Most of the MUO (92%) patients maintained unhealthy phenotypes (MUO-Non-Responders), but 8% became metabolically healthy (MUO-Responders) after a significant decrease in their BMI and FLI-score, with improvement in all metabolic criteria. No differences were found among dietary groups. Conclusions: A greater loss of weight and liver fat is associated with a lower progression of the MHO phenotype to unhealthy phenotypes. Likewise, a marked improvement in these parameters is associated with regression from MUO to healthy phenotypes.Background: Obesity phenotypes with different metabolic status have been described previously. We analyzed metabolic phenotypes in obese coronary patients during a 5-year follow-up, and examined the factors influencing this evolution. Methods: The CORDIOPREV study is a randomized, long-term secondary prevention study with two healthy diets: Mediterranean and low-fat. All obese patients were classified as either metabolically healthy obese (MHO) or metabolically unhealthy obese (MUO). We evaluated the changes in the metabolic phenotypes and related variables after 5 years of dietary intervention. Results: Initially, 562 out of the 1002 CORDIOPREV patients were obese. After 5 years, 476 obese patients maintained their clinical and dietary visits; 71.8% of MHO patients changed to unhealthy phenotypes (MHO-Progressors), whereas the MHO patients who maintained healthy phenotypes (MHO-Non-Progressors) lost more in terms of their body mass index (BMI) and had a lower fatty liver index (FLI-score) ( Obesity is a worldwide public concern due to the effects it has on health and its socio-economic implications. Moreover, this condition continues to be on the rise worldwide . ObesityObesity phenotypes classify individuals by means of a combination of BMI and metabolic status. Obese individuals with a favorable metabolic profile present a phenotype which is called “metabolically healthy obese” (MHO), which has been widely studied , althougAlthough there has been a consistent number of studies evaluating the comparative effects of both types of obesity on clinical and biochemical variables, only a few studies have examined the long-term changes in obesity phenotypes, the factors associated with these changes, and the comparative effects of different dietary interventions ,18,19.Some studies have analyzed lifestyle interventions to control changes in metabolic status in the short/medium-term. Diet programs aimed at losing weight were seen to be associated with improvements in cardiometabolic risk factors in MHO individuals . MoreoveMorbidity rates in MUO are higher than in the MHO group. However, there is still controversy about the metabolic risk of healthy obese individuals over time ,23. A loThere are limited data in the medical literature about the characteristics of obesity phenotypes in coronary patients, their mid- and long-term evolution, and whether dietary interventions have any effect on their evolution. In the present study, we aimed to analyze changes in the two obesity phenotypes  after 5 years of follow-up in cardiovascular patients within a dietary intervention study, and to study possible differences in these phenotype transitions using two healthy dietary models (low-fat and Mediterranean diets).n = 1002) followed two different dietary patterns (MD and LFD), along with conventional treatment for coronary disease and strict follow-up protocols based on dietary and clinical monitoring. Patients were selected if they were between 20–75 years old (inclusive), had a history of established cardiovascular heart disease (but were free of events in the last six months), were willing to follow a long-term dietary intervention, and had no severe disease or a life expectancy shorter than the length of the study. A more detailed explanation of the CORDIOPREV Study has been published elsewhere [The Coronary Diet Intervention with Olive Oil and Cardiovascular Prevention (CORDIOPREV) study  is a randomized, controlled dietary intervention study, involving patients undergoing secondary cardiovascular prevention. The participants : BMI ≥ 30 kg/mcriteria .2 and ≥ 2 metabolic criteria : BMI ≥ 30 kg/mcriteria .Given the previous definitions, in this study we analyzed two obesity phenotypes:At baseline and at the yearly visits, biological samples and anthropometric measures were collected.Fasting blood was collected into tubes with EDTA, and immediately transferred to 4 °C. Serum parameters were measured in Architect c16000 analyzers  using spectrophotometric techniques (enzymatic colorimetric methods). HOMA-IR was derived from fasting glucose and insulin levels ((fasting plasma glucose (mmol/L) × fasting serum insulin (µU/mL)/22.5). Hs-CRP was determined by means of high-sensitivity ELISA . All samples were collected and analyzed in the Reina Sofia University Hospital in Cordoba, Spain. High levels of hs-CRP (≥10 mg/L) were excluded from the analysis to avoid nonspecific inflammation .Weight and height were measured using calibrated scales  and a wall-mounted stadiometer , respectively.Liver fat depots were assessed using the fatty liver index (FLI), which was calculated using the following variables: triglycerides, BMI, GGT and waist circumference. Values of FLI under 30 were considered normal and those above 60 were considered as excessive liver fat .The two dietary intervention models used in the CORDIOPREV studies were: (1) a Mediterranean diet composed of a minimum of 35% of total calories from fat , ≤50% from carbohydrates and 15% from protein, or (2) a low-fat diet comprising <30% of total fat , ≥55% from carbohydrates and 15% from protein. There was no total caloric restriction or weight loss intervention. Every 6 months, the patients had an individual face-to-face visit with dietitians for the assessment of dietary intake and adherence, with an additional phone contact. More information about dietary intervention has been provided elsewhere ,32.Any variables which were skewed were transformed using decimal logarithms. Baseline characteristics are expressed as mean ± standard error of the mean (SEM) for continuous variables, and proportions (%) for categorical variables. Missing values were imputed to the closest known values in time.MHO at baseline was stratified into two groups: MHO-Non-Progressors  and MHO-Progressors .MUO at baseline was divided in MUO-Responders  and MUO-Non-Responders (patients who were MUO at baseline and maintained the same phenotype after follow-up).According to their baseline phenotype and their 5-year metabolic health evolution, we created the following categories:2 test. To determine changes over time we used repeated-measures analysis of variance (rANOVA). Bonferroni’s test was used in the post hoc analysis. The relationship between FLI and metabolic abnormalities was tested using the Pearson correlation.Continuous variables were compared using analysis of variance (ANOVA) and categorical variables were compared using the Chip-value <0.05 was considered statistically significant. Odds ratios (OR) were represented with a confidence interval of 95% (95% CI). All statistical analyses were performed using SPSS  version 24.0 for Windows .A A total of 1002 coronary patients were included in the CORDIOPREV study. Of these, 562 were obese at baseline, and 476 of them had complete clinical and dietary data after the 5-year follow-up (flow chart provided in p < 0.001) and hyperglycemia  were the most frequent abnormalities. A moderate linear correlation was observed between the initial number of abnormalities and the baseline FLI value . n = 71) of the subjects in this study were MHO. Mean BMI was 32.7 kg/m2 and they presented an ectopic fat distribution with an excess of liver fat measured via FLI   .n = 20) at baseline were classified as MHO-Non-Progressors as they remained metabolically healthy  after 5 years of follow-up. These patients decreased their BMI and improved their ectopic fat distribution, as evaluated by means of the FLI score. We found no differences in other metabolic abnormalities  of the MHO at baseline as MHO-Progressors, as they evolved to metabolically unhealthy phenotypes after a 5-year follow-up.p < 0.05). No significant changes in BMI, FLI or other metabolic abnormalities were found at the end of the study . More detailed data of the biochemical and anthropometric values of the different diet groups are shown in the n = 405) of the obese participants. The evolution of these patients was as follows:At baseline, the metabolically unhealthy obese (MUO) group represented 85.1% (n = 32) reversed to metabolically healthy phenotypes, classified as MUO-Responders. These patients evolved to MHO , metabolically healthy overweight  or metabolically healthy normal weight  phenotypes   .n = 373) continued being metabolically unhealthy, and were labeled MUO-Non-Responders.We found that 92.1% of the subjects  and triglyceride levels, reaching normal values. All MUO-Responders who had baseline hypertriglyceridemia reached normalized triglyceride levels by the end of the study.Among the MUO-Non-Responders, a significant percentage of the population had increased metabolic abnormalities, with HOMA-IR, glucose and HDL-c being the abnormalities in which we saw a greater increase in the percentage of patients suffering from them. Notably, there were no increases in the percentage of patients with altered hs-RCP or TG criteria and only a 1.6% increase for hypertension.When we compared the evolution of both groups, significant differences were found between MUO-Responders and MUO-Non-Responders in recovery rates for blood pressure, TG, HDL-c, glucose, HOMA-IR and hs-CRP.2; MD: 34.6 ± 0.3–34.5 ± 0.4 kg/m2; p = 0.011). SBP decreased more with LFD than MD . More detailed data regarding the biochemical and anthropometric values of the different diet groups are shown in the Supplementary Data  evolution and transitions between phenotypes of a large population of coronary patients (more than 400) in a dietary intervention without a calorie restriction.The reported proportions of MHO and MUO in the different cohorts studied varied widely (between 7–75%) , due to In our study, both MHO and MUO had similar demographic characteristics at baseline in terms of age, gender and previous episodes of CVD. As expected, there were significant differences in the diagnostic criteria of metabolic abnormalities ,35,36, wp < 0.001), thus supporting this idea. We observed a linear correlation between the initial number of abnormalities and the baseline value of FLI, reinforcing the theory that the accumulation of hepatic fat is an inducer of metabolic dysfunctions (adiposopathy) [Another suggested factor underlying the existence of MUO is an alteration in the distribution of ectopic fat, especially liver fat ,40,41. Asopathy) ,43.In our study, MHO accounted for less than 15% of the obese population at baseline, and of these, about 70% lost their metabolic health status during the 5-year follow-up. This could support the idea that the MHO phenotype is mostly a transient state of which the natural evolution is its conversion into MUO ,11,44. HAnother key question that our study aimed to evaluate was whether MUO is a permanent state, or was reversible over time. At baseline, MUO was the most common phenotype in our population (85.1%), and the metabolic disease state of most of these patients remained stationary during follow-up, indicating the relatively stable state of this phenotype, as other studies have suggested . NeverthIn the MUO-Non-Responders group, the greater decrease in BMI observed in patients on the LF diet may be due to the lower final caloric intake observed in this group, as already reflected in other previous studies .In summary, we have shown that, among coronary patients in a long-term dietary intervention, those with an MHO phenotype at baseline tend to transform to unhealthy phenotypes during a 5-year follow-up, and that most MUO at baseline remained unhealthy after this period. This would suggest that, in most cases, MHO converts to MUO, the latter being a stable, unhealthy state. However, up to one-third of patients with MHO can maintain this healthier phenotype for at least 5 years when they follow a strict dietary intervention with a healthy diet. Furthermore, up to one in ten patients who were MUO at baseline were able to revert to a metabolic healthy status, which reinforces the importance of dietary interventions as powerful tools to lower cardiovascular risk in these patients.One limitation of our study is the lack of a group without dietary intervention, although in patients undergoing cardiovascular secondary prevention, it would be unethical to have one. There was also an excessive representation of the male sex, derived from the natural epidemiology of coronary heart disease. Nevertheless, few studies in this disease with a five-year follow-up adhering to a strict dietary intervention have contained more than one hundred women.As for the strengths, this study was based on a clinical dietary intervention trial with a broad sample and a long-term follow-up. Although our results cannot be extrapolated to the rest of MHO and MUO patients without CVD, to the best of our knowledge, this is the first large-scale, long-term (5-year) study of dietary intervention without calorie restriction, on the evolution of obesity phenotypes in the cardiovascular secondary prevention population.In this large-scale, long-term, dietary intervention study without energy restriction in coronary patients, we found that most obese persons presented an MUO phenotype at baseline and remained in that state during the 5 years of follow-up. Likewise, most of the MHO participants at baseline transformed into unhealthy phenotypes during follow-up. However, one in ten MUO patients reversed their metabolic disease, and one-third of MHO participants at baseline even kept their healthy status. In both cases, better evolution, greater weight loss and a greater improvement in liver fat were observed, as assessed using the fatty liver index. In addition, the Mediterranean and low-fat diets performed equally well in this study.


