Approximately 40% of Emergency Department (ED) patients with chest pain meet diagnostic criteria for panic-related anxiety, but only 1–2% are correctly diagnosed and appropriately managed in the ED. A stepped-care model, which focuses on providing evidence-based interventions in a resource-efficient manner, is the state-of-the art for treating panic disorder patients in medical settings such as primary care. Stepped-care has yet to be tested in the ED setting, which is the first point of contact with the healthcare system for most patients with panic symptoms.This multi-site randomized controlled trial (RCT) aims to evaluate the clinical, patient-centred, and economic effectiveness of a stepped-care intervention in a sample of 212 patients with panic-related anxiety presenting to the ED of Singapore’s largest public healthcare group. Participants will be randomly assigned to either: 1) an enhanced care arm consisting of a stepped-care intervention for panic-related anxiety; or 2) a control arm consisting of screening for panic attacks and panic disorder. Screening will be followed by baseline assessments and blocked randomization in a 1:1 ratio. Masked follow-up assessments will be conducted at 1, 3, 6, and 12 months. Clinical outcomes will be panic symptom severity and rates of panic disorder. Patient-centred outcomes will be health-related quality of life, daily functioning, psychiatric comorbidity, and health services utilization. Economic effectiveness outcomes will be the incremental cost-effectiveness ratio of the stepped-care intervention relative to screening alone.This trial will examine the impact of early intervention for patients with panic-related anxiety in the ED setting. The results will be used to propose a clinically-meaningful and cost-effective model of care for ED patients with panic-related anxiety.ClinicalTrials.gov NCT03632356. Retrospectively registered 15 August 2018. Panic disorder affects approximately 2% of the general population worldwide , and is International clinical practice guidelines support the use of cognitive behavioural therapy (CBT) and antidepressant medications as first-line treatments for patients with panic disorder –15. CBT A small number of studies have evaluated the impact of educational, pharmacological, and CBT interventions for patients with panic disorder initiated in the ED –21. AlthThe current treatment gap for ED patients with panic-related anxiety constitutes a significant public health problem. It highlights the need to implement targeted early interventions that can improve clinical and patient-centred outcomes while reducing panic-related emergency medicine costs . TailoreThe main objectives of this study are to evaluate the clinical, patient-centred, and economic effectiveness of stepped-care for ED patients with panic-related anxiety, using a randomized controlled trial (RCT) design. The RCT will have two arms: 1) a treatment arm consisting of stepped-care intervention for panic-related anxiety (enhanced care pathway); and 2) a control arm consisting of screening for panic-related anxiety and discharge at the ED . In addition to the baseline assessment, the study will include follow-up visits at 1, 3, 6, and 12 months.Aim 1 (Primary): To evaluate the clinical effectiveness of a stepped-care intervention for ED patients with panic-related anxiety compared to screening alone.Outcomes under Aim 1: The primary outcome under Aim 1 will be clinician-rated severity of panic symptoms, measured using the Panic Disorder Severity Scale (PDSS) [e (PDSS)  and the e (PDSS) . Panic de (PDSS) .Aim 2: To evaluate the patient-centred effectiveness of a stepped-care intervention for ED patients with panic-related anxiety compared to screening alone.Outcomes under Aim 2: We will examine health-related quality of life using the 12-item Short Form Health Survey (SF-12) [ (SF-12) , and the (SF-12) . We will (SF-12) , and heaAim 3: To evaluate the incremental cost-effectiveness of a stepped-care intervention for ED patients with panic-related anxiety compared to screening alone, from the health system perspective.Outcomes under Aim 3: We will calculate the incremental cost-effectiveness ratio (ICER) of stepped-care intervention relative to screening alone, at 12 months from baseline. Direct healthcare costs will be calculated from electronic billing records and the effectiveness of the intervention will be assessed based on the conversion of SF-12 form to a quality of life weight using the Short Form Health Survey 6D (SF-6D) algorithm [lgorithm .clinicaltrials.gov .This 12-month superiority trial will follow a two-stage parallel group multi-site RCT design. Screening will be done at the first stage, followed by baseline assessments and block randomization in a 1:1 ratio to either the screening alone (SCREEN) or stepped-care (STEP) arms at the second stage. Only patients with a confirmed diagnosis of panic-related anxiety will be randomized at stage two. Masked follow-up assessments will be conducted by an independent evaluator at 1, 3, 6, and 12 months , Changi General Hospital (CGH), and Sengkang General Hospital (SKH). All patients will be triaged based on severity using the Singapore Patient Acuity Category Scale . Chest pParticipants will be recruited and assessed for eligibility by clinical research coordinators stationed in the ED during peak operating hours. To reduce the potential for attrition, participants will be given the option of completing follow-up assessments in person or by telephone.Eligible participants at the first stage will be English- or Chinese-speaking men and women aged 21–70 years, who are assigned to triage level 2  or 3 (minor emergency). They will need to present with at least one primary complaint consistent with a possible panic attack . Patients who are initially assigned to triage level 1  and subsequently downgraded to a non-life-threatening condition will also be eligible. We will exclude patients who are assigned to triage level 1 and deemed to have a life-threatening condition, who present with altered mental status  that would impact their ability to provide informed consent, who have symptoms with a clear cardiac or other medical cause (as confirmed by laboratory results and the ED physician), and who are unable or unwilling to complete the study procedures  provide adequate coverage of the core symptoms of panic attacks, panic disorder, and comorbid psychiatric conditions , 2) assess disability and quality of life as well as symptom severity, and 3) have acceptable psychometric properties in English and Chinese. Whenever possible, we chose outcome measures that have been widely used in other clinical trials on panic disorder to facilitate comparison with other studies . In addition to clinician-rated and patient-reported outcome measures, we will collect service-use data from patient medical and billing records, and will ask patients to report on their use of ancillary treatments  and psychotropic medications at each assessment visit.Clinician-rated outcomes: We will use the following clinician-rated assessment instruments to assess the outcomes under Aim 1.Clinical Decision Rule (CDR): The study team has developed a brief 7-item screening tool that can quickly distinguish between ED patients with or without panic-related anxiety [ anxiety . The CDR anxiety .Panic Disorder Module of the Structured Clinical Interview for DSM-5 (SCID): The SCID is the gold standard tool for the reliable diagnosis of Axis I psychiatric disorders in clinical populations [ulations . The stuulations , 43. We Panic Disorder Severity Scale (PDSS): The PDSS is a 7-item semi-structured interview to evaluate panic symptom severity [severity . It contseverity , 44–46. severity .Clinician Global Impression (CGI) severity scale: The CGI is a clinician-rated instrument used to assess global severity of symptoms [symptoms . The CGIsymptoms . Specifisymptoms . The folsymptoms .Patient-reported outcomes: We will use the following instruments to assess the patient-centred outcomes under Aims 2 and 3. All patient-reported outcomes have strong psychometric properties, are available in English and Chinese, and have been used in local studies conducted by the study team.Short Form Health Survey (SF-12): The SF-12 is a reliable and valid 12-item self-report questionnaire that evaluates eight facets of health-related quality of life [ of life , 48. It  of life .Psychiatric Diagnostic Screening Questionnaire (PDSQ): The PDSQ is a reliable and valid self-report diagnostic questionnaire that has been widely used to assess the most common psychiatric disorders in outpatient settings, including major depressive disorder, generalized anxiety disorder, panic disorder, posttraumatic stress disorder, alcohol abuse/dependence, drug abuse/dependence, psychosis, bulimia/binge eating disorder, and somatization disorder [disorder . It inclEuroQoL- 5 Dimension (EQ-5D): The EQ-5D is a patient self-report instrument that evaluates health-related quality of life [ of life  . It incThe decision to step-up interventions for patients in the STEP arm will be guided by remission status as assessed by the PDSS and CGI. Acute remission status is defined by a CGI score of 1 or 2 (no disorder or borderline disorder) and no panic attacks for a one-week period. Full remission is defined by maintenance of this status for two consecutive months . ParticiAll CBT sessions in the STEP arm will be recorded with patient permission. A subset of 20% of the recordings will be reviewed and scored by for adherence to the study protocol using the CBT subscale of the Collaborative Study Psychotherapy Rating Scale (CSPRS), a psychometrically-sound tool for assessing adherence to CBT intervention in clinical trials .Participants in both arms will be involved in the trial for a period of 12 months. Following recruitment at baseline at the ED, masked follow-up assessments will be conducted by an independent interviewer at 1, 3, 6, and 12 months. The timeline of study assessments is shown in Table We will aim to recruit a randomized sample of 212 participants. Sample size was estimated based on change in panic symptom severity with PDSS score at 1-month post-intervention as the primary outcome. Previous studies of the 5-session CBT protocol for patients with panic disorder showed relatively large effect size changes on the PDSS from pre- to post-intervention  (Cohen’shttps://www.r-project.org) and contained within sequential sealed envelopes. We will stratify the participants by the diagnosis of panic attack or panic disorder. Within each stratum, we will apply a permuted block randomization scheme with a block size of 4 and a 1:1 randomization