Background: Medication non-adherence has a dynamic, temporal and multifactorial nature with a significant impact on economic and clinical outcomes. Interventions to improve adherence are complex and require adaptation to patients' needs, which may include patient's medical conditions. The aim of this study was to assess the comparative effectiveness of medication adherence interventions per type of clinical condition on adult patients.Methods: A systematic review with network meta-analysis was performed (PROSPERO registration number of CRD42018054598). An initial Pubmed search was conducted to select meta-analyses reporting results of interventions aiming to improve medication adherence. Primary studies were selected and those reporting results with a long-term follow up (≥10 months) on adult patients were included for data extraction. Study characteristics, description of interventions and adherence outcomes were extracted. Adherence interventions were classified in four groups: educational, attitudinal, technical, and rewards. Clinical conditions were classified in four groups: circulatory system and metabolic diseases, infectious diseases, musculoskeletal diseases, and mental, behavioral or neurodevelopmental disorders. Network meta-analyses with effect sizes expressed as odds ratio (OR) with a 95% credibility interval (CrI) were built. Ranking probabilities for each measure of adherence were calculated by using surface under the cumulative ranking analysis (SUCRA).Results: A total of 61 meta-analysis and 149 primary studies were included in the qualitative synthesis and 80 primary studies in the quantitative analysis. The most effective interventions were: educational + technical 79.6% [OR: 0.44 ] and 73.3% [OR: 0.56 ] in circulatory system and metabolic diseases and infectious diseases respectively. Attitudinal intervention had the greatest probability for musculoskeletal diseases of 92.3% in SUCRA [OR: 0.30 ]. Finally, educational + attitudinal interventions had the greatest effect (SUCRA 73.8%) for mental, behavioral or neurodevelopmental disorders, although this was not significant according to consistency analysis.Conclusion: Effectiveness of interventions seems to be related to the clinical condition. Educational and technical interventions resulted in a major effect on long-term management of medication adherence in patients with infectious diseases (HIV) and circulatory system and metabolic diseases whereas attitudinal components presented a higher effect on musculoskeletal and mental, behavioral or neurodevelopmental disorders. Medication non-adherence represents a continuous burden for the health-care system. Statistics remain constant since 2003, when the World Health Organization reported at least 50% of patients with chronic conditions were non-adherent to their medications Sabate, . A studyThe negative consequences of this phenomenon have been widely reported in the literature. For example, a recent systematic review found the economic impact of non-adherence, including the healthcare costs, ranged from $949 to $44,190 per patient annually across 14 disease groups  assessing the long-term effect of adherence interventions (follow-up of more than 10 months) and reporting measures of adherence  on adult patients with prescribed medications were included for data extraction. Studies were excluded if the interventions were not patient-focused, assessed adherence to the following medications , were not written in Roman characters, or were unpublished studies . From the eligible studies, those reporting adherence results as a categorical variable were included in the network meta-analysis. Studies reporting continuous data were only considered for qualitative analysis. Other studies not included in the network meta-analysis were those with the same intervention in all the study arms (same comparator) and clinical conditions without a sufficient number of studies to perform a comparative analysis. Additional information regarding inclusion or exclusion criteria can be found in Supplementary Material Data from primary studies was extracted by two investigators and recorded on a standard data collection form. This included: authors, year of publication, country, sample size, clinical condition being targeted, sex, age, patient follow up period, study arms, interventions assessed, and measures of adherence. Targeted diseases were identified for each study and then classified in groups based on the International Classification of Diseases 11th Revision (ICD-11)   across the condition groups previously described. This analysis was based on the Markov Chain Monte Carlo simulation. Transitivity analyses were performed by comparing population, interventions, and outcome definitions among the included studies. To analyse the multiple-arms studies a common heterogeneity parameter was considered and a conservative analysis of non-informative priors was conducted  with a 95% credibility interval (CrI). The goodness of fit of the model and consistency were assessed using the lowest residual deviance information criteria (DIC) between fixed and random-effect models tested. Convergence was attained based on visual inspection of Brooks-Gelman-Rubin plots and potential scale reduction factor-PSRF (1 < PSRF ≤ 1.05)  to increase the estimate precision of the relative effect sizes of comparisons and to properly account for correlations between multi-arm trials  , infectious diseases (HIV) , musculoskeletal diseases  and mental, behavioral or neurodevelopmental disorders . The average follow-up time was 14 months with the majority reporting a follow-up of 12 months (n = 115 studies). The most common interventions were educational , followed by educational + technical , technical , educational + attitudinal , attitudinal , educational + attitudinal + technical  and only 3 studies (1.7%) containing the rewards component . In 134 studies (89.3%), standard care was used as a common comparator.Overall, 178,229 patients were included in the analyses, with the following distribution across disease groups: circulatory system and metabolic diseases  as all the papers reported the expected adherence outcomes. Around 20% of studies presented a high risk of bias for incomplete outcome data domain (n = 34) due to the lack of intention-to-treat analysis or missing data. Allocation concealment was classified as unclear risk of bias in most of the studies . Additional information can be found in the Supplementary Material The risk of bias analysis resulted in a low risk on selective reporting (n = 57), (2) same intervention category in all study arms (n = 3); and (3) not enough studies to be categorized and analyzed by disease group (n = 9).In the quantitative analysis, 80 studies were included, with 69 excluded due to the following reasons: (1) categorical medication adherence data not reported  vs. SOC.Thirty-one studies were included in this network, with seven different interventions being compared. Three studies assessed a combination of multiple intervention types, with a majority comparing educational + technical interventions (n = 12 studies) and educational interventions ]  or educational + technical (n = 7) against SOC.A total of 32 studies were included in this network with 6 different interventions. Three of these interventions were multicomponent. The majority of studies compared technical ] and technical interventions  compared to SOC ], educational [OR: 0.37 ] and technical  interventions compared to SOC  when compared to the other interventions. Educational (74.0%) and technical (48.3%) interventions ranked second and third, respectively. The lowest effect was for SOC (14.8%).This network was comprised of 10 studies and compared 2 single component interventions, 2 combination interventions and standard care. Three studies assessed attitudinal interventions and three evaluated educational interventions. Two included educational + technical interventions and another two studies assessed educational + attitudinal interventions. All interventions were compared to SOC. No significant differences were found between types of interventions for this disease group . Second and third rankings consisted of educational (72.5%) and attitudinal (65.3%) interventions respectively  that require tailored and multifaceted approaches  were significantly more effective when combining educational + technical components . Interventions involving educational components only  are one of the most frequent strategies used in health care to change patient behavior  are in agreement with previous literature reporting an increased effect when combining different interventions components  with no significant long-term effect compared to other interventions or SOC. The intervention was focused on full payment coverage of medications (Choudhry et al., The limitations of this study include the categorization of the interventions into four major groups to perform the network meta-analyses. We acknowledge that a different categorization system may lead to some different results. However, this classification system, which was developed based on three previously used classifications, allowed us to have a clearer understanding of the interventions (Roter et al., Educational and technical interventions seem to be more effective on the long-term management of medication adherence in patients with HIV, circulatory system and metabolic diseases, compared to attitudinal interventions that presented a superior effect on mental, behavioral or neurodevelopmental disorders and musculoskeletal diseases. Multicomponent interventions are more effective at enhancing medication adherence in three of the four disease groups. Further analyses assessing the impact of these interventions on clinical outcomes are needed to support the translation of these results to daily practice. The use of network meta-analysis was valuable for comparing