Purpose: Calcitonin gene-related peptide monoclonal antibodies (CGRPmAbs) are new agents approved by the US Food and Drug Administration for preventive treatment of chronic migraine. Comparison between CGRPmAbs and previously approved Botulinum neurotoxin A (BoNT-A) will inform optimal preventive treatment of chronic migraine, but head-to-head trials are lacking. We therefore aimed to perform adjusted indirect comparison between CGRPmAbs and BoNT-A through a meta-analysis.Methods: OVID MEDLINE, EMBASE and the Cochrane central register of controlled trials, clinical registries, and government websites were searched from inception to September 2019. Randomized controlled trials comparing CGRPmAbs or BoNT-A with placebo in the preventive treatment of chronic migraine were included. The primary outcomes were headache days and migraine days measured at week 12. Data were synthesized by using a frequentist approach; and the treatments were ranked by P-score.Results: We included 10 trials  after screening 1049 candidates. Six trials were with low risk of bias. Fremanezumab had an effect similar to BoNT-A in the reduction of headache days at week 12 . Galcanezumab reduced more migraine days than BoNT-A at week 12 ; fremanezumab showed similar findings . Galcanezumab and fremanezumab had better effect in mitigating headache impact at week 12. CGRPmAbs and BoNT-A had similar adverse event rate.Conclusion: CGRPmAbs and BoNT-A had similar effect in the preventive treatment of chronic migraine. BoNT-A might be preferentially selected owing to its cost-effectiveness profiles. Further studies with direct comparison of the two treatments are warranted. ChronicThe treatment of chronic migraine includes two steps. The first is to stop or reduce the intake of acute analgesics to prevent medication overuse, and the second step is to use preventive treatment. Several pharmacological and non-pharmacological treatments are suggested for the preventive treatment of chronic migraine, but very few of them are evidence based. In pharmacological treatments, topiramate is the only orally administered drug with high-quality evidence to support its efficacy and safety in treating chronic migraine, specifically. However, the high rate of adverse events and the potential risk of causing depression restrict its use for chronic migraine. There is a lack of high-quality evidence for non-pharmacological treatments.11. BoNT-A is therefore the main preventive treatment for chronic migraine. In recent years, many studies showed the promising effect of calcitonin gene-related peptide monoclonal antibodies (CGRPmAbs) in the treatment of migraine; and several large-scale studies showed the efficacy and safety of CGRPmAbs (Botulinum neurotoxin A (BoNT-A) is the first treatment that is specifically approved for chronic migraine by the US Food and Drug Administration (FDA), and its efficacy was confirmed in two large-scale trials  and theiCGRPmAbs . On the Which is the optimal selection for the preventive treatment of chronic migraine? The clinical uncertainty could be better resolved by providing evidence of the comparative effectiveness between CGRPmAbs and routinely practiced BoNT-A. However, no head-to-head trial with randomized design exists. Under the condition, indirect treatment comparison was proposed, which was assumed to provide effect estimates of comparison between two interventions that share one or more common comparators .The objective of this study was to compare CGRPmAbs with BoNT-A in the preventive treatment of chronic migraine through an adjusted indirect comparison meta-analysis.The protocol of this study was registered and published on PROSPERO (CRD42018089201) . The desWe included randomized controlled trials (RCTs) comparing CGRPmAbs or BoNT-A with placebo in the treatment of chronic migraine. RCTs with N-of-one design or cross-over design were excluded, since the interventions may have long-term effects and the duration of the persistent effect was unclarified . We inclclinicaltrials.gov were also searched for unpublished trials, and we tried to contact the authors of these unpublished trials for efficacy data. The website of Food and Drug Administration was searched, and the reference of the systematic reviews published in recent 5 years was read, to find out any missed trials. The records of potentially eligible studies were imported into Zotero (version 5.0), and two reviewers (Y-YC and T-WS) independently screened the titles and abstracts of the records, and disagreements on the eligibility of the trials were solved by group discussion. Full-text copies of potentially eligible RCTs were acquired for further evaluation, and then we obtained necessary information from the eligible RCTs.We searched OVID Medline, embase, Cochrane register of clinical trials (CENTRAL) from inception to September 2019 without any language restriction, using search strategies developed in advance. Before developing search strategy, we performed a pilot search using keywords—botulinum toxin, CGRP, and trial. Three experienced reviewers  developed the search strategies, the rationale and the specific details of the stratgies were showed in Standardized data extraction form was designed by using Epi Info (version 7.2.2.6). The following information were extracted: trial characteristics ; participant’s characteristics ; treatment details ; outcomes . Two reviewers (X-QY and T-CT) independently extracted data from the included RCTs; the reviewers compared each data item they extracted, found out the difference between the two datasets, corrected extraction errors, and tidied into one dataset for analysis.Risk of bias of the included trials was assessed by using the Cochrane risk of bias tool . RCTs weThe primary outcomes were the mean change in monthly headache days and the mean change in monthly migraine days. The number of days with headache or migraine is recommended to be adopted as one of the primary outcomes for trials assessing the effect of an intervention for migraine prophylaxis , and theSecondary outcomes included total monthly headache hours, >50% reduction in headache frequency, HIT-6, MIDAS, and treatment-related adverse event rate. We used the total headache hours to assess the cumulative duration of headache attack in a month, since one headache day could be counted when a headache duration lasted longer than 4 h. Responder is normally defined as a >50% reduction in headache frequency in migraine prophylaxis trials, and we aimed to assess the responder rate in this review. HIT-6 and MIDAS are scales for measuring the health impact of migraine; higher scores indicate lower quality of life. Tolerability was measured by calculating the rate of dropouts owing to adverse effect.An adjusted indirect treatment comparison was performed on the basis of Bucher’s method , which cWe analyzed the effect size of CGRPmAbs (treatment A) or BoNT-A (treatment B) by comparing with placebo control (treatment C). Changes in monthly headache days, migraine days, total headache hours, HIT-6, and MIDAS were calculated as standardized mean differences (SMDs) and their relative 95%confidence intervals (95%CIs). >50% reduction in headache frequency, adverse event rate, and tolerability were calculated as relative ratios (RRs) and related 95%CIs. We applied a continuity correction for RCTs with a 0 cell count by adding 0.5 to all cell frequencies .2 statistics was also used to assess the extent of heterogeneity for each outcome measurement, which is roughly classified according to the Cochane handbook (version 5.1): 0–40%, might not be important; 30–60%, may represent moderate heterogeneity; 50–90%, may represent substantial heterogeneity; 75–100%: considerable heterogeneity. Analysis of heterogeneity was also performed by using netmeta packages in R 3.6.0.We assessed between-study heterogeneity by Cochran’s Q test and further assessed the consistency of the analysis by using a design-by-treatment decomposition approach . Global We assessed the P-score of CGRPmAbs or BoNT-A, which measures the extent of certainty that a treatment is better than another  and is cConsidering the potential heterogeneity in the administration ways and timepoints of CGRPmAbs, we performed a subgroup analysis by including the treatment arms of CGRPmAbs that adopted commercially available dosage and recommended treatment intervals . The primary outcomes and responde rate were preferentially analyzed for efficacy outcomes, since these outcomes were the reason for designing CGRPmAbs.Considering the equivalence of baseline characteristics, we performed a sensitivity analysis by including two BoNT-A trials and three CGRPmAbs trials that had similar baseline characteritics and re-analyzing the primary outcomes.n = 4,678) after screening 1049 articles  in week-12 assessment, and the results showed that BoNT-A was the most effective , and we found that the heterogeneity originated from the design of BoNT-A vs. placebo . Similar results were found in the week-8 assessment (We included 6 RCTs (sessment .n = 2452) in week-12 assessment, and the results showed that galcanezumab had the largest reduction in migraine days . The assessments at week 4 and week 8 presented similar results (We included 4 RCTs ( results .n = 2742) in week-24 assessment. The meta-analysis showed that galcanezumab 120 mg group ranked the most effective .We included 4 RCTs (n = 1826) in week-12 assessment, the result showed that galcanezumab 120 mg , and the heterogeneity originated from the design of BoNT-A vs. placebo . The responder rates in the placebo arms were similar in BoNT-A  and CGRPmAbs .We included 4 RCTs (n = 1981) in week-12 assessment, and the results showed that fremanezumab 675/225/225 mg ranked the most effective , and the heterogeneity originated from the design of BoNT-A vs. placebo .We included 4 RCTs (n = 1320) in week-12 assessment, the results showed that galcanezumab 120 mg ranked the most effective  and insignificant heterogeneity was found.We included 3 RCTs (n = 2516) in week-12 assessment. The results showed that BoNT-A caused the least treatment-related adverse events .We included 5 RCTs (n = 1321) were included for the week-24 assessment, and the results showed that eptinezumab 30 mg had the least treatment-related adverse events ; the results showed that BoNT-A was the most effective but it was no significantly superior over fremanezumab 675 mg quartely . The subgroup analysis in migraine days included 5 RCTs (n = 3145); the results showed that galcanezumab 120 mg monthly was the most effective but it was not significantly superior over fremenezumab 675 mg quartely and BoNT-A (n = 1289); the results showed that galcanezumab 120 mg monthly was the most effective, but it was not significantly superior over eptinezumab 100 mg quartely and BoNT-A. The subgroup analyses showed results consistent with the main analysis  CGRPmAbs and BoNT-A were both effective in reducing headache days. Galcanezumab and fremanezumab were superior over BoNT-A in reducing migraine days at week 12, and galcanezumab was superior over BoNT-A in reducing headache hours at week 24, which indicates a short-term superiority of CGRPmAbs over BoNT-A. However, a contradictory finding in >50% reduction in headache frequency showed that there was no difference between galcanezumab and BoNT-A. 2) CGRPmAbs and BoNT-A were both effective in reducing HIT-6 and MIDAS. Fremanezumab was superior over BoNT-A in reducing HIT-6 scores at week 12, galcanezumab had better effect than BoNT-A in reducing MIDAS at week 12, which also indicates a short-term advantage of CGRPmAbs. 3) Both CGRPmAbs and BoNT-A caused similar adverse event rate, and the tolerability rate between them was also similar. There was little difference between them at week 12 but CGRPmAbs (eptinezumab) had lower adverse event rate at week 24.Equivalence in baseline characteristics is the basis of the comparison between CGRPmAbs and BoNT-A. The diagnostic criteria of chronic migraine are mainly ICHD-II in BoNT-A trials—especially the two trials  with theOne consideration in the comparatability of CGRPmAbs vs. BoNT-A was the response rate of placebo. Owing to the difference in ways of administration, placebo response might vary between BoNT-A and CGRPmAbs. A study recently reported that the placebo BoNT-A had a higher responder rate than the placebo CGRPmAbs , howeverAnother consideration in the comparatability was that, unlike BoNT-A that had a definite and univocal injection paradigm, CGRPmAbs presented with different ways of administration ; and CGRPmAbs were tested in dosages that were not used in practice. We therefore performed a subgroup analysis to include CGRPmAbs with commercially available or recommended dosage, and similar results were found with the main analysis, which might indicate that commercially available CGRPmAbs and BoNT-A had similar effects in reducing headache days. The subgroup analysis might also indicate that difference in administration ways was not the main source of heterogeneity of the meta-analysis.We had an interesting finding in the study—although CGRPmAbs and BoNT-A had similar effects on the reduction of headache days, CGRPmAbs caused more reduction in migraine days than BoNT-A. Inconsistent findings between headache days and migraine days were found; the difference in effect may be caused by their difference in biological mechanism. The anti-migraine effect of BoNT-A is associated with relaxation of pathological muscle tension, anti-inflammatory effect, and affecting central afferent transport—includes inhibiting the release of substance P and CGRP . The relAlthough CGRPmAbs showed some short-term benefits in reducing migraine days and headache hours, there are still concerns about its advantages in the preventive treatment of chronic migraine. First, some headache experts would quibble about differentiating between headache days and migraine days. The headaches are milder and resemble tension-type headaches, and they might be actually mild migraines. Making this distinction is probably not useful. Second, Contradicting findings were found across outcomes—CGRPmAbs showed advantages in migraine days and headache hours but no advantages in the >50% reduction in headache frequency. These contradictory findings might indicate heterogeneous definition in the outcomes of headache frequency—headache days, migraine days, migraine frequency, and migraine episodes. Third, CGRPmAbs take action immediately after several days of administration, while the action of BoNTA is often delayed, so CGRPmAbs might not had advantages in the long-term when compared with BoNT-A. Based on these grounds, we concluded that CGRPmAbs and BoNT-A had similar effect in the preventive treatment of chronic migraine. The advantages of CGRPmAbs against BoNT-A should be further examined in head-to-head comparison trials.With the advantage in reducing migraine days, CGRPmAbs were also superior over BoNT-A in reducing headache hours and headache impact (HIT-6 and MIDAS). The superiority of CGRPmAbs over BoNT-A was found based on the results of indirect comparisons. Whether to apply the evidence to clinical practice should be considered in several aspects. First, the confidence of the indirect comparison was a major concern. Although we found moderate heterogeneity in the analysis of migraine days (one of the primary outcomes) and no important heterogeneity in headache hours, and MIDAS, we found considerable heterogeneity in headache days, >50% reduction in headache frequency, and HIT-6. The design-by-treatment analysis by decomposing of Cochran’s Q found that the heterogeneity was from the design of BoNT-A vs. placebo. This finding was consistent with the results of a recently published systematic review . SignifiBoth CGRPmAbs and BoNT-A are with mild adverse effect that were transient and no additional medical care was needed. Their adverse events were similar—most of them were neck pain and injection-site pain; these adverse effects are closely related to the administration instead of the actual effect of drug. Other adverse effects might be the consequence of the actual effect of the drugs; eg, some patients have a feeling of muscle weakness after BoNT-A injection, and some reported hypertonia or infections after CGRPmAbs injection. Although eptinezumab appeared to cause significantly less adverse events than BoNT-A at week 24, BoNT-A was still preferable since most of the adverse events were mild and tolerable.Our study has several limitations. First, we compared CGRPmAbs and BoNT-A indirectly by using placebo as a common comparator; the variations in the placebo effect sizes and heterogeneity between BoNT-A trials might influence our results. Such as the doses of BoNT-A varied from 20 to 200U, and the injection sites varied between studies—although many of the trials followed the injection protocol that were used in two large scale trials , which sIn summary, although CGRPmAbs showed some advantages in reducing migraine days and a possibly small advantage in causing less adverse events, BoNT-A might be preferentially selected owing to its cost-effectiveness profiles. Our study results also indicated that Head-to-head comparison trials with long-term assessments are warranted to verify the study findings.


