitivity analyses results imply that the choice of parametric distributions for key clinical outcomes did not significantly impact the estimated ICER, suggesting this residual uncertainty is unlikely to alter the conclusions of the analysis.Second, as is common in health economic assessments, it is challenging to ascertain the generalisability of the study results to clinical practice in each country considered in the analysis. While a review of real-world studies suggests the baseline characteristics of participants in EMPEROR-Reduced and trial outcomes are reasonably representative of the attributes of patients with HF and outcomes associated with delivery of SoC in each jurisdiction, such comparisons are hindered by significant limitations in the available RWE, including small sample sizes and high proportions of missing data. Furthermore, the inclusion of relatively few participants from any individual country in the EMPEROR-Reduced trial precluded the estimation of country-specific clinical inputs and necessitated the assumption that these inputs are similar across jurisdictions, mirroring challenges identified in another recent health economic evaluation of SGLT2i for the treatment of HFrEF . HoweverThird, due to inclusion criteria applied to the design of EMPEROR-Reduced, estimated utilities for patients occupying the highest KCCQ-CSS quartile (i.e. Quartile 4) were relatively high considering a population consisting of patients living with HFrEF. While the model applied an adjustment to ensure utility weights for KCCQ-CSS Quartile 4 did not exceed population norms in each country, the adjusted weights might still not be fully representative of this subset of patients. This said, utility weights assigned to the KCCQ-CSS quartiles were not significant drivers of model results in sensitivity analyses, and, accordingly, the cost-effectiveness of empagliflozin plus SoC should be robust to uncertainty around these values.Fourth, the model did not include diabetic ketoacidosis, a rare complication of SGLT2is. Very few cases of diabetic ketoacidosis were observed in the EMPEROR-Reduced trial, aligned with other results for empagliflozin from the EMPEROR-Preserved trial  in HF wiIn conclusion, the results of this economic evaluation based on extrapolation of EMPEROR-Reduced trial data demonstrated that compared to SoC alone, empagliflozin added to SoC generates incremental health benefits and represents a cost-effective use of healthcare resources for managing patients with HFrEF from the perspective of payers in the UK, Spain and France.Supplementary file1 (DOCX 231 KB)Below is the link to the electronic supplementary material.


Intimate partner violence (IPV) may have been exacerbated during the COVID-19 pandemic. This analysis aimed to determine how employment disruption during COVID-19, including working from home, was associated with IPV experience among cis-gendered women.The International Sexual Health and Reproductive health (I-SHARE) study is a cross-sectional online survey implemented in 30 countries during the pandemic. Samples used convenience, online panel, and population-representative methods. IPV was a pre-specified primary outcome, measured using questions from a validated World Health Organisation instrument. Conditional logistic regression modelling was used to quantify the associations between IPV and changes to employment during COVID-19, adjusted for confounding.13,416 cis-gender women, aged 18–97, were analysed. One third were from low and middle income countries, and two thirds from high income countries. The majority were heterosexual (82.7%), educated beyond secondary-level (72.4%) and childless (62.7%). During COVID-19 33.9% women worked from home, 14.6% lost employment, and 33.1% continued to work on-site. 15.5% experienced some form of IPV. Women working from home experienced greater odds of IPV than those working on-site . This finding was robust independent of sampling strategy and country income. The association was primarily driven by an increase in psychological violence, which was more prevalent than sexual or physical violence. The association was stronger in countries with high gender inequality.Working from home may increase IPV risk globally. Workplaces offering working from home should collaborate with support services and research interventions to strengthen resiliency against IPV.The online version contains supplementary material available at 10.1186/s12889-023-15785-7. One third of all women will experience physical or sexual abuse by a partner or sexual violence by a non-partner in their lifetime . IntimatThe relationship between a women’s employment status and IPV experience is complex. Employed women may gain economic and decision-making empowerment that can be protective against IPV, especially in contexts where women’s financial autonomy is normalised , 5. HoweWorking from home, defined as generating income at home and not including unpaid domestic labour , was incThe International Sexual Health and Reproductive Health (I-SHARE) survey is a large, global cross-sectional study conducted between 2020 and 21. Demographic and country-level correlates of IPV in this dataset have been reported elsewhere . This anThe study population was drawn from the I-SHARE survey, which collected information about relationships, health and employment during the pandemic. The protocol, including pre-specified outcomes, has been published elsewhere . In summStringency of restriction policies experienced was measured using data on country-level pandemic responses, obtained from the Oxford COVID-19 Government Response Tracker (OX-CGRT) . This opa priori that countries with fewer than 20 participants would be excluded to reduce bias, which meant that 41 women from four countries were excluded (Appendix A). A sensitivity analysis including these women showed almost identical results (Appendix B). Duplicates were removed in Czechia, where two sampling schemes were used.Of the 23,067 participants in I-SHARE, 13,457 (58.7%) identified as cis-women. It was decided IPV was measured using five items from a validated WHO instrument that measure physical, psychological and sexual IPV . ParticiThe primary exposure was working from home during the pandemic. The effect of losing employment or working hours was also assessed. Three other types of work disruption were grouped in an “other” category, because they affected few participants and had less clear relevance to future policy. This included those who were employed but unable to work, changed job, or responded that they experienced some “other” work disruption, which could not be specified in free text. These exposures were compared to a baseline group of individuals who were working in the same job and site or were retired.Demographic variables included as potential confounders were age, sexual orientation, ethnicity, educational attainment, marital status, motherhood, and urban location. Other variables that were tested as confounders included experiences prior to the pandemic relating to employment and participation in transactional sex, alcohol and cannabis use, household income, and prior experience of IPV. The following variables related to experiences during the pandemic were also tested: living with a partner; changes in household composition; stringency of social distancing measures experienced; and length of time spent in lockdown. The processing of these variables is described in Appendix D.Descriptive statistics were used to summarise the prevalence of each exposure and potential confounder. The prevalence of each form of IPV were tabulated by country.a priori. This led to a final estimate adjusted for country, age, prior employment status, cannabis use before COVID-19, and previous experience of IPV in the three months before COVID-19 (Model 2). Further addition of any of the potential confounders listed above did not change the effect size compared to the crude model which excludes those with missing data on that variable.Associations between the types of work disruption and IPV were calculated using a conditional logistic regression model, with country as a fixed effect. A parsismonious set of confounders was identified using a forward modelling strategy and minimisation of mean squared error , with agA minimally adjusted model was fitted (Model 1), only adjusting for country as a fixed effect and excluding those with missing data on variables in Model 2 to make unbiased comparisons (N = 8362).Missing data patterns were described by cross-tabulating outcome nonresponse with the other variables of interest. Multiple imputation was used to explore the results’ sensitivity to missing outcome data (method detailed in Appendix E). Any association between IPV and nonresponse on other modelled variables was also explored using cross-tabulations. The analysis was repeated, stratified into high-income countries (HIC) or low- and middle-income countries (LMIC), stratified based on country-level gender inequality, stratified by whether participants were living with a partner, restricted to probability-based samples, and including those with partial information on IPV as sensitivity tests. All analysis was performed using STATA/SE 16.1.Out of the 9004 participants (67.1% of the study population) who responded to questions about IPV, 15.5% had experienced any form of IPV during COVID-19 social distancing measures  than participants who were employed or self-employed before the pandemic (11.7%). In contrast, informally employed and unemployed participants were substantially less likely to be working from home during the pandemic (6.2% compared to 39.9%) (Appendix H). Working from home was more prevalent among upper-middle-income and high-income countries (37.0% and 33.2% respectively) than low and lower-middle-income countries (16.8% and 20.0% respectively) (Appendix I).Of those working in-person, 12.0% experienced some form of IPV during COVID-19 Table , compareThe results were similar for women in HICs, and LMICs (Appendix J). The association between working from home and IPV was stronger in countries with higher gender inequality  compared to more equal societies , measured using the 2019 United Nations Development Programme Gender Inequality Index (Appendix K) [When the outcome is disaggregated into physical/sexual IPV and psychological IPV Fig. , the ass32.9% of participants had missing data on at least one IPV item during COVID-19. 