ratio between the screening alone (SCREEN) or stepped-care intervention (STEP) arms. This permuted block randomization will ensure balance in the trial. The randomization block will be generated before commencing the study at the various sites. The study coordinator will proceed to open the randomisation envelopes to reveal the allocation only after a patient has been enrolled in the trial.Patients will be randomly allocated to one of the two arms based on a code generated using the open-source software R  principle. We will employ a mixed model approach to analyse the primary outcome variable, with repeated measurements taken at the 1-, 3-, 6- and 12-month follow-up visits. These models allow for different number of observations per subject, use all available data on each subject, and are unaffected by randomly missing data. We will examine the fixed categorical effects of treatment pathway , visit time , and treatment pathway-by-visit time interaction. The restricted maximum likelihood approach will be utilized for estimation. Significance tests will be based on least squares means using a two-sided alpha = 0.05. Primary treatment comparisons will be contrasts in least squares means between treatment groups at the endpoint visit. The CGI scores and SCID diagnoses will be analysed in a similar fashion. As a follow-up to the ITT analyses, we will also conduct a completer analysis. Participants in the STEP arm who are stepped up to CBT and complete four out of five of the CBT sessions will be deemed completers. Those in the STEP arm who complete the psychoeducation session and are not stepped-up to CBT will also be considered completers for the purpose of analysis.Aim 2: To evaluate the patient-centred effectiveness of stepped-care versus screening alone: We will use the same mixed model approach as outlined under Aim 1 to analyse data from the patient-reported outcomes .Aim 3: To assess the cost-effectiveness of stepped-care versus screening alone from the health system perspective: We will estimate the ICER for the STEP arm participants relative to the SCREEN arm participants at 12 months from baseline. The ICER is calculated as the difference between the costs of the two strategies divided by the difference in their effectiveness. Costs from the health system perspective will be the difference in average costs between those in the STEP and SCREEN arms, based on hospital billing data. The difference in effectiveness will be based on the quality of life weights generated by applying the SF-6D algorithm to scores from the SF-12 survey. The STEP intervention will be considered dominant over SCREEN if it incurs less costs and generates higher quality-adjusted life years (QALYs). STEP will be considered cost effective relative to SCREEN if the ICER is below the cost-effectiveness threshold. We will adopt the National Institute for Health and Care Excellence’s cost-effectiveness threshold of £20,000–30,000 per QALY gained, which roughly translates into $63,313 SGD per QALY gained [Y gained .The Principal Investigator and Co-Investigators will be responsible for data and safety monitoring. The study coordinators will meet with the Principal Investigator fortnightly to provide recruitment updates and to review any adverse events or serious adverse events that occur during the study period. Due to the nature of the study procedures , there is not a high risk of adverse events or serious adverse events. In the case of such events, the Principal Investigator will be responsible for reporting any adverse events to the relevant authorities, regulatory bodies, and institutions as required.The present study will evaluate the clinical, patient-centred, and economic effectiveness of a stepped-care intervention for ED patients with panic-related anxiety. We are aware of no prior studies seeking to evaluate screening and stepped-care for this patient population. In the short term, we expect that expedient care of patients presenting to the ED with panic attack symptoms will lead to improved clinical outcomes  as well as reduced burden on the healthcare system due to reductions in unnecessary recurrent ED visits, investigations, and hospital admissions. In the long term, early identification and treatment of patients with panic-related anxiety may help to decrease waiting times at the ED and increase the availability of beds for patients needing urgent care. For example, a recent study from Taiwan found that psychiatric treatment of patients with panic disorder translated into a 30% reduction in related ED costs . The twoThis trial commenced in June 2018. Baseline recruitment is still ongoing, with a planned end date of February 2023. Follow-up data collection will continue until February 2024.


Most COVID-19 fatalities have occurred among older adults; however, evidence regarding the determinants of SARS-CoV-2 infection in this population is limited. Telephone interviews were conducted in November 2020 with a representative sample of 4400 Italians aged ≥65 years from the Lombardy region. We determined the prevalence of a history of SARS-CoV-2 infection. Through unconditional multiple logistic regression models, we estimated the odds ratios (ORs) of infection and the corresponding 95% confidence intervals (CIs). We further evaluated whether infection was related to a reduction in mental wellbeing. Of the participants, 4.9% reported a previous infection. No significant relationship between sex and infection was observed. Prior infection was less frequently reported in subjects aged ≥70  compared to 65–69 years, with no trend after 70 years of age. Those with at least one chronic condition reported a lower infection rate compared to healthy subjects . Participants who lived alone more frequently reported infection than those who cohabited . Prior infection was related to increased depressive symptoms . This representative study of people aged ≥65 years suggests that in Italy, the oldest subjects and chronic patients less frequently exposed themselves to SARS-CoV-2 infection. During the first wave of COVID-19 contagion, Italy’s Lombardy region faced one of the earliest large outbreaks in Western countries, experiencing high levels of hospital congestion and a considerable COVID-19 fatality rate ,3. By thAccording to the national-level COVID-19 surveillance system, in Italy, by the end of 2020 (before vaccines were available), 96% and 86% of COVID-19-related fatalities had occurred among people aged 60 and 70 years and over, respectively . Indeed,Nonetheless, to date, knowledge about the potential determinants of SARS-CoV-2 infection in this population is mostly based on case series (which are inappropriate for investigating the issue as they do not include a comparison group) or surveys enrolling convenience samples  . The fewWithin the Lockdown and lifeSTyles in Lombardia (LOST in Lombardia) project, this study aims to assess the prevalence of individuals self-reporting a history of SARS-CoV-2 infection and, above all, to investigate its possible determinants in a representative sample of Italian community-dwelling people aged 65 years or older.A telephone-based cross-sectional survey was performed by Doxa, the Italian division of the Worldwide Independent Network/Gallup International Association, and coordinated by the Mario Negri Institute and other Italian universities and research institutions . The LOSParticipants were randomly selected from a list of approximately 30,000 families, representative, by province and size of municipality, of families in the Lombardy region. A quota method was applied to ensure the representativeness of the sample in terms of sex, age, and province of residence. Overall, 10,365 older adults were contacted. Of them, 3705 people refused to participate and 2260 telephone calls were interrupted before the end of the questionnaire, while 4400 people completed the interview (response rate: 42%).The study protocol was approved by the ethics committee (EC) of the coordinating group . All participants provided their informed consent to participate in the study.Participants provided information regarding socio-demographic characteristics ; marital status; and diagnosis of selected chronic conditions before pandemic onset (reference time: November 2019).Anxiety and depressive symptoms were assessed using the two-item generalized anxiety disorder scale (GAD-2)  and the Respondents reported if they had been infected with SARS-CoV-2 since the beginning of the pandemic and the type of diagnosis they received: a positive swab test, a positive serological test, or if they thought they had experienced signs or evident symptoms of COVID-19 without a confirmed diagnosis. We defined this measure as history of SARS-CoV-2 infection.To investigate the determinants of SARS-CoV-2 infection, we estimated odds ratios (ORs) and their corresponding 95% confidence intervals (CIs) through unconditional multiple logistic models. As a sensitivity analysis, we re-ran all the models excluding subjects who reported only signs or symptoms but had not received a diagnosis. We defined a worsening in anxiety and depressive symptoms as any increase in the corresponding scales. All the models were adjusted for sex, age, level of education, province, and number of comorbidities. A statistical weight was applied to all the analyses to guarantee the representativeness of the sample in terms of sex, age, and province of residence.All statistical analyses were performed using SAS 9.4 .In November 2020, out of 4400 participants, 213 (4.9%) reported that they had been infected with SARS-CoV-2. Of the participants, 98 (2.2%) received a diagnosis through a positive swab test, 46 (1.1%) through a positive serological test, and 70 (1.6%) had experienced signs or symptoms without a confirmed diagnosis .p for trend = 0.112). People with diabetes less frequently reported SARS-CoV-2 infection compared to subjects without this disease , whereas people with migraine more frequently reported SARS-CoV-2 infection compared to those without this condition . No trend was observed with an increasing number of chronic diseases  when we included those who had tested positive from a serological test and potentially more than doubled (up to 4.9%) when we included those who had experienced signs or symptoms compatible with COVID-19 without any test confirmation. These results might be explained by the fact that, in Italy, in the early stages of the pandemic, swabs tests were almost exclusively administered to patients in severe conditions, thus excluding a large number of individuals with no or mild signs or symptoms . AccordiWith regard to the determinants of infection, an important clarification