Many locations around the world have used real-time estimates of the time-varying effective reproductive number ( The time-varying effective reproductive number (Rt) is useful for monitoring transmission of infections such as COVID-19, but reporting delays impact case count-based estimation methods. Here, the authors demonstrate and validate a method for estimation of Rt based on viral load data from Hong Kong that does not require accurate daily counts. Though efforts have been made to reduce the impact of lag in 4, the majority of these approaches tend only to be able to estimate 5, because of delays between individuals being infected and polymerase chain reaction (PCR) detectable and/or showing symptoms 6, and because of delays between illness onset and diagnosis. In Hong Kong, we estimated 8.Monitoring the transmission of an emerging infectious disease in a timely manner is crucial to evaluate the effectiveness of public health and social measures and to inform better control policies. During the coronavirus diseases 2019 (COVID-19) pandemic, real-time assessment of transmission has generally been achieved through monitoring the time-varying effective reproductive number, 9. While viral loads can vary across individuals, with some shedding more than others11, the mean distribution of viral loads from a group of patients measured around the time of illness onset will tend to have higher values than that of viral loads from a group of patients measured at a later time after infection12. Collectively, higher population-level viral loads would correlate with more infected persons being earlier in the course of infection and vice versa13. Viral loads can be proxied by cycle threshold (Ct) values in the real-time quantitative reverse-transcription polymerase chain reaction (RT-qPCR) assay, with lower Ct values indicative of higher viral loads.An individual infected by SARS-CoV-2 will typically experience viral load peaking around illness onset and monotonically decreasing during the following two weeks13. The method was demonstrated in a modeling study using cross-sectional samples in a small-scale outbreak in Boston13 while the correlation was also observed over an epidemic wave elsewhere14. Here, we incorporated Ct values from COVID-19 cases in Hong Kong, a location with intense surveillance and case-finding efforts, to demonstrate that including data on population viral load distributions from symptom-based surveillance could support real-time tracking of transmission.A recent study showed that the distribution of viral loads among confirmed cases can provide inferences on transmission dynamics within populations, where population-level Ct values skewing towards lower values indicate more individuals have been recently infected, corresponding to an increasing rate of epidemic growth in the community, especially where single strain dominates15 (see Methods). Close contacts of confirmed cases are traced and placed into quarantine outside the home, and repeatedly tested. All laboratory-confirmed COVID-19 cases, including asymptomatic cases, are isolated within the hospital and receive multiple RT-qPCR tests during their stay. After excluding imported cases, we analyzed the first available record of Ct value (derived from RT-qPCR tests targeting E gene16) for each confirmed case and characterized the daily distribution of Ct values (measured by mean and skewness) that were sorted by sampling days. We included two consecutive epidemics in July–August 2020  and November 2020 through March 2021 , which were dominated by local transmissions instead of imported cases17.In Hong Kong, COVID-19 cases are detected through clinical diagnosis for individuals with acute respiratory symptoms and public health surveillance for the community with a priority to people with pre-defined high exposure risks18.A total of 8646 local COVID-19 cases were detected during periods studied, among which 77% : 1.050–1.063) per day after illness onset  Fig. . We cond01) Fig.  and for We performed a further validation of our results by training the model using data from November to December 2020  and predicting the later stage of the fourth wave and the third wave, and found the high accuracy of predictions still held  encountered by incidence-based methods for assessing transmission6. Although studies4 demonstrated nowcasting and projection of incidence-based In this study, we applied a simplified Ct-based method to provide precise estimates of daily 20, while our study provides precise longitudinal 13. Temporal changes in population Ct distribution over an epidemic largely reflect changes in infection-to-sampling delays that is determined by delays of infection-to-onset  and onset-to-testing . We showed that the onset-to-testing did not provide additional information to the population Ct distribution  occur with variant infections26, this may lead to decreased average Ct values when By the time this study was performed, there were limited VoCs circulating in Hong KongTo summarize, in this analysis we applied a simplified method to incorporate the population-level viral loads into the real-time estimation of transmission rates for COVID-19 under symptom-based surveillance. We demonstrated that the Ct-based method could provide accurate nowcasting of 27. Cases were classified as “imported cases”, “local cases epidemiologically linked with imported cases”, “unlinked local cases”, and “local cases epidemiologically linked with local cases” according to their epidemiological characteristics and location of infection. All suspected COVID-19 cases were confirmed by RT-qPCR in a local centralized public health laboratory. A laboratory-confirmed COVID-19 case was defined as a local case if the case did not visit places outside of Hong Kong in the 14 days before symptom onset (for symptomatic cases) or confirmation (for asymptomatic cases); otherwise defined as imported cases.Hong Kong was among the first places to identify COVID-19 cases globally, with its first COVID-19 case detected in late January 202028 and the extremely small number of local cases linked with imported cases in Hong Kong (<0.1%), we assumed that all unlinked local cases were infected from other local cases. We did not include the first two waves  as they were predominately imported cases and smaller clusters linked to those imported cases17.By the time of analysis, four different waves of transmissions have occurred in Hong Kong. In this study, we restricted our analyses to the third (July 2020 to August 2020) and fourth (November 2020 to March 2021) waves which were dominated by local transmission, where 89% were local cases. Since we were interested in the local transmission of COVID-19, we only included local cases  in our analyses. Given the stringent border controls since July 202015. Upon case confirmation, contact tracing was carried out based on epidemiological information, with details described elsewhere29. Among 8646 local COVID-19 cases confirmed during our studied periods, 77% (6700 out of 8646) were detected symptomatic and 65% (5651 out of 8646) were found with epidemiological links with other known cases; across 23% (1946 out of 8646) of cases who were detected as asymptomatic, 81% (1584 out of 1946) of them were linked to other local cases. As such, the surveillance of COVID-19 in Hong Kong is largely symptom and contact-tracing-based.In Hong Kong, local COVID-19 cases were generally detected from clinical diagnoses that targeted people with acute respiratory symptoms and from public health surveillance that targeted populations with predefined high risks of exposures  by health authorities® Modular SARS-CoV-2 (COVID-19) E-gene, TIB Molbiol/Roche, Berlin, Germany)16 were recorded as Ct values in the system. The Ct value is the number of cycles needed to amplify the viral RNA in a specimen where the reported fluorescent signal reaches a pre-defined level in RT-qPCR assays. Therefore, the Ct value is inversely associated with viral load and could be used as a semi-quantitative measurement for viral load. In our main analysis, we used Ct values to measure viral load and analyzed the first recorded Ct value for each local case  during the study period. Population viral load distributions were assessed by the date when samples were collected.In Hong Kong, all confirmed COVID-19 cases (including asymptomatic cases) were admitted to hospitals for isolation and standardized management, with their hospitalization records stored in the data system managed by Hospital Authority (HA). Results for SARS-CoV-2 RT-qPCR tests .Ethical approval for this study was obtained from the Institutional Review Board of the University of Hong Kong (IRB No. UW 20-341).30. Briefly, local COVID-19 cases confirmed on each day 31. We assumed an average 5.2 days (SD 3.9) for the incubation period19 and an average 4.7 days  delay between illness onset to reporting empirically observed in Hong Kong, which were used for deconvolution. In this framework, the daily local 19 and the infectiousness relative to onset5 (details described elsewhere7). To fully utilize available case count information and to provide more timely 30 and calculated 32. To account for the uncertainty of other parameter such as the incubation period, we used an bootstrap approach in Salje et al33 to reconstruct 200 epidemic curves and perform estimation. After that we presented the mean, 2.5% and 97.5% quantiles for those 200 7.We estimated