67.3% of these participants identified as single and 76.3% identified as single, widowed or divorced, and so may not have perceived the questions as relevant. Participants were more likely to have responded to all IPV items if they reported being heterosexual, being in a relationship, being in the majority ethnicity in their country, being in a higher income group, and not experiencing IPV before COVID-19 (Appendix M). The results were robust after multiple imputation for the outcome, imputed using country and relationship status (Appendix E). The results were also robust after restriction to the probability-based samples in Kenya, Botswana, Sweden, Argentina, Denmark and Czechia (Appendix N), and after including those with partial responses to the outcome (Appendix O).This analysis presents evidence that working from home during COVID-19 measures was associated with a 40% increase in odds of IPV compared to working in-person. We found no relationship between losing employment and IPV risk, but strong evidence that those who experienced other disruptions to work, including changing job, or being paid but unable to work, experienced higher IPV. This extends the literature on IPV during COVID-19 by leveraging a large, multi-country study. These findings have important implications for how an employer’s duty of care extends to the domestic environment for staff who are working from home.Amongst this sample of cis-gender women, 15.5% experienced IPV during the initial COVID-19 wave. This is consistent with single-country analyses of IPV during COVID-19 , 28. TheOur data suggest that women who worked from home during COVID-19 were more likely to experience IPV. Odds of experiencing physical, sexual, or psychological IPV were all elevated compared to those working in-person, although statistical evidence for an association between working from home and physical/sexual violence was weaker. Possible explanations for the elevated risk of IPV amongst women working from home include increased time exposed to a partner at home and the removal of workplace support structures, including social contacts and a place from which to access support , 17. FurThe association is consistent with a smaller study in the United States which estimated that IPV increased as a result of people staying-at home during COVID-19 . SeveralWe found that there was no relationship between losing employment and experiencing IPV during COVID-19. This finding was unexpected because unemployment has been found to be associated with IPV in other settings , 28. It A strength of the study was that using an online survey allowed a large international sample to be reached rapidly, despite social contact and travel restrictions. The study benefited from using locally driven surveys and having a pre-specified focus on IPV as a primary outcome. IPV was measured using a validated format which, alongside the anonymity of an online survey, promotes IPV disclosure and facilitates comparison with other IPV surveys .The following limitations must be considered when interpreting these results. First, the cross-sectional design means some IPV experiences could have preceded working from home. We speculate that this alternative explanation is less likely because many women started to work from home early in the first wave. A second key limitation is that most countries relied on convenience sampling. This meant the proportion of childless and university educated women was high, which may limit generalisability to countries with lower education rates, and introduce collider bias effects. However, the results were robust to restricting the analysis to the population-representative or quota-based samples, which are less susceptible to selection bias. Thirdly, in all countries only internet users, who are more likely to be young and highly educated than non-users were able to participate, and women whose internet access was monitored by a controlling partner may have been unable or unsafe to participate. We therefore expect IPV prevalence to be underestimated in this study. Fourth, one third of participants had missing data on at least one IPV item during COVID-19. Of these non-responders, 76.3% identified as single, widowed or divorced so may not have perceived the questions as relevant. Fifth, partner characteristics were not measured, but are important for understanding the context of IPV. For example, relational tension and exposure to an abusive partner could be exacerbated if the partner’s work is also disrupted. Finally, although the overall number of participants is large, few were from low-income countries. Since resilience to employment shocks is lower in developing countries, and working from home is less common in these locations (Appendix I), the association with IPV may differ in these settings .Understanding risk factors for IPV is an important step in developing interventions to prevent violence. A review of reviews revealed that successful interventions aim to address IPV risk factors, including societal expectations around violence and gender relations, as well as providing support to survivors . InterveIn conclusion this analysis provides evidence that working from home during COVID-19 was associated with higher IPV during the pandemic among cis-gender women. During COVID-19 restrictions or other pandemics, workplaces should work with legal, health and social services to strengthen support offered to staff at risk of IPV . Yet, ofBelow is the link to the electronic supplementary material.Supplementary Material 1


