Home care personal support service delivery decreased during the COVID-19 pandemic, and qualitative studies have suggested many potential contributors to these reductions. This paper provides insight into the source (client or provider) of reductions in home care service volumes early in the pandemic through analysis of a retrospective administrative dataset from a large provider organization. The percentage of authorized services not delivered was 17.2% in Wave 1, 12.6% in Wave 2 and 10.5% in Wave 3, nearing the pre-pandemic baseline of 8.9%. The dominant contribution to reduced home care service volumes was client-initiated holds and cancellations, collectively accounting for 99.3% of the service volume; missed care visits by the provider accounted for 0.7%. Worker availability also declined due to long-term absences (which increased 5-fold early in Wave 1 and remained 4× above baseline in Waves 2 and 3); short-term absences rose sharply for 6 early-pandemic weeks, then dropped below the pre-pandemic baseline. These data reveal that service volume reductions were primarily driven by client-initiated holds and cancellations; despite unprecedented decreases in Personal Support Worker availability, missed care did not increase, indicating that the decrease in demand was more substantial and occurred earlier than the decrease in worker availability. Personal Support services are the most commonly delivered form of care, representing approximately 80% of all formal home care delivery.3 It has been well-documented that, as in other countries,5 home care Personal Support service delivery volumes in Ontario, Canada decreased during the first wave of the COVID-19 pandemic6; decreasing by 18.9% at the population-level in April 2020 and rebounding to 94% of pre-pandemic levels by September 2020.Home care services are a vital support used by 6% of the Canadian population to enable them to continue to live in their homes and communities while receiving care.79 and home care provider’s choices regarding their engagement with work during this time1012 are not able to speak to the degree of impact of each of these factors on overall changes to home care service delivery volumes.While Sinn et al’s population-level data from Ontario Health’s Home Care Dataset provides an accurate overview of service volumes, it does not provide insight into whether these service reductions were due to client choices to decline home care  or due to decreased availability of home care Personal Support services . Conversely, qualitative studies that have explored client and family concerns about continuing to receive home care during the pandemicThe purpose of this paper is to bridge this gap by providing insight into the source (client or provider) of reductions in Personal Support service provision through the first 3 waves of the COVID-19 pandemic.This retrospective cohort study leveraged longitudinal administrative data from a large home care organization that provides Personal Support services in the Greater Toronto Area of Ontario, Canada to provide an overview of service utilization by clients and the availability of workers to provide this service. The open cohort comprised all clients who were provided with publicly-funded Personal Support services by this organization from August 26, 2019 until June 27, 2021, and all Personal Support Workers involved in providing this care. Approval for this study was provided by the University of Toronto Research Ethics Board (REB# 40086).Client-level data describing service utilization included the number of Personal Support visits provided each week, the start and end dates of any client-initiated service holds, and the dates of any cancelled visits and missed care. Service holds are defined as a client-initiated suspension of home care Personal Support services, whether due to choice or hospitalization. A cancelled visit is recorded when a client chooses to cancel a single scheduled home care visit. In contrast, a missed care event occurs when the organization does not deliver an individual scheduled visit . Client demographics  were used to describe the sample. Client acuity was defined as low, medium or high based on ‘emergency response level’ (urgency of service) scores received as part of the home care service referral package. These scores are determined by the referring Home and Community Care Support Services organization and are designed to support prioritization of care and wellness calls in emergencies.PSW-level data included both demographics (age and sex) and descriptors of workforce participation during the study period, including workforce entry and exit, short-term absences  and longer-term leaves of absence.During each week of the sample, the total authorized service volume  is described in terms of numbers of visits provided and not provided . The volume of service not received during each week of the study is estimated for each client on hold using their average weekly service volumes in the 4 weeks prior to placing a hold. The total volume of non-received service each week is estimated as the sum of non-receipt due to holds, cancelled visits and missed care and is presented as a percentage of the total authorized service volume.The findings are presented as descriptive summaries  and through the presentation of time series plots to summarize changes in service levels and PSW availability.The cohort includes a total of 14 735 clients who were served by 2007 Personal Support Workers. The average client age was 76.9 years (range: 1.3-106.9 years), 65.8% were female. 38.2% of clients were deemed to have ‘high acuity’ , 28.9% to have medium acuity and 27.8% to have low acuity; acuity scores for the remaining 5.1% of clients were not available. The PSWs averaged 45 years of age (range: 18-77 years) and 96.0% were female.Visit volumes decreased throughout Waves 1 to 3, compared to the 6 months prior to the pandemic . For homClient-initiated service holds were the most substantial contributor to the service volume reductions observed during the pandemic periods. As a percentage of the total reduction in service delivery, client-initiated holds accounted for 83.0% of this reduction during Wave 1, 74.3% in Wave 2 and 73.4% in Wave 3 until Jun 27, 2021. Compared to typical pre-pandemic hold rates that accounted for 5.6% of all authorized service, hold levels rose sharply near the beginning of Wave 1 and remained elevated throughout Waves 2 and 3 . This efClient-initiated visit cancellations were the second most substantial contributor to reduced Personal Support visit volumes. Pre-pandemic, an average of 3.1% of visits were cancelled each week . With thMissed care by the organization was the final contributor to lower service volumes, accounting for 0.6% of the overall reduction