Physical fitness is needed for canine athletes and working dogs to optimize their performance in various disciplines. Application of resistance on movements causes biomechanical and cardiorespiratory responses to physical exercise. However, there is still a lack of research on the effects of high-intensity resistance exercise on cardiorespiratory fitness components such as heart rate in canine athletes. In this article, we investigate the short-term effects of parachute-resisted galloping on heart rate, running speed and stride frequency. Healthy dogs of various breeds were extensively studied in five experimental single cases. The dogs ran on a straight 200 m course with and without resistive drag force applied by a parachute attached to their harness while heart rate, running speed and stride frequency were measured. Subsequently, the measurements were compared to baseline phases at rest. In the present trials we found that heart rate increases similarly with and without parachute-resistance while dogs galloped at lower speeds and with increased stride frequency with applied drag force. Our findings lead us to suggest that parachute-resisted galloping is a clinically applicable exercise in healthy dogs to achieve instant cardiorespiratory response.Physical fitness is required for canine athletes and working dogs to optimize performance in various disciplines. There is a lack of research on the effects of resistance exercise on cardiorespiratory variables in dogs. The aim of this study was to investigate the immediate effects of parachute-resisted (PR) gallop on heart rate, running speed and stride frequency compared to unresisted (UR) gallop in dogs. Five N-of-1 trials RCTs with alternating interventions were implemented. Dogs ran on a 200 m course with and without resistive force applied by a parachute attached to their harness while cardiac inter-beat intervals (IBI), running speed and stride frequency were measured. The results were visually displayed and interpreted in graphs and percentage of non-overlapping data estimated effect size. Both interventions showed large effects on heart rate compared to resting values. Mean IBI increased (10–17%) during PR gallop compared to UR gallop although this change was small relative to decreased running speed (19–40%) and increased stride frequency (18–63%). Minimum IBI showed no difference between interventions indicating similar maximum heartbeat per minute. In conclusion, parachute-resistance resulted in dogs galloping at lower speeds at the same cardiorespiratory level of intensity, which may be useful in canine physical rehabilitation and fitness training.  Physical fitness is a recognized requirement for canine sports athletes and working dogs to optimize performance in tasks that are presented to them in various disciplines ,2. PhysiRepeated resisted exercise can be used to primarily improve muscular strength, speed, power and cardiorespiratory fitness ,8. The eIn fast gaits, such as in acceleration and suspension gallop, dogs need to generate whole-body muscle power ,14,15 whThe aim of this study was to investigate the immediate effects of parachute-resisted gallop on heart rate (HR), running speed and stride frequency compared to unresisted gallop in dogs. Our hypothesis was that drag force executed by a parachute attached to a galloping dog would decrease inter-beat intervals, i.e., increase the amount of heart beats per minute, decrease running speed and increase stride frequency as compared to unresisted gallop.1-B-A2-C-A3, was implemented [A series of five N-of-1 randomised controlled trials (RCT)  with alternating interventions design; Alemented ,29,30,31lemented ,33,34.All dogs enrolled in the studies were privately owned and prospectively recruited via social media in April 2018. The owners signed an informed owner consent, were informed about the study and possible withdrawal of participation at any time. The study was approved by the Local Ethical Committee in Uppsala (Dnr C17/2016). A total of 44 dog owners reported their interest. Inclusion criterion was body weight 20–40 kg and exclusion criteria were recorded or known diseases or injury in the last three months as well as ongoing medication administration. The owners graded their dog’s likelihood to return to the owner on a given signal, the dog’s ability to gallop 200 m and relax in new environment on an ordinal scale from zero to ten. Five dogs with high owner-reported grades were invited to take part of the study. Two of them declined and were exchanged with other participants.1) and following each phase B (A2) and phase C (A3). The IBI recordings at rest were started when the heart beats per minute did not vary by more than five for three subsequent minutes and were recorded for 30 s. Data collection took place in June 2018 outdoors on a straight 200 m pathway in an enclosed area at a local airport. A 200 m pathway was chosen since the dogs were to run at maximum self-selected speed and for enough time to generate many data points in the time series, while the owner was still in contact with their dog. Temperature, wind speed and humidity were registered from the airport weather station during all trials [Heart rate measured as inter-beat intervals (IBI) (time in milliseconds between cardiac R-peaks) were recorded in all phases with Polar V800 HR monitor and H7 HR sensor ,35,36. Ll trials . The runSubjects were asked to report for attendance on two separate occasions. The first session served to give information about the project and to familiarize the dogs and owners to the equipment. The dogs were examined by a veterinarian following a standard protocol and descriptive data, e.g., weight, body condition score  and muscThe dogs were familiarized to the testing area, the test leaders and equipment. Each owner walked their dog on lead back and forth on the running course together with one of the authors as a warm-up and to optimize the dog’s focus during running.The dog was put in its car cage with the boot cover open and the owner sitting beside the dog while baseline recordings were made. One of the authors walked the dog on lead 200 m away from the owner. The dog started from a standing position and the parachute was held off the ground for the resisted trials. Each owner called their dog on a given signal and the dog was released when the IBI recordings were started  from each dog were plotted against subsequent time during each trial (x-axis). Plotted data were displayed in graphs showing baseline and intervention phases in the randomised order. Data points were connected within time and phase, allowing evaluation of patterns within phases and changes between phases. The graphical displays of IBI data were visually inspected and interpreted based on trendline , mean (changes from one phase to another), latency of change  and shift in level (change in level from the last IBI in one phase to the next) ,29,34,42In addition to the systematic visual analysis, the percentage of non-overlapping data (PND) was incorporated as a statistical measure of effect size of the differences between the alternating interventions ,44,45. TThe series of N-of-1 trials involved five cases of different characteristics such as breed, sex, age and weight . Two of The temperature ranged between 11.9–21.1 degrees Celsius and the wind speed was 4.4 m/s in all five dogs. All dogs were running towards the wind in order to fill the parachute. Humidity was between 31–41% and pressure 1013.5–1021.2 hPa . The weaThe error rates in the IBI series were 0% to 16.7%. Artefacts were present in the intervention phases in four dogs and in various baseline phases in all dogs. All artefacts are displayed in the graphs as missing values .The dogs were running 23–35 km/h in phase B and 14–27 km/h in phase C , Hence, 1 had decelerating trend in all cases except case 2, which was accelerating. The trend in A2 was decelerating in case 1, accelerating in case 2 and 5 and close to consistent in case 3 and 4. A3 had a trend for accelerating IBI in all cases except in case 4 which had a pronounced decelerating slope. Overall, mean IBI was 10–17% increased  in phase C compared to phase B in all cases. Mean IBI was decreasing for each baseline during the trials; 4–25% decrease in mean IBI from A1 to A2 and 9–44% decrease in mean HR from A2 to A3 except in case 4 which had a 54% increase in mean IBI. IBImin did not differ between interventions but IBImax was increased in phase C in all cases by 11–111% compared to phase B.All cases showed a consistency in the overall pattern across phases. There was a rapid change in both B and C phases and the shift in level at point of phase change was downshifted from baseline to intervention phases and upshifted from intervention phases to baseline measurements in all cases. This confirms an immediate effect after the interventions was introduced corresponding to immediate cardiorespiratory effects in both interventions. The shift was greater from baseline to C phase compared to baseline to B phase regardless of the randomisation of the interventions in all cases except in case 2 in which it was the opposite. Trendlines showed very small to small change in slopes in both intervention phases in all cases. The trendline showed decelerating IBI  in phase B in case 1 and accelerating IBI in case 2–5. Furthermore, there was a trend for decelerating IBI in phase C in case 1–3 and accelerating IBI in case 4 and 5. The trends were however very small and could in some intervention phases be seen as close to consistent. The trendlines during baseline had, in contrary, overall higher slopes. A3 had the least non-overlapping data when comparing intervention phases to baseline phases, except in case 