must be made. Since COVID-19 is characterized by non-specific signs and symptoms , some ofWe did not observe any significant relationship between sex and SARS-CoV-2 infection, although our data seemed to suggest a marginally higher prevalence of infection in males. This is in line with a recent systematic review , which fWe found a lower frequency of infection in participants aged 70 years or older than in participants aged 65–69 years. This result could be explained by the fact that the latter group included a higher proportion of working subjects, who were more likely to be exposed to SARS-CoV-2 infection because of their more frequent social interactions. In addition, since social isolation increases with age , it is cParticipants residing in the neighboring provinces of Bergamo and Brescia showed a higher infection rate than participants from the Milan province. These results reflect data from seroprevalence studies in Lombardy ,24. In lThe absence of chronic diseases was associated with a higher frequency of infection. This can be explained by the less cautious attitude of this sub-group compared to individuals with at least one chronic condition, who were probably aware of the increased risks they were facing. The presence of specific chronic diseases leads to a depression of the immune system  and an iBoth COVID-19 and Post-COVID-19 Syndrome can occur with migraine ,29; howeA higher frequency of infection was observed in subjects reporting increased depressive symptoms during the pandemic. Evidence from the literature shows that people who suffered from COVID-19 frequently experienced a deterioration in their mental health ,30,31,32Our findings should be interpreted in light of some limitations. The first is that data on diagnostic tests and COVID-19-like signs and symptoms were self-reported, which introduces potential recall bias. Furthermore, it must be noted that the testing capacity in Italy changed during 2020 and that some participants may have experienced an asymptomatic SARS-CoV-2 infection without ever being tested. It must also be taken into account that patients who die from COVID-19 frequently have worse basal clinical conditions compared to healed patients. Moreover, we did not have information on the severity of COVID-19 symptoms for people reporting SARS-CoV-2 infection. We also did not have information on the timing of the SARS-CoV-2 infection. This prevented us from analyzing the relationship with mental health outcomes according to the time since infection. More importantly, as this was a cross-sectional study, we could not establish any causal relationship, although every effort was made to provide a longitudinal context for the analyses. However, to the best of our knowledge, this is the first study to investigate the role of the possible determinants of SARS-CoV-2 infection in older people. We also believe that this study provides useful elements for obtaining a more reliable estimate of the magnitude of the cumulative incidence of COVID-19 in this population than data on swabs alone. Furthermore, we used a large representative sample of the population aged 65 or older from the Lombardy region, and data were collected through a telephone-based interview, which can be considered the most suitable solution for the older population in a pandemic context. During the pandemic, online surveys proved to be an effective tool for overcoming social-distancing measures ; howeverOur results suggest that the oldest old and those with chronic conditions limited their exposure to SARS-CoV-2 infection. Although the COVID-19 fatality rate increases dramatically after the age of 70 , our stu


Kidney transplant recipients are at an increased risk of severe COVID-19-associated hospitalisation and death. Vaccination has been a key public health strategy to reduce disease severity and infectivity, but the effectiveness of COVID vaccines is markedly reduced in kidney transplant recipients. Urgent strategies to enhance vaccine efficacy are needed.Methods: RIVASTIM-rapamycin is a multicentre, randomised, controlled trial examining the effect of immunosuppression modification prior to a third dose of COVID-19 vaccine in kidney transplant recipients who have failed to develop protective immunity to a 2-dose COVID-19 vaccine schedule. Participants will be randomised 1:1 to either remain on standard of care immunosuppression with tacrolimus, mycophenolate, and prednisolone (control) or cease mycophenolate and commence sirolimus (intervention) for 4 weeks prior to and following vaccination. The primary outcome is the proportion of participants in each trial arm who develop protective serological neutralisation of live SARS-CoV-2 virus at 4–6 weeks following a third COVID-19 vaccination. Secondary outcomes include SARS-CoV-receptor binding domain IgG, vaccine-specific immune cell populations and responses, and the safety and tolerability of sirolimus switch.Discussion: Immunosuppression modification strategies may improve immunological vaccine response. We hypothesise that substituting the mTOR inhibitor sirolimus for mycophenolate in a triple drug regimen will enhance humoral and cell-mediated responses to COVID vaccination for kidney transplant recipients.Trial registration: Australia New Zealand Clinical Trials Registry ACTRN12621001412820. Registered on 20 October 2021; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=382891&isReview=true The order of the items has been modified to group similar items (see Kidney transplant recipients (KTRs) are at an increased risk of COVID-19 associated morbidity and mortality, with the combined effects of immunosuppression and prevalent comorbidities contributing to the high rates of adverse outcomes . Meta-anThe development of effective vaccines which target the SARS-CoV-2 spike protein has been crucial to reducing disease burden and the development severe COVID-19 disease . HoweverTo address the inadequate vaccine response observed in KTRs and other immunocompromised groups, additional doses of mRNA vaccine have been recommended. In KTRs, data from a randomised controlled trial suggest that a third mRNA vaccine dose increases the proportion of patients with protective neutralising antibodies to 60%, compared to 25% in the placebo group .Observational data suggests that vaccine responses are significantly affected by immunosuppression regimen. The use of mycophenolate has been identified as a key factor associated with vaccine hypo-responsiveness . Such obThese observations led to recognition of mTOR complex 1 (mTORC1) activity as a key determinant of the effector versus memory fate decision of antigen-experienced T cells following vaccination , 18. SirThe RIVASTIM trials are designed to investigate potential strategies to enhance vaccine immunological responses in KTRs using supplementation of the pre-biotic inulin, or immunosuppression regimen alteration. RIVASTIM-Rapamycin is a multicentre, randomised, controlled trial of immunosuppression alteration in KTRs who have failed to develop vaccine-induced protective immunity to COVID-19, prior to a third vaccination. We hypothesise that cessation of mycophenolate and commencing sirolimus in a 3-drug regimen  will improve the immune response to a third mRNA COVID-19 vaccine.The primary objective is to compare the proportion of participants in each trial arm who develop protective serological neutralisation of live SARS-CoV-2 virus  at 4–6 weeks following a third COVID-19 vaccination. The secondary objectives are to determine whether the sirolimus switch (1) improves the proportion of patients that achieve protective anti-receptor binding domain (RBD) IgG antibody, (2) improves the magnitude of vaccine induced T cell response, and (3) is safe and well-tolerated.RIVASTIM-rapamycin is a multicentre, parallel-arm, randomised, controlled, superiority trial, seeking to examine the effect of ceasing mycophenolate and commencing sirolimus in a 3-drug regimen on the immune response to a third dose of mRNA COVID-19 vaccine in kidney transplant recipients who have failed to demonstrate protective immunity following a two-dose vaccine schedule. KTRs on triple therapy who have received 2-doses of a COVID-19 vaccine will be enrolled and their immune response to vaccination assessed by measurement of serological anti-RBD IgG titre. Those with a satisfactory immune response (anti-RBD IgG ≥ 100 U/mL) will exit the study and be advised to receive a third mRNA COVID-19 vaccination as per recommended guidelines. KTRs who fail to demonstrate protective immunity (anti-RBD IgG <100 U/mL) will proceed to randomisation.Randomisation will occur at a participant level with an allocation ratio of 1:1, stratified by study site and the magnitude of immune response following 2 doses of vaccine . An outline of the trial is shown in Fig. The trial will be conducted at the renal transplant units of two tertiary referral hospitals in Australia: (1) The Royal Adelaide, Hospital, Adelaide, South Australia, and (2) The Royal Prince Alfred Hospital, Sydney, New South Wales.Kidney transplant recipientsAged 18–75 yearsEstimated GFR >25 mL/minSpot urinary albumin to creatinine ratio <100 mg/μmolCurrent immunosuppression regimen comprising tacrolimus, mycophenolate, and prednisoloneTreating nephrologist agrees that patient is suitable for sirolimus maintenance immunosuppressionHave received 2 doses of a COVID-19 vaccine regimen  and have demonstrably not responded (anti-spike RBD IgG antibody titre below 100 U/mL)The inclusion criteria are:Aged <18 years or >75 yearsSignificant kidney dysfunction, estimated GFR ≤25 mL/min or spot urinary albumin to creatinine ratio ≥100 mg/μmolUnable or unwilling to provide informed consent to participate in the trialHave received 2 doses of a COVID-19 vaccine regimen  and have mounted an adequate immune response (anti-spike RBD IgG antibody titre above 100U/mL)Have had documented infection with COVID-19 and/or have detectable SARS-CoV-2 nucleocapsid-specific IgGKnown allergy to or intolerance of sirolimus or everolimusThe exclusion criteria are:The patient’s treating nephrologist will determine participant eligibility and approach the patient regarding their interest in participating in the clinical trial. Trained research staff will then discuss the trial, provide written information, and seek informed consent during a scheduled clinic appointment. All clinical and research staff involved in consent and enrolment have received trial-specific training and adhere to Good Clinical Practice (GCP) requirements.Participants will provide informed consent to the sampling of biological material (blood and stool), which will be deidentified and stored in the