Background—Patients affected by Long COVID often report shorter times spent doing physical activity (PA) after COVID-19. The aim of the present study was to evaluate potential associations between PA levels and parameters of physical function in a cohort of COVID-19 survivors with post-acute symptoms, with a particular focus on individuals aged 65 and older. Materials and methods—PA levels before and after COVID-19 were assessed in a sample of patients that had recovered from COVID-19 and were admitted to a post-acute outpatient service at the Fondazione Policlinico Universitario Agostino Gemelli IRCCS . Participation in PA was operationalized as the engagement in leisure-time PA for at least 150 min per week in the last 3 months. Self-rated health and measures of physical performance and muscle strength were assessed. Results—Mean age of 1846 participants was 55.2 ± 14.4 years and 47% were women. Before COVID-19, inactivity was detected in 47% of the whole study population; only 28% maintained pre-COVID-19 PA engagement. Inactivity was more frequent in women. The stopping of physical activity was associated with increased BMI and CRP levels, lower vitamin D levels and a higher prevalence of post-COVID-19 fatigue, dyspnea, arthralgia, and myalgia. Active participants had higher handgrip strength and performed better on both the six-minute walking test (6MWT) and at the one-minute sit-to-stand test (1MSTST). In particular, at the 6MWT, participants 65 and older that were still active after COVID-19 walked 32 m more than sedentary peers. Moreover, the distance covered was 28 m more than those who were active only before COVID-19 (p = 0.05). Formerly active subjects performed similarly at the 6MWT to inactive participants. PA was associated with better self-rated health. Conclusions—Our findings reveal that inactivity is frequent in the post-acute COVID-19 phase. Stopping physical activity after COVID-19 results in measures of performance that are comparable to those who were never active. Relevant differences in the distance covered at the 6MWT were found between older active subjects and their sedentary peers. Physical activity (PA) represents one of the major determinants of health worldwide . StartinPA plays a role in modulating the immune system, and the exercise-induced anti-inflammatory response seems to be one of the mechanisms implicated in the protective role of PA against several conditions, including infectious diseases . A recenDuring the COVID-19 pandemic, measures taken by governments to control the SARS-CoV-2 transmission have changed the lifestyle habits of millions of people worldwide . If compLittle is known about the role of PA in the post-acute phase of COVID-19. Patients affected by Long COVID, which is characterized by long-lasting symptoms . ReducedThe aim of the present study was to examine the prevalence of physical activity levels before and after the viral infection in a cohort of hospitalized or home-managed COVID-19 survivors with post-acute symptoms, and its association with measures of physical performance, muscle strength, and self-rated health. The Gemelli Against COVID-19 Post-Acute Care (GAC19-PAC) project is an ongoing initiative developed by the Department of Geriatrics, Neuroscience, and Orthopedics of the Catholic University of the Sacred Heart  to analyze long-term sequalae of COVID-19 and their impact on overall health, quality of life, and physical/cognitive performance. The post-acute outpatient service, called “Day Hospital post-COVID-19”, has been established in April 2020 at the Fondazione Policlinico Universitario Agostino Gemelli IRCCS  for people who have recovered from COVID-19 .The study population included individuals aged > 18 years old that have officially recovered from COVID-19 and have been admitted to the post-COVID-19 outpatient service between 21 April 2020 and 31 December 2021. At the moment of the evaluation, all patients met the World Health Organization (WHO) criteria for discontinuation of quarantine .Patients were offered a comprehensive medical assessment. Clinical parameters, anthropometric measures, medical history, current medications, and lifestyle habits including physical activity, were collected in a structured electronic database. Long-term symptoms of SARS-CoV-2 infection were evaluated with a multidisciplinary approach ,27,28,29Body weight was measured through an analogue medical scale. Body height was measured using a standard stadiometer. Body mass index (BMI) was defined as weight (kilograms) divided by the square of height (meters). COVID-19 severity was considered as follows: (1) no hospitalization; (2) hospitalization with no oxygen supplementation; (3) hospitalization with low-flow oxygen supplementation; (4) hospitalization with noninvasive ventilation (NIV) or ICU admission with invasive ventilation.Symptoms that arose during