in Personal Support visit volumes in Wave 1, and 0.7% in each Waves 2 and 3 . In Wave), health-related concerns (though not COVID-19 infection) and a provincial ‘single-site’ policy which prevented PSWs who worked in institutional long-term care from also working in home care. In Wave 2, the proportion of PSWs self-isolating following COVID-19 exposure was also a substantial contributor to leaves of absence. Short-term absences  also rose sharply in the first 6 weeks of the pandemic, but then dropped below pre-pandemic baseline rates.Health system capacity to deliver home care personal support service is typically tied closely to the availability of Personal Support Workers. PSW availability did drop sharply early in Wave 1, but, proportionally, the decline in PSW availability  was lowe6 and internationally5 during the COVID-19 pandemic, but have been unable to provide clarity around the reasons for these reductions. Speculation around reasons for these decreases has pointed to 2 factors identified in the qualitative literature: client choice not to receive service and a shortage of home care workers to provide necessary care  (2021). This home care organization-level data, which reflects similar drops in service volumes to the population-level report provided by Sinn et al, reveals that volume reductions during the first 3 waves of the pandemic were driven heavily by clients’ choices not to receive service, expressed primarily through placing service holds. This decision was made less frequently by clients and families with the most acute service needs, in alignment with the population-level finding that Ontarian home care clients with dementia (who have greater average service needs) reduced their service levels at lower rates than the general home care population (16% vs 19%).6 While home care provider availability is more typically the primary driver of home care service delivery volumes, the reductions in provider availability remained lower than reductions in demand for service through these first 3 waves of the pandemic. This is reflected in the low, stable rates of missed care throughout the study period.Recent publications have highlighted reductions in home care service volumes in Ontario9 In this context, many clients and families decided that the safest option for them was to place their home care services on hold, or to only allow a limited group of familiar home care workers to provide visits and cancel visits for which alternative care providers were scheduled.79 For many families, these decisions to forego publicly-funded care came at significant personal cost to the family caregivers and were not sustainable in the long term.1518 For others, fundamental changes in the work arrangements of family caregivers  may have increased the feasibility of reducing their reliance on paid care.20While the present dataset does not directly address reasons for client choices to decline home care during the COVID-19 pandemic, extensive qualitative literature has identified numerous factors that contributed to these decisions. Fear of infection and a desire to adhere closely to public health advice to reduce contacts where possible have been identified frequently as drivers of these decisions, particularly during the first wave when little was known about the transmission, severity and treatment of COVID-19, and when personal protective equipment was in short supply throughout the world.5 restrictions on worker availability were not a notable driver of reduced service volumes in the present study. While it was less substantial and occurred more slowly than the decline in demand for care, there were notable decreases in the availability of Personal Support Workers, driven primarily by leaves of absence. While the majority of PSWs remained willing to work despite anxiety about contracting and transmitting COVID-19,21 the finding that leaves of absence for PSWs increased 5-fold during Wave 1, affecting nearly one-fifth of this workforce, echoes other literature about the early phases of the pandemic. These leaves were largely driven by lack of childcare (due to school and daycare closures), caregiving responsibilities and fear (either their own or fears expressed by family members) of infection and transmission to vulnerable loved ones.1012 Interestingly, while the rate of short-term absences did rise sharply in the first weeks of the pandemic, it dropped below the pre-pandemic baseline level in mid-April, 2020 and remained below pre-pandemic levels throughout the remainder of the study period. This may have reflected a combination of factors including feeling a duty to work22; restricted travel, appointment and social opportunities related to public health restrictions; broad efficacy of public health precautions; and potentially a ‘healthy worker’ effect as some workers with pre-existing conditions took leaves of absence to reduce their risk of exposure to COVID-19.In contrast with US and Dutch studies,This study used administrative data from a single home care organization and is therefore reflective of how clients and workers experienced this organization’s specific policies, practices and workplace protections. The administrative dataset was captured for service planning rather than research purposes, incorporates inputs from multiple sources  and is not always complete. While the structured data format supports consistency and quantitative analysis, it provides limited insights regarding factors that influenced clients’ decision making regarding their choices to receive or decline service and Personal Support Workers’ decision-making regarding their choices to continue to work or to go on a leave of absence. Additional research will be required to better understand these choices.Home care Personal Support service volumes were much lower in the early phases of the pandemic (Waves 1-3) than before March 2020. Examination of organization-level data reveals that this was primarily driven by clients’ choices to place service holds and cancell service, which aligned with public health guidelines to reduce their contacts and potential exposures. Although there were unprecedented decreases in Personal Support Worker availability, missed care did not increase. This indicates that while both supply of and demand for care decreased in Wave 1, the decrease in demand was more substantial and occurred in advance of the decrease in worker availability. This was fortunate, but by no means inevitable. Further investigation of the factors driving clients’ decisions to place service holds or cancel visits, and contributing to PSWs’ leaves and short-term absences is required to understand how to better support these individuals, inform planning and ensure consistent home care service availability in future crises.