secure research facilities of the participating trial sites and may be used for future studies. Consent for the genomic sequencing of stool microbiota is addressed, with the understanding that no human genomic information will be collected.Standard of care immunosuppression for transplant patients consists of a calcineurin inhibitor , an antimetabolite (most commonly mycophenolate), and a corticosteroid (prednisolone/prednisone) . MycopheContinuation of current immunosuppression regimen including mycophenolate, available in the form of mycophenolate sodium or mycophenolate mofetilCessation of mycophenolate, and commencement of rapamycin, available as sirolimus Participants will be randomly allocated to their inclusion in one of two groups:The study products will be provided through the patients’ elected pharmacy. Control arm participants will continue their usual immunosuppression regimen as directed by their treating nephrologist, with standard target trough tacrolimus levels in our institutions ranging from 5 to 8 ng/mL . InterveAll trial participants will receive a third “booster” dose of a COVID-19 mRNA vaccine, either Pfizer-BioNTech BNT162b2  or Moderna mRNA-1273  determined by local practice and vaccine availability. Study participants will receive written pre-vaccination information on the benefits and potential risks and harms of the COVID-19 vaccine and be screened for contraindications to immunisation such as serious adverse events attributable to a previous dose of a mRNA COVID-19 vaccine. All patients will be advised of the need to continue with additional public health measures .Sirolimus has known dose-related adverse effects (AEs). Trough level targets of 6 ng/mL are generally well tolerated . ParticiRIVASTIM-rapamycin uses the combination of tacrolimus and sirolimus to facilitate lower target sirolimus and tacrolimus exposure without an increase in the risk of graft rejection . This reAll participants will continue with usual transplant management as per local standard of care and at the discretion of their treating nephrologist. Any changes to medications will be recorded. Participants will be asked to continue with their usual diet and medications.Following completion of the trial intervention, patients will be contacted within 1 week to monitor for adverse events. In conjunction with their treating nephrologist, patients will be offered continuation of the trial drug regimen or return to their previous immunosuppression regimen. Patients converting back to mycophenolate will have this arranged by the trial team, with usual post-transplant care and follow-up then continuing per routine practice under the guidance of the treating nephrologist. The trial sponsor has indemnity to compensate those who suffer from potential harm from as a result of their participation in the research study.Study participants who returned a positive COVID-19 result during the trial will be managed in consultation with their treating transplant unit as per local best practice. Participants who contract COVID-19 following randomisation but prior to a third vaccination may have their third vaccine dose delayed. Where possible, participants will be asked to continue with their allocated treatment regimens and attend study visits and follow-up. Positive COVID cases will be excluded from the primary analysis as SARS-CoV-2 infection will confound assessment of the primary outcome measure.The primary outcome is the proportion of participants in each trial arm who develop protective serological neutralisation of live SARS-CoV-2 virus  at 4–6 weeks following a third COVID-19 vaccination. The protective level is defined as 20.2% of the mean neutralisation level of a standardised cohort of COVID-19 convalescent individuals. This threshold correlates with 50% protection from infection with SARS-CoV-2  in the general population .2.The proportion of participants in each trial that reach a threshold of serological anti-SARS-CoV-2  RBD IgG antibody ≥ 100 units/mL . This RBD IgG threshold was chosen on the basis of pre-clinical and clinical studies and is consistent with the reported outcomes in published COVID-19 clinical vaccine trials .3.Positive SARS-CoV-2 PCR test, or rapid antigen test in the setting of symptomatic diseaseDetection of SARS-CoV-2 anti-nucleocapsid antibodies at the time of primary outcome assessment.The development of COVID-19 following randomisation, determined by:4.Change in the median magnitude of the SARS-CoV-2 spike-specific, antiviral T cell response prior to and at 4–6 weeks following vaccination, determined as the frequency of cells that secrete IFNγ in response to stimulation with spike-protein -derived peptides.5.Phenotypic and functional characterisation of T and B lymphocyte populations6.Tolerance of sirolimus as determined by drug cessation, drug adherence, and drug-related adverse events including proteinuria, anaemia, leukopenia, rash, mouth ulcers, and pneumonitis.7.Changes in kidney allograft function, determined by serum creatinine, eGFR (CKD-EPI equation), and proteinuriaThe occurrence of biopsy proven acute allograft rejectionThe recurrence of primary kidney diseasePatient-reported quality of life as recorded by the EQ-5D questionnaireAdverse events following immunisation (AEFI) including adverse events of special interest (AESI) will be assessed via phone consultation at 1 week, and again at 4–6 weeks post-vaccination during the final follow-up visit, and include:8.Changes in the community structure, relative abundance, and functional characteristics of the gut microbiome following 4 weeks of sirolimus intervention, determined by 16S-rRNA metagenomic sequencing of participant stool samples.The secondary outcome measures include the following:Participants are followed from the time of enrolment through until study close-out, 1 week following their final assessment visit. The schedule of enrolment, randomisation, interventions, and assessments is shown in Fig. This study aims to enrol 120 patients across both sites, with 60 assigned to the sirolimus intervention group and 60 assigned to control. This will provide 80% statistical power  to detect an absolute difference of 25% in the proportion of patients who achieve the serological neutralisation titre threshold necessary to provide clinical protection from COVID-19 disease, allowing for a 10% drop-out rate.Review of local transplant recipient databases at each trial site. During routine clinical review with their treating nephrologist or transplant centre.Potential participants may have also indicated their interest in trial participation by responding to a QR code displayed during the Transplant Australia COVID Vaccination Update Webinar, broadcast in November 2021.Prospective participants will be identified through the following means:Potential participants will be approached by their treating nephrologist and offered the opportunity to participate in the trial. Prior to enrolling, patients will be provided with written information regarding the rationale behind the trial, the potential risk and benefits of participation, and the personal commitment involved. Recruitment will continue until target recruitment is fulfilled, or until recruitment of dual-vaccinated transplant recipients is no longer feasible, or if delaying a third vaccination becomes no longer ethically permissible due to clinical urgency. Participants will not receive payment for participation.Participants will be randomised 1:1 to either sirolimus (intervention) or mycophenolate (control). Randomisation will occur via computer-generated stratified block randomisation with randomly permuted block sizes of 2, 4, and 6. Stratification will occur by site and the response to a two dose COVID-19 vaccine schedule .The allocation sequence is contained and administered centrally through an external web-based randomisation module contained within a purpose-built Research Electronic Data Capture (REDCap) data management platform. The randomisation algorithm and treatment allocation are not accessible to study investigators or research staff.The allocation sequence will be generated by an independent and blinded statistician. Trained study investigators will enrol participants, at each study site, and will perform randomisation via the web-based platform and assign the intervention to each participant.Given the significant changes in prescribed immunosuppression, neither the study participants nor clinical staff will be blinded to treatment allocation. Scientific staff performing the laboratory assays for primary and secondary outcomes will be blinded to patient treatment allocation.The design is open label with only outcome assessors being blinded so unblinding will not occur.Trial data are collected prospectively by trial staff and entered on to web-based electronic case record forms (eCRF) maintained on a bespoke REDCap database.Clinical and laboratory data are collected by study staff from the participant’s electronic medical record. Safety laboratory tests  and enrolment criteria (anti-RBD IgG) are performed at the hospital laboratory of each study site. Blood samples for immunological assessment will be collected by clinical research staff and processed in the on-site immunology laboratory at the Royal Adelaide Hospital. Estimation of participants’ habitual diet will be captured using a 4-day food diary, completed at the time stool samples are collected. Validated questionnaires are completed by participants to capture health-related quality of life (EQ-5D) information.Participants who withdraw from the study, are lost to follow-up, or permanently discontinue the study intervention will be asked to continue with scheduled study visits and follow-up. Outcome data relevant to the trial will be collected from clinical records unless the participants specifically withdraws consent. Reasons for withdrawal, discontinuation, or deviations from the study protocol will be captured in an eCRF.All study data are collected by trained research staff and entered directly onto study-specific electronic data capture forms created and housed within a secure, web-based data management tool (REDCap). The data capture forms contain inbuilt protections to promote data quality, including range checks for numerical data values, restrictions on alphanumeric entries, and prevention of duplicate records. The RIVASTIM REDCap database is stored on secure servers in an on-site limited access data centre at the Royal Prince Alfred Hospital and operated behind the Sydney Local Health District (SLHD) firewall. All electronic information and transmissions are protected via Secure Sockets Layer (SSL) encryption. Access to the RIVASTIM REDCap database is limited to approved research staff, with individual user authentication and logging of all data entry and modification, and access to restricted modules  privileged. The database in maintained by the SHLD Information and Communication Technology (ICT) Services with regular back-up processes in place.Prior to study enrolment, participants will consent to research staff accessing their electronic medical record to obtain baseline and demographic information, and the results of laboratory assessments. The privacy and confidentiality of screened and enrolled participants will be preserved with all study data stored in the RIVASTIM REDCap database under a unique numerical study identifier. Access to personal identifying information for participant contact and safety will be limited to trial research staff with privileged access to the REDCap database. Privacy mechanisms within the RIVASTIM REDCap database will remove potential identifiers from data exported for downstream analysis.No identifying information or individually identifiable participant data will be reported in publications, presentations, or in any report arising from this study.