or immediately after the SARS-CoV-2 infection and persisted at the time of the evaluation have been included among sequalae of acute COVID-19. All participants were interviewed concerning their usual physical activity levels prior to acute SARS-CoV-2 infection and at the time of the evaluation. Regular participation in physical activity was operationalized as the engagement in aerobic PA, associated or not with resistance training, for a minimum of 150 min per week in the last 3 months . ConsequVitamin D, plasma albumin, C-reactive protein (CRP), and hemoglobin levels were detected using standard biochemistry methods on fully automated testing systems.Upper extremity muscle strength was measured by handgrip strength testing using a North Coast hand-held hydraulic dynamometer  . After oPhysical performance was evaluated by the one-minute sit-to-stand test (1MSTST) and the six-minute walking test (6MWT). These tests are commonly used to assess exercise-induced respiratory impairment . For theA visual analog scale (VAS) was used to rapidly assess self-rated health on a scale from 0 to 100, with 0 corresponding to the worst perception of health status and 100 indicating the best imaginable health .t test statistics (p for trend), respectively. Continuous variables were expressed as mean ± standard deviation (SD), and categorical variables were expressed as frequencies by absolute value and percentage (%) of the total. Descriptive statistics were used to describe clinical characteristics of the study population according to physical activity levels. Differences in the proportions and means of covariates between study participants across different physical activity categories were assessed using Fisher’s Exact Test and Analysis of covariance (ANCOVA) was used to examine the association between physical activity levels and measures of physical performance, muscle strength, and self-rated health, after adjusting for potential confounding variables. Variables considered as covariates were chosen according to their clinical significance and/or their significant difference at the univariate analyses between inactive, formerly active, and active participants. The interactions of covariates on the relationship between physical function’s measures and physical activity levels were tested by adding the interaction term into the adjusted models. No significant interactions were reported.All analyses were performed using SPSS software . Between April 2020 and December 2021, 1921 individuals were admitted to the post-COVID-19 outpatient service. For the present study, 75 subjects were excluded for missing values in the variables of interest; thus, a sample of 1846 subjects was considered. The mean age of the study sample was 55.2 ± 14.4 years (range 18–86) and 47% were women. Characteristics of the study population according to physical activity levels are summarized in Inactive people were 47% of the whole study population; 53% were physically active before COVID-19, but only 28% maintained usual physical activity levels at the moment of the evaluation . In partp = 0.1). COVID-19 severity had the same distribution in the three groups of interest , except for those who needed invasive ventilation, in which the percentage of inactive subjects was higher (p = 0.01). Compared to active participants, subjects in the inactive and formerly active groups were older and had a higher prevalence of hypertension, diabetes, and chronic obstructive pulmonary disease (COPD). The highest prevalence of unemployed individuals was found in the active group, while retired people were more common in the other two groups. Active and formerly active groups presented the same percentage of people occupied as housewives and declared a similar number of kids. Post-acute COVID-19 fatigue and dyspnea were less common amongst active individuals. Persistent arthralgia and myalgia were more common in formerly active participants. Formerly active and active subjects, especially those who maintained usual levels of PA after COVID-19, showed lower BMI and C-reactive protein (CRP) levels, and higher vitamin D levels. The average number of days from COVID-19 diagnosis to admission to the outpatient service were similar between inactive and active subjects . Sedentary habits of inactive and formerly active individuals were associated with a similar distance covered at the 6MWT. Older people who were still active reported better scores of self-rated health compared to all inactive subjects.Unadjusted and adjusted ANCOVA models were performed to evaluate the association of physical activity levels with measures of physical performance, muscle strength, and self-rated health . In the In the present study, we investigated the prevalence of PA in post-acute COVID-19 patients and its potential association with functional parameters. The proportion of inactive subjects in our cohort of COVID-19 survivors with persistent symptoms was higher compared to the healthy Italian population before the pandemic  . We found that inactivity after COVID-19 was more frequent amongst women, although these results were not explained with major engagement in job and/or home responsibilities . Most likely, women experience