the incidence-based We analyzed the first available Ct value record for each local COVID-19 case  or at ) against34 to measure the distribution of Ct values that were sampled on date We used the mean  and we set lengths of these alternative training periods like 30, 40, 50, and 60 days respectively, after which we compared their adjusted R square and demonstrated the time period covered by the best-fit model over training periods of the same length 8\documeResults suggested similar predictions from models with and without considering cases’ age distribution  did not alter the association between population Ct distribution and incidence-based To assess whether our results would be affected by changes in sampling strategies in Hong Kong, we first looked at temporal changes in the proportion of symptomatic cases among all confirmed local cases  using dWe further performed tenfold cross-validation by randomly splitting the data between 6 July 2020 and 31 March 2021 into ten validation sets, after excluding days when less than five available Ct samples were collected. For each validation, we held one set as a testing set and trained the remaining nine sets using the main model (Eq. ). We comn = 7.5 million, approximately the same size to the population in Hong Kong) and initial infections of 0.001%. Briefly, we simulated infections with a stochastic SEIR model, with compartments for susceptible (S), exposed-but-not-yet-infectious (E), infectious (I), and recovered (R). The compartmental transition equations are listed below:19) indicated the average time for individuals to transit from E to I, while 13) referred to the observed mean infectious period. Detailed descriptions of parameters were listed in Supplementary Table We used a susceptible-exposed-infectious-recovered (SEIR) model to simulate two consecutive epidemic waves assuming a closed population (t to synthesize the process of two consecutive epidemic wavesWe used synthetic 36) would be detected after illness onset. We assumed the incubation period followed log-normal distribution 19, while we estimated the delays between onset to detection with a gamma distribution (shape = 1.83 and rate = 0.43) using observations from Hong Kong.In symptom-based surveillance, we assumed that only individuals who developed symptoms after infections  during the initial stage of the second simulated wave.We simulated four different scenarios to represent various intensities of case detection , with the lowest Ct value  following a normal distribution with a mean of 22.3 and SD of 4.211. The duration of viral shedding since onset was parameterized as normally distributed with mean and SD of 17 and 0.94 days38. Each infected individual, if detected, would then have their corresponding sampled Ct values as the Ct value falling on day We simulated the viral load trajectories over the infection course for each detected symptomatic case using the previously published method3 that has accounted for delays and other sources of uncertainty in a more sophisticated way. The incubation period and reporting delay that were used for deconvolution were assumed to follow the delay distributions that were simulated from symptom-based surveillance. The mean and variance of the generation interval under the SEIR model were specified as https://github.com/epiforecasts/EpiNow2.Incidence-based R square of models fitted over different training periods during the first simulated wave ..6). The To investigate the uncertainty in sampling Ct values and therefore the accuracy of Ct-based All statistical analyses were conducted in R version 4.1.2 .Further information on research design is available in the Supplementary InformationPeer Review FileReporting Summary


Coronavirus disease 2019 (COVID-19) is a viral respiratory infection caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). While SARS-CoV-2 is a leading cause of morbidity and mortality in older adults, COVID-19 also affects newborn infants in nurseries and the Neonatal Intensive Care Units (NICUs). The majority of infected neonates are believed to acquire SARS-CoV-2 by horizontal transmission, and most of them have asymptomatic or mild symptomatic infections. In rare cases, infants with COVID-19 may have severe complications resulting in death. We report a case of COVID-19 in a premature neonate born at 34 weeks gestational age who presented with hypothermia and respiratory distress and subsequently developed clinical and radiological signs of necrotizing enterocolitis (NEC). The neonate received medical management, including antibiotics, suspension of gastric feeds, and intensive NICU support. The neonate's clinical condition improved without surgical intervention, and after 10 days of antibiotics and gradual reestablishment of gastric feeds, patient health condition returned to normal, and weeks later, he was discharged home. COVID-19 in infants is frequently asymptomatic or associated with mild disease, and in rare cases, it may be associated with severe gastrointestinal complications including NEC. The number of deaths due to COVID-19 in the US is the highest in the world and reaching 600,000. Information on the effect of COVID-19 among newborn infants indicates that the majority of infected infants, including neonates in nurseries and Neonatal Intensive Care Units (NICUs), are believed to acquire SARS-CoV-2 by horizontal transmission, and most of them have had asymptomatic or mildly symptomatic infections [Coronavirus disease 2019 (COVID-19) is a viral respiratory infection caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), a betacoronavirus, that has spread worldwide reaching pandemic proportions [fections . Extrapufections , 5. LimiChlamydia negative, and group B streptococci negative. Upon admission to the labor and delivery unit, the mother tested positive for SARS-CoV-2 by routine nasopharyngeal polymerase chain reaction (PCR) screening. The mother denied exposure to COVID-19 sick contacts, but did work in a community urgent care center . The mother did not report any respiratory or nonrespiratory symptoms from her COVID-19 infection during or following her hospital stay.A 27-year-old G1P0 mother presented to the hospital in preterm labor with preterm premature rupture of membranes (PPROM) at 33 1/7 weeks gestation. Pregnancy was complicated by the mother with a history of asthma and obesity. Prenatal laboratory results included HIV negative, RPR nonreactive, hepatitis B negative, rubella immune, GC/Following admission for PPROM, the mother was placed on cardiotocographic fetal monitoring in the labor and delivery unit. The fetal heart tracing was reassuring with a reactive fetal heart tracing. Fetal ultrasound showed the fetus in cephalic presentation with an estimated fetal weight, at the 30th percentile for age, of 2,031 g. The mother was given a course of betamethasone to facilitate fetal lung maturity, and she was started on prophylactic azithromycin and ampicillin, due to risk of infection secondary to PPROM. The mother was kept on the antepartum service until she reached 34 weeks gestation with reassuring daily biophysical profiles and unremarkable serial complete blood count (CBC) monitoring.A planned induction of labor was started at 34 weeks gestation which resulted in a spontaneous vaginal delivery of a healthy male newborn with APGAR scores of 8 at 1 minute and 8 at 5 minutes and weighing 2,065 g. The placenta, evaluated by pathology, showed a small intraparenchymal hematoma and a small focal infarction. The mother did not have contact with her newborn postnatally and was not permitted to visit the NICU until 10 days from her positive COVID-19 testing, per hospital policy and Centers for Disease Control and Prevention (CDC) guidelines. The neonate was admitted to the NICU immediately following delivery. He was breathing room air without tachypnea or increased work of breathing and was started on oral feeds of expressed breast milk and supplemented with formula when breast milk was not available. CBC with differential on admission was stable without a left shift , and a bCase series of COVID-19 in neonates have identified a variety of clinical presentations from asymptomatic to severe disease, most often presenting with respiratory distress . The NatNecrotizing enterocolitis is a significant cause of morbidity and mortality among infants in the NICU. Although necrotizing enterocolitis continues to afflict neonates of all sizes and gestational age, it is much more commonly seen in infants born less than 1500 g in weight and less than 28 weeks in gestation . A studyCoronavirus infection in human subjects is not limited to the respiratory tract. There was a reported cluster of NEC cases associated with infections due to coronavirus-like agents in the early 1980s. Histopathology evaluation of intestinal specimens revealed coronavirus-like particles within intracytoplasmic vesicles of damaged mucosal cells of the small intestine, appendix, and colon , 13. In This was a formula-fed premature newborn infant who shortly after birth had gastric feed intolerance and AXR imaging consistent with NEC. This case of NEC is unusual because the age of onset was too early, the patient was not a very-low-weight premature infant, and the infant had no low gestational weight. The fact that the neonate had COVID-19 at the time NEC was diagnosed suggests that SARS-CoV-2 infection was likely associated with this severe gastrointestinal disorder.


Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the virus responsible for the coronavirus disease 2019 (COVID-19) pandemic. As patients recover from COVID-19, some continue to report persisting symptoms weeks to months after acute infection. These effects have been referred to as post-acute sequelae of SARS-CoV-2 infection (PASC). We report the case of a 38-year-old woman suffering from PASC symptoms following acute COVID-19 in October 2020. During her acute infection phase, she had a home recovery and reported her predominant symptoms as fatigue, headaches, body pain, and shortness of breath. After most of her symptoms were resolved, she continued to have periodic episodes of fatigue and headaches, along with random shortness of breath while at rest and during activities for months beyond the acute phase of the illness. She also noted the presence of “brain fog,” as if lacking the same clarity that she had prior to her illness. These symptoms persisted for three months before the patient underwent enhanced external counterpulsation (EECP) therapy in one-hour sessions, three times per week. This therapy was chosen based on the mechanism of action of EECP benefiting patients with ischemic cardiovascular diseases. After one week, her “brain fog” had improved, with shortness of breath improving after 1.5 weeks. The patient reported returning to pre-COVID health and fitness after approximately five weeks of EECP treatment. To our knowledge, this is the first case of using EECP for post-COVID shortness of breath, fatigue, and “brain fog.” In the unprecedented times of the coronavirus disease 2019 (COVID-19) pandemic, there are increasing reports of persistent symptoms weeks to months after recovery from acute COVID-19 [In October 2020, a 38-year-old Hispanic woman with no preexisting health conditions noted the onset of what she was certain to be her usual allergy symptoms, including itchy eyes, sneezing, sinus drainage, and headache. She was generally healthy and was aware of standard COVID19 precautions being a working healthcare professional. As a precautionary measure she took an additional temperature measurement, which came to be normal. Overnight, she noticed a new onset of fever, severe body aches, and pronounced fatigue. The next day she was tested for both influenza A/B and COVID-19 via antigen test, with a negative flu result but a positive COVID-19 result. For verification, she also took a COVID-19 polymerase chain reaction test that also resulted in a positive for infection. She was prescribed conventional therapy at the time, including a cocktail of three vitamins , hydroxychloroquine 200 mg twice daily for six days, and Tylenol 500 mg two tablets every four to six hours as needed. She had an at-home recovery and reported her predominant symptoms during the acute phase as fatigue, headaches, body pain, and shortness of breath.After most of her symptoms were resolved, she continued to have periodic episodes of fatigue and headaches, along with random shortness of breath while at rest and during activities for months beyond the acute phase of the illness. She also noted the presence of “brain fog,” as if lacking the same clarity that she had prior to her illness. These symptoms persisted for three months before the patient underwent EECP for one-hour sessions, three times per week. The patient underwent a non-standard EECP regimen of three days per week for five weeks due to convenience. This therapy was chosen based on EECP’s unique mechanism of action and the known cardiac and extra-cardiac effects. After one week, her “brain fog” had improved, with shortness of breath improving after 1.5 weeks. The patient reported returning to pre-COVID-19 health and fitness after approximately five weeks of EECP treatment.Several population studies in post-COVID-19 patients have emerged around the world, ranging in follow-up time from a few weeks to several months. An early study conducted during March-June 2020 by the United States Centers for Disease Control and Prevention followed 274 patients at two to three weeks after initial positive COVID-19 test. They found that 34% of the patients reported at least one symptom, the most common symptoms included: cough (43%), fatigue (35%) congestion (30%), dyspnea (29%), confusion (20%) and chest pain (20%) [The underlying pathophysiology of PASC is still being understood. A leading hypothesis is that SARS-CoV-2 causes endothelial dysfunction by infecting endothelial cells around the body via the angiotensin converting enzyme-2 receptor, prompting release of inflammatory cytokines and compromising the epithelial-endothelial barrier at late stages of infection. Several studies assessing post-acute sequelae have found changes in cardiovascular, pulmonary, and neuropsychiatric organ systems. Puntmann et al. performed cardiac magnetic resonance imaging in 100 patients approximately 71 days after the initial COVID-19 diagnosis and found abnormal findings in 78% of the patients . Huang eBased on the pathophysiological changes with PASC, EECP could be a suitable treatment method for such patients. EECP is a Food and Drug Administration-approved, non-invasive outpatient therapy for patients with chronic stable angina and/or heart failure of ischemic etiology. Standard therapy involves 35 one-hour treatments over seven weeks. Patients lie on a treatment table where compressive cuffs (similar to large blood pressure cuffs) are securely wrapped around their calves, thighs, and buttocks. These cuffs inflate in a distal-to-proximal sequence during diastole and deflate simultaneously just prior to the onset of systole. Inflation and deflation are specifically timed to the patient’s electrocardiogram to optimize therapeutic benefit. This mechanical compression induces physiologic and biochemical changes in the vasculature, leading to angiogenesis and increased coronary function. The compression produces pulsatile shear stress, which has been associated with improvements in systemic endothelial function via modulation of vasodilating  and pro-inflammatory agents  .In patients with underlying cardiovascular disease, EECP has been shown to significantly improve Canadian Cardiovascular Society angina class, Duke Activity Score Index, Seattle Angina Questionnaire, and six-minute walking distance, all of which are independent markers associated with mortality benefits. EECP has also been shown to improve time to ST-segment depression, treadmill exercise duration, ejection fraction, and cardiac output/efficiency .2-MaxKg) were seen after three weeks of EECP therapy [The benefits of EECP are also evident in patients without underlying cardiovascular disease. A recently published study showed improved exercise endurance in those with low-to-normal exercise endurance, as well as in chronic obstructive pulmonary disease patients. Significant improvements in maximum oxygen uptake (VO therapy . Lastly,To our knowledge, this is the first case of using EECP for post-COVID dyspnea, fatigue, and “brain fog.” There are no current guidelines for the treatment of PASC, and management of the condition is largely based on patient presentation and symptoms and requires the efforts of a multidisciplinary team. This initial case report of a patient recovering from her post-acute COVID-19 symptoms suggests EECP may serve as a novel treatment modality for the management of PASC. More data are needed to further validate these findings.