interventions aimed to improve medication adherence across chronic diseases in long-term follow-up periods.VG-C, SB, FF-L, AT-R, EW, and FT contributed to the design of the study. EW and AT-R organized the database. FT and FF-L performed the data analysis. AT-R wrote the first draft of this manuscript. All authors contributed to manuscript revision, read and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Objective: Pre-hospital, in-hospital, and patient factors are associated with variation in door to needle (DTN) time in acute ischemic stroke (AIS). Publications are usually from large single centers or multicenter registries with less reporting on national results.Materials and methods: All AIS patients treated with intravenous tissue plasminogen activator (iv-tPA) over 4 years (2013–2016) in Northern Ireland were recorded prospectively, including patient demographics, pre-hospital care, thrombolysis rate, and DTN time. Logistic regression was performed to identify factors associated with DTN time.Results: One thousand two hundred and one patients from 10,556 stroke admissions (11.4%) were treated with iv-tPA. Median NIHSS was 10 (IQR 6-17). Median DTN time was 54 min (IQR 36-77) with 61% treated < 60 min from arrival at hospital. National thrombolysis numbers increased over time with improving DTN time (P = 0.002). Arrival method at hospital (ambulance OR 2.3 CI1.4-3.8) pre-alert from ambulance  and time of day  all P < 0.001, were the independent factors in determining DTN time. Variation in DTN time between centers occurred but was unrelated to volume of stroke admissions.Conclusion: Ambulance transport with pre-hospital notification and time of day are associated with shorter DTN time on a national level. Most thrombolysis was delivered outside of normal working hours but these patients are more likely to experience treatment delays. Re-organization of stroke services at a whole system level with emphasis on pre-hospital care and design of stroke teams are required to improve quality and equitable care in AIS nationally. Reperfusion with intravenous tissue plasminogen activator (iv-tPA) and/or endovascular thrombectomy improves probability of better outcome following acute ischemic stroke (AIS) , 2. PatiWorldwide DTN time is not uniform. Some centers report dramatic reductions in DTN time after service re-organization . ElsewheRegistries have reported clinical factors associated with DTN time including age, stroke severity, and previous medical history, while hospital factors include hospital size, annual number of thrombolysis cases, and academic status , 10. WhiThe components of the clinical team providing stroke care vary within the week. Dedicated stroke nurses and senior medical staff are routine in normal working hours within UK hospitals but smaller teams with less experience can be tasked with providing iv-tPA outside “office” hours. The impact of varying clinical team make-up and different hospital sites on stroke treatment is unclear.We performed a country-wide analysis of AIS patients over 4 years in Northern Ireland to measure delays, benchmark DTN time against international recommendations and explore factors influencing DTN times.2 served by seven lysing stroke centers. All patients who were treated with iv-tPA over four consecutive years from January 1, 2013 to December 31, 2016 were identified from prospective audit logs at each hospital providing acute stroke services. Medical notes and imaging databases were examined retrospectively. Data recorded included age, sex, date of onset of AIS, time of AIS symptom onset , time/method of arrival at hospital, use of pre-hospital notification, clinical stroke risk factors, and co-morbidities, stroke severity measured using the National Institute for Health Stroke Scale (NIHSS), imaging time and modality, time of administration of iv-tPA, and recording of documented reasons for delay . Where AIS occurred in someone who was already a hospital inpatient, arrival time was considered to be the same as symptom onset time. An out-of-hours admission was defined as any hospital admission which occurred outside of 09:00–17:00 on Mondays to Fridays, including public holidays. ICD10 codes for number of stroke admissions (ICD10 codes I63-I64) per hospital per year of study were obtained from the department of health. Ethical permission was provided from each stroke center for the study, which was classified as a regional quality improvement audit. As such the Trusts in Northern Ireland waived the need for written informed consent.The study was conducted in Northern Ireland, population 1.86 million with a geographical area of 14,130 kmTime based measurements were calculated from individual time recordings for each patient as follows:Door to needle time = (Time of iv-tPA bolus) – Onset to hospital arrival time =  – (Time of symptom onset/time last known to be well if onset not witnessed)Onset to treatment time = (Time of iv-tPA bolus) – (Time of symptom onset/time last known to be well if onset not witnessed)* 100) (ICD10 code I63-I64).Proportion of AIS patients receiving iv-tPA = [(number receiving iv-tPA/number admissions with AIS at each center per year)] Data analysis was performed using SPSS . Statistical analysis included the Mann-Whitney test for binary group comparisons, Kruskal-Wallis ANOVA or Chi-squared test for multiple comparators for ordinal and categorical data where appropriate. A binary logistic regression for factors associated with DTN time of <60 min was performed.P = 0.0019) (P = 0.002)  . Median = 0.002) .P = 0.028). The number of patients treated with iv-tPA varied between centers, ranging from 88 cases to 369 cases. The thrombolysis rate within each center ranged from 9.3 to 15.0% . 60.1% of AIS patients were treated with a DTN time of < 60 min. The percentage of patients treated within 60 min of arrival in hospital increased from 47.4% in 2013 to 65.1% in 2016 (P < 0.001). Median onset to treatment time (OTT) time reduced from 145 min in 2013 to 135 min in 2016 (P = 0.019), although median OTT times in 2013 and 2015 were similar. Onset to hospital time was significantly longer in 2015 and 2016 than 2013 and 2014 . A significant reduction in DTN time occurred over the study period, reducing from 64 min in 2013 to 51 min in 2016 (P < 0.001) (P < 0.001)  . Arrival< 0.001) . Onset tn = 698) received iv-tPA outside of typical (09:00–17:00) office hours. Patients treated out-of-hours had significantly longer median DTN times than those patients treated between 09:00 and 17:00 , arrival with pre-hospital alert or arrival by ambulance , year of treatment , and admitting hospital . The most significant factor was treatment occurring in-hours rather than out-of-hours, followed by arrival method. Year of treatment and site of treatment had smaller impacts on DTN time than both arriving in-hours and arriving with pre-hospital notification  who were treated with iv-tPA.The members of a stroke thrombolysis team within office hours can be very different to other parts of the week. For example, a dedicated stroke nurse with experience in delivering iv-tPA as part of a multidisciplinary team is present in most hospitals during usual “office hours” while nursing staff with less thrombolysis experience and other competing clinical commitments are more likely to attend at other times. Senior medical staff with expertise in stroke management may not be present for referrals of AIS patients received out-of-hours but are often present during office hours. Emergency department and radiology department staffing levels also show variation according to time of day and each of these departments plays a critical role in the AIS thrombolysis pathway.Given the critical importance of time to AIS thrombolysis treatment in influencing clinical outcome, the variation in staff levels, and experience according to time of day has important implications. The Helsinki model provided a dedicated and constant staffing resource and avoided out-of hours variation in DTN times . They inTelemedicine is used in hospitals to permit remote clinical assessment of AIS by a senior clinician and has a proven evidence base for increasing access to iv-tPA treatment . Four ofPre-hospital factors had an important influence on subsequent in-hospital performance and overall time to treatment. DTN times improved over the 4 year period, but there was a significant trend toward longer OTH time in 2016 compared to 2013. This had a resultant effect on prolonging OTT time, which is the most relevant measure from the individual patient perspective. Logically any delay in pre-hospital time will counteract the benefits achieved through reducing in-hospital DTN time.Lack of improvement in pre-hospital triage times have been recorded elsewhere and pose a challenge for stroke service delivery . Novel sStroke severity scores were consistent with the known trial and meta-analysis data supporting iv-tPA use in AIS . There wSeveral clinical factors such as past medical history, co-morbidities, hypertension, and treatment with medication such as anticoagulants can result in treatment delay for individual patients . These fLimitations of this study include lack of recorded outcome after thrombolysis treatment but as our focus was on assessing factors associated with delayed treatment this was not a requirement. This was a retrospective study and for a small number of patients a specific DTN time measurement was not recorded due to missing data, but this was a small proportion of all cases (2%). This study has several strengths. We have reported on all AIS patients treated with iv-tPA on a national level. Previous registry data publications from selected centers may be associated with selection bias. Other registries suffer from “inflation bias” where cases associated with known reasons for delay are specifically not recorded and this can influence how reported DTN times appear , 24. SomThis study has demonstrated national trends in AIS lysis treatment and DTN time over a 4 year period. An increasing absolute number and proportion of AIS patients were treated with iv-tPA over time and this occurred with an incremental decline in DTN time. Variation in treatment times was associated with time of day and arrival method, year, and admitting hospital but large volumes of AIS admissions were not a pre-requisite for short DTN time. Specific focus on out of hours and pre-hospital services are required to improve national DTN times and reduce inequality of access to thrombolysis for all AIS patients . This tyThe datasets generated for this study are available on request to the corresponding author.The study qualified as an audit. Each Trust approved the study and declared formal ethics approval was not required.FeM designed the study, collected data, and wrote the first draft. AH, KD, MauM, MicM, IW, DV, JM, JK, and FK collected data and revised drafts of the paper. FiM helped administer the study and revised drafts of the paper. MS performed the statistical analyses and revised drafts of the paper. EH collected data for the paper and revised drafts. MOM designed the study, coordinated data collection, and revised drafts of the paper.