This is paralleled by reduced body weight, ameliorated insulin secretion, increased physical activity, and cognitive eating restraints. Participants with high BMI and insulin resistance have an even larger response, as have non-risk allele carriers for the FTO gene. The findings open a new avenue for scalable lifestyle management with sustained efficacy and highlight a previously unrecognized opportunity for digital precision treatment based on genetics and individual pathophysiology. ClinicalTrials.gov NCT04624321.To address the unmet need for scalable solutions for lifestyle treatment, we developed a new digital method to promote behavioral change. Here we report that patients with type-2 diabetes in Sweden ( Digital tools could enable clinical utility and meet individual preferences in content and timing, but most solutions require coaching, intensified healthcare activities, or user fees, which hinder the broad application. Moreover, there are several critical knowledge gaps2.Lifestyle-related diseases such as type-2 diabetes (T2D) are increasing health problems of large proportions. Structured lifestyle support is a therapeutic cornerstone but is currently offered to less than ten percent of patients because of practical and financial hurdles5. Second, no previous studies have analyzed how the individual pathophysiology or genetic variants influence the metabolic response. Third, it is unclear how digital tools affect concrete behaviors such as physical activity and physiological measures of insulin resistance and insulin secretion5.First, data on long-term efficacy (>6 months) are scarce6. While initial analyses of this intervention have focused on subsets of the most frequent users of the tool6, we here make a full assessment of patients exposed to the intervention over an extensive follow-up of approximately 3 years. This is important since recent meta-analyses have shown declining metabolic response to lifestyle programs already after 6 months, and international guidelines emphasize that more long-term data are needed5. Moreover, to address the current gaps in our understanding of which patients benefit most from digital interventions, we also analyzed the influence of pathophysiological and genetic traits on the response and measured the effects on physical activity, eating behavior, and physiological outcomes, which are largely unknown5.In view of these knowledge gaps and the large clinical need for scalable lifestyle treatment, we have developed a self-managed digital tool that is based on a new approach combining health information with structured self-reflection to effectively promote behavioral changen = 331; Fig. P = 0.009 using an independent t-test; Table Patients with dysregulated T2D (HbA1c ≥ 52 mmol/mol) attended regular visits during a median follow-up of 1038 days  had an even larger metabolic response, with an average HbA1c reduction of 5.5 mmol/mol , as compared with −4.7 mmol/mol (95% CI: −6.6 to −2.9) in those who had a more evenly distributed usage throughout the study. This suggests that patients who have been exposed to the tool get sustained effects on glycemic control long after they stop using it.As adherence to digital interventions can be variable over time7, was improved in study participants compared with controls , which is the major determinant of disease progressionP = 0.008 using paired t-test between first and last measure for each individual with a median 354 days between test and re-test; n = 86). This corresponds to 973 kcal higher energy expenditure related to physical activity per week  without any change in the extent of uncontrolled or emotional eating. The reported usability of the tool was, on average, 70.8 (n = 96), as assessed by the System Usability Scale .Furthermore, eating behavior was studied along three domains: cognitive restraints, uncontrolled eating, and emotional eating9. We observed an association between baseline BMI and change of HbA1c .Studies from individuals at risk for diabetes have indicated an impact of body mass index (BMI) and insulin resistance on the effect of exercise programs, but how the individual pathophysiology influences the response to lifestyle interventions in patients with manifest T2D is unclear10, on the response. The rs1421085 variant of FTO is strongly associated with obesity and has high linkage disequilibrium with several other risk variants10. It was therefore analyzed in 150 of the study participants. Interestingly, the response to the intervention was significantly larger in non-risk allele carriers  compared with heterozygous or homozygous risk allele carriers . The mean difference between the genetic groups was 5.6 mmol/mol (95% CI: 0.5–10.7). Adjustments for baseline covariates indicated that this difference was mainly attributed to higher average baseline HbA1c (65 mmol/mol) and lower baseline score on cognitive eating restraints (2.2 a.u.) in non-risk carriers than in risk allele carriers . The differences for rs1421085 were paralleled by data of another consistent risk variant in FTO, rs9939609 (the variant of FTO that was first associated with obesity11). Non-risk allele carriers for rs9939609 (n = 50) had a 7.3 mmol/mol reduction of HbA1c on average, compared with a 1.9 mmol/mol average reduction in risk allele carriers . This further suggests that carriers of non-risk haplotype for FTO have a greater response to the intervention.The influence of genetic variants on the response to lifestyle interventions is also largely unknown. Since the baseline BMI of the participants was associated with the glucose-lowering efficacy of the tool, we wanted to investigate the impact of the FTO gene, which has the strongest genetic association with obesity13, suggesting broad applicability. The average reduction of HbA1c in patients exposed to the tool was 4 mmol/mol compared with controls, independent of adherence.The digital intervention, with its emphasis on self-reflection, enables a new approach to lifestyle management with sustained efficacy. The present findings extend beyond previous research in digital medicine in three main ways. First, the metabolic improvement was sustained during a median follow-up of three years and was of similar magnitude to common glucose-lowering drugs14, it is of note that participants who ceased using the tool after the first year had sustained reductions of HbA1c during the entire follow-up period, more than a year after their last session. They also sustained improvement of insulin secretion, which is the major determinant of disease deterioration7. In this context, it is of interest that the enhancement of secretory function by pharmacological treatment, such as glucagon-like peptide-1 receptor agonists, is lost almost immediately after treatment