The antipsychotic clozapine is known to have immune-modulating effects. Clozapine treatment has been reported to be associated with increased risk of COVID-19 infection. However, it remains unclear whether this is because of increased testing of this patient group, who are closely monitored. We linked anonymised health records from mental health services in Cambridgeshire (UK), for patients taking antipsychotic medication, with data from the local COVID-19 testing hub. Patients receiving clozapine were more likely to be tested for COVID-19, but not to test positive. Increased testing in patients receiving clozapine suggests prudent judgement by clinicians, considering the overall health vulnerabilities of this group. However, it remains unclear whether such patients are more likely to be tested for COVID-19 in the first place, given the close clinical monitoring offered to this patient group. It also remains unclear whether patients with schizophrenia taking clozapine are more likely to test positive for COVID-19 after considering testing frequency.Clozapine is one of the most effective antipsychotic medications, and the only medication licensed for treatment-resistant schizophrenia in the UK.7 ‘Exposure to antipsychotics’ was operationalised as at least two mentions of the same British National Formulary class antipsychotic, at least 1 month apart. Patients receiving clozapine were identified by matching CPFT Research Database records with the CPFT clozapine database. Logistic regression was used to calculate odds ratios and 95% confidence intervals for COVID-19 outcomes, adjusting for age, gender and ethnicity.We linked de-identified electronic health records of the secondary-care NHS mental health provider in Cambridgeshire, Cambridgeshire and Peterborough NHS Foundation Trust (CPFT), with one of the two local COVID-19 testing hubs . COVID-19 testing data included all molecular  tests performed at the CUH in the given time frame. We investigated whether, compared with patients treated with other antipsychotics, patients receiving clozapine were more likely to be tested for COVID-19; if tested, were more likely to test positive for COVID-19; and were more likely to receive a positive COVID-19 test result overall (irrespective of the rate of testing). We compared patients treated with clozapine with those treated with any other antipsychotic medication. Two patient groups were made: patients treated at any point over an approximately 7-year period (from 1 January 2013 to 30 April 2021) and patients treated ‘currently’ (from 1 May 2019 to 30 April 2021). Patients were selected through an electronic search of the CPFT Research Database.https://doi.org/10.1192/bjo.2022.537 for further information on methods.The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008. All procedures involving human patients were approved by the UK NHS Research Ethics Service (references 12/EE/0407 and 17/EE/0442); linkage to COVID-19 test data was obtained, in de-identified fashion, via the EpiCov project (CUH) (CPFT project reference M00997). See Supplementary material available at A total of 13 726 patients were prescribed an antipsychotic during the study period (January 2013 to April 2021) and were included in the study. Of these, 1943 (14%) had a COVID-19 test, 2123 (15.5%) had a coded diagnosis of schizophrenia and 778 (6%) were prescribed clozapine.P < 2×10–16) versus patients on other antipsychotics, after adjusting for age, gender and ethnicity. After adding a coded diagnosis of schizophrenia as a predictor, the odds ratio reduced to 1.32  (Supplementary Table 1).The odds ratio for patients receiving clozapine being tested for COVID-19 was 1.99  for a positive test result, after adjusting for age, gender and ethnicity. The odds ratio adjusted further for a coded diagnosis of schizophrenia was 1.06  (Supplementary Table 2).Among patients tested for COVID-19, clozapine use was associated with an odds ratio of 1.22 , after adjusting for age, gender and ethnicity. The odds ratio further adjusted for a coded diagnosis of schizophrenia was 1.25  (Supplementary Table 3).Finally, the odds ratio for patients receiving clozapine (versus others) having a positive test for COVID-19 irrespective of testing rates was 2.09 .Our findings suggest that, compared with secondary healthcare patients treated with other antipsychotics, patients receiving clozapine were more likely to be tested for COVID-19, but they were not more likely to test positive if tested. However, our results also show that patients receiving clozapine were more likely to test positive for COVID-19 irrespective of the difference in testing rates, if a schizophrenia diagnosis was not taken into account.6 and extend it in various ways. We show that the potential association between clozapine treatment and an increased risk of testing positive for COVID-19 could, at least in part, be attributed to increased rates of testing in this patient group, who are under greater surveillance, and appropriately so. Furthermore, we use two sets of complementary analyses based on either patients treated with antipsychotics over a longer 7-year period or current treatment limited to the latest 24 months, yielding compatible findings. Limitations of the work include reliance on electronic health record data, which depends upon clinicians recording information and thus is prone to missing information, a common problem for electronic health record-based studies. For example, schizophrenia was likely significantly undercoded in this data-set, rendering tentative conclusions about diagnosis. Our study period captures the first 12 months of the COVID-19 pandemic in the UK, and so may not be generalisable to other countries or time frames. Further, COVID-19 testing data did not include community testing results, or tests carried out at the other Cambridgeshire hospital ; therefore, the EpiCov data-set included all emergency department and in-patient tests performed at the CUH, covering approximately half of CPFT's catchment area by population. Finally, PCR test availability for SARS-CoV-2 varied considerably over time: initially only available for in-hospital testing of high-risk cases, it became gradually available for home self-testing of any symptomatic member of the public over the course of the pandemic. However, we do not believe that availability would have differentially affected secondary healthcare patients treated with other antipsychotics versus patients receiving clozapine.Our findings are compatible with previous work,We conclude that increased testing for COVID-19 in patients receiving clozapine, as observed in our results, shows prudent clinical judgement by clinicians and should continue, considering the notable health vulnerabilities of this patient group, which include multimorbidity and the immune-mediated effects of clozapine.


Lynch syndrome (LS) is characterized by germline mutations in the DNA mismatch repair (MMR) genes. In colorectal cancer (CRC), germline mutations of DNA MMR genes commonly lead to microsatellite instability-high (MSI-H) subtype formation. Recent studies have demonstrated that CRC patients with MSI-H or mismatch repair-deficient (dMMR) status can benefit from anti-PD1 immunotherapy. However, almost 50% of CRC patients with MSI-H status do not respond to it. It is reported that heterogeneity of tumor and abnormal activation of cancer-related signaling pathways contribute to resistance to anti-PD1 therapy. To improve the clinical efficacy of such patients, the underlying mechanisms of resistance to anti-PD1 treatment must be explored. In this case, we describe an LS-associated CRC patient with MSI-H who suffered resistance to anti-PD1 therapy. Here, we attempted to elucidate the potential reasons, and thus appropriate strategies may be derived to overcome this clinical problem. Lynch syndrome (LS) is caused by germline inactivation of one allele of genes involved in the mismatch repair (MMR) system, namely MLH1, MSH2, MSH6, and PMS2 . ClinicaDespite the remarkable efficacy of anti-PD1 therapy in advanced MSI-H/dMMR CRC patients, nearly half of MSI-H/dMMR CRC patients do not respond to it. Studies have indicated that the underlying resistance mechanisms and the most straightforward reason are the absence of tumor antigens leads to a lack of recognition by T cells . RecentlKRAS gene mutation in this patient, bevacizumab combined with the FOLFIRI regimen was used as a second-line treatment for her. In addition, we performed local radiotherapy on her right iliac crest metastatic lesion. However, after two cycles of combined targeted therapy with chemotherapy treatment, she developed disease progression again, presenting with enlarged tissue mass shadow around the right iliac crest and multiple metastases in the thoracolumbosacral vertebral body and appendages  examination showed no metastasis. Then, this patient underwent a radical resection of left colon cancer. The postoperative pathological stage was pT3N2aM0. Postoperative baseline assessment showed no recurrence and metastasis in this patient. We chose the XELOX regimen as postoperative adjuvant chemotherapy. However, this patient had progressive disease (PD) after six cycles of XELOX chemotherapy. ECT and CT examination suggested bone destruction of the right iliac crest, which was considered metastasis. Colonoscopy revealed a neoplasm at the top of the anastomosis, and pathology revealed a moderately differentiated adenocarcinoma  associated MSI-H CRC patient.Interestingly, when we reviewed her family history, it was worth noting that her grandmother had CRC, three uncles had CRC, and her grandmother’s siblings and their children all had CRC. Her family history fulfilled Amsterdam criteria. We presented her family history in We used IHC assay to detect the protein expression of MLH1, MSH2, MSH6, PMS2, CD8, and PD-L1 in the formalin-fixed, paraffin-embedded (FFPE) tumor tissues. For quantitative analysis, we used ipp software to analyze the density of CD8 and PDL1. These data showed a small number of CD8+T cells were infiltrated in the tumor, and a large number of CD8+T cells were infiltrated in the stroma . Circulating tumor DNA (ctDNA) was extracted from plasma using the QIAamp Circulating Nucleic Acid Kit . The tissue DNA and ctDNA were measured by Qubit 2.0 Fluorometer with a Qubit double-stranded DNA assay kit . Capture-based targeted sequencing was performed on tumor tissue and plasma samples using a panel  consisting of 520 cancer-related genes. Sequencing data analysis was performed by OncoScreen Plus™. The result from the peripheral blood test revealed nine gene mutations with high frequency, including This is a case of failure from anti-PD1 therapy in LS-associated MSI-H CRC. This is also a CRC case to describe characteristics such as TMB, tumor immune infiltration factors, and some gene alterations in LS-associated MSI-H CRC patients. In this case, we tried to elucidate the reasons for resistance to ant-PD1 immunotherapy.Two forms of testing are commonly used in screening MMR or MSI status. IHC was used for detecting MMR proteins and PCR testing for MSI. Due to the development of gene sequencing platforms, NGS has been applied more and more in gene detection. In this case, the IHC assay revealed a loss of MSH2 protein expression. Besides, the PCR test also showed all five single nucleotide sites  were changed. Thus, there is no doubt that this patient is an MSI-H/dMMR CRC patient. As a germline mutation, LS-associated tumors are commonly microsatellite unstable. In this case, the NGS test showed this patient had an MSH2 germline mutation and high TMB. Combined with her family history, she was diagnosed with an LS-associated MSI-H CRC.Recent studies have demonstrated that solid tumors with MSI-H/dMMR subset commonly obtained a favorable response from anti-PD1 mAb, including CRC –14. The The keynote-158 clinical trial has confirmed that TMB is a robust biomarker for predicting the efficacy of PD1 mab, with higher TMB indicating better efficacy . For TMBAPC biallelic mutations associate with increased WNT signaling and decreased TILs in MSS and MSI-H tumors , the Nanjing Science and Technology Development Project (ZKX21028), and the High-level Innovation and Entrepreneurship Talent Introduction Plan of Jiangsu Province (JSSCBS20211532).