4 which had the greatest shift in A3 as previously mentioned , which may limit the measurement of heart rate in dogs. There was however only one data point at 251 milliseconds in our series of N-of-1 RCTs, which strengthens the internal validity. A previous investigation had measured HR up to 237 BPM [The presented studies showed no difference between interventions regarding IBI 237 BPM  with a P 237 BPM . The pre 237 BPM . ArtefacA limitation in these N-of-1 studies is that we had to re-estimate the running times since we were not able to stop the time measurements on Polar V800 instantly after the dogs finished their runs. To estimate the appropriate end of the IBI time series we had to use running time from the 50 m video recording. The video recordings were similar in all five studies and are therefore comparable.Our research presents short-term effects of a novel intervention. The trials were completed without significant training of the subjects, indicating a feasible training method and potential clinical applicability. Parachute-resisted galloping applies to the overload principle which is fundamental in training programs for pet, athlete or working dogs. Short bouts of high intensity physical activity mirrors life and behaviour of dogs. High intensity interval exercise combined with parachute resistance as a novel intervention potentially targets cardiorespiratory capacity, muscle strength and power components of canine physical fitness.In these single case experimental studies presented here we found that parachute-resisted galloping enables similar physiological stimulus and adaptation as compared to unrestricted high intensity galloping when it comes to cardiorespiratory capacity measured as heart rate. Notably the running speed decreased with parachute-resisted intervention in all five N-of-1 RCTs which may indicate that the dogs had to generate great propulsive forces. Drag force elicited by a parachute is related to speed and in these dogs the resistive force possibly decreases with slower self-selected running speed. Hence, the dogs might have adjusted the running speed due to the onset of muscle fatigue and inability of the muscles to generate force and speed of contraction. It was necessary to allow the owners to encourage their dogs throughout the trials. Regardless, the dogs were unable to maintain the same running speed with drag force resistance. This leaves us with several questions that require further investigation regarding long-term effects of parachute-resisted exercise, biomechanical changes, differences in time to full recovery and biomarkers of energy pathways. Finally, parachute-resisted running may be an alternative training method to uphill high intensity interval training. Although, there is a need for shorter diameter parachute equipment for dogs out of various sizes to increase usability of this training method.In conclusion, interval exercise with parachute-resistance at gallop may be beneficial in canine fitness and rehabilitation training to produce slower running speed longer running times and increased stride frequency, at the same cardiorespiratory level of intensity as unresisted high intensity intervals.


Examinations for early detection of diseases  are among the most important prevention measures at childhood age. According to KiGGS Wave 2 data, participation rates are over 95% for most of these examinations. 99.7% and 99.6% of children, respectively, who had reached the recommended age for these examinations participated in the U1 and U2 examinations, 98.0% and 98.1%, respectively, the U8 and U9 examinations. Participation rates for children from families with low socioeconomic status and those with a two-sided migration background are slightly lower. A comparison with previous KiGGS waves shows that the utilization of early detection examinations has increased significantly over the last ten years. During this time, social differences which were previously pronounced have decreased. Examinations for early detection of diseases  are part of the most important prevention measures during childhood. The statutory health insurance catalogue includes the early screening programme which aims to detect development disorders and diseases early and, where necessary, to provide adequate measures for treatment . In addiWhereas the U1 and U2 examinations usually take place within the maternity clinic, the following examinations generally take place at a paediatric or general medical private practice. This article considers the examinations U1 to U9 that are recommended for children up to the age of six. Two further early detection examinations, U10 (7-8 years of age) and U11 (9-10 years of age) are scheduled to take place at primary school age, the J1 (12-14 years of age) and J2 (16-17 years of age) examinations are for adolescents. However, it should be noted that not all statutory health insurers cover the costs for the U10, U11 and J2 examinations.All findings of the early detection examinations are documented in an examination record  that maternity wards or midwives provide to parents immediately after birth. The booklet also contains a detachable card, which practices then use to document the participation in the U2 to U9 examinations by marking the date, and including the practice’s stamp and signature. Early detection examinations are scheduled for specific ages and should be attended within a relatively closed time frame . Also foSecond follow-up to the German Health Interview and Examination Survey for Children and AdolescentsData owner: Robert Koch InstituteAim: Providing reliable information on health status, health-related behaviour, living conditions, protective and risk factors, and health care among children, adolescents and young adults living in Germany, with the possibility of trend and longitudinal analysesStudy design: Combined cross-sectional and cohort studyCross-sectional study in KiGGS Wave 2Age range: 0-17 yearsPopulation: Children and adolescents with permanent residence in GermanySampling: Samples from official residency registries - randomly selected children and adolescents from the 167 cities and municipalities covered by the KiGGS baseline studySample size: 15,023 participantsKiGGS cohort study in KiGGS Wave 2Age range: 10-31 yearsSampling: Re-invitation of everyone who took part in the KiGGS baseline study and who was willing to participate in a follow-upSample size: 10,853 participantsKiGGS survey waves► KiGGS baseline study (2003-2006), examination and interview survey► KiGGS Wave 1 (2009-2012), interview survey► KiGGS Wave 2 (2014-2017), examination and interview surveyMore information is available atwww.kiggs-studie.de/englishThe article reports current figures for the participation in early detection examinations (U1 to U9) based on data from the second wave of the German Health Interview and Examination Survey for Children and Adolescents . With reference to the earlier surveys of the KiGGS study, we also discuss the development of participation rates during the last ten years.New data for action. Data collection for KiGGS Wave 2 has been completed in issue S3/2017 as well as in KiGGS Wave 2 cross-sectional study – participant acquisition, response rates and representativeness in issue 1/2018 of the Journal of Health Monitoring [The German Health Interview and Examination Survey for Children and Adolescents (KiGGS) is part of the health monitoring system at the Robert Koch Institute (RKI) and includes repeated cross-sectional surveys of children and adolescents aged 0 to 17  that are representative for Germany. The KiGGS baseline study (2003-2006) was conducted as an examination and interview survey, the first follow-up study  as a telephone-based interview survey and KiGGS Wave 2 2014-2017) as an examination and interview survey. A detailed description of the methodology used in KiGGS Wave 2 can be found in -2017 as nitoring .KiGGS Wave 2 measured the utilization of early detection examinations through a questionnaire which was filled out by parents, answering the question: ‘What early detection examinations did your child take part in?’ All responses on early detection examinations were recorded, including the U10 and U11 examinations, which, however, are not considered in the following. As children born outside Germany are often not able to take part in the first examinations, the analysis also only includes children born in Germany. Children who were younger than the admitted age tolerance at the time of surveying and therefore could theoretically still have participated in the examinations were also excluded from the analysis for methodological reasons . Beyond The analyses are based on data from 13,799 children and adolescents born in Germany  aged 0 to 17, whereby the number of cases varies depending on the examination considered. Data on participation in the complete examination series refer to the age range from 7 to 13 years and stem from the data from 5,867 children and adolescents . The results are presented as prevalences with 95% confidence intervals (95% CI) and stratified according to gender, socioeconomic status of the family and migration background.nd-4th quintile) and 20% to the high status group (5th quintile) [In KiGGS Wave 2, the socioeconomic status (SES) was measured through an index based on the information the parents provided on educational background, occupational status and income situation . Based on an index built using a point score that equally considers the three indicators, a distribution-based distinction is established according to which 20% of children and adolescents belong to the low (1st quintile), 60% to the medium (2uintile) .As a category, migration background is built on