discontinuation15.Second, since long-term adherence to lifestyle intervention programs is often variable16. Accordingly, the present data demonstrate improved HbA1c in risk allele carriers for FTO exposed to the intervention. Interestingly, the results also show that participants who do not carry the risk haplotype have an even larger response to the intervention. This was mainly attributed to higher baseline HbA1c and lower cognitive eating restraints in non-risk compared with risk allele carriers. Multiple genetic variants influence metabolic control16, but it is conceivable that individuals with increased genetic risk for obesity are more prone to develop T2D independently of lifestyle, while metabolic control is more related to behavioral factors in non-risk allele carriers, who would consequently benefit more from a lifestyle intervention. It is also of note that previous studies have shown that the risk allele for rs1421085 reduces oxygen consumption and mitochondrial thermogenesis10. The present data represent a step to better understand the heterogeneity of treatment response to lifestyle interventions and help identify those who are most likely to have a pronounced effect. As this could have important clinical and cost-effectiveness implications, future studies should further explore how lifestyle treatment can be personalized based on pathophysiological and genetic characteristics.Third, as there is considerable interest in personalizing the treatment of lifestyle diseases based on pathophysiological characteristics, it is of relevance that both baseline BMI and baseline insulin resistance were associated with the change of HbA1c, suggesting that obese insulin-resistant individuals benefit particularly from the tool. Moreover, it is currently unknown how genetic risk variants influence the response to lifestyle interventions. The FTO region has the strongest genetic association with obesity, and previous studies have indicated that risk allele carriers for FTO benefit metabolically from healthy behaviors such as physical activityParticipants were followed for approximately 3 years, making this one of the most extensive investigations of a digital lifestyle intervention to date. The provision as a stand-alone support under conditions that were as similar as possible to the everyday contexts of the patients increases the general significance of the results by demonstrating what can be expected in real-life situations over extended time. It also means that the tool can be provided at a very low cost.17. In view of those risks, matched controls may enable more stable comparisons. On the other hand, the risk of placebo and selection bias is increased17. To explore the extent to which selection bias or placebo may skew the analyses, the participants were also compared with patients in a longitudinal cohort who underwent metabolic and behavioral assessments during three years without the intervention  to attend regular visits during several years. It has also been shown that individuals randomized to a control group may be affected in unpredictable ways, including changed motivation and expectancy artefacts9, the metabolic improvement in response to the intervention was sustained during the entire follow-up of approximately 3 years. The tool provides a self-reflective approach to lifestyle treatment that has previously been lacking18 and does not require additional healthcare resources, which is often a major hurdle for broad utility. It therefore opens an avenue to address the large unmet need for scalable treatment of lifestyle diseases with sustained efficacy.In summary, this study showed that patients with type 2 diabetes exposed to the digital tool had improved long-term metabolic control. While previous meta-analyses have shown declining effect of lifestyle programs after 6 months6. Briefly, it is based on the theoretical foundation of self-affirmation19 and motivational interviewing20 and implemented as a digital tool to enable broad applicability. The tool is web- and app-based and is used as a stand-alone continuous support without coaches or the requirement of additional healthcare activities.A detailed description of the intervention and its systematic development with patients is described elsewhere19. Self-affirmation theory postulates that perceived threats to one domain  can be managed more effectively by reflecting on strengths in other domains. From that broader perspective, people may regard changes to specific behaviors, such as eating patterns and physical activity, as less threatening to overall self-integrity, leading to a less defensive attitude19. The principles of motivational interviewing were included in the tool to promote reflection on ambivalence and commitment to change, which has been shown to increase intrinsic motivation20. To enable this without a traditional interviewer, the digital tool contains a large number of questions to stimulate self-reflection. Self-reflection has played an important role in, for example, later forms of cognitive behavioral therapy20 but has not been of major focus in diabetes self-management.Self-affirmation theory is based on the observation that people may react defensively when reminded of unhealthy behaviors and therefore reject the informationThe tool is composed of 80 different themes, focusing on diet and exercise but also a range of other areas, including stress management, decision-making, social interactions, loneliness, and the emotional burden of having diabetes.18. All texts were written by scientists specifically for this tool and underwent careful editing for style, tone, and language by a panel of physicians, nurses, psychologists, journalists, and literary experts, followed by final approval for accuracy and clarity by the principal investigator.A theme takes approximately 10–30 min to complete and contains one or more of the following components: self-assessment tests to raise awareness of current behavior, structured methods to promote behavioral change and information on topics of relevance to health and lifestyle-related diseases. Texts are based on international consensus recommendations for lifestyle management6, we also include a set of themes covering the different aspects of existential health that the World Health Organization (WHO) has proposed21. These themes aim to stimulate questions on overall life context and how it relates to current habits and disease coping.The tool is used as a continuous support in daily life without a finite number of sessions. There is a diary function for bookmarking texts, writing comments, and getting an overview of personal progression. Users receive regular email prompts about their next round. The tool also contains video webinars and recordings with scientists in