+ cells will be assessed. The capacity of pre- and post-immunisation serum to induce spike-protein-specific antibody-dependent innate immune responses will be measured.Blood samples will be taken from participants for immunological assessment at randomisation and at 4–6 weeks following vaccination. Blood will be drawn from participants by clinical research staff and collected in 7 × 9mL lithium heparin and 1 × 8mL CAT serum separator vacutainer tubes. Peripheral blood mononuclear cells (PBMCs) will be isolated from whole blood by density gradient centrifugation in Ficoll-Paque and aliquoted and cryopreserved in liquid nitrogen for batch testing. Sera will be aliquoted and stored at -80°C. Phenotypic and functional assessments of vaccine specific T and B-cell responses will be determined using a variety of laboratory techniques including but not limited to cytometric analysis with intracellular cytokine staining and activation-induced marker (AIM) assays and IFNγ enzyme-linked immunosorbent spot (ELISpot) assays. Using participant serum, the titres of SARS-CoV-2 spike-protein-specific IgG and the capacity of participant serum to neutralise SARS-CoV-2 viral entry into ACE2rd vaccine dose. Stool samples will be aliquoted and stored at −80°C until batch testing. Analysis of the faecal metagenome will be performed by comparative sequencing of the 16S-rRNA amplicons (V3-V4 region) to identify changes in community structure, relative abundance, and functional characteristics of the gut microbiome.Stool samples will be self-collected by participants using an at home collection kit  at baseline and at time of 3All biological specimens will be deidentified and labelled with the participants unique study identifier. Stool and blood samples will be stored and maintained in access-restricted laboratory freezers at their corresponding trial site .The primary analysis will be by intention-to-treat, with participants assessed according to their treatment allocation. Participants who develop a positive SARS-CoV-2 PCR result during the study will be excluded from the primary analysis to avoid confounding. A per-protocol analysis will also be reported, with participants who failed to adhere or tolerate sirolimus, and participants who withdrew or were lost to follow-up excluded from the analysis. A sensitivity analyses adjusting for potential confounding may be performed should significant imbalances in baseline characteristics between the treatment groups occur.The primary endpoint is the proportion of patients who achieved a post-intervention serological neutralisation of live SARS-CoV-2 virus  in both groups using the chi-square test. An unadjusted and adjusted relative risk (RR) will be calculated. For the adjusted RR estimate, the primary outcome of a threshold SARS-CoV-2 serological neutralisation titre will be analysed using a log-binomial regression model. The initial immune response to a two-dose vaccine schedule  will be included in the model as a fixed effect, with study site as a random effect.Secondary outcomes will be analysed using univariate and multivariate methods dependant on the outcome type. Baseline characteristics and demographic data will be reported as mean ± SD for normally distributed data and median ± IQR for non-normally distributed data, with categorical variables reported as frequencies. All statistical analyses will be described in detail with arising publications. A two-sided significance level of 5% will be used for all analyses.No interim analyses are planned.Subgroup analyses will be performed to examine for statistical interaction between the treatment arm and (1) initial response to 2-dose vaccine schedule (non-responder or low-responder) and (2) duration between previous vaccine dose  and randomisation. Patients who develop primary COVID-19 infection during the study period will have both primary and secondary outcomes analysed as a pre-specified subgroup analysis.A per-protocol analysis will also be reported, with participants who failed to adhere or tolerate sirolimus, and participants who withdrew or were lost to follow-up excluded from the analysis. Multiple imputation will be used to handle data missing at random from baseline characteristics. Data missing at random for the primary and secondary outcome will not be imputed, with these cases excluded from ITT analysis. If > 10% of the primary outcome data is determined to be missing not at random, a best-worst and worst-best case sensitivity analyses will be performed.The complete trial protocol and statistical code used for analyses will be made publicly available following publication of the primary results. Following publication of all study results, deidentified participant-level data may be made available upon reasonable request to the principal investigator, or in the case of published works, through the corresponding author.The coordinating trial centre is located at the Royal Adelaide Hospital. The Trial Steering committee (TSC) is co-chaired by the Principal Investigator (PI) at each study site and includes the trial associate investigators. The TSC is responsible for the study conception, drafting, and completion of the study protocol and associated documents, recruitment plan, data monitoring and integrity, end point adjudication, and approving publications arising from the study.A data safety monitoring board has not been established and was not warranted in this study, given the short duration of the intervention and follow-up. The TSC is responsible for the scientific integrity of the trial and will monitor safety and operational data and will fulfil reporting obligations to the trial sponsor.All protocol deviations and AEs will be documented, regardless of their potential relationship to the study intervention. AEs will be recorded using an adaptation of the National Institute of Health’s Common Terminology Criteria for Adverse Events by a study team member on an eCRF. Recorded information on each AE will include a descript of the AE, the onset date, duration, the resolution of the AE, the severity and seriousness, any action taken as a result of the AE, the outcome of the AE, and the likelihood of the relationship of the AE to a study intervention. Screening for adverse events will occur during each study visit and during scheduled clinical follow-up with their treating nephrologist and will be captured up to 7 days following the final study visit. Adverse events following immunisation (AEFIs) with the exception of mild and/or short-lived symptoms will be reported to the Therapeutic Goods Administration (TGA). Serious adverse events (SAEs) will be reported to the trial sponsor with 24-h of the study team being made aware of the event.There are no plans for trial audit given the short duration of the trial intervention and follow-up.Amendments to the study protocol will be approved by the human research ethics committee (HREC) at the coordinating trial centre, followed by local site governance prior to implementation. The trial registration information contained with the Australia New Zealand Clinical Trial Registry (ANZCTR) will be updated with any protocol modifications.The results of the RIVASTIM-inulin trial will be published in peer-reviewed academic journals and presented at national and international scientific meetings. Additionally, a lay summary containing the study aim, salient findings, conclusions, and a take home message will be prepared and distributed to trial participants, research staff, and interested members of the transplant community. The lay summary will be distributed via direct approaches to trial participants and be made widely available through electronic media including newsletters, social media, and websites.Interventions to improve COVID-19 vaccine responses in transplants recipients are required. Preclinical studies and observational findings in KTRs suggest that the mTOR inhibitor sirolimus may enable enhanced immunological responses to COVID-19 vaccination, as compared to standard of care immunosuppression which includes mycophenolate.This multi-centre, prospective, randomised, controlled trial has been designed to measure the effect of temporarily modifying maintenance immunosuppression with sirolimus, in conjunction with withdrawal of mycophenolate, on correlates of immune protection from COVID-19. The trial uses a pragmatic, established immunosuppression protocol to boost vaccine responses. Sirolimus is a commonly used immunosuppressant that is well tolerated at trough target levels of 3–6 ng/mL. As such, improved immunity in the treatment arm would provide strong justification for the use of sirolimus switch to enhance vaccine-induced protection against COVID-19 among KTRs.There are limitations to a rapidly designed trial in the context of the COVID-19 pandemic. At the commencement of the trial, Australia had a largely SARVS-CoV2-naïve population with minimal community transmission. However, with the easing of social restrictions and border controls there is increasing community prevalence. Thus, trial recruitment may be limited by the prerogative to not delay booster vaccination in a vulnerable population, and in the loss of potential recruits to either having already had booster vaccination or having developed COVID-19. Additionally, while this study will provide a targeted strategy for immunosuppression modification, it will not be possible to discern the individual contributions of withdrawing mycophenolate versus addition of sirolimus on the immune response.