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Control mice (10 WT and 10 MMP-9-/-) received normal drinking water. Fecal samples were collected at time of sacrifice and immediately frozen at −80 °C. Microbiota analysis was performed using 16S rRNA amplicon sequencing on Illumina MiSeq and taxonomic annotation was performed using the Ribosomal Database Project as reference. Statistical analysis correcting for multiple testing was done using R. No significant differences in clinical or histopathological parameters were found between both genotypes with DSS-induced colitis. Observed microbial richness at genus level and microbiota composition were not significantly influenced by host genotype. In contrast, weight loss, disease activity index, cage, and phenotype did significantly influence the intestinal microbiota composition. After multivariate analysis, cage and phenotype were identified as the sole drivers of microbiota composition variability. In conclusion, changes in fecal microbiota composition were not significantly altered in MMP-9-deficient mice compared to wild-type littermates, but instead were mainly driven by DSS-induced colonic inflammation.Gut microbiota help to educate the immune system and a number of involved immune cells were recently characterized. However, specific molecular determinants in these processes are not known, and, reciprocally, little information exists about single host determinants that alter the microbiota. Gelatinase B/matrix metalloproteinase-9 (MMP-9), an innate immune regulator and effector, has been suggested as such a host determinant. In this study, acute colitis was induced in co-housed MMP-9 A protein that regulates aspects of the immune system has been proposed to influence gut microbial populations implicated in the inflammatory conditions known as colitis, but new evidence suggests the protein has no such effect. Ghislain Opdenakker and colleagues at the Rega Institute for Medical Research in Belgium examined the issue in mice with chemically induced colitis. The gut microbes of normal “wild-type” animals were compared with those in animals lacking the gene for the protein, “gelatinase B/matrix metalloproteinase-9”. The absence of the gene, and therefore of the protein it codes for, caused no significant alteration in the gut microbial population. The presence of colitis, however, did alter the gut microbial population relative to mice with no colitis. The results will assist work to understand the networks of cause and effect linking gut microbes and colitis. Whereas in these reactions the cellular elements are well studied,5 specific molecular targets are poorly defined. This implies that, whereas cellular targeting is well defined for the development of novel therapies, molecular targeting needs much more research. With the use of mouse models of colitis it has been shown that heterogeneity in age, gender, genetic background, and type of colitis models may give contradicting observations and difficulties to extrapolate findings to the human situation.9 Nevertheless, animal models may provide valuable information as the experimental conditions can be well controlled.Chronic immune-mediated conditions, including inflammatory bowel disease (IBD), are characterized by an interplay between genetic, immunological, and environmental factors.13 Microbial and immunological changes seem to appear before the development of colitis, indicating that these changes may play a role in the potentiation of the abnormal inflammatory response seen in DSS-treated animals.12Supplementation of dextran sodium sulfate (DSS) to the drinking water of mice is commonly used to induce experimental colitis as a model for IBD to investigate host factors contributing to IBD and potential new therapeutic targets. Importantly, oral DSS supplementation promotes gut microbial dysbiosis in mice with a decrease in microbial richness.19 Heimesaat et al. investigated the effect of MMP-2 and MMP-9 deficiency on the development of acute DSS-induced colitis and concluded that MMP-2 plays a causal role in the establishment of colitis.14 In addition to other lowered inflammatory parameters, the authors observed less overgrowth of the colon by Escherichia coli (E. coli) in MMP-2 knockout mice, but not in MMP-9 knockout mice. Moreover, blocking gelatinases (MMP-2 and MMP-9) with a selective gelatinase inhibitor (RO28-2653) also resulted in less overgrowth of E. coli.15 The effect of gelatinase deficiency or blockage was further studied in models of bacterial-induced intestinal inflammation.18 Consistent with previous studies, MMP-2 seemed to play a more prominent role than MMP-9 in mediating bacterial-induced intestinal immunopathology. Finally, an infectious model with Citrobacter rodentium (C. rodentium) was used to induce colitis in MMP-9 knockout mice.19 Consistent with our recent data on MMP-9 knockout mice in DSS-induced and TNBS-induced models of inflammatory colitis,9 similar development of inflammatory parameters was observed in MMP-9 knockout and WT mice. Furthermore, the authors showed that MMP-9 knockout mice had lower colonization levels of C. rodentium, were protected from reductions in fecal microbial alpha diversity, and had a larger population of segmented filamentous bacteria. It is well known that MMP-9 alters immune functions20 and that altered microbiota affect the immune system.5 Therefore, it was important to study whether host factors, such as MMP-9, induce alterations in microbiota. However, in all the mentioned studies, sequencing techniques for a complete assessment of microbiota composition were lacking. In the present study, we used 16S rRNA gene sequencing to investigate the effect of MMP-9 deficiency on fecal microbiota in control conditions and after induction of acute colitis with DSS.A possible role of MMP-9 in bacterial-dependent or bacterial-induced models of intestinal inflammation has been described in several studies.23 we did not observe protective effects by MMP-9 gene deletion on colitis phenotypic scores. Both MMP-9-/- mice and WT littermates developed severe acute colitis after DSS administration with loss of body weight . Moreover, no differences were found in observed microbial richness at genus level between both phenotypes   , whereas genotype (WT vs. MMP-9-/-) had no influence . The variability in microbiota composition was smaller in the control group compared to the DSS group.The observed microbial richness  at genus level was not significantly different between both genotypes  Fig. . As show88) Fig. , the oveBacteroides, Clostridium XI, Clostridium sensu stricto, Enterococcus, Enterorhabdus, Romboutsia, and Turicibacter . Analysis of the overall microbiota composition, using genotype as constrained variable, identified the main genera contributing to the separation of the samples within the control (WT control vs. MMP-9-/- control) or DSS group (WT DSS vs. MMP-9-/- DSS) . The genera Bacteroides, Alistipes, and Lactobacillus explained most of the variability of the microbiota composition between WT and MMP-9-/- in the control group  adjusted p < 0.05). These results were confirmed with Linear discriminant analysis Effect Size (LEfSe) . These covariates were then included in a forward stepwise redundancy analysis on genus-level PCoA (Bray–Curtis dissimilarity) in order to identify non-redundant covariates. Cage had a non-redundant effect size on microbiota composition of 63.86%. Gender did not significantly correlate with microbiota composition . In addition, association between metadata variables and microbial community relative abundance at genus level was performed with multivariate statistical framework (MaAsLin), isolating the influence of possible confounders. Cage and phenotype were the only variables that remained significantly associated with microbial genera  sources, with different dietary food and fluid intake and different microbiota. We recently demonstrated that induction of colitis with DSS was not attenuated in MMP-9 knockout mice compared to WT mice.9 These data are in contrast with current literature and we believe this is due to several factors, as described previously.9 In addition to optimal control for genetic background and leakiness of the used mice, the aim of the current study was to investigate the influence of the environment on our results and, vice versa, the influence of MMP-9 gene deficiency on the composition of the microbiota.It is increasingly recognized that many knockout studies in mice cannot be reproduced, not only due to the failure of the knockout by homologous recombination, but because of the lack of stringent control conditions.