different health areas. Patients use the tool at their own pace. They can follow a prespecified order of themes or complete them at their own preference. The various themes allow users to see how different areas are connected and how problems in one domain, e.g., unhealthy eating, could be managed by changes in other domains, such as stress coping. Since initial patient interviews during the development phase identified a need to frame diabetes management within a larger perspectiveThe tool is maintained and provided via academic institutions . It is technically prepared for multiple languages with a language select function and is currently available in English and Swedish. The tool is constructed to enable large scalability and can be implemented as stand-alone support or combined with other lifestyle management activities. It can be easily accessed directly by patients or healthcare providers.To maintain privacy, healthcare providers are not able to access user data. Technical functions are, however, prepared to enable users to download a report of their personal questions and reflections in case they wish to share all or parts of their activities on the tool with healthcare professionals to facilitate consultation .6. Here we report the full long-term analysis of participants. The change of HbA1c in study participants from baseline to end of follow-up (up to 31 Dec 2022) was compared with matched controls on usual care who were followed during a corresponding time period. Usual care refers to routine diabetes management and treatment based on the general guidelines from the European Association for the Study of Diabetes and the American Diabetes Association.We conducted a clinical study  to test the hypothesis that glucose control would improve in patients with type 2 diabetes exposed to the digital tool. In the study, participants were randomized to access the tool or wait for 12 weeks (1:1 ratio). The two groups were then merged to enable all participants to use the tool during an extended open-label period. Previous reports have focused on the early randomized evaluation and initial open-label follow-up of the most frequent usersStudy personnel were instructed to remain neutral at blood sampling visits and not reinforce usage in order to assess the frequency of use and resultant outcomes that can be expected in real-life situations over an extended time without the need for increased healthcare support. Technical problems were referred to a study coordinator, who also responded to requests to clarify content in a general manner without providing personal advice. The study was performed according to the Declaration of Helsinki and Good Clinical Practice. The protocol was approved by the regional Ethics Review committee in Gothenburg and is appended to the paper. All participants provided written informed consent. The tool is provided via academic institutes. The study was conducted by academic investigators, and funders had no role in design, data collection, analysis, or interpretation.Patients older than 35 years with prior documentation of type 2 diabetes and HbA1c ≥ 52 mmol/mol (standard glycemic treatment target according to current guidelines) were eligible for enrolment. Diabetes mellitus was diagnosed in routine healthcare based on the WHO criteria (fasting plasma glucose ≥ 7.0 mmol/l or 2-h post-load plasma glucose ≥ 11.1 mmol/l or HbA1C ≥ 48 mmol/mol). All participants provided written informed consent. Exclusion criteria were: type 1 diabetes, maturity-onset diabetes of the young, secondary diabetes, other conditions, treatments, or participation in clinical studies that, in the judgment of the investigator, could affect the evaluation.Participants were recruited via letters sent to patients with a known history of type 2 diabetes in the All New Diabetics in Scania (ANDIS) cohort or by advertisements. Those who met the study criteria attended regular study visits every third month during the first year and thereafter every 6 months. Each visit lasted approximately 20 min and included blood sampling and anthropometric measurements.The study center was located at Scania University Hospital, Malmö, Sweden. Participants received travel reimbursement but no other financial incentives. Study participants were managed by their ordinary healthcare providers throughout the study.Controls were selected from patients with type 2 diabetes in the ANDIS cohort. ANDIS was approved by the regional ethics review committee in Lund (584/2006 and 676/2012) and aims to include all incident cases of diabetes in Scania, which is one of the largest regions in Sweden with 1,200,000 inhabitants in both rural and urban areas and a wide distribution of socioeconomic background. Approximately 25,000 diabetic patients (>90% of the estimated number of eligible cases in the region) are included. Most individuals with type 2 diabetes are managed in primary care. Prospective data on metabolic variables and medication are obtained via the Swedish National Diabetes Registry and clinical registries on drug prescription and laboratory tests.The controls were matched exactly with study participants on gender and on Mahalanobis distance based on age (at the index date), body mass index (BMI), and HbA1c. The first possible index date for controls was set to be at least 2 years after the diagnosis date. The index date was selected at random among all registrations meeting the requirements for available follow-up time. Selection of the index date and potential controls were done in a Statistical Analysis System (SAS) program. Balance before and after matching was evaluated using the standardized mean difference.6. These patients were recruited from ANDIS via letters or advertisements by a corresponding recruitment process as the intervention group. They attended visits at similar frequency and interacted with the same study personnel as users of the tool. All patients provided informed consent .In addition to matched controls, the change of HbA1c in the intervention group was also compared with patients in a cohort of 48 patients with type 2 diabetes and baseline HbA1c ≥ 52 mmol/mol that had semiannual visits at the study center for metabolic and behavioral analyses during three years without exposure to the interventionThe following baseline data were collected at the first visit: age, sex, length, body weight, level of education, socioeconomic status, time since diabetes diagnosis, and current glucose-lowering treatment.The primary study variable was HbA1c in blood. Secondary variables included body weight, fasting blood glucose, and homeostasis model assessment-2 estimates of insulin resistance (HOMA2-IR) and beta-cell function (HOMA2-B) based on fasting glucose and C-peptide.Blood samples were taken in the