child/adolescent and parent country of birth and parent nationality. A ‘one- sided migration background’ means that one parent was not born in Germany and/or is not a German national. A ‘two-sided migration background’ is assumed when the child has migrated to Germany from another country and at least one parent was not born in Germany or does not have German nationality or when both parents were born outside of Germany or are not German nationals .The calculations were carried out using a weighting factor that corrects deviations within the sample from the population structure with regard to regional structure , age (in years), gender, federal state (as at 31 December 2015), German citizenship (as at 31 December 2014) and the parents’ level of education (Microcensus 2013 ). P-valuKiGGS Wave 2 data indicates that nearly all children in Germany participate in the early detection examinations. For U1 and U2, which take place immediately or a few days after birth, the participation rates are 99.7% and 99.6%, respectively . ParticiNo statistically significant differences between girls and boys are found regarding participation in early detection examinations. With regard to SES, significant differences between low compared to medium and high status groups exist, however for most examinations these differences are in the order of one to two percentage points. Only for the U8 and U9 are the differences slightly over two percentage points. Like children from low status groups, children with a migration background are slightly less likely to participate in early detection examinations. However, the differences are only statistically significant for children with a two-sided migration background.When analysing the participation in the total set of examinations (U3 to U9 without U7a), clearer statistically significant differences related to SES and migration background become visible . Of the Compared to the results of the KiGGS baseline study 2003-2006) and KiGGS Wave 1 (2009-2012), it is apparent that participation in early detection examinations has increased significantly over the past ten years  and KiGG. ParticiThe increasing participation in early detection examinations is confirmed by the results of the school entry examinations of public health services that require parents to bring the yellow booklet and/or the detachable card. For example, in the case of Brandenburg, the results indicate that the proportion of children who have made full use of examinations U1 to U8 has increased between 2004 and 2015 from 71.6% to 90.2% . For NorThe increased utilization of early detection examinations and also the reduction of social differences in participation rates can be linked to various measures. Since 2007, new invitation, reminder and feedback systems were introduced in all federal states, even though the regulations vary from one federal state to the other , 14. In When interpreting the results, it should be borne in mind that the prevalences are based on self-reported information provided by the parents. In recent years, the importance of early detection examinations has been discussed and highlighted more in the public debate. In addition to the measures mentioned to promote child health, this process has been driven by the role of early detection examinations in the national health target process (gesundheitsziele.de) and in Germany’s Preventive Health Care Act (Präventions gesetz – PrävG). Against this backdrop, it cannot be ruled out that the marked increase in participation rates can be attributed to socially desirable response behaviour. As they assume that participating is what is seen as normal, some parents possibly will say their children have participated when they actually have not. This would explain why prevalences based on school entry examinations that require parents to bring the yellow booklet are slightly lower.Finally, a frequent criticism of early detection examinations should also be mentioned. Participation in and quality of early detection examinations can only be scientifically analysed and evaluated based on a correct and complete documentation. A current analysis of examination results as recorded in the yellow booklets, which was conducted during the LIFE Child study at the University of Leipzig, for example indicates that information is often incomplete and frequently implausible. Inconsistencies exist particularly regarding psychosocial conditions . The incParticipation rates for most early detection examinations are over 98%, and sometimes even over 99%.97.2% of 7- to 13-year-old children have participated in all of the recommended examinations .Participation rates for children from families with low socioeconomic status and those with a two-sided migration background are slightly lower.Utilization of early detection examinations has increased significantly over the last ten years.


We use a regression discontinuity design to estimate the causal effect of antiretroviral therapy (ART) eligibility according to national treatment guidelines of South Africa on two risk factors for cardiovascular disease, body mass index (BMI) and blood pressure. We combine survey data collected in 2010 in KwaZulu-Natal, South Africa, with clinical data on ART. We find that early ART eligibility significantly reduces systolic and diastolic blood pressure. We do not find any significant effects on BMI. The effect on blood pressure can be detected up to three years after becoming eligible for ART. In this region, about 70% of the people living with HIV (PLHIV) had access to antiretroviral treatment (ART) in 20191. ART increases life expectancy drastically4, such that its expansion will trigger a change in the age composition of PLHIV5. In 2007, adults aged 50 and above already constituted 14% of PLHIV in sub-Saharan Africa6. If the present treatment coverage rates remain constant, the number of PLHIV aged 50 + will triple over the coming years7.In 2019, 38 million people were estimated to be living with HIV, more than half of them living in Eastern and Southern Africa8: As age is an important risk factor for CVD, the burden will increase with the aging of PLHIV. Additionally, observational studies indicate that PLHIV might be subject to a higher risk of CVD than their counterparts11. Potential reasons are direct impacts of the virus on the body, unhealthy risk factors, comorbidities, or an association with the geographical variation of CVD risks11. ART might mitigate the impact of HIV on CVD risks by viral suppression, but ART drugs might also increase CVD risks directly. Observational studies show an increased CVD risk for patients on ART compared to ART naïve PLHIV, especially for protease inhibitor-based regimen9. However, the START randomized controlled trial suggests that the overall impact of early compared to deferred ART on CVD risk factors might be clinically negligible within the first years13.The expansion of ART and upsurge in life-expectancy of PLHIV might impact the burden of cardiovascular disease (CVD)16. The risk of developing hypertension seems to increase with duration of ART18. Contrastingly, the START trial did not detect any significant impact of early compared to deferred ART on blood pressure or hypertension, but a small reduction in the use of blood pressure lowering drugs13. Also, systematic literature reviews on sub-Saharan Africa do not find a significant association between ART and blood pressure or hypertension20.This study focuses on two intermediate risk factors of CVD; body mass index (BMI) and blood pressure. Similar to CVD risk, systematic literature reviews show that patients on ART have higher BMI and blood pressure measurements, and higher odds of obesity and hypertension compared to ART naïve patients21: Observational data from a large population-based sample allows us to analyze the ‘real-life’ effect of ART eligibility. While causal inference in an observational study usually requires strong assumptions such as unconfoundedness, our quasi-experimental design allows us to replace this with weaker assumptions, such that we can plausibly identify the causal effect of early ART eligibility22. Thus, our observational data gives us the advantage of a real-life context, while the quasi-experimental nature brings in an internal validity comparable to RCTs21.We add to this literature by investigating a natural experimental setting, in which we can estimate the causal effect of early ART eligibility on individual’s BMI, systolic blood pressure (SBP) and diastolic blood pressure (DBP). To this end, we employ a quasi-experimental technique which combines characteristics of observational studies and randomized controlled trials23, and they initiate ART at lower CD4 counts than women24. However, patients presenting with similar CD4 counts can be assumed to be on average comparable to each other. Hence, individuals presenting with a CD4 cell count slightly below 200 cells/μl are plausibly similar to individuals with a CD4 count slightly above 200 cells/μl, except for the fact that the former received the possibility to initiate ART, while the later had to return after some time. Under certain assumptions, comparing the outcomes of these two groups gives us the causal effect of early versus deferred ART eligibility.We exploit the fact that ART eligibility was determined by national guidelines during our observation period. Individuals with a CD4 cell count 25. The first round of data collection was conducted in 2000. Since 2003, data is collected every 6 months25. Individuals are included in the survey if they are considered as a member by one or more households within the surveillance area and have spent at least one night in this household within the past 12 months25.We