-/- mice from the same unique breeding insulator over a period of 15 years.9 During our colitis experiments, WT and MMP-9-/- mice were co-housed according to phenotype. This implicates that WT and MMP-9-/- mice received the same drinking bottle with normal drinking water or water supplemented with DSS, which excludes potential DSS intake-related differences within the same cage. However, we did observe a significant effect of cage on the composition of the microbiota, more specifically with Clostridium sensu stricto. As shown in Fig. 25 In our study, this was 63.86% for control and DSS-treated mice combined. This difference was probably due to the phenotype distribution according to cage. The effect of cage within the DSS phenotype was 44.9%. However, this did not significantly influence microbiota composition. The choice of co-housing does have its limitations, since a potential bias includes synchronization of microbiota between both genotypes due to coprophagia.25 This effect was previously described by several groups who demonstrated that microbiota-related phenotypes could be transferred between co-housed mice after several weeks of sharing a cage.28 This implies that if any subtle differences in microbiota composition would exist between both genotypes, we would possibly miss these due to fact that mice within the same cage will transfer their microbiota. However, since we showed that there is a large effect between cages (63.86%), we decided that co-housing of both genotypes was the correct experimental design for our study. This decision was also based on previous guidelines for experimental design that take into account the key variables that affect gut microbiota composition with respect to housing conditions.7 Additional studies are warranted to further evaluate the effects of co-housing and coprophagia on microbiota composition in mice with different genotypes.As described earlier, we did not observe any differences in infections or seroconversion against a number of classically tested animal pathogens between sentinel WT and MMP-912 However, in contrast to our study, these authors observed decreased levels of Bacteroidetes and increased levels of Firmicutes. Moreover, they identified Firmicutes as the most abundant phylum, whereas this was the case for Bacteroidetes in our study. A potential explanation for the observed differences is the fact that Nagalingam and colleagues studied cecal tissue with T-RFLP analysis. In addition, our observations were in contrast to earlier published data by Munyaka et al., whereby a reduction in Bacteroidetes and an increase in Proteobacteria in colonic and fecal samples from acute DSS colitis were observed.10 However, many other aspects of this study were complementary to our data. For instance, these researchers also identified Firmicutes, Bacteroidetes, Proteobacteria, Deferribacteres, Tenericutes, and Verrucomicrobia as the six most abundant phyla, whereas Actinobacteria was identified as a low-abundant phylum. At genus level, Bacteroides was identified as the predominant genus involved in dysbiosis caused by DSS as it accounted for more than 70% of the identified bacterial genera. Furthermore, we observed that DSS-supplemented mice had lower relative abundances of Alistipes, Alloprevotella, Prevotella, Odoribacter, Lactobacillus, and Helicobactor; and higher relative abundances of Romboutsia, Akkermansia, Escherichia, Shigella, and Clostridium sensu stricto compared to control mice. The genus Romboutsia is a newly described bacterial genus, first described in 2014,29 which may explain the lack of evidence about this genus in the literature. Moreover, the family Enterobacteriaceae was significantly increased in mice that received DSS (p < 0.001) and a linear relationship was found between DAI and the incidence of Enterobacteriaceae  (data not shown). These findings confirm previous observations described by Hakansson and colleagues.11Several microbial taxa contributed to the observed dysbiosis caused by DSS. At phylum level, we observed that DSS-supplemented mice had higher relative abundances of Bacteroidetes and Verrucomicrobia and lower relative abundances of Firmicutes and Proteobacteria in comparison with corresponding control mice. In a study by Nagalingam et al., higher relative abundancies of Verrucomicrobia and lower relative abundancies of Proteobacteria were also observed in mice with DSS-induced colitis.-/- mice in control and acute DSS-induced colitis conditions. Although limited to co-housed animals, we observed no effect of MMP-9 gene knockout on microbial profiles, whereas DSS had a considerable effect and caused dysbiosis in both WT and MMP-9-/- mice. These data complement our earlier findings that MMP-9 gene knockout has no effect on development of colitis, and, in addition, has no influence on the composition of the intestinal microbiota.In this study, we investigated changes in microbiota in co-housed WT and MMP-9-/- mice and their WT (C57BL/6J) littermates were selectively backcrossed by siblings over 13 generations9 and bred under specific pathogen-free conditions. All mice were transferred to conventional housing at 7 weeks of age and were co-housed 1 week prior to start of the experiment. Mice were raised under identical environmental conditions . All mice were confirmed for their MMP-9-/- or WT genotype by PCR30 and the genetic background of the mice was carefully characterized by SNP analysis.9MMP-9The study was approved by the local ethics committee for animal experimentation of the University of Leuven (P178-2011) and was conducted following all relevant guidelines and procedures. Exclusion criteria included >30% weight loss and/or severe malaise of the animals.31 Briefly, 8–10-week-old male and female WT (n = 10) and MMP-9-/- (n = 10) mice received 3% DSS  in the drinking water during 7 days followed by 2 days on regular drinking water  and MMP-9-/- (n = 10) mice received regular drinking water throughout the duration of the experiment. Each group consisted of five male and five female mice and sample size was chosen based on previous experimental experiences. Of importance, WT and MMP-9-/- mice were co-housed (maximum n = 5 per cage) during the experiment ensuring identical environmental conditions as well as controlling for cage-related effects .Acute colitis was induced as described previously.ter Fig. . Control-/-) of the mice.Mice were weighed daily or every other day until time of sacrifice (day 9). Relative weight loss was calculated based on the weight of the mice at the start of the experiment and absolute weight loss was measured at time of sacrifice. The DAI was calculated based on stool consistency, presence of blood, and weight loss at time of sacrifice. As measurements of colonic inflammation, colon weight/length ratio, and macroscopic damage score  were included. The investigators were blinded for the genotype  weight of 88 (10–137.5) mg was used for bacterial DNA extraction. The PowerMicrobiome RNA Isolation Kit  was used with an adapted protocol. Briefly, samples were homogenized with the use of mechanical beating in a lysis buffer containing 1% β-mercaptoethanol. In addition, the samples were incubated at 90 °C for 10 min. The supernatants containing DNA and RNA from both bacterial and murine cells were then bound to a spin filter membrane with the use of centrifugation. After three washing steps, the nucleic acids were eluted from the membrane in 100 µl RNase-free water and were stored at −80 °C. Bacterial DNA was quantified with a Qubit™ 2.0 fluorometer . After PCR amplification, Fragment analyzer™  was used for quality control and quantification of the libraries.32 Sequencing was performed on an Illumina MiSeq sequencer  yielding 250 bp pair-ended reads. After de-multiplexing, fastq sequences were merged using FLASH software™ 33 with default parameters. Combined reads quality threshold was set at minimum 30 quality score over 90% of read length  and chimeric sequences were filtered out (UCHIME34). Downsizing to 10,000 reads by random selection of quality-checked reads was performed for each sample. Ribosomal Database Project reference database (v2.12)35 was used for taxonomic assignment. The operational taxonomic unit (OTU)-level relative abundance matrix was obtained by de novo clustering of reads at 97% identity (USEARCH36).The V4 region of the 16S rRNA gene was amplified with primer pairs 515F and 806R, with single multiplex identifier and adapters as described previously.p-values < 0.05 were considered significant. Student’s t-test was used to test the differences in microbiota species richness (metric = observed). PCoA with Bray–Curtis dissimilarity on genus-level community composition was used to visualize microbiota variation across samples . Within the vegan package (version 2.4-2),38 vector fitting was performed with envfit function, community differences between groups were tested with Adonis non-parametric tests, and the contribution of different bacterial genera in the genus-level community composition was evaluated with correspondence analysis (rda function) and distance-based redundancy analysis . Further analysis of the influence of genotype and phenotype in the intestinal microbiota was inferred with unconstrained and constrained partial least squares discriminant analysis . Correlation between taxa relative abundances and continuous metadata was performed with Spearman correlation. Differences in the taxa relative abundances between different groups were tested with Mann–Whitney U tests. These results were compared with LEfSe performed in the Galaxy platform, with the implementation of phenotype as class and genotype as subclass.39 Multivariate analysis was performed with MaAsLin R package V.0.0.3.40R software (v3.3.3) was used and non-parametric tests were performed unless specifically stated elsewhere. Shapiro–Wilk test was used to test continuous variables for normality. FDR correction was applied when needed. Adjusted http://www.ebi.ac.uk/ena/data/view/PRJEB21337). The metadata supporting the conclusions of this article are available MixS format as Supplementary File Raw sequencing reads were deposited in the European Nucleotide Archive (PRJEB21337, MIMARKS survey