morning (between 7.30 and 10.00). Participants were instructed to be fasted since 10 pm the previous day and to avoid nicotine use the same day and alcohol consumption and strenuous physical activity within 24 hours of the visit. Fasting blood glucose was measured at the study center using a HemoCue Glucose System . HbA1c was analyzed according to the International Federation of Clinical Chemistry (IFCC) standard by a Capillary 3 TERA Haemoglobin A1c Kit. C-peptide was measured on Cobas .HOMA2-IR and HOMA2-B were calculated based on C-peptide concentrations  using the HOMA calculator .22. The questionnaire was completed online at baseline and during follow-up by participants on repeated occasions, and responses were converted to Metabolic Equivalent Task minutes (MET-minutes) per week according to the IPAQ scoring protocol22. MET-minute scores are equivalent to kilocalories for a 60-kg person, and the number of kilocalories was computed from MET-minutes asParticipants completed the International Physical Activity Questionnaire (IPAQ), which assesses intense and moderate physical activity as well as walking during the last 7 days8. Study participants completed it online using a four-point Likert scale, and the items were summed and analyzed along three domains: uncontrolled eating, cognitive eating restraints, and emotional eating.Participants also completed the three-factor eating questionnaire, which is a widely used self-assessment scale to assess various types of eating behavior, including uncontrolled eating, emotional eating, and restrictive eating24.The usability of the tool was assessed by the system usability scale, which contains ten items with a total score ranging from 0 to 100 (with 100 being the highest and scores above 68 considered to indicate good usability)The rs1421085 and rs9939609 single nucleotide polymorphisms of the fat mass and obesity-associated (FTO) gene were genotyped from genomic DNA on an ABI 7900 sequencer (Applied Biosystems).The primary endpoint was the change of HbA1c from baseline to end of follow-up. The tool was provided in addition to current medication (as prescribed by the ordinary physician) and compared with matched controls on standard care. The baseline for study participants was defined as HbA1c before getting access to the tool. The full analysis set in this study includes all participants who have at least one measurement of HbA1c after baseline, independent of adherence, duration of participation, or glucose-lowering medication. Missing data were not imputed. In a supportive analysis, we also adjusted for changes in glucose-lowering medication during follow-up in study participants and matched controls, such that data from the last measurement with unchanged medicines was used in the analysis.The change in HbA1c was compared between study participants and matched controls (1:1 ratio) by a two-sided independent t-test. We needed 142 participants in each group to have 80% power at alpha=0.05 to detect a significant difference between the groups, assuming that the true treatment effect of the tool is 2 mmol/mol with a standard deviation of 6 mmol/mol for the change of HbA1c. A considerable surplus was recruited to account for potential dropouts.t-tests and are presented as averages with 95% confidence intervals.Secondary endpoints included the change of secondary variables from baseline to end of follow-up between the intervention group and controls. For controls, data on body weight was obtained via ANDIS and the Swedish National Diabetes Registry, and data on fasting glucose, HOMA2-IR, and HOMA2-B were obtained from longitudinal measurements of ANDIS patients at the Clinical Research Center, Malmö, Sweden. The differences between study participants and controls were compared using independent Changes in physical activity and eating scores between initial and final tests were analyzed in study participants by paired comparisons and presented as a point estimate with a 95% confidence interval.The association between baseline variables and changes in HbA1c was analyzed using linear regression.Summary statistics are presented as point estimates with 95% CI. The widths of the intervals have not been adjusted for multiplicity. Statistical analyses were performed using SPSS (v26). The study is registered at ClinicalTrials.gov NCT04624321 (10 Nov 2020).Further information on research design is available in the Supplementary information cleanReporting Summary


The standard of care (SOC) for LARS relies on transit control (low-fibre diet); pelvic floor exercises, and medications. Colonic irrigation has recently been evaluated, with promising results5. A newly developed Peristeen® cone catheter  has been designed with specific clinical and anatomical considerations in mind for patients with LARS. This anatomical cannula does not have any inflatable balloon; instead, a cone is used that the patient keeps digital contact with during the irrigation. The aim of this randomized trial was to evaluate the superiority of transanal irrigation (TAI) with the cone catheter against traditional SOC.The incidence of low anterior resection syndrome (LARS) has increased over time owing to an increasing rate of sphincter-sparing surgery6 at least 3 months after stoma closure. After rectal examination and assessment of the anastomosis, patients were allocated randomly to either TAI or SOC alone. All centres had previous expertise in Peristeen® balloon catheter use. The primary objective was to demonstrate the superiority of TAI over SOC in improving the LARS score at 3 months. Secondary endpoints were safety of the device and adverse events, and patient satisfaction rates, including daily time spent on bowel management and Faecal Incontinence Quality of Life (FIQL) scale scores.This multicentre (7 centres) open-label RCT included patients with a low colorectal or coloanal anastomosis who had major LARS (LARS score at least 30)SOC was delivered by the treating physician to every patient based on a pathway of bowel management, including a low-fibre diet, laxatives and/or loperamide, physiotherapy (biofeedback and pelvic floor retraining), and small-volume enemas (over 150 ml). For patients allocated to TAI, specific education and training was undertaken by a dedicated nurse or the treating physician in a consultation dedicated to patient education. Subsequently, irrigations were administered by the patient daily, starting with a maximum 1-litre enema, with a self-reported diary being used to record daily irrigation efficacy.7 with a balloon catheter, it was estimated that 13 patients per group  would give sufficient power to establish superiority. The primary endpoint was LARS score analysed by unpaired t test. Statistical analysis was performed with SAS® version 9.4 .A minimal difference in LARS score of 7 between the TAI and SOC groups was deemed clinically relevant. Based on data from a previous studyFig. 