Is variation in care management during terminal hospitalization among adults with metastatic cancer associated with sociodemographic status?In this cross-sectional study of 21 335 patients with metastatic cancer who died in the hospital, racial and ethnic minority patients and those with Medicare or Medicaid coverage were more likely to receive low-value, high-cost aggressive medical interventions at the end of life.This study’s findings suggest that identifying and understanding factors associated with the observed disparities will be helpful to inform communications with patients with metastatic cancer about end-of-life care. Many patients with metastatic cancer receive high-cost, low-value care near the end of life. Identifying patients with a high likelihood of receiving low-value care is an important step to improve appropriate end-of-life care.To analyze patterns of care and interventions during terminal hospitalizations and examine whether care management is associated with sociodemographic status among adult patients with metastatic cancer at the end of life.This retrospective, population-based cross-sectional study used data from the Healthcare Cost and Utilization Project to analyze all-payer, encounter-level information from multiple inpatient centers in the US. All utilization and hospital charge records from national inpatient sample data sets between January 1, 2010, and December 31, 2017 (n = 58 761 097), were screened. The final cohort included 21 335 patients 18 years and older at inpatient admission who had a principal diagnosis of metastatic cancer and died during hospitalization. Data for the current study were analyzed from January 1, 2010, to December 31, 2017.Patient demographic characteristics, patient insurance status, hospital location, and hospital teaching status.Receipt of systemic therapy (including chemotherapy and immunotherapy), receipt of invasive mechanical ventilation, emergency department (ED) admission, time from hospital admission to death, and total charges during a terminal hospitalization.P < .001; Black patients: OR, 1.39 ; P < .001; and Hispanic patients: OR, 1.45 ; P < .001), receiving invasive mechanical ventilation , and incurring higher total charges  compared with White patients. Privately insured patients had a lower likelihood of being admitted from the ED , receiving invasive mechanical ventilation , and incurring higher total charges  compared with Medicare and Medicaid beneficiaries.Among 21 335 patients with metastatic cancer who had terminal hospitalizations between 2010 and 2017, the median age was 65 years ; 54.0% of patients were female; 0.5% were American Indian, 3.3% were Asian or Pacific Islander, 14.1% were Black, 7.5% were Hispanic, 65.9% were White, and 3.1% were identified as other; 58.2% were insured by Medicare or Medicaid, and 33.2% were privately insured. Overall, 63.2% of patients were admitted from the ED, 4.6% received systemic therapy, and 19.2% received invasive mechanical ventilation during hospitalization. Racial and ethnic minority patients had a higher likelihood of being admitted from the ED (Asian or Pacific Islander patients: odds ratio [OR], 1.43 ; In this study, patients with metastatic cancer from racial and ethnic minority groups and those with Medicare or Medicaid coverage were more likely to receive low-value, aggressive interventions at the end of life. Further studies are needed to evaluate the underlying factors associated with disparities at the end of life to implement prospective interventions. This cross-sectional study uses data from the Healthcare Cost and Utilization Project national inpatient sample between 2010 and 2017 to examine care management patterns during terminal hospitalization among adult patients with metastatic cancer. Current guidelines define and discourage aggressive, invasive, and expensive medical services that represent low-value care at the end of life. The American Society of Clinical Oncology and the National Quality Forum define aggressive care as multiple hospital, intensive care unit, or emergency department (ED) admissions in the last 30 days of life, receipt of chemotherapy in the last 14 days of life, or enrollment in hospice 3 days or fewer before death.9 Patients with advanced cancer often experience a substantial worsening in health during their final months, occasioning inpatient admission and intensive procedures that add to the substantial emotional and financial burden of care during the final stages of illness12; yet, this intensive inpatient care often does not achieve end-of-life goals for patients and their families or caregivers.14 Furthermore, previous studies have reported higher rates of invasive end-of-life interventions and higher costs incurred among racial or ethnic minority individuals and patients with low socioeconomic status.20 Higher rates of life-extending medical interventions have been found among Black patients, prolonged hospitalizations among Black and Asian patients, and a higher likelihood of dying in the hospital among Black, Asian, and Hispanic patients compared with White patients.19Despite best practice guidelines from the American Society of Clinical Oncology and the National Quality Forum that discourage low-value end-of-life care, many patients with metastatic cancer continue to receive aggressive medical interventions throughout their final weeks of life.8 We aimed to assess additional measures of low-value care among this patient population in the context of terminal hospitalization; these measures included receipt of mechanical ventilation and systemic therapy, duration of hospitalization, total costs, and ED admission as a sign of unplanned care. An analysis of terminal inpatient encounters provides insight into the intensity of care received immediately before death and highlights opportunities for improved end-of-life care planning among patients with terminal cancer. We ultimately aimed to examine sociodemographic patterns in the use of interventions and the associated costs of inpatient care among this national cohort in the final days before an in-hospital death.To our knowledge, no previous study has specifically examined inpatient deaths among those with metastatic cancer on a population level in the US. The current study analyzed records of patients who died in the hospital and therefore received at least 1 measure of low-value end-of-life care according to previously cited signs of aggressive care.21 All records from national inpatient sample data sets between January 1, 2010, and December 31, 2017 (n = 58 761 097), were screened. Our cohort included all patients 18 years and older at hospital admission who had an in-hospital death and a principal diagnosis of metastatic cancer according to diagnostic codes from the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM); the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM); and the International Classification of Diseases, Tenth Revision, Procedure Coding System (ICD-10-PCS) (ICD-9-CM or ICD-10-CM diagnostic codes that were used to define the cohort are available in the eMethods and eTable 1 in the STROBE) reporting guideline for cross-sectional studies.This cross-sectional study analyzed data from the Agency for Healthcare Research and Quality Healthcare Cost and Utilization Project (HCUP) national inpatient sample, which includes 20% of all discharge records from community hospitals across the US.-10-PCS) . We sele22 Socioeconomic status was obtained from the estimated median household income quartile of residents in the zip code on record, with quartile 1 representing the lowest income22 ; HCUP coding includes race and ethnicity in 1 data element, with ethnicity taking precedence over race if the original record provided race and ethnicity separately.ICD-9-CM codes, and ICD-10-PCS codes  and 95% CIs, including all exposures as covariates for the following binary outcomes: ED admission, receipt of systemic therapy, receipt of mechanical ventilation, time from admission to death greater than the median value of the total cohort, and total charges billed to insurance greater than the median value of the total cohort. The preliminary analysis revealed no multicollinearity. We assessed and reported the inclusion of standardized residuals with a value greater than 2.5 SDs. Model significance and accuracy were evaluated using omnibus tests and analysis of receiver operating characteristic curves. We used and reported 2-tailed P values with a significance level of .05 for all comparisons. All statistical analyses were performed using SPSS software, version 27 (IBM SPSS Statistics).We generated descriptive statistics using χAmong 21 335 patients with metastatic cancer who had terminal hospitalizations between 2010 and 2017, the median age was 65 years ; 54.0% of patients were female, 45.9% were male; 0.5% were American Indian, 3.3% were Asian or Pacific Islander, 14.1% were Black, 7.5% were Hispanic, 65.9% were White, and 3.1% were identified as other . Most paIn the multivariate analysis, several factors were associated with the receipt of aggressive inpatient services near the end of life. Overall, patients from several racial and ethnic minority groups, including Asian or Pacific Islander patients, Black patients, and Hispanic patients, and patients with Medicare or Medicaid coverage had a higher likelihood of being admitted from the ED, receiving more aggressive and higher-cost care, and having a longer terminal hospitalization compared with White patients and patients with private insurance. A higher likelihood of these outcomes was also observed among patients receiving care at urban hospitals, particularly urban teaching hospitals, compared with those receiving care at rural hospitals. Detailed results of the multivariable analysis are presented in the following paragraphs and shown in P = .02); patients who were Asian or Pacific Islander , Black , and Hispanic ; patients living in zip codes with higher median income quartiles ; and patients receiving care at an urban nonteaching hospital  (P < .001), patients with private insurance , self-payers or those with other insurance , and patients receiving care at a hospital located in the Midwest , South , or West .A higher likelihood of ED admission was observed among patients aged 50 to 59 years  A. A loweP = .02) and patients receiving care at urban teaching  or urban nonteaching  hospitals (P < .001), Black patients , self-payers or those with other insurance , and patients receiving care at a hospital in the Midwest .A higher likelihood of receiving systemic therapy was observed among female patients  and patients receiving care at urban teaching  or urban nonteaching  hospitals (P < .001), female patients , patients with private insurance , self-payers or those with other insurance , and patients living in zip codes with higher median income quartiles .A higher likelihood of receiving invasive mechanical ventilation was observed among Black patients , Black , Hispanic , and of other races and ethnicities ; patients living in zip codes with higher median income quartiles ; patients receiving care at urban teaching  or urban nonteaching  hospitals; and patients receiving care at a hospital located in the West  (P < .001), female patients , American Indian patients , patients with private insurance , self-payers or those with other insurance , and patients receiving care at a hospital located in the Midwest  or South .A higher likelihood of greater total charges was observed among patients who were Asian or Pacific Islander  B. A loweThis cross-sectional study is the first, to our knowledge, to find sociodemographic disparities in the receipt of high-cost intensive services among patients with metastatic cancer during terminal hospitalization based on a contemporary, population-based cohort. These results highlight an unmet need for improved quality and equity of end-of-life care among patients with metastatic cancer who receive care management in the inpatient setting.17; in particular, studies have found high rates of aggressive care among Black patients.20 Previous studies have also reported an association between greater use of aggressive medical interventions and lower rates of hospice enrollment among Asian, Black, and Hispanic patients with advanced cancer.24 Among our sample of patients with metastatic cancer who died in the hospital, minority race or ethnicity was associated with several measures of aggressive end-of-life care. Although previous work has found similar disparities,19 the current findings highlight existing disparities that are specifically associated with inpatient terminal cancer management. The current findings do not account for patterns of care in the home or outpatient setting, and we were not able to directly evaluate palliative care or hospice use in the study population. However, our observations in the context of previous findings suggest several aspects of patient care that may be associated with disparities in end-of-life