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Participants’ heart rates, pulmonary functions, total energy expenditure and metabolism were measured over a 5-consecutive-day session at health clinics. (3) Results: Combining the results for both above- and underground locations, workers at high-altitude mining sites had significantly higher peak heart rate (HR), minimum average HR and training impulse as well as energy expenditure due to all substances and due to fat than those at low-altitude sites. They also had significantly higher uric acid, total cholesterol, creatine kinase and N-osteocalcin in their blood samples than the workers at low-altitude mining sites. At underground worksites, the participants working at high-altitude had a significantly higher average respiratory rate than those at low-altitude regions. (4) Conclusion: In addition to underground mining, attention should be paid to high-altitude mining as working under a hypoxia condition at such altitude likely presents physiological challenges.(1) Background: While previous studies revealed how underground mining might adversely affect the cardiopulmonary functions of workers, this study further investigated the differences between under- and aboveground mining at both high and low altitudes, which has received little attention in the literature. (2) Methods: Seventy-one healthy male coal mine workers were recruited, who had worked at least 5 years at the mining sites located above the ground at high (>3900 m;  Coal is an important source of energy, accounting for 27.62% of primary energy consumption worldwide . That peUnderground mining can present health risks to workers due to poor ventilation and dustiness ,6. TheseAlthough ventilation can be better at aboveground mining sites, recent trends in developing high-altitude sites present another health challenges to workers. High altitude can lower oxygen saturation, which can cause acute mountain sickness, long-term chronic intermittent hypoxia, chronic intermittent hypobaric hypoxia, chronic mountain sickness (CMS) and high-altitude pulmonary hypertension. They can produce symptoms of cardiorespiratory capacity and metabolism ,13,14. M2max) [The effects of mining activities on cardiopulmonary functions have been investigated in previous studies, as reviewed in . Cardiov2max) , which i2max) . While p2max) , these sThe energy expenditure of different coal-mining tasks has long been documented . Other tThe objective of this study was to compare the heart rate variability, cardiorespiratory capacity and metabolism in coal mine workers at different altitudes  and worksites (aboveground vs. underground). Based on the previous studies, it is expected that aboveground/high-altitude coal mine workers would demonstrate more red blood cells, higher energy expenditure, oxygen consumption and protein metabolism and smaller heart rates than the underground/low-altitude workers. The results from this study can provide insights into occupational health in coal mining.n = 19), high altitude and underground , low and aboveground  and low altitude and underground . The participants in the High-Above and Low-Above groups were working only in aboveground mines, while the participants in High-Under and Low-Under were working in only underground mines during the entire employment period. There were no significant differences in height, bodyweight and body mass index (BMI) (Ps > 0.05) among the four groups. The participants were required to have at least five years of experience working and living close to the same mining work sites. They were excluded if they had changed their working environment from aboveground to underground or from underground to aboveground at any time. All participants had no coronary artery disease, anemia or other cardiovascular disease. They were free of any clinically evidenced history of chronic bronchitis. All participants provided their informed consent before any measurements in this study.A total of 71 healthy male coal mine workers, who were machine operators, were recruited from the coal mines located at Tibet  and Tangshan . These two mining sites were selected as they passed the national safely accreditation. They also had the same mining equipment and were operated on the same working schedule. The participants were categorized into one of four groups, based on the altitude (high vs. low) and type of worksite (aboveground vs. underground) : high al2max) test over five consecutive days. They stayed overnight at the health clinics —Health 100 Body Check Center, Huatailong Mining Company, Lasa, Tibet, China; low altitude (100 m above the sea)—KaiLuan General Hospital Body Check Center, Tangshan, Hebei, China). The participants were asked not to consume any alcohol or caffeine one day (after 4:00 p.m.) before the measurements. On the first day, we measured the height and bodyweight of all participants. At 8:00 p.m., the heartbeat monitor  was attached to the participants to continuously monitor R-R interval heartbeat profiles over the coming 72 h . The participants were asked to keep their phones and any other electrical devices with transmitters at least two meters away from the bed to avoid any electrical interfere with the recordings. To allow complete rest for the BMR test in the morning the following day, the participants lay down and minimized physical activity in low-illumination rooms  [All participants performed heart rate test, basal metabolism rate (BMR) test, pulmonary test, blood test and maximum oxygen consumption  was used to measure the complete basal metabolism rate and pulmonary function with breath-by-breath gas-exchange monitoring simultaneously while the participants were fully awake. Before the measurement was initiated, participants were lying on the bed for 10 min to allow stable data collection. The participants were then instructed to adopt a supine position for data recording and remained at rest for 25 min . A five-On day 3, in the morning, blood samples were obtained between 7:00 a.m. and 8:00 a.m. after an overnight fast. The samples were obtained from an antecubital vein and collected in a BD Vacutainer plasma tube . Plasma was isolated by centrifugation at 3500 rpm for 10 min and frozen at −80 °C within two hours of collection . Analyse2max test on Day 5.On day 4, the participants were instructed to avoid any intake of caffeine (8 h), medicine (12 h) and alcohol (24 h) and asked not to perform any vigorous physical activity for 12 h before the VO2max). The graded exercise test design was used to assess the cardiorespiratory fitness including VO2max and maximum aerobic speed (Vmax) [−1 on a motorized treadmill. The Cortex Metalyzer  was used for measurement in the breath-by-breath mode and the mean values were calculated from expired air at 30 s intervals [On day 5, the participants were instructed to perform a graded treadmill running test in accordance with the Bruce protocol to determine the maximal oxygen uptake (VOd (Vmax) . At the ntervals .T = duration of the workoutHRex = heart rate during workoutHRrest = resting heart rateHRmax = maximal heart ratee = 2.718The test variables were selected as they were related to the potential differences between underground and aboveground and between high-altitude and low-altitude regions ,24,29,302 and percent VO2max were analyzed [For metabolism data, five-minute stable metabolism data from the Cortex Metalyzer were selected from the original data to calculate the basal metabolism rate (BMR). The BMR indicates the daily rate of energy metabolism an individual needs to sustain and preserve the integrity of vital functions . In addianalyzed ,30.p < 0.05, one-way ANOVA or Welch’s heteroscedastic F-test  was then performed, followed by post hoc multiple comparisons (Bonferroni or Games–Howell test). The alpha was set at 0.05.All statistical analyses were performed in the SPSS program . The normality and homogeneity of variance were assessed with the Shapiro–Wilk test and Levene’s homogeneity test, respectively. Two-way Altitude (high vs. low) x Worksite (above vs. under) ANOVAs were performed to determine whether there is any significant interaction and main effects on all test variables. The main effects refer to any significant differences in the measured parameters (1) between the high and low altitudes and (2) between above and underground sites. The interaction looks into any significant differences among all 4 working conditions . When significant interaction was determined at p < 0.05, p < 0.05), while no such difference was found in the low-altitude region (p > 0.05). The significant main effects of altitude indicated that when compared with the low altitude (Low-Above and Low-Under), participants working at high altitude (High-Above and High-Under) displayed higher peak HR, minimum average HR, training impulse (TRIMP) and low power frequency to high power frequency (LF/HF) ratio (p < 0.05) but lower RMSSD-Sleep, RMSSD-Awake and SDNN values (p < 0.001).The ANOVA indicated a significant interaction on average HR  had smaller peak HR, minimum average HR and TRIMP but larger RMSSD-Awake values than the aboveground participants , while no significant difference was found between underground and aboveground worksites at low-altitude regions (p > 0.05).The ANOVA indicated significant interaction on higher total energy expenditure due to EE-carbohydrates  and fat (EE-Fat) at high altitude (High-Above and High-Under) than in the low-altitude region , but no differences between altitudes in aboveground worksites (p > 0.05).The ANOVA indicated a significant interaction on average respiratory rate (2) in the high-altitude