Metastatic non-small cell lung cancer (NSCLC) is associated with a limited survival when treated with palliative intent platinum-based chemotherapy alone. Recent advances in imaging and therapeutic strategy have identified a subset of patients with limited metastases who may benefit from early local ablative therapy with either surgery or radiotherapy, in addition to standard treatment. Stereotactic body radiotherapy (SBRT) is increasingly used in the treatment of extra-cranial oligometastatic NSCLC (OM-NSCLC) due its non-invasive conduct and ability to deliver high doses. Clinical evidence supporting the use of SBRT in OM-NSCLC is emerging and consistently demonstrates significant benefit in local control and progression-free survival. Here, we discuss the definition of oligometastases (OM), review current available data on SBRT treatment in extra-cranial OM-NSCLC including evidence for site-specific SBRT in lung, liver, and adrenal metastases. Lung cancer continues to be the leading cause of cancer death in many countries . UnfortuThe term “oligometastatic” disease has been used commonly (and sometimes loosely) in the cancer literature ever since 1995. Hellman and Weichselbaum were the first to introduce this concept of OM disease, which represented an intermediate state in the spectrum between locally confined and widely metastatic cancer . They prSurgical metastasectomy was initially the only way to radically manage these patients . With thIn this mini-review, we will discuss the definitions of OM disease (in the context of NSCLC), patient selection, prognostic factors as well as completed and ongoing trials to support the use of SBRT for OM-NSCLC.To date, there is no universal definition of what constitutes OM with regards to the number of lesions or sites involved. The most accepted number of metastatic lesions is considered to be 5 or less (with up to 3 metastases in an organ) –14.As definitions of OM vary from study to study, it is hard to estimate the exact incidence of OM in NSCLC at diagnosis. Moreover, the routine use of staging FDG/PET-CT scan and MRI brain imaging may increase the incidence of OM, due to increased sensitivity compared to older imaging modalities. The International Association for the Study of Lung Cancer (IASLC) Lung Cancer staging project found that 225 out of 1,025 (22%) patients had synchronous single metastatic lesion at diagnosis; this group of patients had a better prognosis compared to patients with metastases in multiple organs . In anotIn terms of classifying oligometastatic cancer, there are three possible scenarios:Synchronous oligometastatic disease: Patients who present with up to 5 metastatic lesions (in one or a few organs) at first or within 6 months of diagnosis. These typically occur in the brain, lung parenchyma, liver or bone .Oligo-residual (or oligo-persistent) disease: Widely metastatic disease (>5) at diagnosis, which has responded well to systemic therapy , with the remaining lesions (up to 5) amenable to radical local therapy  .Metachronous (or oligo-recurrence): Patients who had been treated with curative intent, and then present with limited sites of metastatic disease (up to 5) after an interval of stable disease .As oligoprogression is a biologically distinct entity whereby patients with upfront widespread metastases progress, in a limited number of sites, after initially achieving stable disease or partial response, we have not included it in this definition. It is possible that patients with oligoprogression have a worse prognosis compared to the above scenarios.Selecting the most effective method for local treatment of oligometastases requires thoughtful considerations. Patient-related factors , tumor-related factors  and treatment-related factors  have to be taken into account.In the latest National Comprehensive Cancer Network (NCCN) guideline for stage IVA NSCLC, definitive RT to OM, with particular mention of SBRT, is recommended as an appropriate option in suitable patients with good performance status provided it can be delivered safely . This reThere are no head-to-head studies comparing surgery, SBRT, and RFA. In liver metastases, SBRT is superior to RFA in treating larger lesions >3 cm, or for lesions near blood vessels where there can be a heat-sink effect with RFA , 22. WidPatient selection is not only important to ensure the safe delivery of SBRT but also has prognostic significance . SeveralIn a retrospective cohort study involving 186 patients, ECOG performance status >2, higher nodal-status (N2-3), squamous histology and metastases to multiple organs were associated with a worse prognosis . AshwortThe number (and possibly volume) of metastatic sites has also been shown to be a potential prognostic factor. In a SWOG study by Albain et al., involving 2,531 patients with advanced NSCLC, median survival was highest in patients with a single lesion (8.7 months), compared to patients with multiple lesions in one organ (6.2 months) and multiple lesions in multiple organs (5.1 months) . SimilarP = 0.012)  of SBRT was at least 100 Gy –32. De R= 0.012) . Pre-tre= 0.012) . SBRT to= 0.012) , 31 and = 0.012) .Liver: Ahmed et al. evaluated the radiosensitivity of liver metastases from different primary histology using a multigene expression index for tumor radiosensitivity (RSI) . They suAdrenal: SBRT to adrenal metastases in OM-NSCLC was specifically evaluated in a study by Celik et al. whereby 15 patients received 42 Gy in 6 fractions of CyberKnife® SBRT . Of thesA retrospective analysis of patterns-of failure after first-line systemic therapy in 387 patients with NSCLC reported local progression as the predominant pattern-of failure and suggested that local consolidative therapy with SBRT to known sites of disease following systemic therapy to prolong the time to first progression . Since tCollen et al. reported on 26 patients with synchronous OM-NSCLC patients with up to 5 metastases treated with SBRT (50 Gy in 10 fractions)  who were amenable for radical therapy to all tumor sites including the primary  . The vasBauml et al. recently published their single-arm Phase II trial comprising of 51 patients with ≤4 lesions who completed locally ablative therapy to all sites, following which they were given pembrolizumab. They reported a median PFS of 19.1 months and 1-year OS of 90.9%. This is notably much improved compared to historical controls (P = 0.01). Toxicities were similar in both arms.Iyengar et al. then conducted a randomized phase II trial for 29 patients with NSCLC and up to 5 OM lesions. NSCLC who had achieved partial response or stable disease to first-line chemotherapy . EGFR/ALP = 0.022). OS was also significantly improved . There are two observations from this study. Firstly, the OS benefit was seen despite patients crossing-over from maintenance/observation to local therapy, suggesting earlier local therapy to be superior to local therapy on progression. Secondly, none of the patients suffered from Grade 3 toxicity.Gomez et al. conducted a multi-center Phase II randomized study in 49 patients with up to 3 OM NSCLC with no progression for at least 3 months post 1st line chemotherapy , 52. EigP = 0.09). Unfortunately, there were significantly more toxicity in the SBRT arm (29 vs. 9%) with treatment-related death (Grade 5) being experienced by three patients (4.5%).Palma et al. conducted the international SABR-COMET Phase II trial including 99 patients with up to 5 OM lesions from a variety of primary histological types (20% lung primary) . PatientNo Phase III trial has reported the benefit of SBRT in OM-NSCLC. In view of the convincing Phase II data, there are multiple ongoing Phase III trials which are eagerly awaited. These trials are summarized in Considerable progress has been made in the realm of OM-NSCLC. Improvements in survival stem partly from more effective systemic therapy, but also aggressive consolidation therapies  in patients with a favorable disease biology. Although the results from randomized Phase II data are exciting, adequately powered Phase III trials with clear inclusion/exclusion criteria  and appropriate primary endpoints are much awaited to change practice. The upper limit of the number of acceptable OM lesions were set rather arbitrarily. It remains unclear if we should limit this to 3, 5 or 10 . As suchStage IV NSCLC represents a heterogenous group of patients with an overall poor outcome. However, a sub-group of patients with limited metastatic disease may achieve long-term survival with effective systemic therapy and aggressive local therapy. SBRT is a good option to obtain durable local control, and possibly prolong survival for these patients. At the same time, SBRT can be a double-edged sword, with toxicities in a minority of patients. As always, appropriate patient selection remains paramount, and ongoing Phase III trials will provide clarity.CW, BV, and SL contributed conception and design of the study. CW and BV organized the database and wrote the first draft of the manuscript. All authors wrote sections of the manuscript, contributed to manuscript revision, read, and approved the submitted version.SS reports grants from Varian Industries outside the submitted work. AL reports personal fees from Varian Medical Systems Inc. outside the submitted work. The Department of Radiation Oncology at VU University Medical Center has a research collaboration with Varian Medical Systems. BS has received honoraria and/or travel support from Varian Medical Systems and ViewRay. SL reports research support from Elekta AB in Elekta Gamma Knife ICON Expert Group outside of submitted work. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