post-acute COVID-19 symptoms more than men ,37. FreqLombardo et al. have shown that the incidence of post-COVID-19 fatigue, dyspnea, and joint-muscle pain is lower at young ages (<47 years old), but it tends to be similar among adults (47–58 years old) and older adults (>58) [We found no substantial differences in the prevalence of inactivity after COVID-19 according to age. ts (>58) .Our findings revealed a positive trend in BMI and CRP levels from sedentary to active subjects. It is noteworthy that—as a consequence of unhealthy dietary habits and reduction in PA—many adults gained weight during lockdown restrictions . MoreoveVitamin D levels were higher among physically active participants, particularly in those who did not stop practicing physical activity after COVID-19. Consistent with our findings, a correlation between normal vitamin D levels and habitually practicing PA has been identified in a cohort of 86 forensic inpatients . HoweverIn the present investigation, we found that PA was associated with better physical performance and higher values of muscle strength. Differences in the distance covered during the 6MWT were found particularly in the older subgroup, in which active participants walked 32 m more than inactive peers and 28 m more than formerly active subjects. According to Bohannon and Crouch, a minimum change of 30.5 m in the distance covered at the 6MWT may be considered clinically meaningful . These rIn our sample, physically active participants declared better self-rated health. Older subjects who maintained usual PA levels after COVID-19 manifested better scores on their quality of life than sedentary participants. Several RCTs found that changing the PA regimen may reduce psychological distress and improve the quality of life among community-dwelling older adults ,63. ConsMaintaining usual PA levels after the infection is crucial. Lockdown restrictions and the fear of contagion have influenced choices about the well being of millions of people worldwide. The large cohort of Long COVID patients enrolled, and the attempt to emphasize the potential role of PA and persistent symptoms, including fatigue, in determining muscle function in the post-acute phase of the infection represent the strengths of this study.Some methodological issues should be taken into account in the interpretation of the results. A major limitation of cross-sectional studies is the lack of longitudinal data that capture changes on an individual level over time, thus not allowing a thorough follow-up of post-COVID-19 symptoms and PA levels. The observational nature of our study design prevents the evaluation of cause-effect relationship between sedentary habits and poor physical function in patients with Long COVID. Therefore, we cannot assert whether persistent symptoms influence physical performance more than PA levels.Furthermore, information about the type, volume, and intensity of activity practiced before COVID-19 and/or maintained after COVID-19 were not assessed. Data on dietary habits and physical function before COVID-19 that may have influenced patients’ health status and physical function after the infection were not available. Moreover, our sample included predominantly symptomatic patients attending a post-COVID-19 outpatient service, which may induce a selection bias. Indeed, we cannot determine if further factors might be implicated in the deterioration of physical function after COVID-19. The involvement of different anatomical districts that follows the SARS-CoV-2 infection shows us the complexity of this illness and the difficulty in understanding the pathogenesis of long-term sequalae. Finally, the long period of enrollment does not allow us to distinguish whether specific SARS-CoV-2 variants might have influenced post-COVID health status more than others, although following the spread of variants in Italy during this period of time, our sample is unlikely to contain individuals infected with the omicron variant, which is likely the variant associated with a fewer number of persistent symptoms .In conclusion, we analyzed the prevalence of physical activity levels and its association with parameters of physical function in a sample of COVID-19 survivors with post-acute symptoms. We found a high prevalence of inactivity after COVID-19, especially in women. Lower BMI and CRP levels, and higher vitamin D levels were more common in active people. Post-acute COVID-19 symptoms were less frequent in active people. Being physically active, particularly after COVID-19, was associated with better performance on the 6MWT, a higher number of repetitions at the 1MSTST, and higher values of handgrip muscle strength. Differences in the distance covered at the 6MWT were relevant between active and inactive older people. We found that formerly active subjects performed similarly to habitually sedentary subjects. Moreover, physical activity was associated with higher values of self-rated health.  Future studies are warranted to further assess associations between physical activity levels and muscle function in the post-acute COVID-19 and to evaluate whether improving exercise training may ameliorate functional outcomes after the SARS-CoV-2 infection.