region (High-Above and High-Under) were higher compared with that in the low-altitude region . The main effect of worksite indicated that participants had higher average pulmonary ventilation during work , average oxygen consumption and percentage of maximum oxygen consumption when working aboveground (High-Above and Low-Above) than in the underground worksites .The main effect of altitude indicated that the average pulmonary ventilation during rest and work and average oxygen consumption  may impact health, which can be identified by some biomarkers such as heart rate variability, metabolism, blood composition and pulmonary capacity; comprehensive health care for workers requires deeper insights into the relationship among worksite, altitude and biological reaction. This study examined these biomarkers in coal mine workers who had at least five years of experience working in one of these worksites . The current results supported the hypothesis that altitudes and types of worksites play some important roles in these markers.Over half of the participants worked at high-altitude coal-mining sites , which create a condition of hypoxia. Although these workers have been working at the same worksites for more than 5 years, which may have already lowered the impact of hypoxia, these people still displayed significantly higher maximum average HR ratio, peak HR, minimum average HR, training impulse (TRIMP) and low power frequency to high power frequency (LF/HF) ratio, compared with their counterparts working at low altitudes. This suggested that having worked under the condition of high-attitude hypoxia for at least five years, such a condition still required the heart to work harder to provide the oxygen needs to sustain and preserve the integrity of vital functions ,35. ThisHigh-altitude workers also showed higher total energy expenditure due to all substances  and fat (EE-Fat) than those in the low-altitude regions. This could be related to cold temperature and lower oxygen concentration at high altitudes, which require more active fat metabolism for higher exergy expenditure needed to maintain the basic blood circulation, breathing, body temperature and internal body homeostasis ,35. FurtWhile most of the previous studies have investigated the changes in pulmonary function during maximum exercises , little To our best knowledge, this is the first study to report the differences between aboveground and underground worksites in terms of the biomarkers of mining workers. The underground worker had smaller peak HR, minimum average HR and TRIMP and smaller total energy expenditure  but larger RMSSD-Awake values than the aboveground participants. This indicates a lower activity intensity when working at underground worksites. The RMSSD reflects the tension of sympathetic and parasympathetic nerves, which are related to mental stress and psychological state . From thInterestingly, there are some interaction effects between altitudes and worksites. Our study showed that at high-altitude regions, participants working aboveground had higher EE-carbohydrates than the underground region, while there was no significant difference between underground and aboveground at low-altitude regions. As high-altitude regions present thinner air and lower temperature, mining workers increased their breath rate and degree of anaerobic capacity. The superposition effect on physiology stimulus can be explained by the altitude and worksites. On the other hand, further analysis of the correlation of pulmonary ventilation levels and type of workplace revealed that, at the underground mining worksites, the participants had higher average respiratory rate when working in high altitude than in the low-altitude region, but no differences were found between altitude regions in aboveground worksites. This would suggest a limit to the breathing rate.There are some limitations when interpreting our findings. First, only healthy coal miners were recruited, which makes this study not generalizable to all coal mine workers. Previous studies reported that the prolonged mining work may cause lung diseases (pneumoconiosis and silicosis), cardiopulmonary function injury and cardiovascular disease among mining workers ,8,9,10. High-altitude mining workers can present higher HR, total energy expenditure, metabolism indicators and pulmonary function than those in the low-altitude region, which may be related to the hypoxic environment. Compared to the aboveground worksites, workers in underground mining demonstrated smaller HR, TRIMP and total energy expenditure. These findings provide some insights for designing the work schedule and intensity among workers at mining worksites.


In conclusion, lipoprotein dysfunctions seem to be involved in ATX physiopathology and progression in FH patients.Achilles tendon xanthoma (ATX) formation involves macrophage cholesterol accumulation within the tendon, similar to that occurring in atheroma. Macrophage cholesterol homeostasis depends on serum lipoprotein functions, namely the high-density lipoprotein (HDL) capacity to promote cell cholesterol efflux  and the serum cholesterol loading capacity (CLC). We explored the HDL-CEC and serum CLC, comparing 16 FH patients with ATX to 29 FH patients without ATX. HDL-CEC through the main efflux mechanisms mediated by the transporters ATP binding cassette G1 (ABCG1) and A1 (ABCA1) and the aqueous diffusion (AD) process was determined by a cell-based radioisotopic technique and serum CLC fluorimetrically. Between the two groups, no significant differences were found in terms of plasma lipid profile. A trend toward reduction of cholesterol efflux via AD and a significant increase in ABCA1-mediated HDL-CEC (+18.6%) was observed in ATX compared to no ATX patients. In ATX-presenting patients, ABCG1-mediated HDL-CEC was lower (−11%) and serum CLC was higher (+14%) compared to patients without ATX. Considering all the patients together, ABCG1 HDL-CEC and serum CLC correlated with ATX thickness inversely ( Familial hypercholesterolemia (FH) is defined as an inherited autosomal codominant genetic disease, characterized by elevated plasma low-density lipoprotein (LDL) cholesterol (LDL-c) and a high risk of premature cardiovascular disease (CVD) ,2. PatieThe presence of ATX provides the opportunity for an early definitive diagnosis of FH and a timely optimization of effective lipid-lowering therapy. Early treatment indeed can reduce LDL-c burden, resulting in attenuation of atherosclerotic disease progression and improved cardiovascular (CV) outcome ,6. Moreover, xanthomas could represent a tool to better assess the cardiovascular risk of FH patients. Tendon xanthomas are associated with other CV risk factors, such as age, smoking, arterial hypertension, and premature CVD, suggesting that their detection represents an early marker for more aggressive lipid-lowering intervention ,8.The presence of ATX and the genetic status of FH are independently as well as additively associated with an increased coronary artery disease (CAD) risk . FurtherIn this context, while LDL has a proatherogenic role, HDL exerts an atheroprotective function . The HDLOn the other hand, the serum cholesterol loading capacity (CLC) is the ability of serum lipoproteins to induce cholesterol accumulation in macrophages, representing an index of serum atherogenicity. It is, in fact, raised in pathological conditions leading to a higher CV risk ,21.In this study, we present, for the first time, the existence of a relationship between alterations in serum lipoproteins functions and the presence of ATX in FH subjects. p < 0.001), partly attributable to familiarity, with early atherosclerotic CVD found to be statistically more relevant in patients with xanthoma . The percentage of smokers was higher among subjects not presenting with ATX , while subjects did not differ in terms of presence of hypertension or diabetes mellitus. The subjects were stratified based on the absence (n = 16) or presence (n = 29) of objectively and/or ultrasonographically detectable ATX. The demographic and clinical features of the population are reported in The two groups displayed no significant differences in terms of the plasma lipid profile . Similarly, plasma levels of oxidized LDL and apolipoprotein B (apoB) did not differ between groups. The intensity and type of cholesterol-lowering therapy, mainly statins and ezetimibe, do not differ either in the two groups; only a small fraction of subjects was untreated, with equal distribution between subjects with or without ATX.p = 0.473). However, by individually analyzing the two contributions to total HDL-CEC, the efflux mediated by the aqueous diffusion (AD) process (AD HDL-CEC) and the efflux mediated by the ATP-binding cassette transporter A1 (ABCA1 HDL-CEC), we found a trend towards a reduction in AD HDL-CEC in FH patients presenting ATX compared to patients not presenting ATX . Results are reported in p = 0.003; As cell cholesterol content is the result of cholesterol efflux and influx, we evaluated whether the presence of ATX is associated with changes in the pro-atherogenic potential of the serum by measuring its cholesterol loading capacity (CLC) in macrophages. We found that serum CLC was significantly increased in patients with ATX compared to those without, showing an increment of 14% .Concerning the relationship with HDL-CEC through the different pathways, AD and the ABCG1-mediated processes showed inverse and significant correlations with Achilles tendon thickness . Achillep < 0.0001; p = 0.202), oxidized LDL  and apoB plasma levels . Moreover, we observed a robust association between serum CLC and the Achilles tendon thickness  to promote cell cholesterol efflux and serum capacity to promote cell cholesterol loading) were evaluated in FH patients to compare subjects presenting ATX with those not presenting ATX. This protocol allowed us to correlate, for the first time, lipoprotein functions with cholesterol accumulation in peripheral tissues. The two groups of patients were homogeneous in terms of age, BMI, lipid profile and lipid-lowering treatments, variables that might affect xanthoma development ,23. ImpoOur findings clearly suggest that the presence of a serum with a high CLC might directly contribute to cholesterol accumulation within the tendons, promoting tendon thickening. This relationship is strengthened by the positive correlation between serum CLC and Achilles tendon thickness found in this study, again clearly indicating that a higher serum CLC is associated with cholesterol accumulation in peripheral tissues such as macrophages in Achilles tendons. On the other hand, LDL-c, apoB and oxidized LDL seem not to contribute to Achilles tendon thickness.The pathophysiological process responsible for the formation of tendon xanthomas has significant similarities with that of pathogenesis and progression of atherosclerotic plaque, involving cholesterol accumulation in macrophages of arterial wall and foam cell