MIR181B1 and MIR103A1) exhibited high levels of gene expression in the manic state. For coding genes, we reported that the taste function-related genes, including TAS2R5 and TAS2R3, may be mania state-specific markers. Additionally, four genes showed a nominal p-value of less than 0.05 in all our microarray data, mega-analysis, and RNA-Seq analysis. They were upregulated in the manic state and consisted of MS4A14, PYHIN1, UTRN, and DMXL2, and their gene expression patterns were further validated by quantitative real-time polymerase chain reaction (PCR) (qRT-PCR). We also performed weight gene coexpression network analysis to identify gene modules for manic episode. Genes in the mania-related modules were different from the susceptible loci of BD obtained from genome-wide association studies, and biological pathways in relation to these modules were mainly related to immune function, especially cytokine–cytokine receptor interaction. Results of the present study elucidated potential molecular targets and genomic networks that are involved in manic episode. Future studies are needed to further validate these biomarkers for their roles in the etiology of bipolar illness.Bipolar disorder (BD) is highly heritable and well known for its recurrent manic and depressive episodes. The present study focused on manic episode in BD patients and aimed to investigate state-specific transcriptome alterations between acute episode and remission, including messenger RNAs (mRNAs), long noncoding RNAs (lncRNAs), and micro-RNAs (miRNAs), using microarray and RNA sequencing (RNA-Seq) platforms. BD patients were enrolled with clinical information, and peripheral blood samples collected at both acute and remission status spanning for at least 2 months were confirmed by follow-ups. Symptom severity was assessed by Young Mania Rating Scale. We enrolled six BD patients as the discovery samples and used the Affymetrix Human Transcriptome Array 2.0 to capture transcriptome data at the two time points. For replication, expression data from Gene Expression Omnibus that consisted of 11 BD patients were downloaded, and we performed a mega-analysis for microarray data of 17 patients. Moreover, we conducted RNA sequencing (RNA-Seq) in additional samples of 7 BD patients. To identify intraindividual differentially expressed genes (DEGs), we analyzed data using a linear model controlling for symptom severity. We found that noncoding genes were of majority among the top DEGs in microarray data. The expression fold change of coding genes among DEGs showed moderate to high correlations (∼0.5) across platforms. A number of lncRNAs and two miRNAs ( Bipolar disorder (BD) is a severe and highly heritable psychiatric disorder, characterized by repeated manic episodes and depressive episodes . Having Recently, with the advances in RNA-sequencing (RNA-Seq) technology  and breaBDNF gene, is widely studied for its association with disease status of BD  to assess demographic characteristics and lifetime history of psychiatry disorders . For sym™ reagent at −80°C freezers. We used chloroform for lysis, followed by isopropanol with incubation and centrifugation to retrieve total RNA precipitates from mononuclear cells. Then, we used 70% ethanol for washing. Finally, we solubilized the RNA pellet in 20–50 μL of RNase-free water and 0.1 mM EDTA for further application. RNA samples had undergone quality controls with the following criteria: OD260/280 was between 1.8 and 2.0, and OD260/230 was larger than 2.0. The quality control criteria of BioAnalyzer to obtain the RNA integrity number (RIN) and 28S/18S values were as follows: RIN ≥ 6 and 28S/18S ≥ 1.0. Most of our sequenced samples were of fine RNA quality. The mean of the RIN in all samples was 8.8, with only two samples with RIN values ranging from 6 to 7  2.0, which contained more than 6.0 million probes and can be annotated to 44,699 coding transcripts and 22,829 noncoding transcripts, including miRNAs and lncRNAs. We used qualified 500 ng RNAs to be synthesized to cDNA and hybridized to the HTA microarrays. All procedures followed the Affymetrix protocols and performed in the Microarray Core Lab of Core Instrument Center in the National Health Research Center. The transcriptome microarrays used by Witt et al.  were Affaffy package  package to select the represented probe expression value in gene-level comparison and increase between-study consistency. The MaxMean function was originally developed to perform cross-platform microarray mega-analysis and has been extensively validated (sva package (limma package (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/) for quality check for sequence files and used trimmomatic , with sequence-specific primers of each targeting genes , and glyceraldehyde 3-phosphate dehydrogenase (GAPDH) was used as internal control. Threshold was set above nontemplate control background and within linear phase of target gene amplification to calculate cycle number at which the transcript was detected [threshold cycle (CT)].For qRT-PCR, we performed standard RNA isolation and reverse transcription (RT) using PrimeScript RT reagent Kit  following the manufacturer’s protocol. The analysis was conducted with SYBRWGCNA package  correlations >0.75. MEs were defined by their first principal component and were labeled with different colors as module names in the Results section. After the modules were generated, we conducted different enrichment analysis to explore the functional interpretation of genes within the modules.We ran weighted gene coexpression network analysis using the  package  for 17 B package . A soft-p-value of 5*10−6 and reannotated them with Ensembl database   signals for BD. We downloaded the summary statistics results from one of the latest GWA study of BD from the Psychiatric Genomic Consortium from BioRxiv . We useddatabase . In tota (MAGMA) . The bac (MAGMA)  and Brai (MAGMA) . The sigr = 0.44) (r = 0.19)  showed signals with high levels of gene expression in the manic state (fold change ranged from 1.8 to 3.0). These results of ncRNAs, however, are not able to be examined in our RNA-Seq data , and interestingly, all DEGs enriched in this module were ncRNAs  treatments in patients with major depressive disorder  and mega-analysis (p = 1.94*10−2), was found to be related to taste reduction in attention-deficit/hyperactivity disorder children who underwent methylphenidate treatment (in vivo/in vitro experiments are needed to verify the medication effects on these taste-related genes. Recent development of BD patient-derived induced pluripotent stem cells (iPSCs) provides information for medication effects on gene expression  gene was reported to be associated with thyroid cancer . Researcretation , and morretation . Furtherretation . The tarIn total, we identified 33 modules by WGCNA with ideal soft threshold (Beta = 4), and 6 modules were significantly related to clinical outcomes (YMRS or manic stage). The mania-related modules were not enriched with GWAS signals even when the signals were from one of the largest BD studies so far . The staIn the DEG enrichment analysis for modules, we found that most of the modules were not enriched with DEGs, which could be explained by the “omnigeneic model” proposition. This model suggests that the DEGs within the module network are highly connected with other genes, and the biological functions are decided by the whole module but not a few signals. Among the six mania-related modules, we found that the Royalblue and Cyan modules are enriched with gene expression in substantia nigra and BA24 (anterior cingulate cortex) brain regions, which are highly relevant to BD , 72. TheThere are several limitations in the present study. First, we had limited sample size in the present study, as follow-up of manic BD patients is a difficult challenge. We used different platforms and independent samples for replication and validation, and conducted mega-analysis to increase generalizability. In addition, within-individual paired data are less prone to confounding effects for gene expression study and increase the power for DEG identification. However, the sample size in the present study was small and may not have enough power to detect gene with weak effects. Nevertheless, among our selected gene targets for qPCR validation, all of them showed significant differences with the same expression patterns as the original analyses, which increased our confidence of finding meaningful targets despite moderate power. Second, we used only peripheral blood samples for state-specific transcriptome analysis but not brain tissues for practical reasons. We cannot control the blood drawing time in different subjects and time points, and may slightly influence gene expression results due to potential circadian rhythm in a certain proportion of human gene expressions. Third, the assessment of symptom severity is subject to interviewer bias. Nevertheless, by treating YMRS score as one of the covariates in our linear model, this concern maybe minimized. Lastly, although medication might influence gene expression results, we were not able to control the medications among BD patients in our observational study design, and the medication effects on gene expressions cannot be directly assessed as we are comparing the same individuals at two times points with the same medication treatment during follow-up. Instead, we tried to adjust medication usage of different categories of drugs in regression models, and results remain similar with or without adjustment.TAS2R5, TAS2R3, and CES1) and other common targets across different platforms  might be important targets for episodic onset. Results of network and enrichment analyses suggest the potential role of cytokine-related pathways for mania, and gene expression network is independent of the signals from susceptible genetic loci for BD identified from previous GWA studies. These results bring insights to designing future study for early diagnosis and detection of manic episodes in bipolar illness.In summary, the present study represents one of the very few studies that focused on manic feature of BD using intraindividual comparisons. Using genome-wide exploration for gene expression patterns with different experimental platforms and sets of independent samples, our results provide the first line of evidence for the involvement of coding and noncoding transcriptomic alterations for manic episode. In particular, with experimental validation, taste-related genes , Ministry of Science and Technology Project (MOST 105-2628-B-002-028-MY3), and the National Taiwan University Career Development Project (104R7883) to PI, Dr. PH Kuo, and MOST 107-2314-b-038-085 to PI, Dr. CH Chen, and Taipei City Hospital Research Project (TPCH-108-057) to PI, Dr. MC Huang.