use data from a Demographic Information System run by the Africa Health Research Institute. The surveillance area is located in the Hlabisa sub-district of uMkhanyakude in KwaZulu-Natal26. All residents of the surveillance area > 15 years of age were eligible27. WHO STEPS protocol was followed to measure height, weight and blood pressure. The survey addressed 4,608 individuals, of which 55% agreed to blood pressure and 45% to height and weight measurement26.During the surveillance period in 2010, a cross-sectional anthropometric survey was conducted in a random subsample of 30 areas28. Data on ART and CD4 counts prior to 2007 was collected retrospectively. CD4 counts were measured at each clinic visit28.We received data on ART eligibility from a linked clinic-based database. The database tracks laboratory data and clinic visits of HIV-positive individuals who accessed services at one of the 17 public health clinics within the surveillance area since 200729. Pregnant women and patients with tuberculosis were eligible with a CD4 count of 29. Ineligible patients were asked to return to the clinic within six months if their CD4 count was 28. Less than half of the patients which were ineligible returned within a year after the first clinic visit30. Subsequent guidelines increased and finally abolished the threshold, but are not covered by our data.From 2004 to August 2011, adults with a CD4 count of 30, we only consider an individual’s earliest CD4 cell count. Also, only clinical data recorded between January 2007 (the first date of the database tracking) and the date of the anthropometric data collection were considered. Duplicates were dropped. The final sample consisted of 1132 patients. Data-driven optimal bandwidths as described in the statistical analysis reduced this number to 241 for the BMI analyses and 165 for the blood pressure analyses.Only individuals 15 years or older and with a non-missing value for at least one of the pairs height/weight, second/third SBP, or second/third DBP were considered. Patients who had been on ART treatment previously were excluded. As there was a substantial loss in care of patients not yet eligibleThe data is secondary to the authors. Primary data collection was approved by the University of KwaZulu-Natal's Ethics Committee and administered by the Africa Health Research Institute. Informed consent was obtained from all study participants. All methods were carried out in accordance with relevant guidelines and regulations. Access to the anonymized data was granted by the Africa Health Research Institute for the purpose of this study.We analyze the data for three outcomes, BMI, SBP, and DBP. We use data on weight and height collected in the anthropometric survey to calculate BMI scores by dividing weight (in kilogram) by squared height (in meters). Due to missing observations for either of the two variables, BMI scores could be obtained for 943 individuals (83%) only. For SBP and DBP, the average of the second and third measurement is calculated, as advised by the STEPS protocol. The average SBP and DBP could be calculated for 1,106 individuals (98%).29. Deviation from this eligibility threshold was calculated as the difference between the first CD4 cell count and the threshold. Initiation of ART was defined as uptake of ART within 6 months after the first CD4 count test and before the survey date.Eligibility is defined as having a first CD4 cell count of We use information on education years, age, squared age, sex, and years since the first CD4 test for balance checks and as controls in some of the regressions. Data on education was captured during another survey round in the same year.31. The random noise in CD4 count measurement further supports this assumption of a quasi-random assignment of eligibility in a small bandwidth around the threshold31. However, in the absence of ART, the CD4 counts of PLHIV will decrease over time, bringing formerly non-eligible patients to the lower side of the threshold. Thus, any estimated difference will reflect the effect of early versus deferred ART eligibility.We employ a regression discontinuity design to examine the effect of ART eligibility on BMI and blood pressure. At the time of the anthropometric survey, national guidelines created a threshold which divided patients based on their CD4 count into ART eligible and ineligible individuals. Under certain assumptions, this threshold is arbitrary to patients with a CD4 count very close to the threshold. For example, patients presenting with a CD4 count of 201 cells/μl and patients presenting with a CD4 count of 199 cells/μl are assumed to be on average very similar with respect to their clinical condition and sociodemographic background. It is assumed that the only difference between the two groups is that to the latter, ART was offered, while the former was advised to return after six months. Thus, any difference we see in BMI and blood pressure across the two groups is plausibly attributable to the offer of ART32 and a balance check using t-tests.The identification strategy hinges on the assumption that the groups just below and just above the threshold do not differ systematically except for their eligibility status. We employ two falsification tests by running a density check around the threshold following the procedure by Cattaneo et al.33. For BMI, the optimal bandwidth is estimated at + /− 64 CD4 cells/μl around the threshold, reducing the estimation sample to 241 individuals. For SBP and DBP, the optimal bandwidth is estimated at + /− 40 CD4 cells/μl, reducing the estimation sample to 165 individuals.Similarly, the choice of the bandwidth around the threshold is crucial. Within a very small bandwidth, e.g., comparing individuals with a CD4 count + /− 1 CD4 cells/μl around the threshold, the individuals are convincingly similar, and the assumptions more likely to hold. At the same time, very small bandwidths contain only few observations, such that the power to detect any meaningful effects might be too small. To identify the optimal bandwidth around the threshold, we use a data-driven procedure minimizing the mean squared error (provided by the user-written Stata package rdrobust)As eligibility did not predict treatment uptake perfectly, we apply a reduced-form estimate to obtain the intention-to-treat effect at the threshold. We employ a linear functional form of the deviation of the CD4 count from the threshold to allow for a linear trend in our outcomes as the CD4 count increases. More specifically, our main estimation reads as follows:Here, In addition to the main specification, we analyze the robustness of the results to the inclusion of control variables using education, age, age squared, sex, and years since the CD4 test. We test for robustness to different bandwidths and to more flexible forms by employing higher-order polynomials. Finally, we analyze heterogeneous treatment effects by sex and over time using the following specification:Here, Balance checks for a bandwidth of + /− 50 CD4 cells/μl are depicted in Table 32, we cannot reject the null hypothesis of a joint distribution.Figure The distribution of eligibility and treatment uptake over years and by sex are depicted in Fig. Figure Table We assess the robustness of the results by employing different bandwidths and including a quadratic function for the deviation from the threshold. We choose one smaller bandwidth of ± 25, approximately halving the distance to the threshold, one larger bandwidth of ± 75, increasing the distance to the threshold by the same span, and the largest possible symmetric bandwidth of ± 200. The coefficient estimates and 95% confidence intervals are depicted in Fig. Next, we test for heterogeneity by sex. As depicted in Table Finally, we investigate whether there are heterogeneous effects over time. As depicted in Fig. To our knowledge, our study is the first to identify the causal effects of early ART eligibility on BMI and blood pressure employing a regression discontinuity design. Our approach allows us to compare the BMI and blood pressure of individuals with similar characteristics except for ART eligibility. In contrast to approaches comparing the change in BMI and blood pressure after ART initiation, or comparing BMI and blood pressure across ART naïve and ART individuals, this yields us the causal effect of early compared to deferred ART eligibility at the threshold of 200 CD4 cells/μl.34, this impact is also clinically relevant. The effects are robust to controls and to using a quadratic function instead of a linear function for the running variable.We do not find any significant effect of early ART eligibility on BMI. However, we find a significant negative effect of early ART eligibility on SBP  and DBP  in a bandwidth of + /− 40 CD4 cells/μl. As a reduction of SBP by 10 mmHg significantly reduces major CVD events20. Nevertheless, previous studies showed that especially stavudine and efavirenz, which were the most common treatment regimes in our sample at that time, can contribute to fat loss35. At the same time, initial CD4 counts below 200 cells/μl were significantly associated with weight gains after treatment initiation36, which might result in counter-balancing effects on weight. It is possible that this changed over time, as newer ART regimes seem to be associated with more weight gain than older regimes36. With the rising prevalence of overweight in southern Africa37, any weight gains under newer ART regimes need to be carefully examined to differentiate between a return to a healthy weight and an increase in overweight and obesity38.The null findings for BMI do not exclude any actual impact of ART on BMI. As BMI might incur substantial measurement