The ongoing pandemic of coronavirus disease (COVID-19) is a global health crisis that has posed enormous pressure on workers in the health sector (WHS), having a massive impact on their mental health. In this study, we aimed to evaluate the sleep quality of WHS during the pandemic and compare frontline WHS to those who are not directly engaged in the care of COVID-19 patients. This cross-sectional, self-reported online survey assessed the sleep quality of WHS in Austria using the Pittsburgh Sleep Quality Index (PSQI). The same questionnaire was sent out two times. Due to the unequal sample and anonymity of the study participants, we analyzed the data of each time point separate from each other. The first study was conducted in April/May 2020, during the first lockdown in Austria (Study1), and the second study was conducted in July/August 2020, when the social restrictions were loosened (Study2). T-test was used to compare the mean values of PSQI scores between frontline vs. non-frontline WHS, while two two-way ANCOVAs were used to analyze differences in the PSQI mean scores (controlled for age) for male vs. female between frontline vs. non-frontline WHS. During the first lockdown in Austria (Study1) we identified a shorter sleep duration of frontline WHS compared to the non-frontline group, however the difference in global PSQI score between these groups was statistically not significant. In the period after loosened restrictions (Study2) the sleep quality, sleep latency, sleep duration, sleep efficiency and global PSQI score was worse in frontline WHS compared to the non-frontline WHS. Furthermore, female WHS scored higher in the PSQI indicating a worse sleep than male WHS. In addition, nurses and nursing assistants had a higher prevalence of poor sleep quality than other occupational groups. Our results indicate that the COVID-19 pandemic negatively impacts the sleep of WHS, affecting particularly frontline WHS. Preventive interventions aiming to promote good sleep quality in WHS during a healthcare crisis like this pandemic are essential to enhance resilience and mitigate the vulnerability of this specific population. The global ongoing coronavirus disease COVID-19) pandemic is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Up to now, COVID-19 has affected 223 countries and territories worldwide, thus becoming a major global health concern [9 pandemiTo contain the pandemic’s spread, governments worldwide have passed new laws and implemented restrictions on private and public issues. Although, to date, the United States Food and Drug Administration has approved drug treatments for COVID-19 and has authorized others for emergency use during this public health emergency, the most effective weapon that society has against this virus is the prevention of its spread . Hand hyIn Austria, on March 15th, 2020, the government announced a nationwide lockdown, enforced exit restriction, social distancing, and wearing a face mask in public [The rapid increase in the number of patients infected with the virus has placed extraordinary healthcare systems demands worldwide. Medical Staff had to work under enormous care pressure dealing with longer duty hours, work in isolation units, and uncertainty regarding effective disease control . FurtherIt is already known that stress can have consequences on biological systems as well as different aspects of private and work-related life . NeuroenNight shift work seems to play a role in generating stress in the workers. Due to a study among security guards, night-time shift cortisol levels significantly increase before and after the work shifts. According to that, cortisol and blood pressure can be considered sensitive markers of biological responses to severe work stress . In addiThe evolution of the COVID-19 pandemic has forced multiple abrupt adjustment demands in work with homeworking at the beginning of the pandemic and then return to work, mainly due to vaccination of the population. A long prospective study investigated the effect of adaptation demands on an Italian banking group in the job-related framework. Their data showed that massive adjustment demands in work and family routines represented a significant source of stress for workers, regardless of the different pandemic stages . These rResearch on the association between working stress and sleep quality has been limited, despite the growing recognition of the consequences of sleep problems. A relationship between sleep problems and myocardial infarct has been demonstrated . Poor slThere is evidence about the development of sleep disorders due to exposition to socially stressful situations such as wars, economic crises, or public health risk situations –23. AccoTo date, little is known about the effects of the COVID-19 pandemic on the sleep quality of workers in the health sector (WHS). Regarding a recent review on the impact of the COVID-19 pandemic on mental health, health care personnel appear to be at an increased risk of stress-related psychological symptoms compared to the general population . A ItaliBased on the clinical relevance of sleep quality on physical and mental health and the direct exposition of WHS to this public health crisis, we want to expand the existing scant literature about this topic.In this study, we aimed to assess the sleep quality of WHS during the pandemic in Austria, comparing frontline WHS to those not directly engaged in the care of COVID-19 patients (non-frontline WHS).We hypothesized that (1) the COVID-19 pandemic negatively influenced the sleep quality of WHS in Austria. Furthermore, we hypothesized that (2) during lockdown as well as after loosened restrictions, frontline WHS had a worse sleep quality compared to the non-frontline WHS.https://www.limesurvey.org/de). Considering that our investigation included healthcare workers, administrative staff, housekeepers, and technical workers, we used the term "workers in the health sector (WHS)" to describe our sample. Informed consent was given online. Participation in the online survey was voluntary and anonymous. The Medical University of Graz’s ethics committee approved the study in accordance with the current Helsinki Declaration (EK number: 32 329 ex 19/20).An anonymized, self-reported online questionnaire survey was conducted at the Medical University of Graz, Austria, Department of Psychiatry and Psychotherapeutic Medicine, as a part of the study “Psychosocial effects of the SARS-Cov-2 pandemic on workers in the health sector in Austria “. Another research article from this survey has been recently accepted for publication . All empInclusion criteria included voluntary participation (confirmation of the informed consent at the first page of the online survey), pursuing a health profession in Austria and business e-mail availability. Participants who terminated the questionnaire too early did not have a valid data set; thus, they were excluded from the study. The other exclusion criteria included persons who did not have an active employment relationship in the health care system in Austria and those who refused to participate after receiving the invitation. The type of facility affiliated was used as criteria to distinguish between frontline and non-frontline WHS. Frontline WHS were defined as those professionals working in organizations dedicated to the assessment, isolation, and treatment of COVID-19 infected patients. The contact with patients who tested positive for COVID-19 infection occurred either during the daily routines in the clinical care of the infected patients or as part of a medical consult within the framework of general medical care. In comparison, WHS working in other hospital departments not directly involved in COVID-19 treatment were defined as non-frontline group.The first online survey was sent out during first strict lockdown in Austria (from March to April 2020). In the investigation were 160 participants  included. Detailed information about the study procedure and the participants is graphically presented in The second online survey was sent out when the social restrictions were loosened (from July to August 2021). Compared to Study1, in Study2 the number of participants and the diversity of the occupational group was larger. In total 1490 participants were included in the study, 654 of them were directly engaged in care of patients infected with COVID-19 virus (frontline workers), thus 836 belonged to the non-frontline group. A study flow diagram is presented in The current investigation was