inpatient care management: communication, cultural awareness, access to care, and structural racism.Previous studies have reported increased use of low-value end-of-life medical services among minority populations25 Palliative measures have also been associated with decreased use of aggressive, invasive, and expensive medical services27; thus, barriers to the use of palliative services may be associated with aggressive inpatient care at the end of life. Hispanic patients have cited limited information and education about advanced care planning from health care professionals as obstacles to creating an end-of-life care plan and receiving palliative care.29 In addition, among patients with limited English proficiency, professional interpreters are often used unsuccessfully or not at all, impairing patient and family understanding of illness, prognosis, and end-of-life medical decisions.30The observed association between measures of high-cost, low-value care and minority race and ethnicity may reflect differences in cultural and environmental factors associated with preferences for end-of-life medical care as well as disparities in the use of palliative and advanced care planning services. Palliative care discussions and services enhance quality of life for both terminally ill patients and their caregivers and promote goal-concordant care, including the option of an at-home death.34 Additional studies have highlighted faith-based objections to hospice enrollment among Hispanic patients.34 Comprehensive goals-of-care discussions require that the practitioner be able to recognize and address patient preferences that are based on personal and cultural beliefs. Cultural barriers between patient and practitioner may influence patient decisions to pursue aggressive therapies and perpetuate the use of invasive interventions among terminally ill ethnic and racial minority patients.34 In addition, physician factors, including practice norms and expectations regarding patient goals, have been cited as factors associated with challenges in successful communication regarding end-of-life care management.36 These obstacles highlight opportunities to promote high-value care for minority patients through improved patient-practitioner communication and understanding.Another factor that may be associated with end-of-life care disparities is variation in cultural awareness among health care professionals. Previous work has found a greater preference for life-extending treatments among Black patients, particularly among those who reported relying on spirituality to cope with terminal illness.37 Many ethnic and racial minority patients have lower incomes and limited insurance coverage, and those with undocumented immigration status do not qualify for Medicaid coverage in many states.24 The higher likelihood of ED admission among Asian, Black, and Hispanic patients in the current sample may suggest unplanned end-of-life care and underlying barriers to accessing advanced care planning services that may limit the use of aggressive inpatient care at the end of life.In addition to communication barriers, obstacles to accessing health care have been associated with lower rates of hospice enrollment among racial and ethnic minority individuals and may therefore be associated with greater use of aggressive care. The criteria for hospice enrollment may alienate racial and ethnic minority patients; these criteria are variable and can require a prognosis of 6 months or less from a primary care physician, the presence of physical symptoms, and an obligation to forgo curative treatments.40 Previous work has reported high rates of aggressive care and low rates of advanced care planning among minority groups despite previous end-of-life care discussions with a practitioner41 as well as fewer positive nonverbal communication cues from practitioners during end-of-life care discussions with Black patients compared with White patients.42 These findings necessitate further investigation of the challenges encountered by patients from minority groups regarding end-of-life care management that may be associated with other factors, including possible racial discrimination.The least studied and arguably the biggest challenge in addressing cancer care disparities is structural bias.43 and suggests a pattern in the context of inpatient care received during terminal hospitalization among a large national cohort of patients with metastatic cancer. Previous work has found high rates of intensive care, low rates of routine goals-of-care discussions, and low rates of hospice use among Medicare beneficiaries in the general population46; 1 study has also reported increasing rates of late hospice enrollment and late hospitalizations among this population in the past 13 years.9 A substantial proportion of Medicare spending is devoted to hospital inpatient care. In 2018, payments for inpatient care accounted for $137 billion of Medicare spending compared with $19.3 billion for hospice care.47 Similar patterns have been found among Medicaid beneficiaries, albeit with even lower hospice use.48 Further examination of barriers to palliative care use among publicly insured patients is warranted to understand factors associated with the greater likelihood of aggressive care observed among this group.In addition, the current study found greater use of low-value end-of-life care among patients with Medicare or Medicaid coverage compared with private insurance; this finding is consistent with those of previous studies reporting low-value care among publicly insured patients50Although we define markers of low-value end-of-life care, the value of care is ultimately determined by a patient’s goals. Depending on a particular patient’s end-of-life wishes, goal-concordant care can encompass interventions that aim to maximize patient comfort as well as intensive life-extending interventions. In addition, although ED admission may be a sign of unplanned care for some patients, others may be transferred from a clinic to the ED for direct admission as part of routine care. Accurately defining goal-concordant care is dependent on context, and individual considerations must be balanced when making end-of-life care decisions.53The possible factors associated with disparities in end-of-life care among patients with metastatic cancer are complex, encompassing patient-practitioner communication, cultural preferences, access to care, and other systemic factors, including biases. Investigating and identifying specific barriers to high-value care encountered by racial and ethnic minority patients and patients with public insurance will be important in designing targeted interventions.This study has limitations. The study is retrospective and observational; therefore, the associations reported cannot be equated with causation. Our multivariate model does not adjust for unmeasured confounders or completely eliminate sociodemographic confounding factors. The cross-sectional study design reflects a single inpatient stay and does not reflect level of care, health care use, and costs before terminal hospitalization; the current analysis also pertains to data specific to the inpatient setting only and does not examine end-of-life care administered in the home or other outpatient settings. In addition, specific practice patterns may be associated with individual hospitals, and patients receiving treatment at the same facilities may experience similar care management approaches compared with patients with equivalent circumstances receiving treatment at different facilities; however, we were unable to account for within-center differences in the analysis.The immediate cause of death among patients in the sample is unknown; a proportion of in-hospital deaths analyzed may not be directly associated with terminal cancer and may instead be associated with unexpected acute illness or treatment complications. Metastatic cancer diagnoses are established through the primary diagnosis, which is defined as the condition associated with inpatient admission, and do not represent cancer registry diagnoses with more specific prognostic information. In addition, it is possible that patients with metastatic cancer may have been admitted using the diagnostic code corresponding to the primary cancer site and thus were not captured in this study. Further data regarding end-of-life care, including hospice enrollment, previous goals-of-care conversations, and comorbid conditions, are not available in the data but can have substantial implications for the course of treatment.Among patients with metastatic cancer who died in the hospital, increased rates of aggressive high-cost care were associated with Black and Asian or Pacific Islander race, Hispanic ethnicity, public insurance status, and admission to an urban teaching hospital. This study identified groups at risk of receiving high-cost, low-value interventions that may oppose the patient’s goals and exacerbate the physical, emotional, and financial burdens of terminal cancer. Future directions include qualitative studies assessing patient perspectives on end-of-life discussions and care options, including palliative services. Interventions may focus on initiating discussions and palliative measures earlier as well as facilitating discussions that emphasize assessing patient goals and optimizing patient education about care options. Identifying these disparities is important in guiding interventions designed to improve accessibility and the equitable use of high-value end-of-life services for patients with metastatic cancer.


Despite the effectiveness of cART, people living with HIV still experience an increased risk of serious non-AIDS events, as compared to the HIV negative population. Whether pre-cART microbial translocation (MT) and systemic inflammation might predict morbidity/mortality during suppressive cART, independently of other known risk factors, is still unclear. Thus, we aimed to investigate the role of pre-cART inflammation and MT as predictors of clinical progression in HIV+ patients enrolled in the Icona Foundation Study Cohort.We included Icona patients with ≥2 vials of plasma stored within 6 months before cART initiation and at least one CD4 count after therapy available. Circulating biomarker: LPS, sCD14, EndoCab, hs-CRP. Kaplan-Meier curves and Cox regression models were used. We defined the endpoint of clinical progression as the occurrence of a new AIDS-defining condition, severe non-AIDS condition (SNAEs) or death whichever occurred first. Follow-up accrued from the data of starting cART and was censored at the time of last available clinical visit. Biomarkers were evaluated as both binary (above/below median) and continuous variables .p = 0.056 for median-based model; p = 0.002 for 33% percentile-based model).We studied 486 patients with 125 clinical events: 39 (31%) AIDS, 66 (53%) SNAEs and 20 (16%) deaths. Among the analyzed MT and pro-inflammatory markers, hs-CRP seemed to be the only biomarker retaining some association with the endpoint of clinical progression (i.e. AIDS/SNAEs/death) after adjustment for confounders, both when the study population was stratified according to the median of the distribution (1.51 mg/L) and when the study population was stratified according to the 33% percentiles of the distribution . In particular, the higher the hs-CRP values, the higher the risk of clinical progression (Our data carries evidence for an association between the risk of disease progression after cART initiation and circulating pre-cART hs-CRP levels but not with levels of MT. These results suggest that pre-therapy HIV-driven pro-inflammatory milieu might overweight MT and its downstream immune-activation.The online version contains supplementary material available at 10.1186/s12879-021-06260-y. Despite the unquestioned success of cART in recovering CD4 T-cell count and in preventing disease progression –3, a fewThis is particularly true among patients who initiate cART at advanced disease stages and fail to achieve a significant CD4 recovery upon virologically-suppressive cART –12. GlooPersistently heightened immune activation and inflammation on cART have been associated with both inefficient CD4 recovery –17 and tIn untreated HIV infection, our group and others have shown that the markers of immune activation derived from the systemic translocation of bacterial byproducts through a damaged gut mucosal barrier, mainly lipopolysaccharide (LPS), are independent predictors of disease progression , 24. IntAmong PLWHIV on suppressive cART in North America, markers of innate immune activation and inflammation were much more strongly predictive of mortality than T-cell activation , 30, posNevertheless, whether or not markers of microbial translocation and systemic inflammation pre-cART predict morbidity/mortality during suppressive cART, independently of other known risk factors, is still under debate.Given these premises, we explored the possible associations between circulating markers