error, our sample might not be sufficiently large to detect any changes. Alternatively, as weight gains might emerge over time, our observation period might be too small to identify significant differences to the control group, especially as previously ineligible patients are likely to become eligible sometime after the first CD4 test. Even so, our null results are in line with a meta-analysis for sub-Saharan Africa finding no association between BMI and ART across 36 studies39. Secondly, the information on ART eligibility and/or the transfer into treatment might alleviate patients’ distress regarding the lethal implications of HIV/AIDS. Quality of Life studies report an increase in the physical but also in the psychological and emotional dimension for patients after ART initiation40. The improved well-being could transfer into a stress reduction and hence a decrease of the blood pressure level. Thirdly, the stress-blood pressure link could also work in the other direction: patients informed that they are (just) not eligible for treatment might be faced with a higher fear of dying from AIDS, which could raise their blood pressure. While a systematic literature review indicates a positive correlation between psychological stress and blood pressure, substantial variation in the definition and measurement of stress and blood pressure makes a conclusive assessment of this relationship difficult42.ART eligibility might decrease blood pressure for several reasons. Firstly, antiretroviral drugs might decrease blood pressure. However, previous evidence suggests that some drug combinations rather increase blood pressure17. There is evidence that an increase in BMI, the type of ART drugs, or both might mediate this relationship39. For sub-Saharan Africa, no clear association of ART exposure with blood pressure or hypertension is found20. However, the role of ART duration might matter: an observational study on the same population found a lower blood pressure for ART-exposed PLHIV compared to ART-naïve PLHIV, but a higher blood pressure for PLHIV which have been longer on ART26. Thus, our results might be explained by a negative short-run effect of ART eligibility on blood pressure through stress reduction, but a positive long-run effect of ART on blood pressure through either the specific drugs, or weight increases observed in other studies27.Empirically, there is mixed evidence on the link between ART and blood pressure. Globally, a positive correlation is observed after one year of ART, with a progressively stronger correlation over duration of ART43. The introduction of large testing programs over the past decade might have exacerbated this trend further, such that PLHIV are linked to care earlier and present with higher CD4 cell counts nowadays. After 2010, the threshold was increased at first to 350 cells/μl, then to 500 cells/μl, and finally lifted. Investigating the impact at these thresholds would be desirable to assess potential heterogeneous effects at higher CD4 cell count levels, but is not possible with our data, as the anthropometric measures were taken only in 2010. Secondly, the results might not be valid for different study settings. Finally, the share of non-responses in the anthropometric survey evokes the question of representativeness. In our quasi-experimental design, this additionally introduced problems of statistical power, which might be one reason why we cannot identify an impact on BMI.Our study results should be treated with some caution. First of all, the identification in this regression discontinuity design is purely local, in the sense that it is estimated at the threshold. Hence, the estimated effect cannot be extrapolated to observations further away from the threshold without imposing further assumptions. As guidelines for ART eligibility were shifted to larger CD4 counts and finally lifted, our results explain impacts for patients presenting with comparatively low CD4 counts rather than for patients with comparatively high CD4 counts at the first test. Over time, the CD4 count at first presentation increased in the study regionInvestigating the intermediate risk factors BMI, SBP and DBP, we do not find impacts of ART eligibility during the


Healthcare triage for those subject to section 136 powers (MHA 1983/2007) remains challenging. Camden and Islington NHS Foundation Trust opened a dedicated Health-Based Place of Safety (HBPOS) in 2020, situated separately from an emergency department (ED). There was concern that this may lead to physical health problems going unrecognised. We aimed to design a simple, efficient algorithm to be used by non-medically-trained staff to identify those who are subject to s.136 powers who would benefit from medical clearance before being admitted to the HBPOSWe chaired a consensus meeting with nursing staff, police and emergency medicine consultants when designing the algorithm. Case notes of those presenting under s.136 to the POS over 1 calendar-month in 2019 were reviewed, and the proportion of those who the algorithm would have diverted for medical clearance was calculated. We then reviewed the proportion of cases sent for medical clearance during a single calendar month in 2020, after the HBPOS had opened, to see whether there was a significant difference.37 patients were admitted to the ED-based POS in July 2019, of which 36 records were analysed. 9 patients (25%) were referred for medical clearance, with 2 (6%) requiring medical admission. 8.6% were identified as needing medical clearance when the algorithm was applied retrospectively .Review of records over 1 calendar-month after the HBPOS was established showed 30.6% of patients had been diverted for medical clearance prior to entering the HBPOS. Of the 65 patients, 1 (2%) required transfer to ED within 48 hours of entry. No statistical difference in the proportion of patients sent for medical clearance was observed since the formation of the HBPOS away from the ED , suggesting the algorithm successfully identified those patients who needed medical clearance prior to admission.We observed high rates of intoxication amongst those admitted (30–40%).The algorithm showed high specificity and negative predictive value, allowing for a degree of confidence when admitting those deemed at low-risk of physical deterioration, though it does not eliminate the need for clinical judgement. Interpretation of the results is complicated by the COVID19 pandemic in 2020, which was not accounted for in the algorithm, which possibly led to deviations from the algorithm in real-world clinical practice.


Background: Four-dimensional (4D) flow cardiovascular magnetic resonance imaging (MRI) is an emerging technique used for intra-cardiac blood flow assessment. The role of 4D flow cardiovascular MRI in the assessment of trans-valvular flow in patients with atrial fibrillation (AF) has not previously been assessed. The purpose of this study was to assess the feasibility, image quality, and internal validity of 4D flow cardiovascular MRI in the quantification of trans-valvular flow in patients with AF.Methods: Patients with AF and healthy controls in sinus rhythm underwent cardiovascular MRI, including 4D flow studies. Quality assurance checks were done on the raw data and streamlines. Consistency was investigated by trans-valvular flow assessment between the mitral valve (MV) and the aortic valve (AV).Results: Eight patients with AF  83±16 beats per minute (bpm)) were included and compared with ten healthy controls . All scans were of either good quality with minimal blurring artefacts, or excellent quality with no artefacts. No significant bias was observed between the AV and MV stroke volumes in either healthy controls  or in patients with AF . A significant correlation was demonstrated between MV and AV stroke volumes in both healthy controls  and in AF patients .Conclusions: In patients with AF, 4D flow cardiovascular MRI is feasible with good image quality, allowing for quantification of trans-valvular flow. Recent data suggest the prevalence of AF is between 2% and 4% worldwide1, with this figure expected to rise3. Whilst AF can occur in individuals without other cardiovascular comorbidities, it is frequently associated with cardiac disease, including heart failure (with reduced and preserved ejection fraction), valvular disease, and ischaemic heart disease. Cardiovascular magnetic resonance imaging (MRI) is assuming a prominent role in the management of patients with AF, both in the assessment of atrial substrate in the pre-ablation setting4 and in those with associated cardiovascular conditions with concomitant AF5.Atrial fibrillation (AF) is the most common sustained cardiac rhythm disturbance in adults7. Furthermore, 4D flow-derived valvular flow assessment circumvents issues with Doppler-based echocardiography measurements and two-dimensional phase-contrast (PC) acquisition cardiovascular MRI8. As with most cardiovascular MRI techniques, 4D flow traditionally requires cardiac gating using electrocardiography (ECG) in order to depict the various cardiac structures and movements. Cardiac rhythms with high R-R interval variability such as AF can result in significant image quality degradation and challenging image analyses. As a result, the feasibility, precision, and reliability of valvular flow quantification in patients with AF have not previously been assessed.Four-dimensional flow (4D flow) cardiovascular MRI is an emerging technique used for intra-cardiac blood flow assessment in the research and clinical setting. Previous studies have demonstrated accurate and reliable assessment of valvular flow and regurgitation quantification using retrospective valve tracking methodsWe hypothesised that 