part of a large-scaled research project and thus contained several questionnaires in German language, however, only some of them were analyzed for the purpose of the current study. The socio-demographic variables, including sex, age, professional background, and type of facility affiliated with, were included in the statistical analysis. Furthermore, the self-reported questionnaire Pittsburgh Sleep Quality Index (PSQI) was used to assess the participants’ sleep quality of the previous month. The questionnaire consists of 19 items, generating seven components that produce one global score . The sevStatisticsThe data were analyzed in IBM SPSS, version 26.0. We calculated the differences between frontline and non-frontline workers cross-sectionally (data from March/April and July/August separately), using Chi-Square Test (χ2), T-test and Mann-Whitney-U-Test. A two-way co-variance analysis (ANCOVA), controlled for age, was used to determine the interaction effect between the independent Study1 and Study2.A total of 160 of the 196 approached participants finished the survey and were included in the analysis. The largest age group were 31-40-year-olds; about 62.50% of all participants were females. Medical doctors  represented 55.00% of the group, followed by the scientific staff with about 41.25%. Furthermore, 32.50% of WHS reported direct contact with COVID-19 patients. The global PSQI score for the entire sample was 4.30 . Furthermore, frontline WHS scored higher than the non-frontline WHS, however, the difference was not statistically significant . A close inspection of the individual components of PSQI showed that the sleep duration of frontline workers in lockdown was significantly shorter than that of the non-frontline group (T(106.80) = -2.77; p = .006).The individual components of PSQI and the differences between frontline WHS and non-frontline WHS are graphically presented in From 1759 participants who initially opened the survey, 1490 completed it and were included for statistical analyses. Nursery staff represented the majority of the group with 730 participants (48.99%), followed by the medical doctors (12.34%). The largest age group in the Study2 was made up of 31-40-year-old and 41-50-year-old participants (both 19.80%), da 17.58% were represented by males and 75.36% by females. In total 43.89% of WHS were engaged in the direct care of patients positively tested for COVID-19. The mean PSQI sum score for the entire sample in Study1 was 4.34 . Furthermore, frontline WHS scored higher than the non-frontline WHS, the difference was statistically significant (T(1080) = -3.662; p < .001). A close inspection of the individual components of PSQI showed that, the subjective sleep quality (T(1252.44) = -3.194; p = .001), sleep latency (T(1174.73) = -2.667; p = .008) and sleep efficiency (T(956.53) = -2.488; p = .013) of frontline WHS was significantly worse compared to the non-frontline group . The indWe used two two-way ANCOVAs to analyze differences in the PSQI mean scores (controlled for age) for male vs. female between frontline vs. non-frontline WHS in both studies. In Study2, we found significant main effects for the variable sex  = 3.69, p < .05) and for the variable frontline vs. non-frontline WHS  = 1.38, p < .05). Women reported higher scores of PSQI than men and frontline WHS reported higher PSQI scores than non-frontline WHS  in Study1 was 12.30% and in Study2 was 18.20%. Frontline WHS had a higher rate of poor sleep quality in both Studies . Based on the professional background, we found that the medical doctors in training and nurse or nursing assistants were more likely to have a poor sleep quality than other groups of WHS. The prevalence of poor sleep in both studies is presented in In this investigation, we focused on sleep quality of WHS during the COVID-19 pandemic in Austria. According to our first study survey, we observed that during the strict lockdown in Austria frontline WHS had a higher global PSQI score than the non-frontline WHS; however, the difference between these groups was statistically not significant. In addition, a close inspection of the individual components of PSQI showed that the sleep duration of frontline WHS in lockdown was significantly shorter than that of the non-frontline group.In our second study we observed closely the sleep quality of WHS four months after the Austrian breakdown after a strict lockdown during times of loosened restrictions. We found a significantly worse sleep quality of frontline group than the non-frontline group. Inspecting the individual components of PSQI, we observed a significantly worse subjective sleep quality and sleep efficiency as well as a prolonged sleep latency of frontline WHS. These results are not unexpected, as other studies showed a high prevalence of poor sleep quality among healthcare workers ,31,32. FIn addition, in our investigation, a direct impact of the working environment and duration of exposition was significant. The mean PSQI score of frontline workers in our second study was significantly higher than the non-frontline counterparts. Our finding is consistent with another study done in China at the pandemic peak in Wuhan in January/Feb 2020. The authors reported that frontline workers had a higher risk of developing mental health problems, including sleep problems than non-frontline workers . In contFurthermore, female WHS scored higher in the PSQI than male workers. Results regarding differences of PSQI scores between men and women are consistent with previous studies ,37. We aSex differences in sleep become apparent after the onset of puberty. The alterations in sleep architecture are associated with normal physiologic periods such as puberty, menstruation, pregnancy, and menopause. Sex steroids appear to influence sleep, as gonadectomy eliminates these differences ,41. AccoIt is already known that women tend to provide much more negative appraisals to emergencies than men . They haNotably, during the first lockdown in Austria (Study1) we found a general shorter sleep duration of frontline WHS. A recent study that evaluated the impact of lockdown due to the COVID-19 pandemic on sleep across several European countries and a South American state found that sleep duration in lockdown increased in the general population but not in health professionals . The chaSleep problems are commonly associated with drug and alcohol use. This association appears to be bidirectional, with sleep problems increasing the risk for developing substance use disorders and substance use leading to problems with sleep . Work acThe results of our study suggest that frontline WHS have been subjected to a tremendous amount of stress related to extensive exposure to new pandemic disease, directly impacting their sleep. The hospital administration should provide optimal working conditions, such as regular working hours with enough breaks, monitor the doctor-patient ratio, and offer educational and training programs to reduce stress among WHS. These preventive interventions would positively affect self-efficacy of WHS, enabling them to maintain stable emotions, promote self-control during pressure and possibly improve sleep quality.This study has several limitations. To avoid possible infections, we used an online survey and self-reported tools. It is always desirable to carry out direct evaluations, although it has not been possible due to the unique circumstances of this pandemic.Furthermore, since participation in our survey was voluntary and anonymous, it was impossible to compare the datasets, even though some subjects participated in both studies. Because of limitations from the work council departments, the online survey had to be short; therefore, we could use only a few standardized questionnaires.In conclusion, we identified a worse sleep quality in frontline WHS compared to a non-frontline group during the COVID-19 pandemic in Austria. Furthermore, female WHS scored higher in the PSQI than male WHS. In addition, nurses and nursing assistants had a higher prevalence of poor sleep quality than other occupational groups.Preventive interventions aiming to promote good sleep quality in WHS during a healthcare crisis like this pandemic are essential to enhance resilience and mitigate the vulnerability of this specific population. Which interventions might be useful and effective has to be proven in further interventional studies in this cohort.S1 File(PDF)Click here for additional data file.S2 File(PDF)Click here for additional data file.