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Behavioural interventions for weight loss (WL) are successful in the short term but often result in weight regain over time. Self-regulation of eating and activity behaviours may significantly enhance weight loss maintenance (WLM) and may be effectively augmented by contextual behavioural approaches to emotion regulation. The NoHoW trial tests the efficacy of a theoretically informed, evidence-based digital toolkit using a mobile-enabled website, activity trackers and Wi-Fi scales for WLM aiming to target (1) self-regulation and motivation, and (2) emotion regulation in adults who achieved clinically significant (≥5%) WL in the previous 12 months  ≥25 kg/mThe study is an 18-month, 3-centre, 2×2 factorial single-blind, randomised controlled trial, which recruited 1627 participants achieving ≥5% WL between March 2017 and March 2018. Participants are randomly allocated to one of four arms: (1) self-monitoring only (self-weighing and activity tracker), (2) self-regulation and motivation, (3) emotion regulation or (4) combined self-regulation, motivation and emotion regulation. Participants attend four clinical investigation days at 0, 6, 12 and 18 months and are instructed to use the digital toolkit for 18 weeks during the first 6 months and at their discretion for the remaining 12 months. The primary outcome is change in weight (kg) at 12 months from baseline. Secondary outcomes are body composition , health biomarkers , dietary intake, physical activity, sleep, motivational, self-regulatory, emotion regulatory moderators/mediators of WLM, engagement, user experience, acceptability and cost-effectiveness of the interventions.Ethical approval was granted by Institutional Ethics Committees at the Universities of Leeds , Lisbon  and Capital Region of Denmark . Results will be published in scientific journals.ISRCTN88405328. The first project to develop and evaluate  an information and communications technology toolkit combining continuous tracking of physical activity and body weight with theoretically informed, evidence-based digital interventions targeting self-regulation and motivation, and emotion regulation in a 2×2 design, to target long-term weight management.The 2×2 factorial design is a step forward from a conventional two-armed trial to determine the effect of self-regulation/motivation, emotion regulation interventions and their interactions on weight and health outcomes.Analyses of primary outcomes will test the hypotheses that self-regulation of energy balance behaviours improves longer term weight outcomes and that emotion regulation strategies help prevent weight relapse. Moderator analysis will determine if participant psychological/behavioural profiles predict response to self-regulation or emotion regulation interventions. Mediation analyses will examine mechanisms of action by which self-regulation and emotion regulation-based approaches affect energy balance behaviours, weight and health.Participants are blinded to study allocation, but they can access similar interventions from other real-world sources.There was no zero-intervetion control. The active control arm includes self-monitoring of physical activity and weight but the inclusion of the Fitbit devices across all arms potentially contaminates or diminishes the effect of self-regulatory components. Social support was excluded as a potential contaminant of the digital intervention.Overweight, obesity and associated diseases are key societal challenges. Obesity prevalence accounts for 3%–8% of health costs and 10%–13% of deaths in Europe.self-monitoring of weight and behaviour; (2) goal-setting: agreement of clear weight targets/trigger points for weight control efforts; (3) feedback on behaviour and weight; (4) action plans for weight control through dietary and physical activity behaviours; and (5) plans to cope with risk factors for weight regain and relapse prevention .Core features of effective WLM interventions include behaviour change techniques in line with self-regulation theories such as (1) Individuals with obesity or those trying to lose weight can experience increased stress, depression, anxiety and weight-related stigmaRecently, there has been interest in digital interventions to promote and maintain health.The effectiveness of long-term evidence-based digital interventions and strategies to support WLM is limited.Secondary objectives are to determine (1) how the intervention affects health markers ) and body composition; (2) examine the intervention impacts on physical activity, sleep, dietary intake, depression, anxiety, stress, quality of life and well-being; (3) examine mediators of WLM, such as self-regulation , motivation  and emotion regulation processes ; (4) analyse baseline moderators ) to identify participants who are more responsive to motivational and behavioural self-regulatory or CB-emotion regulatory approaches for WLM; (5) conduct quantitative and qualitative assessment of user-experience, acceptability, engagement and dropout; (6) examine intervention cost-effectiveness; and (7) to determine the efficacy of individualised feedback from data on physical activity self-tracking.The NoHoW trial is a three-centre (University of Leeds (UK), The Parker Institute (Denmark) and University of Lisbon ) 2×2 factorial, randomised, single-blind, controlled trial testing the proof-of-concept of a digital toolkit for WLM. The study duration is 18 months with a follow-up at 6, 12 and 18 months postbaseline . The stuhttp://uk.nohow.eu; http://dk.nohow.eu; http://nohow.fmh.ulisboa.pt) and completed an online eligibility screener using Qualtrics. The eligibility screener categorised respondents as eligible, potentially eligible (wait-list) and ineligible. Eligible individuals were contacted for a telephone screening interview, provided with study information, medical history questions and the Physical Activity Readiness Questionnaire.The study recruitment and intervention schedule is outlined in 10.1136/bmjopen-2019-029425.supp1Supplementary dataMembers of the public that matched the study’s inclusion criteria at the three trial centres were consulted via a survey to inform the recruitment strategies, trial conduct, questionnaires, assessment of burden and reviewing or testing the intervention content at all trial centres. During the toolkit development stage, the public were involved in two ways. First, a panel of 10 people, matching the trial criteria, tested the toolkit V.1 written in English for 1 month in the UK. A mixed methods approach was used for the analysis of the data assessing technical maturity of the intervention and user experiences, through questionnaires (quantitative data), interviews , TK usage log data and data from wireless scales and activity trackers (Fitbit). These analyses will be published in a separate paper. The results were used to inform toolkit V.2. Toolkit V.2 was then tested for 18 months using a panel of 30 people (10 in each centre) starting 3 months before the launch of the trial. Trial staff regularly collaborated with the panel to identify technological glitches that could be corrected early on so as not to impact on the main trial participants.Participants were randomly allocated to treatment arms by researchers using an online trial administration portal. Adaptive stratified sampling using minimisationThe toolkit is a mobile-enabled website, delivered as a portfolio of embedded tracking technologies, mini-apps and web resources  accessibThe active control arm includes a toolkit dashboard containing weight, steps and sleep graphs using data from the Fitbit devices, healthy eating and mood data , a diary to populate with notes from these five tiles and a help tile. The content is generic and does not relate to any theoretically informed, evidence-based behaviour change approaches.After randomisation, participants received standardised training from researchers during the first CID, specific to their arm allocation. Trial arms 2–4 include the same components as arm 1 but participants also receive a personal virtual road map (the ‘NoHoW Journey’) with intermediate destinations represented in that map by circles, each comprised of evidence-based theoretically informed thematic modules targeting self-regulation and motivation (arm 2), emotion regulation (arm 3) and combined self-regulation and emotion regulation (arm 4). Arm 4 includes the same number of thematic modules as arms 2 and 3. Each weekly module opens into submodules. The active intervention involves 18 weekly sessions delivered throughout a 6-month period. Users are encouraged to complete ≥1 submodule per week following the sequence in the road map, consisting of videos/audios, interactive graphs, text, images, questionnaires and mini-apps. Weekly arm-specific emails are sent during the active 6-month intervention phase, which provide WLM information, suggestions and reminders to visit specific content. The toolkit automatically