4D flow cardiovascular MRI is feasible in patients with AF and can accurately and consistently quantify valvular flow. The aims of this study were to (i) assess the feasibility of acquiring 4D flow MRI in patients with AF and (ii) investigate the consistency and reliability of retrospective valve tracking in the quantification of aortic and mitral valvular flow, comparing patients with AF, against healthy controls.The study protocol was approved by the National Research Ethics Service (12/YH/0169) in the UK. The study was approved by the local ethics committee and complied with the Declaration of Helsinki. All patients gave written informed consent immediately prior to MRI examinations.This was an observational cross-sectional study. In order to assess for internal validity, a healthy cohort was used as a comparator. For the study group, we recruited eight patients with persistent AF from the cardiology department at Leeds Teaching Hospitals NHS Trust. Patients were approached during either hospital admission or outpatient clinic review. Inclusion criteria included patients over the age of 18 years old with AF and a stable heart rate between 70 to 110 beats per minute; the only exclusion criterion was contraindication to MRI. For the healthy control group, another cohort of volunteers in normal sinus rhythm with no previous cardiovascular disorders were recruited. Controls were approached through an appeal for healthy volunteers via the University of Leeds and were not matched to AF cases. As the purpose of the study was to determine feasibility of 4D flow cardiovascular MRI in AF, power calculations were not performed to determine sample size.Cardiovascular MRI. All patients underwent cardiovascular MRI on a 1.5 Tesla system , with a 28-channel flexible torso coil, with digitisation of the MR signal in the receiver coil, at the University of Leeds between January 2014 and December 2017. As previously described10, the cardiovascular MRI protocol included baseline survey, cine imaging  acquired using balanced steady-state free precession in a single slice breath-hold sequence, and whole heart 4D flow acquired using a fast field echo pulse sequence (echo-planar imaging [EPI] based with sensitivity encoding [SENSE] acceleration) with retrospective ECG triggering. Typical 4D image parameters were as follows: EPI acceleration factor of 5 and SENSE factor of 2, flip angle 10°, velocity encoding 150 cm/s, field of view 400 mm, echo time 3.5 ms, repetition time 10 ms, 90% partial k-space coverage in phase-encoding directions, number of signal averages 1; images were acquired during free breathing; the number of slices was 35–40, with a temporal resolution of 40 ms; the reconstructed number of phases was 3010.Image analysis. Image analysis was performed offline using MASS software . Similar types of analysis can be carried out by open source software packages likeFourFlow. All images were analysed by an imaging cardiologist (PG) with more than five years’ experience working with 4D flow cardiovascular MRI. Left ventricular volumes and ejection fraction were calculated from cine images using standard methods11: endocardial and epicardial contours were traced on the left ventricular and right ventricular cine stack at end-systole and end-diastole to determine end systolic volume, end diastolic volume, stroke volume, ejection fraction and left ventricular mass. Volumes were indexed to body surface area. For each 4D flow data set, a visual quality assessment on the phase contrast and magnitude images was performed to determine image quality and presence of artefact, and scored on a 4-point scale10: 0, excellent quality without artefacts; 1, good quality with mild blurring artefacts; 2, moderate quality with moderate blurring artefacts; 3, poor quality with severe artefacts leading to non-evaluable data.Flow and velocity measurement. Contour segmentation was performed manually. 4D flow assessments were performed using validated techniques including retrospective valve tracking, with measurement planes located perpendicular to the inflow direction on two- and four-chamber cines12  and mitral valve (MV) was calculated as the difference between absolute forward flow and regurgitant flow through each valve .Baseline cardiovascular MR scan parameters are summarised inThere was no significant difference in MV and AV stroke volumes in healthy controls  or in patients with AF  . MV forwThis study investigated the feasibility of performing 4D flow cardiovascular MRI in patients with AF for the accurate assessment of trans-valvular flow. We demonstrated that 4D flow cardiovascular MRI is feasible in patients with rate-controlled AF, and that it allows accurate quantification of trans-valvular flow and regurgitation in patients with AF. 23, the assessment of LA and LV function following cardioversion24, and the effect of AF on aortic flow25. Kimet al. observed that LV stroke volume and components of LV flow  were significantly different between patients with paroxysmal AF (in sinus rhythm at the time of 4D flow cardiovascular MRI) and healthy controls26, suggesting that the substrate leading to AF in itself may lead to LV flow impairment, rather than the rhythm disturbance alone.Previous research applications of 4D flow cardiovascular MRI in patients with AF are limited and include the assessment of left atrial (LA) flow and stasis28. Similarly, we measured trans-valvular flow as the average of velocities over many heart beats, in order to remove beat-to-beat variability. 4D flow MRI may therefore have an advantage to quantify transvalvular flow in atrial fibrillation. We noticed that the LV stroke volume from cine segmentation were higher in both the healthy and AF cohorts when compared to respective mitral and aortic flows. We suspect this is mainly due to variation of basal slice segmentation on cine, as it is well known that slight variations in basal segmentation of endocardium can result in significant differences in stroke volume.No previous 4D flow cardiovascular MRI studies have examined the assessment of trans-valvular flow in patients with AF. In order to ensure the appropriate application of 4D flow cardiovascular MRI in patients with AF in both the research and clinical settings, the validity, accuracy, and reliability of trans-valvular flow measurements are fundamental. Our study demonstrates that there is no significant bias between AV and MV stroke volumes in patients with AF, similar to healthy controls, and found a strong correlation between MV and AV stroke volumes in both groups. As no reference method for MV or AV trans-valvular stroke volumes exists in patients with AF, we used a mean of both measurements when examining for agreement between measurements . In echo30. Our data highlights the precision with which 4D flow cardiovascular MRI is able to calculate mitral regurgitant volume in AF, within 3–4 ml Creative Commons Zero "No rights reserved" data waiver (CC0 1.0 Public domain dedication).Data are available under the terms of theAll patients gave written informed consent prior to MRI examinations. The authors have fully addressed my concerns and I am happy to approve the article without reservation.Is the work clearly and accurately presented and does it cite the current literature?YesIf applicable, is the statistical analysis and its interpretation appropriate?YesAre all the source data underlying the results available to ensure full reproducibility?PartlyIs the study design appropriate and is the work technically sound?YesAre the conclusions drawn adequately supported by the results?YesAre sufficient details of methods and analysis provided to allow replication by others?YesReviewer Expertise:4D flow, congenital heart disease, cardiac MRII confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. No new comments to make. Appreciate the work done by the authors.Is the work clearly and accurately presented and does it cite the current literature?YesIf applicable, is the statistical analysis and its interpretation appropriate?YesAre all the source data underlying the results available to ensure full reproducibility?YesIs the study design appropriate and is the work technically sound?YesAre the conclusions drawn adequately supported by the results?YesAre sufficient details of methods and analysis provided to allow replication by others?YesReviewer Expertise:Cardiac MRII confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. This article aims to assess the use of 4D flow in patients with atrial fibrillation. In particular it looks at the trans-valvular flow across the mitral compared to aortic valve.  