N = 1222) and Australia (N = 1197) that were nationally representative on factors of age, gender, and geographic location. High levels of booster intent were found . Exploratory Structural Equation Modelling (ESEM) revealed three key predictors of the intention to receive a booster vaccine that emerged across both UK and Australian samples: concern regarding the COVID-19 virus, positive perceptions of the COVID-19 vaccines, and the perceived severity of side effects experienced to the last COVID-19 vaccine dose. Several additional factors  were present in the Australian dataset. These findings provide important evidence that targeting psychological perceptions of the COVID-19 vaccine and virus may serve to maintain participation in the COVID-19 vaccination programme, paving the way for future behavioural research in this area.As the global pandemic perpetuates, keeping the population vaccinated will be imperative to maintain societal protection from the SARS-CoV-2 (COVID-19) virus. However, while empirical evidence regarding predictors of the intention to receive a first COVID-19 vaccine has amassed, our understanding regarding the psychological and behavioral drivers of continued COVID-19 vaccination remains limited. In this pre-registered study , factors predicting the intention to receive a COVID-19 booster vaccine were investigated in two adult samples from the UK ( At the time of writing, the SARS-CoV-2 COVID-19) virus has been circulating in the population for over two and a half years and has caused in excess of six million deaths worldwide. The future trajectory of the virus remains unclear, with some hope that it may ultimately reduce to a milder endemic state 9 virus h, continuCurrent evidence demonstrates that the efficacy of COVID-19 vaccines wane over time , with boOver the past few years, considerable empirical evidence has amassed regarding the factors that predict the intention to receive the primary course of a COVD-19 vaccine. Meta-analyses of these data indicate that, beyond basic sociodemographic variables, psychological perceptions comprising concern regarding COVID-19 virus and positive perceptions of the COVID-19 vaccine, as well as situational and contextual factors such as previous COVID-19 infection, and regular experience with the influenza vaccine, are some of the strongest predictors of COVID-19 vaccine acceptance ,14,15,16In the present study, we investigated the psychological and contextual predictors of the intention to receive a COVID-19 booster vaccine in two nationally representative samples that are currently underrepresented in terms of evidence; the United Kingdom  and Australia . As such, we focused on identifying the factors that keep previously vaccinated individuals within a given booster vaccine programme. Given that these factors are psychological in nature, these results highlight potential routes through which behavioural intervention may increase vaccination intention in future.Ethical approval was obtained from the University of Sydney Human Research Ethics Committee  with the research pre-registered (aspredicted#78370 and #81667).N = 1222) was collected between 27 October–8 November 2021 and the Australian sample (N = 1204) between 3–13 December 2021. Inclusion criteria for both studies were: (1) 18+ years of age; (2) currently residing in the target country ; (3) self-reported English fluency; (4) two doses of the primary COVID-19 vaccines on offer at the time of testing ; (5) no COVID-19 booster vaccine. Please note, a minority of respondents in the Australian sample  reported receiving both the Pfizer and AstraZeneca vaccine and were therefore removed from the sample to ensure equivalence with the UK dataset . All participants were paid a nominal fee for their participation (£3.50/$2). It was ensured that participants had no known medical reason  that prohibited them from receiving a booster vaccine.All participants were recruited via Pureprofile, an ISO-certified panel provider, with participants screened for age, gender, and geographic location. Quotas were applied during recruitment to ensure that the samples closely matched national statistics regarding these variables. Data from the UK sample  investigating the effect of an intervention  on booster intentions . Howdefinitely won’t receive a vaccine) to high intention (definitely will receive a vaccine). In the Australian survey, the same primary outcome was measured via a 5-point Likert-type scale .The primary outcome in both studies was the general intention to receive a COVID-19 booster vaccine . In the UK survey this was measured via a 100-point visual analogue scale (VAS) ranging from low , personal vaccine confidence  and confidence regarding others (“How much do you think getting a COVID-19 vaccine for yourself will protect other people in your community from COVID-19?”). Responses were collected via 100-point VAS for consistency with the other measures in the survey. Items were selected when the guidelines were first published and therefore limited psychometric data existed. Based on theory ) and concern regarding the COVID-19 virus  positively predicted Booster Intention. Side effect severity to the second dose of the primary course . Vaccine status (AstraZeneca vs. Pfizer) neared significance, with those receiving the AstraZeneca vaccine reporting numerically higher Intention .The final model (Stage 6) was a good fit for the data  and accounted for 54% of the variance in Booster Intention . The full model is depicted in β = 0.63, SE = 0.03, p < 0.001, 95% CI ) and concern regarding the COVID-19 virus  positively predicted Booster Intention, while side effect severity to the second dose of the primary course . Several additional predictors were retained in the model. As the respondents age  and the number of months since their last COVID-19 vaccine increased , so did Intention. Conversely, self-report familiarity with the side effects of the three COVID-19 booster vaccines on offer decreased Intention . Finally, those who reported receiving the flu vaccine yearly had higher Intentions than those who did not .The final model was an adequate fit for the data on some, but not all, indicators . However, 49% of the variance in Booster Intention could be explained . Similar high rates of acceptance have been reported regarding the primary vaccine course, estimated at 84% (UK) and 82%  in one recent meta-analysis  and 67% Consistent with the results of the present study, positive vaccine perceptions and concern regarding the virus have repeatedly been found to predict the intention to receive the first dose of a COVID-19 vaccination ,34,35,36That trust and importance of COVID-19 vaccination predicted booster intention is consistent with evidence demonstrating that a lack of trust in the COVID-19 vaccines due to the speed of development and approval , or fearConcern regarding infection with the COVID-19 virus, both personally and among close others, also increased booster intention in both UK and Australian samples. This is consistent with previous research concerning COVID-19 booster vaccine intent ,59,60. IFinally, the severity of side effects experienced to the most recent COVID-19 vaccine predicted a decreased intention to receive a booster vaccine in both samples. While one study reported limited association between side effects and booster intentions , severalAn additional four predictors emerged from the Australian sample that were either not predictive  or not measured (regular immunization with the flu vaccine) in the UK dataset. There are several reasons why these results may have been observed. For example, there were seasonal differences between samples, and different cumulative infection rates of COVID-19, with the UK experiencing a far greater number of infections at the time of data collection . ClearlConsistent with results from the Australian sample, perceived familiarity with vaccine side effects have been found to decrease the intention to receive a primary course of a COVID-19 vaccine, with speculation that media discourse and misinformation may exacerbate the perceived risk of vaccination in this instance, lowering intention . ConsistThere are several strengths to the present study, including the recruitment of nationally representative samples from two countries where limited evidence regarding booster vaccine intent presently exists . While oIn summary, the intention to receive a booster vaccine was found to be high in two nationally representative samples drawn from the UK and Australia. Three key variables emerged as predictors: psychological perceptions regarding the COVID-19 vaccine and virus as well as previously experienced side effects. A key insight is that all three variables have the potential to be modulated to encourage continued vaccination. The current research therefore makes a significant contribution to understanding the psychological and behavioural drivers of vaccine intent; a factor which continues to play an important role in the control and management of COVID-19.In summary, while empirical evidence has amassed regarding the predictors of the intention to receive an initial COVID-19 vaccine, our knowledge of the factors associated with continued participation in the COVID-19 vaccination programme remains limited. Specifically, most published research has focused on sociodemographic predictors of COVID-19 booster vaccine intent, with few studies investigating psychological and contextual predictors related to the COVID-19 virus and vaccine. The current study addresses this critical gap in knowledge. The intention to receive a booster vaccine was found to be high in two nationally representative samples drawn from the UK and Australia. Three key variables emerged as predictors: psychological perceptions regarding the COVID-19 vaccine and virus as well as previously experienced side effects. A key insight is that all three variables have the potential to be modulated to encourage continued vaccination. The current research therefore makes a significant contribution to understanding the psychological and behavioural drivers of vaccine intent; a factor which continues to play an important role in the control and management of COVID-19.


Comparing age and sex differences in SARS-CoV-2 hospitalization and mortality with MERS-CoV, seasonal coronaviruses, influenza and other health outcomes opens the way to generating hypotheses as to underlying mechanisms driving disease risk. Using 60-year-olds as a reference age group, we find that relative rates of hospitalization and mortality associated with the emergent coronaviruses are lower during childhood and start to increase earlier (around puberty) as compared with influenza and seasonal coronaviruses. The changing distribution of disease risk by age for emerging pathogens appears to broadly track the gradual deterioration of the immune system (immunosenescence), which starts around puberty. By contrast, differences in severe disease risk by age from endemic pathogens are more decoupled from the immune ageing process. Intriguingly, age-specific sex differences in hospitalizations are largely similar across endemic and emerging infections. We discuss potential mechanisms that may be associated with these patterns. We then leverage the commonalities and differences of these patterns across age and sex for endemic and emerging pathogens to shed light on the underlying immunological mechanisms associated with the burden of the pandemic virus, SARS-CoV-2.Our analysis contrasts three emerging pathogens  with influenza and the endemic coronaviruses. Since our focus is on outcomes following infection, we consider the variability in risk of infection across age  to be secondary to underlying variability associated with severe disease. Put differently, we are assuming that what we observe is a fair reflection of the health outcome of an . 2a–c) and fit generalized additive models with spline terms where outcome data is available in single-year age classes . This approach also allows us to adjust for differences in mortality between pathogens  that affect all age groups and the age structure of the underlying population. We also compare the incidence between males and females .We analysed age and sex data for hospitalization, severe disease (requiring intensive care or resulting in death) and death for SARS-CoV-2 , MERS-CoV (Saudi Arabia), SARS (China), influenza (France and USA), as well as hospitalization for seasonal coronaviruses (Scotland), and all-cause hospitalization (France) and mortality (28 European countries) . While underlying differences in the (often unknown) underlying population attack rates make comparisons in the absolute risk of hospitalization or death difficult across pathogens, examinations into the patterns of disease by age and sex can provide insight into potential mechanisms driving severe disease. For each pathogen, we compare the incidence of hospitalization and mortality within each age-group with the incidence observed in 60-year-olds a–c and fThe relative increase in the pathogen-specific probabilities of hospitalization, severe disease and death are strikingly consistent for older individuals across pathogens as well as with all-cause hospitalization and mortality. For COVID-19 cases over 40 years of age, each additional year of life was associated with a 10.7% (95 %CI: 10.3–11.0) increase in probability of death. This was very similar to SARS , MERS-CoV 7.1%, 6.2–8.0), influenza  and all-cause mortality , and, indeed, the latter has been previously noted .