formation . Thus, tAlthough a higher level of total cholesterol and LDL-c is reported in patients with xanthoma than in those without xanthoma , in our Among LDL subclasses, the small dense particles have an increased ability to induce macrophage cholesterol accumulation ,31. In tAnother important factor influencing macrophage cholesterol homeostasis is the capacity of HDL to interact with the membrane transporter ATP-binding cassette A1 (ABCA1) and G1 (ABCG1), thereby promoting cholesterol efflux and opposing LDL cholesterol loading. In our study, the ABCG1-mediated HDL capacity to promote cholesterol efflux (CEC) was lower in patients with xanthoma and inversely correlated with CLC in the entire population of our study. In addition, ABCG1-mediated HDL-CEC inversely correlated with Achilles tendon thickness. These results suggest that the increased CLC in ATX patients and its correlation with xanthoma formation may be, at least in part, explained by the reduced ABCG1-mediated HDL-CEC, according to the notion that serum CLC is the net result from all serum lipoprotein contribution. On the contrary, ABCA1-mediated HDL-CEC in patients with ATX raised as compared to no ATX FH patients and did not correlate with CLC, suggesting its minor role in CLC level and xanthoma formation.https://doi.org/10.3389/fmolb.2022.925587, accessed on 27 June 2022).The observed reduction of ABCG1-mediated CEC in ATX-presenting patients occurred despite no significant changes in HDL serum levels, consistent with the previously reported weak or absent relationship of this parameter with serum HDL-c levels ,37. ConvThe hypothesis of a defect in the maturation process of HDL might involve an alteration of the activity of the plasma enzymes responsible for HDL remodeling, such as lecithin-cholesterol acyltransferase (LCAT) and/or cholesteryl ester transfer protein (CETP) ,40. In t3 particles isolated from FH patients  cholesterol  at 2 μCi/mL, and, to prevent accumulation of cholesteryl esters, in the presence of 2 μg/mL of an inhibitor of the cholesterol esterifying enzyme acyl-coenzyme A: cholesterol acyltransferase . After 18 h of equilibration in the absence or presence of cAMP analogue in 0.2% bovine serum albumin-containing medium , J774 were incubated for 4 h with 2% (v/v) of HDL fraction from FH patients with and without ATX. HDL-CEC was given as a percentage: the amount of radiolabeled cholesterol released into the medium was corrected for the total radioactivity incorporated by cells. As internal controls, the HDL fraction of a standard serum, obtained from a pool of normolipidemic subjects, and lipid-free human apolipoprotein A-I  were tested together with subjects’ HDL fraction in each assay. To correct for the inter-assay variability, the HDL-CEC percentage in these conditions was used to normalize the different experiments. Intra-assay CV for HDL-CEC assays was <10%.Total HDL-CEC and its major constituents, the efflux through aqueous diffusion (AD) process (AD HDL-CEC) and thorough the ATP binding cassette transporter A1 (ABCA1 HDL-CEC), were performed on the J774 murine macrophages cell line. In particular, in basal conditions, J774 were used to evaluate AD, whereas, to measure total HDL-CEC, J774 were incubated with a cAMP analogue , inducing ABCA1 expression . The ABCABCG1 gene. The difference between HDL-CEC evaluated in ABCG1-transfected cells and in non-transfected cells represents the specific ABCG1 contribution. For the seeding period, CHO cells were plated in 10% FCS containing Ham’s F-12  in the presence of antibiotics . Cells were labelled for 24 h with  cholesterol at 1 μCi/mL. Then they underwent an equilibration period for 90 min in a 0.2% BSA-containing medium. Cells were successively incubated for 6 h with the 1% (v/v) of the HDL fraction from FH patients with and without ATX. HDL-CEC was given as a percentage: the amount of radiolabeled cholesterol released into the medium was corrected for the total radioactivity incorporated by cells. As internal controls, the HDL fraction of a standard serum, obtained from a pool of normolipidemic subjects, and isolated human HDLs were tested together with subjects’ HDL fraction in each assay. Human HDLs (d 1.063–1.21 g/mL) were isolated and purified from the plasma of healthy volunteers not affected by FH by sequential ultracentrifugation. HDL CEC through the ATP binding cassette transporter G1 (ABCG1) (ABCG1 HDL-CEC) was measured on Chinese hamster ovary (CHO) cells transfected and not transfected with the human To correct for the inter-assay variability, the HDL-CEC percentage of these conditions was used to normalize the different experiments. Intra-assay CV for HDL-CEC assays was <10%.v/v) of whole serum from FH patients with and without ATX for 24 h. After that, cell monolayers were lysed in a solution of 1% sodium cholate  and 10 U/mL DNase . On cell lysates, cholesterol was measured fluorometrically using the Amplex Red Cholesterol Assay Kit  following the manufacturer’s instructions, and cell protein content was evaluated by the bicinchoninic acid assay . CLC was indicated as micrograms of cholesterol on milligram of protein. As an internal control, sera obtained from pools of normolipidemic and hypercholesterolemic subjects were tested together with whole subjects’ serum samples in each assay to check for adequate cell responsiveness. To correct for inter-assay variability, the CLC values of these conditions were used to normalize the different experiments. Intra-assay CV for the CLC assays was <10%.As for CEC, to prevent lipoprotein remodeling, sera were slowly thawed in ice immediately prior CLC measurement. CLC was evaluated with a fluorometric technique on human monocyte-derived THP-1 macrophages . Human TFor a priori sample size estimation, G*Power software  was used. Relying on data from a previous study  that comStatistical analyses were executed using GraphPad Prism version 7.00  and IBM SPSS software. Each sample was run in triplicate. Data are given as mean ± SD for parameters with normal distribution or as median with interquartile (IQR) range (25th to 75th percentile) for parameters with skewed distribution. Normality of distribution was assessed using the D’Agostino and Pearson normality test. Differences between FH patients with and without ATX were evaluated using the unpaired two-tailed Student’s t-test for parameters with normal distribution or the Mann–Whitney test for parameters with skewed distribution. p < 0.05.Correlation analyses were assessed to highlight the relationship between parameters by using univariate logistic regression. Pearson correlation coefficients were reported for data with normal distribution, and Spearman correlation coefficients were reported for data with skewed distribution. The statistical significance was identified as


Self-monitoring of behavior can support lifestyle modifications; however, we do not know whether such interventions are effective in supporting positive changes in hypertension-related health behaviors and thus in reducing blood pressure in patients treated for hypertension.This systematic literature review evaluates the extent to which smartphone app–based self-monitoring of health behavior supports reductions in blood pressure and changes in hypertension-related behaviors. It also explores the behavioral components that might explain intervention effectiveness.A systematic search of 7 databases was conducted in August 2021. Article screening, study and intervention coding, and data extraction were completed independently by reviewers. The search strategy was developed using keywords from previous reviews and relevant literature. Trials involving adults, published after the year 2000, and in the English language were considered for inclusion. The random-effects meta-analysis method was used to account for the distribution of the effect across the studies.χ2=9.65, P=.002; DBP: –2.05 mmHg, 95% CI –3.10 to –1.01, n=968 vs 1.54 mmHg, 95% CI –0.53 to 3.61, n=400, χ2=9.19, P=.002).We identified 4638 articles, of which 227 were included for full-text screening. A total of 15 randomized controlled trials were included in the review. In total, 7415 patients with hypertension were included in the meta-analysis. The results indicate that app-based behavioral self-monitoring interventions had a small but significant effect in reducing systolic blood pressure (SBP), on average, by 1.64 mmHg  and in improving changes in medication adherence behavior  compared to usual care or minimal intervention. The review found the intervention had a small effect on supporting improvements in healthy diet by changing habits related to high sodium food  and a trend, although insignificant, toward supporting smoking cessation, low alcohol consumption, and better physical activity behaviors. A subgroup analysis found that behavioral self-monitoring interventions combined with tailored advice resulted in higher and significant changes in both SBP and diastolic blood pressure (DBP) in comparison to those not providing tailored advice (SBP: –2.92 mmHg, 95% CI –3.94 to –1.90, n=3102 vs –0.72 mmHg, 95% CI –1.67 to 0.23, n=4199, Self-monitoring of hypertension-related behaviors via smartphone apps combined with tailored advice has a modest but potentially clinically significant effect on blood pressure reduction. Future studies could use rigorous methods to explore its effects on supporting changes in both blood pressure and hypertension-related health behaviors to inform recommendations for policy making and service provision.PROSPERO CRD42019136158; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=136158 Hypertension, or high blood pressure, affects over 1 billion adults globally and is a leading risk factor for premature morbidity and mortality . HoweverModifying health-related behaviors to address the underlying risk factors of hypertension could result in clinically significant health improvements and reduce morbidity, mortality, and treatment cost. Practitioners have an important role in prescribing lifestyle modifications; however, the time they can spend providing advice about and supporting adherence to health behavior change recommendations is limited and expensive , and theThere is growing interest in the potential of digital innovations as an inexpensive and scalable method to deliver personalized advice to people with long-term health conditions, enabling them to improve adherence to their recommended health behavior modifications and achieve health improvements -19. MobiMoreover, reporting and monitoring health behaviors using apps could act as a behavior change strategy to support the individual in self-regulating health behaviors and thus lead to sustained improvements in clinical health indicators ,24. SelfWhile smartphone app–based self-monitoring of health behaviors has the potential to have a direct, positive effect on patients’ health and an indirect effect on service provision, to date there is a lack of evidence on the clinical effectiveness