1a). Mean age was 63.1 years. Characteristics of the patients are summarized in Table S1.Some 64 patients with severe LARS were considered eligible. Of these, 32 (22 men) met the inclusion criteria and were randomized. One patient in each group was excluded  (P < 0.001). The comparison between TAI and SOC is summarized in Table 1. The mean LARS score was significantly lower in the TAI group at study termination (P = 0.008). Because of the small number of patients, a sensitivity analysis was performed (Wilcoxon non-parametric test) that confirmed this result. The change from baseline between the treatments was analysed ad hoc using a linear regression model ; this confirmed the superiority of TAI with cone catheter over SOC. The results were particularly significant for leaks and clustering, but there was an absolute improvement in four of five categories of the LARS score (Table S2). The coping behaviour subscale of the FIQL scale showed a difference between groups (P = 0.047) (Table 1).By 3 months, the mean LARS score in the overall population had decreased from 38.3 to 26.5 . During the 3 months, only nine use events were reported: water leakage (2), immediate reuse of cone (3), and low water flow/pressure (4). All patients who used a Peristeen® cone requested to continue with this treatment at the end of the study.A total of 17 adverse events occurred in 14 patients (none severe). Seven events in five patients were related to irrigation pain at the anus (2), and abdominal spasms and transit disturbance during irrigation (5). The mean(s.d.) volume of water used per irrigation per day was 718(135) ml. The time spent on bowel management per day decreased significantly in TAI group as compared to SOC group (7–9.In this study, there was a marked improvement in LARS score in patients using TAI compared with the SOC group at study termination after 3 months. These positive results of TAI with a cone mirror outcomes reported in other preliminary studies with a balloon catheteret al.9 reported a rate of difficulties of 20 per cent for catheter insertion or irrigation even after 12 months. Therefore, using a dedicated anatomical device could improve the ease of use and potentially decrease the drop-out rate. Additionally, all patients allocated to the Peristeen® cone group decided to continue treatment after study termination. This was possibly related to the improvement in symptoms and simplicity of the procedure, with fewer user steps as there was no balloon to inflate.Selection of the best candidates for colonic irrigation is still a matter of debate, and the optimal postoperative period for starting the irrigations has not been clearly defined. In the present study, the majority of patients had chronic LARS, and so future studies should validate earlier use of the device. Education when introducing TAI is crucial, and the use of a cone catheter requires training for patients to orientate the device and maintain the catheter during irrigation. The major advantage is the safety of the anatomical design. Other studies with a balloon catheter have reported greater difficulties with the use of TAI. Pieniowski 11. An audit of the risk of perforation during TAI estimated an average risk of 1 in 167 000 for bowel perforation. This risk could be higher in patients who had undergone pelvic radiotherapy and/or rectal surgery previously, and particularly with a pouch or side-to-end anastomosis12. The Peristeen® cone catheter is therefore suggested as a better option for patients with a history of rectal surgery owing to the anatomical design.The risk of rectal perforation during TAI should be acknowledged. Perforations were reported when TAI was used for other indications, including neurogenic sources of incontinence9. Moreover, the wide range of duration of symptoms could have been a source of bias, and spontaneous evolution influenced the response to management as mentioned by Varghese et al.13. It is generally accepted that LARS symptoms can improve spontaneously over time and then perception of severity could also be modified13. Nevertheless, studies have also reported adverse symptoms and severe impairment of quality of life for as long as 15 years3. The patients enrolled in the present study were all naive to bowel management programmes or colonic irrigations. This probably increased the homogeneity between groups. Finally, the LARS score is a validated, but probably not ideal, tool for assessment of the LARS in all patients; future research, including qualitative assessment and patient-reported outcome, are mandatory to overcome bias owing to the long follow-up period and its impact on the LARS score.Despite these promising results, the present study is limited by the short follow-up of 3 months. These results must be confirmed with longer follow-up to allow conclusions to be drawn regarding the long-term efficacy of TAI and evaluation of the patient’s comfort with the coneznad078_Supplementary_DataClick here for additional data file.


It is characterized by elevated low-density lipoprotein cholesterol (LDL-c) levels leading to premature coronary artery disease. FH can be clinically diagnosed using established clinical criteria, namely, Simon Broome (SB) and Dutch Lipid Clinic Criteria (DLCC), and can be identified using the Familial Hypercholesterolemia Case Ascertainment Tool (FAMCAT), a primary care screening tool.Familial hypercholesterolemia (FH) is predominantly caused by mutations in the 4 FH candidate genes (FHCGs), namely, This study aims to (1) compare the detection rate of genetically confirmed FH and diagnostic accuracy between the FAMCAT, SB, and DLCC in the Malaysian primary care setting; (2) identify the genetic mutation profiles, including novel variants, in individuals with suspected FH in primary care; (3) explore the experience, concern, and expectation of individuals with suspected FH who have undergone genetic testing in primary care; and (4) evaluate the clinical utility of a web-based FH Identification Tool that includes the FAMCAT, SB, and DLCC in the Malaysian primary care setting.This is a mixed methods evaluation study conducted in 11 Ministry of Health primary care clinics located at the central administrative region of Malaysia. In Work stream 1, the diagnostic accuracy study design is used to compare the detection rate and diagnostic accuracy of the FAMCAT, SB, and DLCC against molecular diagnosis as the gold standard. In Work stream 2, the targeted next-generation sequencing of the 4 FHCGs is used to identify the genetic mutation profiles among individuals with suspected FH. In Work stream 3a, a qualitative semistructured