Because severe acute respiratory syndrome coronarivus 2 (SARS-CoV-2) leads to severe conditions and thrombus formation, evaluation of the coagulation markers is important in determining the prognosis and phenotyping of patients with COVID-19.In a prospective study that included 213 COVID-19 patients admitted to the intensive care unit (ICU) the levels of antithrombin, C-reactive protein (CRP); factors XI, XII, XIII; prothrombin and D-dimer were measured. Spearman’s correlation coefficient was used to assess the pairwise correlations between the biomarkers. Hierarchical and non-hierarchical cluster analysis was performed using the levels of biomarkers to identify patients´ phenotypes. Multivariate binary regression was used to determine the association of the patient´s outcome with clinical variables and biomarker levels.The levels of factors XI and XIII were significantly higher in patients with less severe COVID-19, while factor XIII and antithrombin levels were significantly associated with mortality. These coagulation biomarkers were associated with the in-hospital survival of COVID-19 patients over and above the core clinical factors on admission. Hierarchical cluster analysis showed a cluster between factor XIII and antithrombin, and this hierarchical cluster was extended to CRP in the next step. Furthermore, a non-hierarchical K-means cluster analysis was performed, and two phenotypes were identified based on the CRP and antithrombin levels independently of clinical variables and were associated with mortality.Coagulation biomarkers were associated with in-hospital survival of COVID-19 patients. Lower levels of factors XI, XII and XIII and prothrombin were associated with disease severity, while higher levels of both CRP and antithrombin clustered with worse prognosis. These results suggest the role of coagulation abnormalities in the development of COVID-19 and open the perspective of identifying subgroups of patients who would benefit more from interventions focused on regulating coagulation.The online version contains supplementary material available at 10.1186/s12959-023-00524-0. According to disease severity, excessive production of thrombin, damage to the endothelial cells, inhibition of fibrinolysis, activation of the complement pathway, deposition of microthrombi and microvascular dysfunction, are characteristics of COVID-19 patients . PatientExcessive inflammation caused by SARS-CoV-2 systemically activates blood clotting, probably due to the release of von Willebrand factor (vWF) and increased endothelial cell surface expression of adhesion molecules, favoring thrombus formation –11. ConsElevated levels of clotting markers are important for determining the prognosis of patients with COVID-19, as infection with SARS-CoV-2 can lead to severe conditions and thrombus formation , 15. AssPatients with COVID-19 have high D-dimer levels, prolonged prothrombin time (PT) or activated partial thromboplastin time (aPTT), decreased factor V activity, and hypofibrinogenemia –21. A reThe present prospective cohort study of hospitalized COVID-19 patients aimed to verify the following hypotheses: a) patient clustering of non-conventional coagulation parameters is predictive of in-hospital survival, and b) these biomarkers can be used in combination with conventional clinical parameters in the prognostication of in-hospital survival.A prospective cohort study was conducted on patients admitted to two tertiary hospitals in southern Brazil between June 2020 and November 2020. The study was approved by the Institutional Review Board of each institution. In addition, all patients or their surrogates provided written informed consent before their inclusion in the study.The study sample consisted of all consecutive patients admitted to the intensive care unit (ICU) of participating hospitals from June 2020 to November 2020.Patients aged > 18 years who were diagnosed with COVID-19 through reverse transcriptase reaction or rapid antigen test and required supplementary oxygen  class 4), noninvasive ventilation (WHO class 5), or invasive mechanical ventilation (WHO class 6) due to COVID-19 pneumonia were included in the study. By contrast, patients with severe chronic diseases  or diseases that alter the inflammatory response, such as those with long-term use of immunosuppressants, with cancer without disease control, with human immunodeficiency virus infection without disease control, and who received palliative care, or with a life expectancy of less than 24 h as judged by the attending physician were excluded.After patient inclusion, venous blood samples were collected within 24 h after ICU admission; meanwhile the sociodemographic and clinical information was collected directly from the patient, their surrogate, or the electronic medical records. The levels of CB ; factors XI, XII, and XIII; and prothrombin) were measured using the Coagulation 6-Plex Human ProcartaPlex Panel 1 (Cat. #EPX060-10824–901), from Thermo Fisher Scientific,  in a Luminex MAGPIX® system . Final protein concentrations were calculated using the online Procarta Plex Analysis Application (Thermo Fisher Scientific) and expressed as arbitrary units from the reference plasma. Additionally, as a conventional coagulation biomarker D-dimer was measured using an ELISA kit according to manufacturer instructions . K-means clustering analysis was performed to assess for CB clustering, which was subsequently related to the outcome. Multivariate binary (logistic) regression was used to determine the association of the patient´s outcome with other independent variables, conceptually divided into core demographic (age and sex) and clinical prognostic factors  score, and body mass index (BMI)), hitherto denominated “core predictors”, and the aforementioned CB. The latter were categorized into quintiles owing to their highly non-normal distributions, with missing values fitted as an additional category to avoid the impact of selective dropout. The receiver operating curves (ROC) for core alone and core plus the CB predictors were compared in terms of accuracy, measured by the area under the ROC (AUROC), as well as the sensitivity, specificity, positive and negative predictive values, and likelihood ratios of positive and negative tests. The AUROC was cross-validated on five independent samples to avoid model fitting and evaluation of the same sample. Bootstrap bias corrected 95% confidence intervals (CI) were used to express the AUROC uncertainty.The independent groups were compared using a Mann–Whitney U test or a Kruskal–Wallis test and chi-square test for continuous and categorical variables in the univariate analyses. Spearman’s correlation coefficient was used to assess the pairwise correlations between the numerical variables. A hierarchical cluster of the corresponding correlation matrix was performed to identify the clusters of co-expressed biomarkers. Additionally, a non-hierarchicalData were analyzed using IBM SPSS Statistics version 22.0  and Stata version 13.1  software. The type I error level was set to 0.05 in all statistical analyses.The demographic data, comorbidities, disease characteristics at hospital admission and clinical outcomes of the 213 patients in the analytical sample are listed in Table p = 0.01 and p = 0.013, respectively), being higher in those with less severe types of COVID-19. The levels of prothrombin . Additionally, the levels of antithrombin .First, the differences in the levels of measured CB between the three crescent WHO ordinal scale severities , from 79% (95% CI 73%—84%) to 86% (95% CI 81%—90%). Significant improvements were also observed in the sensitivity value (from 38 to 57% (p = 0.02), positive predictive value (PPV) (from 65 to 81% (p = 0.054), and for likelihood ratios of a positive/negative test (p < 0.001). A two-fold increase in the likelihood ratio of a positive test following the addition of the biomarkers (Table vs 80%—95% CI 72% to 88).We further investigated the diagnostic performance of the CB in the multivariate logistic regression analysis of in-hospital death Table 2, . Adding If the false positive test result ranges from 10–20%, which is considered acceptable in several screening applications, the addition of CB increases the chance of correctly predicting the in-hospital death among COVID-19 patients by approximately 20%-30% compared with the ROC without the CB Fig. 1, .Here, a significant improvement was observed in predicting COVID-19 in-hospital mortality when non-conventional CB were added to the core clinical indicators of disease severity assessed on ICU admission. The significant improvements in various diagnostic parameters, such as sensitivity, PPV, accuracy, and diagnostic odds, indicate the relevant gains in various aspects of predicting in-hospital death. Additionally, two different biomarkers were associated with mortality, and were clustered based on CRP and antithrombin levels. Conventional coagulation parameters, such as D-dimer, were also associated with mortality, but surprisingly did not help to clustering patients in phenotypes.p = 0.068) and prothrombin (p = 0.067) showed a trend to be higher, reinforcing the possible role of a procoagulant state in the progression of COVID-19. However, Ceballos et al. 2021 [From the beginning of the pandemic, blood coagulation, assessed based on the D-dimer levels, has been associated with higher mortality rates . Additioal. 2021  study haal. 2021  divided Another relevant aspect of coagulation disorders and COVID-19 is whether a specific treatment aimed at coagulation would benefit the patients. Early in the pandemic, some authors recommended stratifying doses according to the D-dimer levels or extended post-discharge thromboprophylaxis . ExistinThis study has some limitations. First, the data were collected only from two hospitals in South Brazil, thus multicenter studies are needed to verify the generalizability of the study findings. Nevertheless, many patients with sufficient outcomes  were included to allow robust regression and cluster analyses. Second, only a restricted number of coagulation proteins were analyzed at a single time point after hospital admission, leading to the lack of information on coagulation modifications over time and on more conventional coagulation parameters. However, several studies were conducted in the latter , hence oCB were associated with the in-hospital survival of COVID-19 patients over and above the core clinical factors on admission. Adding these biomarkers significantly increased the sensitivity, PPV, accuracy, and diagnostic odds. Lower levels of some blood clotting factors were associated with disease severity, while higher levels of both CRP and antithrombin clustered with worse prognosis. These results suggest the role of coagulation abnormalities in COVID-19 development and help to identify the subgroups of patients who would benefit more from interventions focused on coagulation.Additional file 1.