of app-based behavioral self-monitoring to support patients treated for hypertension.Previous systematic reviews have evaluated the impact of app-based interventions to support changes in behavioral or clinical outcomes, suggesting some promising evidence of their potential effectiveness ,27-30. FThis review investigates whether app-based self-monitoring of health behavior reduces blood pressure and improves health behaviors in patients treated for hypertension. The review also explores the intervention components combined with the behavioral self-monitoring interventions and estimates whether and to what extent they explain intervention clinical effectiveness.This systematic literature review involved searching the electronic databases MEDLINE via Ovid, Embase via Ovid, Web of Science, PsycINFO, Scopus, CINAHL, and the Cochrane Central Register of Controlled Trials (CENTRAL) in August 2021 to identify eligible studies. References for additional trials involved searches in 1 additional database: JMIR Publications .The search strategy was developed using keywords from previous reviews and relevant literature , and disagreements were discussed by another reviewer (AK). Articles had to meet all of the following criteria to be eligible for full-text screening: (1) the population comprised adult individuals treated for hypertension; (2) the intervention consisted of self-monitoring of hypertension-related health behaviors via a mobile app; (3) the intervention aimed to support changes in both blood pressure and related health behaviors; (4) the comparator was usual care, enhanced usual care, or a minimal behavioral intervention; (5) the study included measurements of both blood pressure and health behaviors; and (6) the study design was a randomized controlled trial.Outcome data were extracted for measurements of systolic and diastolic blood pressure , as well as health behaviors for medication adherence, physical activity, healthy diet, alcohol consumption, and smoking cessation. Outcome data for blood pressure and health behaviors were extracted for baseline and follow-up values for most of the studies; otherwise, only the follow-up values were extracted. When follow-up values were missing , the baseline values were selected to estimate intervention effects.The Taxonomy of Behavior Change Techniques  was seleA random-effects meta-analysis was conducted to estimate the weighted, pooled effect for each of the blood pressure and behavioral outcomes to account for the true effect that may vary across the individual studies . Effect Change-from-baseline outcomes were calculated unless baseline data were missing, in which case changes at follow-up were included in the analysis. The random-effects meta-analysis method was used to account for the distribution of the effect across studies .I2 statistic was used to estimate the percentage of the variability in the effect estimates that is due to heterogeneity rather than chance [The n chance . HeterogFrequencies were used to summarize the behavioral strategies coded for each of the intervention and comparator groups . IntervePublication bias was examined by visual inspection of funnel plots and the Egger test. The meta-analysis was conducted using RevMan  .The systematic search of the 7 databases identified 4638 articles, of which 227 were included for full-text screening. One additional trial was identified from another source. A total of 15 randomized controlled trials with 7415 participants met all the eligibility criteria and were included in the analysis .The majority of the included trials were conducted in the United States -45, wherThe meta-analysis suggested that behavioral self-monitoring interventions via smartphone apps have a small but significant effect on reducing SPB by an average of 1.64 mmHg , suggesting that there is potentially small, unimportant variation in the effect beyond chance between the 2 studies that operationalized the blood pressure outcome using categorical thresholds.Heterogeneity between studies was low for most blood pressure outcome measurements  . EffectsThe most frequent behavior change technique coded in app-based behavioral self-monitoring interventions was feedback on behavior (n=13). Many app-based interventions (n=8) prompted participants to obtain advice from a health care provider following the behavioral measurements, and some (n=6) provided tailored advice to address the underlying mechanisms of behavior change. Goal setting of behavior, information about health consequences, and generic information about hypertension were strategies each coded in a small number of interventions (n=4). The most frequent strategy coded across both the intervention and control groups was reporting blood pressure and feedback on blood pressure .χ2=9.65, P=.002; DBP: –2.05 mmHg, 95% CI –3.10 to –1.01, n=968 vs 1.54 mmHg, 95% CI –0.53 to 3.61, n=400, χ2=9.19, P=.002). The differences between the 2 conditions were statistically significant and clinically meaningful  on the observed effect.The risk-of-bias analyses suggested that studies were of low risk of bias. Inspection of funnel plots and the Egger test suggested a low risk of publication bias .This systematic literature review and meta-analysis included 15 randomized controlled trials with 7415 participants and found that patients treated for hypertension receiving an app-based behavioral self-monitoring intervention reduced SBP by an average of 1.64 mmHg (95% CI 2.73-0.55) and were, on average, 60% more likely to reduce SBP to <140 mmHg and DBP to <90 mmHg compared to those in the control group. Further subgroup analysis suggested that behavioral self-monitoring interventions combined with tailored advice had a higher and potentially clinically meaningful effect on reducing both SBP (mean reduction of 2.92 mmHg) and DBP (mean reduction of 2.05 mmHg) .This study found that app-based self-monitoring of behavior interventions increased the odds of achieving medication adherence by 3 folds in the intervention group compared to the control. The significant effect of the app-based behavioral self-monitoring interventions in supporting improvements in both blood pressure and medication adherence provides us with confidence that such interventions could be effective solutions to support health behavior change and thus reduce blood pressure in patients treated for hypertension during blood pressure checks or similar clinical consultations.The behavioral interventions indicated positive effects for supporting improvements in healthy diet by reducing the consumption of high sodium food, as well as positive trends in supporting physical activity, smoking cessation, and alcohol consumption. Although promising, a small number of studies contributed to these meta-analyses, and thus the results should be treated with caution.This review has several strengths and limitations. It did not include gray literature or unpublished studies and was limited to searching a few publicly accessible databases only. Nevertheless, this review summarizes the currently available evidence and suggests that behavioral tailored self-monitoring interventions are effective in changing SBP and DBP by –2.92 mmHg and –2.05 mmHg on average, respectively, compared to usual care, enhanced usual care, or a minimal behavioral intervention.A limitation of the included studies is the use of self-reported measurements for the behavioral outcomes, which are inherent to bias. This might have diminished the validity of the observed intervention effect on health behaviors. Future trials should employ valid methods of measurement to assess behavioral outcomes and thus inform recommendations for policy making and practice.This review has evaluated randomized controlled trials that compared behavioral self-monitoring interventions with usual care, enhanced usual care, or minimal behavioral interventions. We have used an extensive search strategy and identified all publicly available evidence. We have adopted a rigorous approach to data extraction and intervention coding to generate the results and form recommendations for best practices and future intervention development.The included trials had a duration of 1 to 12 months; thus, the evidence for the sustained effects of the intervention remains uncertain. However, a limited number of studies with long-term measurements had positive trends toward blood pressure reduction. Considering the wide reach and low-cost use of mobile technologies, this evidence indicates the potential impact of behavioral interventions on overall hypertension-related morbidity and mortality.The comparator group included usual care , enhanced usual care , or minimal generic lifestyle interventions , suggesting that tailored behavioral self-monitoring is an acceptable addition to usual care and has a small, though clinically meaningful, effect on reducing blood pressure beyond and above usual care clinical practice.Many studies involved clinicians in signposting participants to the app-based behavioral intervention, which might have influenced participants’ engagement with the intervention and their health care. Moreover, the most frequent strategies reported being used with the behavioral self-monitoring interventions were feedback on health behaviors and prompts to obtain advice from a health care provider following behavioral measurements that require further support and monitoring. Although none of these strategies individually explained clinical effectiveness, they could have a synergistic effect in supporting patients’ engagement with self-monitoring processes and thus in generating the observed improvements in health behaviors and reductions in blood pressure.However, due to the limited information reported by primary studies, this review could not provide comprehensive, theory-based evidence on the mechanism by which the self-monitoring intervention achieved the observed clinical effectiveness -26. OnlyThis systematic literature review suggested that tailored behavioral self-monitoring of hypertension-related behaviors facilitated via smartphone apps is effective in reducing blood pressure by an average of 2 mmHg above and beyond usual care, enhanced usual care, or minimal behavioral interventions. Thus, clinical practice should recommend behavioral self-monitoring combined with tailored behavioral advice to achieve clinical effectiveness. Considering the wide use of smartphone apps and their potential to reach large numbers of people, app-based behavioral self-monitoring interventions combined with tailored behavioral advice could potentially be a cost-effective addition to usual care blood pressure consultations. However, due to the limited quality of the trials included in this review, future research with rigorous methods is required to determine the direct impact of such interventions on both health behavior change and blood pressure, as well as their indirect effects on service provision and hypertension-related morbidity and mortality.