10 healthy controls and 8 patients with atrial fibrillation were enrolled in the study. All scans were deemed to be of sufficient quality for analysis. The study found good correlations between MV and AV flow and no significant bias in these stroke volumes.Given there was no statistical difference in LV end diastolic volume when indexed values are used I would remove the comment about non-indexed end diastolic volumes being significantly different. Do you have any echo data on these patients? The very low EF is quite striking and I wondered how accurate that is or whether it is a reflection of the difficultly of imaging these patients with MR cine images.When presenting the data for the flow across the mitral valve then aortic valve it would be easier if you kept the order the same between all figures - figure 1 has Ao valve, then mitral whereas all other figures have the other order. Additionally fig 2 shows the bars as MV then Ao valve but the figure legend says Aortic valve first. Also on Figure 2 the bar graph for AF patients has a stroke volume 1 as the y axis label - I presume this should just be stroke volume?Table 1 has a tiny typo of 'health' rather than 'healthy'.Figure 3 - can all data be presented to the same number of significant figures please - I would assume whole numbers are most appropriate as I doubt the techniques can be as accurate as to two decimal places. et al., 20181 who found likely physiological variability to be important over time).Otherwise this is a soundly conducted study showing that 4D flow parameters can be measured in patients with AF. Did any patients undergo repeat scans to look at stability over time? If not it would be worth adding this lack of temporal assessment to the limitations section as it would be interesting to see if AF patients have more or less variability then healthy controls . The figure 1 legend has also been amended to reflect this change. The legend to figure 2 has been amended to state “Mitral and aortic valve stroke volumes […]”. The y axis on Figure 2 (AF patients) has been corrected to “stroke volume”.Table 1 has a tiny typo of 'health' rather than 'healthy'.Response: Thank you for identifying this. We have modified it.Figure 3 - can all data be presented to the same number of significant figures please - I would assume whole numbers are most appropriate as I doubt the techniques can be as accurate as to two decimal places.Response: We thank the reviewer for pointing this out. We have changed this to whole numbers.Otherwise this is a soundly conducted study showing that 4D flow parameters can be measured in patients with AF. Did any patients undergo repeat scans to look at stability over time? If not it would be worth adding this lack of temporal assessment to the limitations section as it would be interesting to see if AF patients have more or less variability then healthy controls .Response: Thank you for your comment. Patients did not undergo repeat scans. We have added the following sentence to the limitations section: “Third, patients underwent a single scan only, without longitudinal follow-up. Given previous evidence of physiological variability over time in patients with AF , a temporal assessment would be beneficial.” This new reference has also been added to the reference list (reference 31).J Cardiovasc Magn Reson. 2018;20(1):15. 10.1186/s12968-018-0432-4 31. Stoll VM, Loudon M, Eriksson J, et al.: Test-retest variability of left ventricular 4D flow cardiovascular magnetic resonance measurements in healthy subjects. With this original paper, the authors provide further insight on the feasibility of 4D flow analysis in a complex cohort for obtaining cardiac images such as in patients with atrial fibrillation. Introduction: Well balanced with clear identification of the clinical problem and the main purpose of the study. Materials & methods and results: Well presented and detailed. Image analysis methodology clearly displayed. Graphics and results help to explain the main objective of the study.  Minor comment: The AV and MV abbreviations are defined in the abstract but should be defined in the main text.Discussion and conclusion:  Well-conducted. Comprehensive exposure of the limitations. Conclusion well presented. Tables: Well balanced with clear information and adequate regarding the objectives stated in the study.Images: Figure 1a. The only comment I have with this figure is that the large amount of images in it makes difficult to visualize the great quality of the 4D flow images. I would suggest to reduce the number of images included in figure 1a.Is the work clearly and accurately presented and does it cite the current literature?YesIf applicable, is the statistical analysis and its interpretation appropriate?YesAre all the source data underlying the results available to ensure full reproducibility?YesIs the study design appropriate and is the work technically sound?YesAre the conclusions drawn adequately supported by the results?YesAre sufficient details of methods and analysis provided to allow replication by others?YesReviewer Expertise:Cardiac MRII confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. With this original paper, the authors provide further insight on the feasibility of 4D flow analysis in a complex cohort for obtaining cardiac images such as in patients with atrial fibrillation.Response: We thank the insightful reviewer for their positive feedback.Introduction: Well balanced with clear identification of the clinical problem and the main purpose of the study.Response: We thank the reviewer for their feedback.Materials & methods and results: Well presented and detailed. Image analysis methodology clearly displayed. Graphics and results help to explain the main objective of the study.Response: We thank the reviewer for their feedback.Minor comment: The AV and MV abbreviations are defined in the abstract but should be defined in the main text.Response: Thank you for highlighting this. This has now been modified.Discussion and conclusion: Well-conducted. Comprehensive exposure of the limitations. Conclusion well presented.Response: We thank the reviewer for their feedback.Tables: Well balanced with clear information and adequate regarding the objectives stated in the study.Response: We thank the reviewer for their feedback.Images: Figure 1a. The only comment I have with this figure is that the large amount of images in it makes difficult to visualize the great quality of the 4D flow images. I would suggest to reduce the number of images included in figure 1a.Response: We thank the reviewer for this comment. The reason for inclusion of all the images is to show how 4D flow 2D vectors performed throughout the cardiac cycle.Hence, we have not made changes to this figure. Nevertheless, we have addressed comments from reviewer 2 regarding all figures.


The COVID-19 pandemic has disrupted cervical cancer screening services. Assuming increases to screening capacity are unrealistic, we propose two recovery strategies: one extends the screening interval by 6 months for all and the other extends the interval by 36/60 months, but only for women who have already missed being screened.Using routine statistics from England we estimate the number of women affected by delays to screening. We used published research to estimate the proportion of screening age women with high-grade cervical intraepithelial neoplasia and progression rates to cancer. Under two recovery scenarios, we estimate the impact of COVID-19 on cervical cancer over one screening cycle (3 years at ages 25–49 and 5 years at ages 50–64 years). The duration of disruption in both scenarios is 6 months. In the first scenario, 10.7 million women have their screening interval extended by 6 months. In the second, 1.5 million women (those due to be screened during the disruption) miss one screening cycle, but most women have no delay.Both scenarios result in similar numbers of excess cervical cancers: 630 vs. 632 . However, the scenario in which some women miss one screening cycle creates inequalities—they would have much higher rates of excess cancer: 41.5 per 100,000 delayed for screened women compared to those with a 6-month delay .To ensure equity for those affected by COVID-19 related screening delays additional screening capacity will need to be paired with prioritising the screening of overdue women. In England, cervical screening is mostly carried out in general practice by specially trained nurses. Until December 2019, when the national roll-out of human papillomavirus (HPV) primary testing was completed, screening was done using liquid-based cytology. Screening has been offered to women aged 25–49 years at 3-yearly intervals  and to those aged 50–64 years at 5-yearly intervals. The age-appropriate coverage is ~72% of the eligible women.2Vaccination against HPV  was introduced in England in 2008–2009 to girls aged 12–13 years (born from 1st of September 1995 to 31st of August 1996) and to a catch-up cohort aged 14–18 years (born from 1st of September 1990 to 31st of August 1995). Coverage among girls aged 12–13 years has remained ~86% since.3 Although call/recall was reinitiated in June, primary care providers were given the option to delay invitations for screening for up to 6 months if necessary.4 Similar disruptions to screening have been reported in other countries.6 It is likely that the second and future waves of the pandemic will result in further disruption to screening.Due to the COVID-19 pandemic, cervical cancer screening has been severely disrupted the world over. In England, invitations for screening were suspended from April 2020.As the pandemic is not yet over, it is currently unknown how quickly primary care and laboratories will be able to restore cervical screening services to pre-pandemic levels, what capacity will be available to address the screening backlog that has accumulated since GP practices closed for non-urgent face to face contact in March 2020 and how many women will be willing to take up their screening invitation in the post-COVID-19 era. Nevertheless, it is possible to estimate the size of the effect that a disruption like this is likely to have on cancer incidence, depending on the screening programme’s approach to compensate for the lost opportunity to be screened.Assuming that the health service will not be able to increase screening capacity considerably compared with previous years, it will be difficult or impossible to “catch-up” with the backlog of screening. Rather, the service must choose between extending the screening interval for a whole round of the programme or trying to confine the disruption to women who have already missed being screened. Here, we model the impact of delays to cervical cancer screening on the excess diagnosis of cervical cancers among women of screening age (25–64 