interview methodology is used to explore the experience, concern, and expectation of individuals with suspected FH who have undergone genetic testing. Lastly, in Work stream 3b, a qualitative real-time observation of primary care physicians using the “think-aloud” methodology is applied to evaluate the clinical utility of a web-based FH Identification Tool.The recruitment for Work stream 1, and blood sampling and genetic analysis for Work stream 2 were completed in February 2023. Data collection for Work stream 3 was completed in March 2023. Data analysis for Work streams 1, 2, 3a, and 3b is projected to be completed by June 2023, with the results of this study anticipated to be published by December 2023.This study will provide evidence on which clinical diagnostic criterion is the best to detect FH in the Malaysian primary care setting. The full spectrum of genetic mutations in the FHCGs including novel pathogenic variants will be identified. Patients’ perspectives while undergoing genetic testing and the primary care physicians experience in utilizing the web-based tool will be established. These findings will have tremendous impact on the management of patients with FH in primary care and subsequently reduce their risk of premature coronary artery disease.DERR1-10.2196/47911 The data collection for Work stream 3a and 3b was completed in March 2023. Data analysis for Work streams 1, 2, 3a, and 3b is projected to be completed by June 2023, with the results of this study anticipated to be published by December 2023.LDLR, APOB-100, PCSK9, and LDLRAP1) as the gold standard. The findings will also include molecular analysis of the 2 HCAGs (ABCG5 and ABCG8). The full spectrum of genetic mutations in these 6 genes including novel PVs will be identified. This study also included nested qualitative research exploring the experience, concern, and expectation of patients with suspected FH who have undergone genetic testing and also real-time observation of PCPs using the “think-aloud” method to evaluate the clinical utility of the FAMCAT web-based FH Identification Tool in the Malaysian primary care setting. In a nutshell, it is a comprehensive mixed methods study that uses both quantitative and qualitative research methods to answer complex research questions, understand the process, and strengthen the impact evaluation [To the best of our knowledge, this is the first study to assess the diagnostic accuracy of different clinical diagnostic criteria  in identifying FH in the Malaysian primary care setting, with molecular diagnosis targeting the 4 FHCGs (aluation .A previous diagnostic accuracy study that included 755 individuals with an LDL-c level of 4.0 mmol/L or more from secondary care clinics and community health screenings in Malaysia showed that the SB criteria appeared to be the most useful in identifying FH compared with the Japanese FH Management Criteria and the US Make Early Diagnosis to Prevent Early Deaths criteria, when assessed against the DLCC as the gold standard . HoweverRecent studies have shown that NGS is the method of choice ,59 and iThe nested qualitative research exploring the patients’ perspectives while undergoing genetic testing and the PCPs experience in utilizing the web-based tool will add tremendous value in developing a clinical care pathway that is patient-centered . A recenThe findings from this study will be shared through scientific publications, conference presentations, and through a resource impact report with the key stakeholders. The resource impact report will include a patient-centered clinical care pathway that will be implemented by the stakeholders in primary care. FH management training modules for primary care providers will also be developed and delivered through online webinars or face-to-face workshops, to enhance their knowledge and skills in managing FH. Dissemination of knowledge regarding FH and its genetic causes will also be made available to the general public through public health campaigns using various mass media channels and social media platforms. All of these imperative measures will accelerate early FH identification in the Malaysian primary care setting and subsequently reduce the risk of premature CAD.This study has several limitations. First, the selection of sites was limited to the clinics located in the urban and suburban conurbations that can access genetic testing facility at the I-PPerForM Genetic Laboratory. Future research should include a wider selection of clinics including those in the rural parts of Malaysia. Second, only those clinics with EMR were invited to participate as the screening for patients with elevated LDL-c levels was conducted through the EMR. This could potentially cause selection and recruitment bias. To minimize this bias, purposive sampling was conducted by targeting those with the highest LDL-c levels, with study invitations sent to all patients in the highest LDL-c groups of 7.0 mmol/L or more and 6.0-6.9 mmol/L, while an equal number of patients were invited from the lower LDL-c groups of 5.0-5.9 mmol/L and 4.0-4.9 mmol/L.Third, this study will provide insights into the nature of mutations in the 6 targeted genes, but it does not include functional studies to validate the pathogenicity of the potential PV, which is warranted in future studies. The polygenic hypercholesterolemia genes were also not included as they are not within the scope of this study. Therefore, future studies are warranted to evaluate the impact of polygenic hypercholesterolemia genes on patients with clinically suspected FH without any PV. Additionally, the targeted NGS method used in this study was not able to detect large gene rearrangements, which may account for a small proportion of PV in patients with FH ,66.Fourth, the molecular analysis was performed only in index cases. Cascade screening of family members will be conducted and they will be clinically diagnosed with SB or DLCC. Unfortunately, we are not able to offer genetic testing to the family members due to financial constraints and this is also beyond the scope of this study.This comprehensive mixed methods study will provide objective evidence on which clinical diagnostic criterion is the best to detect FH in the Malaysian primary care setting against molecular diagnosis as the gold standard. The full spectrum of genetic mutations in the 6 targeted genes including novel PVs will be identified. Patients’ perspectives while undergoing genetic testing and the PCPs experience in utilizing the web-based tool will be established in this study. These findings will have a tremendous impact in advancing the scientific knowledge and skills on the clinical and genetic diagnosis of patients with FH in primary care and subsequently reduce their risk of premature CAD.