It is unclear whether heavy alcohol use and associated hangover symptoms changed as a result of the COVID-19 pandemic. Due to a lack of available accurate and nonretrospective self-reported data, it is difficult to directly assess hangover symptoms during the COVID-19 pandemic.This study aimed to examine whether alcohol-induced hangover-related internet searches  increased, decreased, or remained the same in England before versus during the COVID-19 pandemic (2020-2021) and during periods of national lockdown. Secondary aims were to examine if hangover-related internet searches in England differed compared to a country that did not impose similar COVID-19 lockdown restrictions.Using historical data from Google Trends for England, we compared the relative search volume (RSV) of hangover-related searches in the years before (2016-2019) versus during the COVID-19 pandemic (2020-2021), as well as in periods of national lockdown versus the same periods in 2016-2019. We also compared the RSV of hangover-related searches during the same time frames in a European country that did not introduce national COVID-19 lockdowns at the beginning of the pandemic (Sweden). Hangover-related search terms were identified through consultation with a panel of alcohol researchers and a sample from the general public. Statistical analyses were preregistered prior to data collection.P=.10; robust d=0.02, 95% CI 0.00-0.03). However, during national lockdowns, searches for hangover-related terms were lower, particularly during the first national lockdown in England . In a comparison country that did not introduce a national lockdown in the early stages of the pandemic (Sweden), there was no significant decrease in hangover-related searches during the same time period (P=.06). However, across both England and Sweden, during later periods of COVID-19 restrictions in 2020 and 2021, the RSV of hangover-related terms was lower than that in the same periods during 2016-2019. Exploratory analyses revealed that national monthly variation in alcohol sales both before and during the COVID-19 pandemic were positively correlated with the frequency of hangover-related searches, suggesting that changes in hangover-related searches may act as a proxy for changes in alcohol consumption.There was no overall significant difference in the RSV of hangover-related terms in England during 2016-2019 versus 2020-2021 (Hangover-related internet searches did not differ before versus during the COVID-19 pandemic in England but did reduce during periods of national lockdown. Further research is required to confirm how changes in hangover-related search volume relate to heavy episodic alcohol use.Open Science Framework 2Y86E; https://osf.io/2Y86E The COVID-19 pandemic brought about unprecedented changes to everyday life during 2020-2021. Restrictions imposed to reduce the spread of COVID-19, including national and local level lockdowns, are thought to have had substantial effects on population health and behavior. For example, there is some evidence that during the early stages of the pandemic, mental health symptoms increased sharply before decreasing as COVID-19 restrictions were removed  with 90% statistical power).The preregistered analysis strategy, analysis code, and data set are available on the web (Open Science Framework 2Y86E). For deviations from the preregistered protocol, see There was public involvement in the identification of search terms used in the study.The research was exempt from institutional ethics review as there was no new collection of data from human or nonhuman research subjects.t8670=1.63; P=.10; robust d=0.02, 95% CI 0.00-0.03). However, there was a small and significant increase in searches related to the control search term, trapped wind . RSV was greater in nonpandemic periods (trimmed mean=9.32) versus pandemic periods  but also on weekends (trimmed mean=19.83) versus weekdays . The interaction was the result of the difference in RSV between pandemic and prepandemic time periods being smaller on weekdays  versus weekends .The main effects of prepandemic versus pandemic periods and weekday versus weekend were significant and subsumed under a significant interaction . RSV was greater in nonpandemic periods (trimmed mean=7.77) versus pandemic periods  but also on weekends (trimmed mean=19.00) versus weekdays . The interaction was the result of the difference in RSV between pandemic and prepandemic time periods being smaller on weekdays  versus weekends .The main effects were significant and subsumed under a significant weekday/weekend vs pandemic/nonpandemic interaction . RSV was greater in nonpandemic periods (trimmed mean=6.20) versus pandemic periods  but also on weekends (trimmed mean=16.68) versus weekdays . The interaction was the result of a difference in RSV between pandemic and prepandemic time periods being smaller on weekdays  versus weekends .The main effects were significant and subsumed under a significant weekday/weekend vs pandemic/nonpandemic interaction . There was a significant difference between weekend (trimmed mean=15.95) versus weekday searches . There was no significant interaction .During this period, there was no significant COVID-19 restrictions in Sweden. The main effect of prepandemic versus pandemic periods was not significant  and weekday/weekend  were subsumed under a significant interaction . The RSV was significantly greater before the pandemic (trimmed mean=8.25) compared to during the pandemic . It was also greater on weekends (trimmed mean=15.95) versus weekdays . The interaction was the result of a difference in RSV between pandemic and prepandemic time periods being smaller on weekdays  versus weekends .During this period, some COVID-19 restrictions were introduced in Sweden. The main effects of time  and weekday/weekend . The RSV was greater before the pandemic (trimmed mean=6.82) compared to during the pandemic . It was also greater on weekends (trimmed mean=14.77) versus weekdays . There was no significant interaction .During this period, there were a number of COVID-19 restrictions in Sweden. There was a main effect of time , but this difference was very small and not statistically significant based on our preregistered analysis plan.As in the main analyses for England, we also examined whether hangover-related searches differed across the total prepandemic versus pandemic time periods. Similar to England, hangover-related RSV was somewhat reduced during the pandemic versus before the pandemic , but this was not statistically significant based on our preregistered α of P<.01.As we unexpectedly observed an increase in trapped wind searches during versus before the pandemic, we explored whether this change in search volume may have been caused by the spread of COVID-19. We extracted daily estimates of verified COVID-19 cases from January 30, 2020, to December 31, 2022, from the UK Government COVID-19 database and examined the association between daily trapped wind searches and the number of daily cases reported. There was a small positive association . See To explore the possibility that the frequency of hangover-related searches acts as a proxy for alcohol consumption, we were able to obtain monthly alcohol sales data in the form of alcohol duty within the United Kingdom. We correlated this monthly data against the average RSV across our hangover-related search terms for the same months from March 2016 to December 2021 and found a significant positive correlation both before and during the pandemic  changed before versus during the COVID-19 pandemic (2020-2021) and during periods of national lockdown restrictions in England. The frequency of hangover-related internet search terms was similar in the years before (2016-2019) versus during (2020-2021) the COVID-19 pandemic in England. However, during periods of national lockdown, there was a significant decrease in the frequency of hangover-related internet search terms when compared to the same periods in the years before the pandemic. This decrease in hangover-related searches was observed on both weekdays and weekends.Studies estimating changes to population-level alcohol consumption patterns have been limited to inferring consumption from household alcohol sales data or have relied on retrospective participant self-reports of alcohol consumption ,7,8,10. In addition to being a likely proxy measure of heavy episodic alcohol drinking, changes to hangover-related search activity could also occur due to changes in help-seeking motivation . There is some evidence that lockdown measures in the United Kingdom were associated with worsening mental health, stress, and loneliness ,31, whicThe severity of hangover symptoms is likely to differ based on a range of factors and population characteristics, including genetic differences in susceptibility to the pharmacological effects of alcohol, level of alcohol dependence, and amount of alcohol consumed during drinking episodes -34. In aA strength of this research is our use of a comparison country with fewer COVID-19 restrictions during the early stages of the pandemic. Sweden did not implement any national lockdown measures at the beginning of the pandemic, and during this period, unlike the RSV data for England, we found no evidence of a significant decrease in the frequency of hangover-related search terms. This increased confidence in our conclusions that reductions to hangover-related searches likely occurred as a result of COVID-19 restrictions. From November 2020 onward, Sweden introduced restrictions that limited social movement . In line with this, during the November to December 2020 and January to March 2021 periods, we observed a decrease in hangover-related search frequency for both England and Sweden. A further strength of this research is that we were able to compare data in the pandemic years (2020-2021) with similar data spanning 2016-2019. Although we selected search terms on the basis of consultation with alcohol researchers and the general public to capture likely terms searched for when hungover and we present data suggesting that hangover-related searches and alcohol sales are correlated, as discussed, we do not know to what extent changes in internet search–related activity definitively predict changes in heavy drinking patterns. It would therefore be valuable for future research to further examine the associations between hangover  internet searches, alcohol sales, and heavy alcohol consumption patterns. As has been suggested for other topics of public health importance  and a prHangover-related internet searches did not differ before versus during the COVID-19 pandemic in England but did reduce during periods of national lockdown.