years) in England.The effect of a delay in attendance to cervical screening is explored under two scenarios. For both scenarios, the impact of COVID-19 on the provision of cervical cancer screening would affect services over one screening cycle (3 years in women age 25–49 years and 5 years in women aged 50–64 years) only. The length of the COVID-19-related disruption is the same in both scenarios (6 months), but the delay to screening thereafter and hence the proportion of women affected by the delay differs in each recovery scenario . Both scenarios assume that follow-up of women testing positive at screening before the disruption was followed up on time and that follow-up services do not experience delays once the disruption ends.The first scenario considers a rolling delay of 6 months for all women in England over one screening cycle. This means that for a single screening cycle, women would be invited for HPV testing at 3.5 or 5.5 years (i.e. 6 months delay regardless of age) after their previous invitation to cytology screening, depending on their age. They would resume with a standard interval thereafter. The age at which screening is offered would be permanently increased by 0.5 years (up to age 65.5 years). Young women entering the programme after the disruption has been resolved would not be affected.The second scenario assumes invitations to screening were likewise disrupted for a 6-month period and that during the recovery period women who were due a screen during the COVID-19-related disruption do not receive screening during this cycle (i.e. a 36- or 60-month delay depending on age). Women whose invitation was not affected by COVID-19 disruption would continue to be invited as normal.Both scenarios assume no disruption to screening uptake once screening resumes.7 were used to estimate the number of women by age group who would have normally been routinely screened over a 12-month period. In the first scenario, the number of women screened in 1 year was multiplied by 3 or 5 depending on the age group to obtain the total population affected by the delay . In the second scenario, the affected population was half of those attending over 12 months .The age-specific numbers of women screened in England following an invitation for screening , “recall” (second and later routine invitations to screening) and “outside the programme” (predominantly women who were invited but attended 12 months or more after the invitation is issued)) as reported in the NHS Cervical Screening Programme statistics for years 2018–20198The national statistics was the source of data for the estimated size of the female population in mid-2019 in England by age group.9 The pilot reported that 6.6% women at the age of 25–29 years, 1.6% at the age of 30–49 years and 0.5% at the age of 50–64 years had a CIN grade 2 or worse detected following HPV primary screening, either at baseline or at one of two early recalls.To estimate the number of screened women with a high-grade cervical intraepithelial neoplasia (CIN) detectable through HPV screening, data reported from the first round of screening in the English HPV primary screening pilot was used, where by far the majority of women were unvaccinated.10 and are presented in Supplementary Table 11 (comparing to cohorts that were not offered vaccination) were used to adjust the proportion of high-grade CIN per 100,000 screened women to better reflect the detection in vaccinated cohorts. Compared to unvaccinated women, the odds of high-grade CIN were the lowest (OR = 0.14) among those who were vaccinated at ages 12 or 13 years. The OR increased thereafter to 0.18 in those vaccinated age 14 years, 0.29 at age 15 years, 0.27 at age 16 years, 0.55 at age 17 years and 0.85 at age 18 years.The proportion of women estimated to have high-grade CIN was multiplied by the total population affected by the disruption, in order to obtain the number of women in whom CIN2 or worse diagnoses were delayed because screening could not take place as scheduled. Estimates of the population affected were adjusted for the proportion of women aged 25–29 and 30–34 years who were vaccinated with three doses. The proportions of the birth cohort who were vaccinated (and the age of vaccination) were taken from the national statistics12 modelling study. In that study, parameter sets were chosen to be consistent with the literature. They reported 6-monthly progression rates from high-grade CIN to asymptomatic cancer of 0.12% for women aged <30 years, 0.25% at age 30–34 years, 0.35% at age 35–39 years, 0.65% at age 40–49 years, 0.9% at age 50–61 years and 1.1% at age 62 years or more. For the second scenario, cumulative transition probabilities 13 up to 36 months (for women aged 25–49 years) or 60 months (for those aged 50–64 years) were calculated from the same 6-monthly progression rates to estimate the cumulative number of women whose undetected CIN would have progressed to cervical cancer during one age-appropriate screening round  would result in ~10.7 million women being affected by the disruption, whereas delaying screening for an entire screening cycle (scenario 2) only to those directly affected would impact 1.5 million women , the excess cervical cancer incidence rates differed vastly between the two scenarios. Those who miss an entire round (scenario 2) would have seven times higher rates of excess cancer compared with those whose screening was delayed by 6 months . However, the risk of cervical cancer to an average woman who would have attended screening is seven times higher if they had to delay their screening for a whole screening round than if they had to delay screening for only 6 months.Cervical screening at regular intervals prevents cervical cancer.17 Evaluation of screening histories from women diagnosed with cervical cancer once screening services resume will provide the best evidence of the actual impact of COVID-19 delays to cervical screening.It will be challenging to assess the impact of COVID-19 related delays by monitoring population rates of cervical cancer. The impact at a population level will be spread over a number of years. Further, given the roll-out of HPV primary screening in 2020 an initial increase in cancer diagnoses is expected (because the test is more sensitive than cytology).12 We have not taken into account the effect of any delays in diagnostics and treatment of women with a positive screen, nor any drop in the coverage once screening fully resumes; both would result in additional cases of cervical cancer. Finally, we focused on the additional burden of cancer due to the disruption. Any worsening of the prognosis of screen-detectable cancers due to a delayed diagnosis was beyond the scope of our analysis, but would further worsen the impact of the COVID-19 disruption.Our model can be applied to a variety of situations that have the ability to derail a cervical screening programme in the same way as has happened with the COVID-19 pandemic. A limitation of our analysis is that we had to rely on the indirectly estimated parameter for the rate of progression of CIN to cervical cancer. This is not unusual in modelling studies, but the parameters used in this study had been previously calibrated to replicate cancer rates in England.Our results show that the overall population burden of cervical cancer does not depend on whether scenario 1 or scenario 2 takes place. The two scenarios, however, clearly differ in terms of how this burden is distributed among the population. Scenario 2 culminates in a substantially higher excess risk per affected woman. Because the CIN2/3 lesions left undetected would have a longer time to progress (compared to scenario 1), it is also more likely that the excess cancers under this scenario would be diagnosed at later stages. In the name of equity, therefore, our analysis calls for measures that ensure that women do not miss an entire screening round on account of the COVID-19 disruption, that is, scenario 2 should be avoided and scenario 1 would be preferable. Under naive assumptions used in our model, this means that an additional nine million women would be affected by the shorter disruption that is also not without a risk. However, this risk could be diminished in the programmes by (a temporary) increase in the screening capacity in order to clear the screening backlog . If, for example, the screening capacity increased by 33%, it would still take 18 months to clear the 6-month backlog, but it would significantly decrease the total number of excess cancers. We note that a small increase in capacity is assumed in scenario 1 to ensure that women entering screening for the first time are not affected. Unfortunately, the demand for reagents to carryout HPV testing competes directly with the demands for COVID reagents and hence increasing screening capacity may not be feasible.18Increasing the screening capacity alone will not be sufficient. Making sure that women feel confident enough to attend for screening when they are due should be another priority. This is, again, highlighted by the seven-fold higher excess risk of cervical cancer among those who are unable or unwilling to access screening for a whole round, and highlights the importance of messaging to encourage women overdue their screen to attend as soon as possible. Unfortunately, it is often difficult for primary care providers to assess a woman’s prior screening history at the time when they are offered a screening appointment. Nevertheless, consideration should still be given to strategies that will allow the identification and prioritisation of screening of women affected by the COVID disruption to ensure that cervical screening remains a truly equitable service.Supplemental Tables