of microbial translocation  and systemic inflammation (hs-CRP) measured before cART introduction and the risk of long-term disease progression upon cART start in PLWHIV enrolled in the Icona Foundation Study Cohort. Among markers of inflammation, we chose to investigate hs-CRP given its frequent routinary use in the clinical management of PLWHIV, reasoning that it might be an easy and informative biomarker to be exploited in the most personalized clinical management of cART-treated patients.The study population was selected from the Icona  Foundation cohort. Icona is an Italian multicenter prospective observational cohort study, set up in 1997 and including HIV-1 infected subjects . To dateDemographic, viro-immunological and clinical data as well as details on antiretroviral regimen, are registered in an electronic case report form (eCRF). All the clinical events, lab and viro-immunological parameters are registered in the electronic database from the enrollment till the last available follow-up, a follow-up visit is scheduled at least every 6 months.Of all participants in the cohort, we selected a subset of 2376 who on January 01, 2015 had already started cART, had ≥2 vials of plasma stored over the 6 months between entry and the date of cART initiation and ≥ 1 CD4 count after cART initiation. We have then extracted a random sample of 500 patients from this universe. For 24 of these patients (5%) the second vial could not be located and were not eventually included. CD4 count and HIV-RNA are typically measured on the same collected sample, so all patients also had ≥1 viral load during cART. Death and clinical events are recorded from the information on the medical record of the patients. Death records are not linked to national or regional registry and the accuracy of AIDS-defining and non-AIDS events diagnoses are checked by both central and on-site monitoring. Central monitoring to check the accuracy of the data entered is performed every 6 months while on-site monitoring annually. Of all participants in the cohort, we selected a subset of 2376 who on January 01, 2015 had already started cART, had ≥2 vials of plasma stored over the 6 months between entry and the date of cART initiation and ≥ 1 CD4 count after cART initiation. We have then extracted a random sample of 500 patients from this universe. For 24 of these patients (5%) the second vial could not be located and were not eventually included.The Icona Foundation study was approved by the Ethics Committee  of each participating institution. All of the individuals enrolled provided written informed consent at the time of enrolment.On the extracted stored samples, we retrospectively measured plasma levels of microbial translocation markers, such as LPS , sCD14 , EndoCAb  and the pro-inflammatory marker hs-C reactive protein, CRP , according to manufacturers’ instruction. Only one sample per participants stored prior tocART initiation was used.The Limulus amoebocyte lysate (LAL) test, an assay generally used to quantify endotoxin, presents several technical issues, due to reagent contaminations, as well as to the inhibitory nature of some plasma components . The proWe defined a primary composite endpoint of clinical progression as the occurrence of AIDS-defining condition, non-AIDS severe events (SNAEs) or death whichever occurred first. SNAEs included: cardiac decompensation, chronic renal insufficiency , end-stage liver diseases, myocardial infarction, malignancies, pneumonia, end-stage renal diseases (defined as 2 consecutive measurements of eGFR< 60 ml/min at least 3 months apart) and septic infections. More details regarding the exact endpoint-defining events included are provided in Supplementary Table We next defined two alternative composite endpoints after distinguishing non-infectious related events from infectious-related events. The latter group included i) AIDS-defining infections; ii) end-stage liver diseases caused by viral agents; iii) infectious-related malignancies; iii) pneumonia; and iv) sepsis  was used to evaluate the association between MT and systemic inflammation markers and each of the defined endpoints. Participants’ follow-up accrued from the date of starting cART up to one of the endpoint defining events . For those who did not develop any of the endpoint-defining events, was censored at time of last available clinical. Separate Cox regression models were fitted for each of the biomarkers both univariable and after controlling for key baseline time-fixed confounding factors . A final model was also constructed under the assumption that the association with each of the markers could have been further confounded by the remaining markers. Repeated measures of the markers were not available, and this prevented us from planning correction for potential post-baseline confounding.MT and pro-inflammatory markers were evaluated using both a binary variable (above and below median) and as a continuous variable . Dichotomisation was based on the median value of the study population because there are no standardised clinical cut-off values for these markers. For hsCRP we have also a categorization that used the 33% percentile in order to compare the risks between patients with low and intermediate values vs. high. The 66% percentile corresponds to the clinically relevant cut-off of 5.4 mg/l. The natural logarithmic scale was used to reduce variance, increase power and comparability between the results across markers.We also performed a number of sensitivity analyses: i) by repeating the main analysis on the subset of patients who had CD4 count less than 350 cell/mmc before cART starting, ii) after further controlling for mode of HIV transmission, smoking and alcohol consumption, iii) after excluding participants who showed hsCRP levels > 10 mg/L and iv) after restricting to those who had a complete profile for all biomarkers evaluated.We analyzed the data of 486 patients fulfilling the inclusion criteria and overall contributing to 1605 biomarker measures: 278 with LPS, 375 with hs-CRP, 477 with sCD14 and 475 with EndoCAb. Table p = 0.524), sCD14 (p = 0.821), EndoCAb (p = 0.083) and hs-CRP (p = 0.119) strata. Similar results were observed when we restricted the analysis to the 70 infectious-related events (data not shown).Using the primary composite endpoint of clinical progression, 125 progression events were recorded: 10.8 (0.77–14.8)/1000 PYFU new AIDS, 18.3 (14.2–23.3)/1000 PYFU SNAEs, and 5.56 (3.40–8.57)/1000 PYFU deaths, corresponding to 39 (31%) AIDS, 66 (53%) SNAEs and 20 (16%) deaths. Among the 66 SNAEs events we identified: 1 cardiac decompensation, 3 chronic renal insufficiency, 4 liver diseases, 5 myocardial infarctions, 16 malignancies, 1 myelitis, 1 pancreatitis, 11 pneumonia, 22 renal diseases, 2 septic infections. We found no major differences in the Kaplan Meier estimated cumulative probability of disease progression according to plasma LPS  and remained virtually unchanged after further adjustment for the other biomarkers , intermediate (1.2–5.3 mg/L) and high (> 5.3 mg/L). These results confirm those of the above-mentioned analysis and show a dose-response relationship with the outcome: the higher hs-CRP values, the higher the risk of clinical progression . Results of this analysis were similar to those of the main analysis.milieu might differently affect the pathogenesis of infectious and non-infectious related diseases in course of long-term suppressive cART. In this analysis the breakdown of the 70 infectious-related events were as follows: 39 AIDS-defining infections, 5 infectious-related malignancies, 4 viral hepatitis, 2 septic infections, 11 pneumonia and 9 infectious-driven death. Although the association was weaker, possibly because of the reduced statistical power, again, hs-CRP was the biomarkers which was most strongly associated with clinical progression after controlling for confounders and for the other biomarkers , as well as when it was fitted as continuous variable . However, the association was lost after controlling for confounders and for the other biomarkers .Over years of successful cART, serious non-AIDS events (SNAEs) have become the major causes of morbidity and mortality in PLWHIV . DespiteHere we have evaluated the association between pre-therapy systemic inflammation and microbial translocation and clinical outcome measured after cART.milieu might be a more important mediator of long-term HIV-disease progression.Our data show some evidence for an association between pre-therapy circulating hs-CRP, but not microbial translocation, and higher risk of clinical progression after cART initiation, regardless of patients’ key confounding factors such as age and nadir CD4 count, in all suggesting that pre-therapy HIV-driven pro-inflammatory While both IL-6 and D-dimer have been shown to be independently associated with serious non-AIDS conditions or death among HIV-positive adults with suppressed virus , posing Interestingly, by performing the same analysis according to infectious vs non-infectious clinical conditions, a similar yet non-significant association was retained uniquely between hs-CRP and infectious-related events, whereas a much weaker association was shown between EndoCAb and non-infectious diseases. Given that inflammation, as well as endotoxin immunity, has been shown to have a pathogenetic role in both infectious and non-infectious diseases, further studies should specifically address this issue in well-defined cohorts of HIV+ patients on cART.MT and activation/inflammation markers have been associated with mortality and disease progression among cART initiators in some, but not all studies , 45, 46.According to a recent hypothesis , the rooIn our analysis, circulating MT markers failed to predict disease progression even after restricting the analyses to PLWHIV with severe pre-cART CD4 below 350 cell/mmc, suggesting that other factors probably encompass the effect of MT alone in contributing to disease progression. Whilst seemingly divergent from data by Hunt et al.  that demSeveral limitations to our study need to be acknowledged. First, CD4 count nadir of our study population was low (243 cells/mm3 on average) and this could have influenced the results of the analysis. Further data are needed to confirm the role of both pre-therapy inflammation and MT as clinical predictors also in individuals who initiate cART earlier in the infection. Secondly, our results rely on the usual assumption of a correctly specified model  and no unmeasured confounding. We cannot rule out that the lack of association is masked by residual or unmeasured confounding factors. In a sensitivity analysis we further controlled for mode of HIV transmission, alcohol consumption and smoking and none of these adjustments attenuated the association to the null. Third, selection bias could be an issue due to the non-negligible proportion of participants with missing data for one or more of the biomarkers (namely LPS was only available for 278 and hsCRP for 375 participants). However, main characteristics of participants with missing values and risk of outcomes were similar to those of the other analyzed groups suggesting that non-successful testing had occurred at random. Importantly, although all of the tested hypotheses have been pre-specified, many comparisons were performed without controlling for possible inflation of the type I error. Finally, the high quality of care received by patients enrolled in our study could have led to a lower number of clinical events, compared to other studies, possibly limiting the power of the analysis.While our study failed to find an association between LPS and disease progression in our cohort of PLWHIV, it must be acknowledged that LPS measurement might not entirely capture the extent of MT, given its fluctuation during the day and its association with food intake and the fact that repeated measures of the markers post cART initiation were not available. A deeper understanding of the role of MT as cause of inflammation and disease progression in the course of cART could be gained by the comprehensive assessment of additional and reliable markers of both MT and inflammation, including the fungal translocation marker Beta d glucan (BDG) that has proven to maintaining stable plasma levels over 24 h, with stronger association with pro-inflammatory markers –49. AlsoOur analysis suggests that the inflammatory marker hs-CRP measured before cART initiation is a predictor of long-term clinical disease progression. As a consequence, more frequent clinical monitoring and disease-specific screening after cART initiation should be considered for PLWHIV showing high levels of hs-CRP while still untreated.To date, a number of studies have been conducted to evaluate strategies aimed to reduce persistent immune activation on ART, such as cART intensification, treatment of co-infections, the use of anti-inflammatory agents and improvement of immune recovery through cytokine administration (as reviewed in 7 [Additional file 1.