Older adults who fall commonly require emergency services, but research on long-term outcomes and prognostication is sparse. We evaluated older adults transported by ambulance after a fall in the Northwestern United States (US) and longitudinally tracked subsequent healthcare use, transitions to skilled nursing, hospice, mortality, and prognostication to one year.This was a planned secondary analysis of a cohort study of community-dwelling older adults enrolled from January 1–December 31, 2011, with follow-up through December 31, 2012. We included all adults ≥ 65 years transported by 44 emergency medical services agencies in seven Northwest counties to 51 hospitals after a fall. We matched Medicare claims, state inpatient data, state trauma registry data, and death records. Outcomes included mortality, healthcare use, and new claims for skilled nursing and hospice to one year.There were 3,159 older adults, with 147 (4.7%) deaths within 30 days and 665 (21.1%) deaths within one year. There was an initial spike in inpatient days, followed by increases in skilled nursing and hospice. We identified four predictors of mortality: respiratory diagnosis; serious brain injury; baseline disability; and Charlson Comorbidity Index ≥ 2. Having any of these predictors was 96.6% sensitive  and 21.4% specific  for 30-day mortality, and 91.6% sensitive . and 23.8% specific  for one-year mortality.Community-dwelling older adults requiring ambulance transport after a fall have marked increases in healthcare use, institutionalized living, and mortality over the subsequent year. Most deaths occur following the acute care period and can be identified with high sensitivity at the time of the index visit, yet with low specificity. In the United States 25% of older adults fall each year,Among older adults injured by a variety of mechanisms and requiring ambulance transport, a fall mechanism was independently associated with death within one year.In this study we analyzed a cohort of community-dwelling older adults requiring ambulance transport after a fall to evaluate subsequent healthcare use , mortality, and mortality prognostication using information available during the index ED/hospital visit. We sought to generate practical information to guide clinicians, patients, and families about what to expect in the year after a fall requiring ambulance transport.This was a planned secondary analysis of a retrospective cohort study7We conducted the study in seven counties in the Northwestern US, including two major metropolitan areas Portland, Oregon and Seattle, Washington and two rural counties. Forty-four emergency medical services (EMS) agencies serve these counties and transport to 51 acute care hospitals. We included six additional hospitals after tracking interhospital transfers from the initial receiving facility. The 57 hospitals have varying capabilities and services, and included the following: three Level I trauma centers; seven Level II trauma centers; 10 Level III trauma hospitals; nine Level IV hospitals; one Level V hospital; and 27 non-trauma hospitals. In US trauma systems, Level I hospitals are equipped to care for the most complex trauma patients. Level II, III, and IV hospitals each have sequentially fewer comprehensive resources and capacity to care for trauma patients.What do we already know about this issue?Although falls among older adults are common and frequently require emergency services, research on long-term outcomes and prognostication is sparse.What was the research question?Among older adults who fall, what is healthcare use and mortality to one year? Can mortality be predicted during the index visit?What was the major finding of the study?There was a large increase in healthcare services and death after a fall and mortality can be predicted during the index visit.How does this improve population health?These findings provide practical information to guide clinicians, patients, and families about expectations in the year after a fall requiring ambulance transport.We included consecutive, community-dwelling adults ≥ 65 years with Medicare fee-for-service coverage with a fall requiring ambulance transport to an acute care hospital from January 1–December 31, 2011, with follow-up through December 31, 2012. We required that patients had continuous Medicare fee-for-service coverage for one year before and after transport (or until death) to provide comprehensive information about baseline function, comorbidities, frailty, and healthcare utilization. Medicare patients without fee-for-service coverage  function under a different payment model that generates different claims data, which are less useful for research. We included patients regardless of the receiving hospital, their injury severity, or admission status. We restricted the sample to community-dwelling older adults to minimize the effect of patients with different goals of care . We excluded patients with any of the following in the year prior to ambulance transport: skilled nursing facility (SNF) claim; hospice claim; or Provider Order for Life Sustaining Treatment (POLST) form specifying “limited interventions” or “comfort measures only” (Oregon only).We collected EMS data as part of a prospective, all-age cohort study evaluating field trauma-triage processes in the seven counties.10We included the following variables: age; gender; field trauma-triage status; initial prehospital physiologic measures ; prehospital procedures; mode of transport (ground vs air); and initial receiving hospital. We calculated baseline health measures using Medicare claims and other record sources available for the year prior to ambulance transport, including the following: Charlson Comorbidity Index (CCI)International Classification of Diseases, 9th Rev, Clinical Modification (ICD-9-CM) diagnosis codes; ICD-9-CM procedure codes, categorized using the Agency for Healthcare Research and Quality Clinical Classification System (CCS);We considered the initial ED visit associated with ambulance transport after the fall to be the “index” visit, whether or not a patient required admission. Variables from the index visit included the following: Abbreviated Injury Scale (AIS) score for different body regions;The primary outcomes were mortality and healthcare use from the date of ambulance transport to one year. We measured the following types of healthcare use: inpatient days; ambulance transports; ED visits; SNF days; and hospice days. Among patients who died within one year, we evaluated causes of death (including the primary cause and contributing factors) using ICD-9-CM diagnosis codes from matched death certificates and the location of death.We used descriptive statistics to characterize patients, diagnoses, procedures, healthcare use, and mortality. The percent missingness for variables ranged from 0–28.4%, with most variables having less than 4% missing values and mortality with 0% missing . To hand19To derive a prognostication tool for short-term (30-day) and long-term (one-year) mortality, we used classification and regression tree (CART) analysis, v8.0To reduce the potential for overfitting the dataset and to minimize bias, we used 10-fold cross-validation methods to select the final decision tree.As a complement to CART analysis, we also used a multivariable logistic regression model with the same variables to assess factors independently associated with 30-day and one-year mortality. We removed variables with multicollinearity and calculated area under the receiver operating characteristic (AUROC) curve to determine model discrimination. We adjusted all measures of variance for multiple imputation. We examined model diagnostics to assess goodness of fit, influential values, and multicollinearity. We used SAS v9.4  for these analyses.Of the 10,628 older adults transported by ambulance after a fall, 4,025 had matched Medicare fee-for-service records for one year before and after 9-1-1 contact, and 3,159 met our criteria for community-dwelling older adults . CompariOf the 3,159 patients in the primary sample, 147 (4.7%) patients died within 30 days and 665 (21.1%) died within one year. The sample was 70% female, with a median age of 84 years (interquartile range [IQR] 77–89), and 84% had at least one comorbidity. Baseline disability was low, as was use of healthcare services for the year prior to the fall event. During the index visit, non-injury diagnoses were common. There were 173 (5.5%) patients with overall serious injury (ISS ≥ 16). Serious extremity injury was the most common type of injury , and orthopedic surgery was the most common hospital intervention . We characterize the sample in In We illustrate the prognostication tool in Results from multivariable models for 30-day and one-year mortality are shown in Among the 665 patients who died within one year, 629 (95%) had death certificate information available. Cardiovascular causes were the most common cause of death at 30 days and overall  . Most otIn this study we demonstrate marked changes in healthcare use, institutionalized living, and mortality among community-dwelling older adults requiring ambulance transport after a fall. The findings suggest that a fall requiring emergency services is a life-changing event for older adults, rather than simply a marker of steady decline. We also demonstrate that 30-day and one-year mortality for these patients can be predicted with high sensitivity using information available during the index visit. Prognostication after a fall event may have an important role in decision-making among clinicians, patients, and families. The four-variable decision tool had high sensitivity with relatively low specificity, which influences how this information might be used in practice. Because most patients who died had one of the four predictors, patients lacking these factors were much more likely to be alive at 30 days and one year after the event. However, based on the low specificity of the tool, having one of the four predictors did not necessarily put a patient at high risk of death; so this rule should not be used to guide decision-making about limiting or withdrawing care. Furthermore, the decision tool requires prospective validation before consideration for clinical use.There were substantial and measurable increases in healthcare use, institutionalized care, hospice, and mortality after a fall requiring ambulance transport. While approximately one quarter of older adults fall each year,27Mortality rose quickly after transport and then followed a steady upward linear slope to one year. While the mortality curve was steepest in the first two weeks, most deaths occurred after the acute phase of care. Mortality did not plateau at any point in the subsequent year. The findings demonstrate the importance of risk-prediction beyond hospitalization. While injuries are often the clinical focus among older adults who fall, our results demonstrate the importance of non-injury conditions. Previous research has shown that brain injuryMethods to quantify fall-risk among older adults have been established,31Our prognostication tool differed in that it focused on community-dwelling older adults who fell and required ambulance transport (whether or not the patient was admitted), had higher sensitivity and lower specificity for predicting mortality compared to CriSTAL, and included certain measures not identified for CriSTAL (serious brain injury and comorbidity burden). Similarities between our tool and CriSTAL included respiratory function and functional status. Other prediction tools for older adults have identified comorbidity burden, frailty, age, and cancer as important factors,There were limitations in our study. The cohort was enrolled 10 years ago. While the cohort was unique in its development and capture of long-term outcomes, it is possible that patients and/or clinical care have changed during the interim period. Using publicly available, national non-fatal and fatal injury data from 2011 (study year) through 2018 (most recent available data) for older adults suggests that the population-based rate of non-fatal ED visits for falls among patients ≥ 65 years in the US did not substantially change,Comparison of patients included vs excluded from the sample demonstrated similar demographics, initial physiology, ambulance transport patterns, and one-year mortality. In addition, we used the mechanism of injury recorded by EMS at the time of the event, but the fall mechanism was not separated by ground-level, fall from height , or fall down stairs, and did not detail the type of landing surface. The sample was drawn largely from two metropolitan areas in the Northwestern US. It is possible that older adults in other regions or countries with differing demographics, baseline disability, or comorbidity burden may have different trajectories and prognostication after a fall. Finally, other analytic approaches  may be able to derive a tool with higher predictive performance and prospective validation of our prognosti-cation tool will be important before these results are considered for clinical care.Our results show that a fall requiring ambulance transport represents a major shift in the lives of many older adults, with increased use of healthcare services, need for institutionalized living, hospice, and high mortality in the following year. We also demonstrate that patients dying within 30 days and one year can be identified with high sensitivity using information available during the index visit, but with low specificity, which affects how such information might be used in practice.An abstract of the findings of this research was published for the Society for Academic Emergency Medicine Annual Meeting (May 2020).


This cohort study aims to evaluate the predictive validity of multimodal clinical assessment and quantitative measures of in- and off-laboratory mobility for fall-risk estimation in patients with cerebellar ataxia (CA).N = 36) and sporadic or secondary (N = 57) forms of CA and 63 healthy controls. Participants completed a multimodal clinical and functional fall risk assessment, in-laboratory gait examination, and a 2-week inertial sensor-based daily mobility monitoring. Multivariate logistic regression analyses were performed to evaluate the predictive capacity of all clinical and in- and off-laboratory mobility measures with respect to fall (1) status , (2) frequency , and (3) severity  of patients. Occurrence, severity, and consequences of falling were prospectively assessed for 6 months in 93 patients with hereditary , primarily based on their retrospective fall status. Clinical scoring of ataxic symptoms and in- and off-laboratory gait and mobility measures improved classification and provided unique information for the prediction of fall severity (84% accuracy).These results encourage a stepwise approach for fall risk assessment in patients with CA: fall history-taking readily and reliably informs the clinician about patients’ general fall risk. Clinical scoring and instrument-based mobility measures provide further in-depth information on the risk of recurrent and injurious falling. Gait disturbances are a common and disabling complication in patients with cerebellar ataxia (CA) with significant implications for patients’ capacity for independent living and quality of life , 2. WalkFall prevention in CA requires reliable screening and classification procedures to assess and identify individuals at particular risk of falling and severe fall-related complications. Distinct risk factors including symptom severity, the number of non-ataxic symptoms, and the duration and etiology of disease were associated to higher fall rates in CA patients –5, 8. HoRecent advances in off-laboratory mobility assessment using body-worn inertial sensors promise a more specific characterization of patients’ balance impairments and fall risk in environmentally valid settings . InertiaThe aim of this study was to evaluate and compare the predictive validity of currently available and recently established screening tools for fall risk identification in patients with CA. To this end, we prospectively assessed the occurrence, frequency, and consequences of falling in a comprehensive cohort of patients with CA of different etiologies. Subsequently, multimodal score-based and clinical fall risk assessment outcomes as well as measures from instrument-based in-laboratory gait examination and long-term off-laboratory mobility monitoring were evaluated with respect to their relevance for forecasting the occurrence, frequency, and severity of falls.Longitudinal cohort study with 93 patients with CA and 63 healthy controls recruited (study ID: DRKS00007762) from 06/2015 to 02/2018 at the University Hospital Munich. Patients were included based on the following criteria: (1) presence of clinical ataxia [All patients and controls underwent a standardized physical examination, which included a survey of the following information: ambulatory status, functional status, medication, and falls within the preceding 6 months. According to the WHO criteria, a fall was defined as an event which results in a person coming to rest inadvertently on the ground or floor or other lower level . A near-Each participant was provided with a fall diary covering a 6-month follow-up period. Participants were asked to document near-fall and fall events on a daily basis with information on the time, the environmental circumstances, the fall mechanism , the duration of the post-fall lying phase, and the related HFGS of each event. Participants were additionally contacted by phone monthly to cross-check and validate the documented information. Based on the prospective fall assessment, participants were categorized with respect to fall status, frequency, and severity.In-laboratory gait assessment was performed on a 6.7 m-long pressure-sensitive carpet  at 120 Hz. Participants walked over the carpet at their self-chosen (PWS), slow (SWS), and maximum walking speed (MWS). Each condition was recorded 4 times. Gait assessment was conducted without additional ambulatory aids. For each walking condition, the following spatiotemporal gait parameters were analyzed: gait velocity, base of support, stride length, stride time, swing phase percentage, double support percentage, coefficient of variation (CV) of the base of support, CV of stride time, CV of stride length, gait asymmetry index, and phase synchronization index .Following the initial visit, monitoring of daily mobility was undertaken for 14 days. Participants wore an inertial sensor-based activity monitor , which recorded the sequence and period of individual bouts of ambulatory, sedentary, and sleeping behavior at 10 Hz. The inertial sensor was placed on the thigh of the dominant leg approximately 0.1 m cranially and 0.05 m laterally to the patella. Participants were advised to continue their daily activities as usual and not to change their routine. Upon completion of the recording period, participants removed the sensor by themselves and send it back by mail.The following parameters (expressed as average daily estimates) were computed from the ActivPAL data , 32: daiF value ≤ 0.05 were considered in the respective regression model. To avoid collinearity, relationships among parameters were examined using Pearson’s correlations. If parameters were strongly correlated (r > 0.7), only the one most strongly associated with the dependent measure was retained. This statistical approach is based on [Descriptive statistics are reported as mean ± SD. In a first step, analysis of variance (ANOVA) and chi-squared tests were used to test for differences of metric and categorical parameters from clinical assessment, in-laboratory gait examination, off-laboratory mobility assessment, and retro- and prospective fall assessment between patients and controls. The subsequent statistical analyses focused solely on patient data: multivariate backward logistic regression analyses  were performed to identify independent predictors associated with the three dependent prospectively assessed fall measures of interest: (I) non-faller vs. faller, (II) occasional vs. frequent faller, and (III) non-severe vs. severe falling (defined as HFGS 3 or 4). For each regression model sensitivity, specificity and correct classification are reported as quality parameter derived by the classification matrix. Initially, all potential predictor parameters from clinical and mobility assessment were subjected to an ANOVA (including post hoc comparison via Sheffé procedures) with respect to the three above-mentioned fall categories. Subsequently, only those parameters that yielded a significance level of their based on . StatistN = 36), sporadic degenerative forms of ataxia , ataxia due to focal vascular or neo-plastic cerebellar lesions (N = 3), and downbeat nystagmus syndrome (N = 18). Patients had a mean SARA score of 10.2 , indicating an on average moderate severity of ataxic symptoms. Accordingly, assessment of functional mobility revealed mildly impaired balance and gait capacity of patients compared to controls  despite normal performance in the TUG. Patients reported increased fear of falling , decreased balance confidence , and showed moderately reduced cognitive function . Health-related quality of life scores did not differ between patients and controls.Demographic information and clinical characteristics of patients and controls are summarized in Table F1,153 = 39.9, p < 0.001), prolonged double support phases , increased base of support , spatiotemporal variability , and asymmetry within their stride-to-stride pattern . Off-laboratory monitoring of daily life mobility revealed a general reduction of energy expenditure  with a reduced daily amount of time spent during ambulation  and a smaller step count  in patients compared to controls.Descriptive information on outcomes from in- and off-laboratory mobility assessment is summarized in Table Fall epidemiology in patients and controls is summarized in Tables In the 6-month follow-up period, all participants registered fall information in their falls diary that was counter-checked by structured monthly telephone interviews. Falls diary information from 13 patients and 7 controls was considered invalid and excluded from further analysis due to missing telephone contact data or discrepancies between the falls information documented in the diary and surveyed during monthly phone interviews. The total numbers of near-fall and fall events in patients registered during prospective assessment were 313 and 612, respectively. A majority of falls in patients with CA occurred indoors (75%) in domestic environments (71%), primarily on even surface (71%). Most falls were linked to walking or turning (71%) and 74% occurred either forwards or backwards. The most frequent causes of falling in patients were tripping (33%) and imbalance (23%). The most commonly reported associated symptoms with falling were dizziness and vertigo (20%)  was obtained after 10 iteration steps and yielded a correct prediction of 78% . The model included 5 predictive factors from socio-demographic and in-laboratory mobility assessment, with the most important being retrospective fall status and CV of stride time during slow walking  was obtained after 13 iteration steps and achieved a correct prediction of 81% . The model included 3 predictive variables from socio-demographic and off-laboratory mobility assessment, with the most influential being retrospective fall status and intensity of daily mobility  was obtained after 12 iteration steps and yielded a correct prediction of 84% . The model only considered 2 parameters from clinical and off-laboratory mobility assessment, namely the subscore “heel-shin-test” of the SARA and ambulatory bout alpha . In contrast, two previous studies on patients with hereditary CA at more advanced disease stages observed considerable impairments of daily activities that correlated with the severity of ataxic symptoms , 19. OurOur 6-month prospective fall assessment in patients with CA revealed a fall incidence of 64%, which lies within the range of previous reports  with respect to previously established criteria for fall risk assessment approaches , 40. AccPrediction of patients’ general fall status further relied on parameters from in-laboratory gait assessment. In particular, increased levels of gait variability were identified as an independent risk factor for experiencing falls during the follow-up period. Irregularity of movement is a defining characteristic of cerebellar disease , 10 and Interestingly, off-laboratory mobility measures did not contribute to basic fall risk estimation, but only became relevant for identifying patients at particular risk of frequent and injurious falling. Accordingly, prolonged periods of sedentary activity were predictive for injurious falling and a higher intensity of daily-life activity for experiencing recurrent falls. At first glance, the latter observation appears to be counterintuitive, since the level of daily physical activity is considered a global health marker  and traiWhether the severity of ataxic symptoms directly influences fall risk in patients with CA is still controversial. A retrospective study in patients with spinocerebellar ataxias found that fall frequency was associated with the severity of ataxia assessed by the SARA score . HoweverTaken together, the differential contributions from clinical and instrument-based measures for predicting fall risk in CA encourage and provide guidelines for a multi-level, stepwise fall risk assessment approach in these patients: Accordingly, basic index information that is readily available from medical history taking allows a good estimation of the general fall risk and may promptly inform the clinician which patient would or would not benefit from a more in-depth examination. For those patients at risk of falling, a more elaborate disease severity rating and measures from instrument-based gait and mobility examination provide additional, unique information with respect to the severity of their fall susceptibility and the likelihood for the occurrence of severe fall-related injuries.The cross-sectional study design yielded a heterogenous sample of patients including hereditary, sporadic, and secondary forms of CA which comfounds a direct comparison to previous reports that only considered hereditary forms of CA , 5, 18.