sends an email notifying participants to slow down if they complete three sessions ahead of schedule. After 6 months, they are encouraged to revisit the toolkit for a further 12 months at their discretion.Individualised feedback is a component of the self-regulation and motivation arms (arms 2 and 4) automatically provided by the toolkit in response to the individual’s weight trajectory. Feedback is generated from the data extracted from three sources: (1) weight from the Fitbit Aria scales; (2) activity and sleep from the Fitbit Charge 2; and (3) user engagement with the toolkit, including day of the week. After daily usage patterns are analysed, feedback is displayed in the toolkit consisting of one of a set of short statements .The toolkit sends automated weekly emails to participants to encourage engagement, prompt log-in and recommends sessions to complete (arms 2–4 only). The control group receives the same number of emails but with links to generic content . Intervention adherence is continuously monitored by collecting information on the number of days since users last logged into the toolkit and the number of days since the last synchronisation between the Fitbit devices and data-hub. If no activity is detected after 21, 28 and 35 days, three attempts are made to contact participants by email. After 42 days of no activity, researchers telephone participants to resolve issues. Reasons for no activity are recorded.The primary outcome is change in weight (kg) between baseline and 12 months (primary endpoint). Follow-up measures for WLM are completed at month 18 for comparability with other longitudinal studies.10.1136/bmjopen-2019-029425.supp2Supplementary dataRandomised participants are contacted at least 2 weeks before each visit and sent an email/text reminder. If participants deviate from planned assessments, three attempts are made to contact them by phone, email and a final written letter across 1 month. At least weight (primary outcome) is obtained if possible.Body weight (±0.1 kg) is measured using a Seca 704 s instrument  in participants wearing light clothing. Participants are asked to weigh themselves at least twice weekly, in the morning after voiding and before eating using the Fitbit Aria scales for 18 months.Multifrequency whole bioimpedance spectroscopy is measured by ImpediMed , which measures impedance over a spectrum of frequencies for the estimation of body composition. Hanai mixture theory equations and standard resistivity constantsWaist and hip measurements are taken according to the WHO’s guidance. A tape measure is used to record the hip and waist circumference to the nearest centimetre.Fasted capillary blood samples are collected to determine HbA1c , estimated average glucose  and full lipid profiles, including total cholesterol, low-density lipoprotein, high-density lipoprotein (HDL), triglycerides, non-HDL and cholesterol/HDL (mmol/L) assayed using a benchtop analyser .Systolic and diastolic blood pressure (BP) and resting heart rate (HR)  are measured three times with the participant at rest in the sitting position. The mean value is recorded.Hair samples are collected by cutting a small tuft of hair close to the scalp to measure the stress hormone, cortisol, and analysed following a previously described protocolPhysical activity is measured by the self-reported International Physical Activity Questionnaire (IPAQ)The Fitbit Charge 2 estimates sleep quantity (hours/minutes) and quality (stages of sleep). Data are collected throughout the trial.Four consecutive 24-hour-web-based dietary recalls, including at least 1 weekend day, are collected within 7 days of each visit using INTAKE 24.Quality of life and well-being are assessed using the 5-level EQ5D (EQ5D-5L)Self-regulation is measured using the Action Planning and Coping Planning ScalesSatisfaction of psychological needs are assessed using the Basic Psychological Needs and Frustrations Scale.Self-efficacy is assessed using the Self-Efficacy for Weight Maintenance Scale.CB-emotion regulation and stress management constructs are measured using the Weight Focused Self-Criticism/Self-Reassurance Scale,A profiling questionnaire, adapted from the DiOGenes study,Questionnaires adapted from the Technology Acceptance Model for Mobile Services (TAMM)www.easytrial.net). Quality checks are performed by all centres and reviewed during weekly trial management meetings. Separate publications will detail the technologies to host the toolkit, and the ICT architecture linking the toolkit, trial administration portal, trial management software and NoHoW data-hub.A NoHoW data-hub was developed by the James Hutton Institute (Edinburgh) and led by GH, which collates, monitors and stores anonymised data securely from each centre. Data from each centre are entered into trial management software  analysis.To determine the mechanisms that underlie intervention efficacy, linear models are used to test whether the treatment (independent variable) causes a change in the potential mechanisms of change (mediators), which, in turn, cause a change in the primary and secondary outcomes (dependent variables). Models also investigate the effects of covariates that may moderate the effect of the interventions. Although a repeated measures/mixed model might potentially detect treatment effects not apparent when 6-month and 12-month outcomes are considered separately, our choice was driven by the primary role of the 12-month outcome. To be considered worthwhile, a WL or maintenance effect of treatment must be detectable at 12 months, whatever might happen during the time interval between then and baseline. Because of this, we chose to define the primary outcome and its analysis at 12 months alone.For the primary outcome of weight, we intend to present results from an analysis of completers, of compliant participants and of the ITT population. Baseline and last observation carried forward are likely to be optimistic for dropouts, implying full WLM. So, for these dropouts, we will examine analyses which assume regain of all or a range of proportions of the weight lost since highest weight . Again, assuming return to baseline may be optimistic, but we do not have values at the time of greatest weight. Accordingly, we plan multiple imputation based on the imputed weight changes described above, using also centre and gender. This is not available for other health outcomes, such as HbA1c or blood pressure.2 goodness-of-fit test, Bollen’s incremental fit index (0.95) and the standardised root mean residual (0.08) values. Tests of mediation will be conducted using a resampling method. To test the significance of specific indirect effects of multiple mediators , a tool developed by Selig and PreacherMediation is assessed where change in weight, as represented by a categorical endpoint (maintenance vs weight regain), is the dependent variable, intervention group is the predictor variable, and self-regulatory, emotion regulatory and other psychosocial variables are mediators. Hybrid models, combining latent and observed variables, may be specified to ensure sufficient power to conduct the analysis and to stay within the limits of sample size requirements. Model fit will be assessed using the χInteractions between condition factors and baseline participant groupings  will be prioritised as a priori subgroup analyses in the primary and secondary outcomes. Age, BMI and weight will be analysed as categorical variables to avoid assumptions of linearity  and for ease of presentation. These pre-planned analyses will be conducted by the inclusion of appropriate interaction terms in the regression models. Where interactions are significant, results for each subgroup will be reported. This will mitigate the problems of multiple testing due to many subgroup comparisons. We recognise that statistical power in subgroups will vary with sample size and provide a plot of detectable effect size versus sample size for reference .Cost-effectiveness analysis will be conducted to model costs and intervention effects for a lifetime horizon. An existing decision-analytical model will be used to estimate BMI category transitions, incidence of secondary diseases , quality of life and healthcare costs.Power calculations were based on the primary outcome (weight change). To detect a difference between treatment arms of >1.5 kg body weight gives a (Cohen's) d value of 0.25.The trial was registered with the ISRCTN registry (ISRCTN88405328). Ethical approval was granted by each institutional ethics committee before study commencement at each centre. The protocol complies with relevant EC legislation, international conventions and declarations relating to ethical research practices.This is the first project to develop and formally evaluate  a new ICT toolkit combining continuous tracking of physical activity and body weight with theoretically informed, evidence-based digital interventions targeting self-regulation and motivation, and CB-emotion regulation in a 2×2 design, to target long-term weight management.The NoHoW toolkit comprises evidence-based behaviour change techniques and CB-emotion regulation strategies, which are hypothesised mechanisms of action that may impact EB behaviours and longer term weight outcomes. Analyses of primary outcomes will enable us to test the hypotheses that self-regulation of EB behaviours improves longer term weight outcomes and that CB-emotion regulation strategies help prevent weight relapse. Secondary outcomes of the trial moderator effects will enable us to determine if different psychological and behavioural profiles of participants predict response to self-regulation or emotion regulation interventions. Mediation analyses will enable us to determine the mechanisms of action by which self-regulation and emotion regulation-based behaviour change approaches affect EB behaviours and longer term weight and health. Secondary analyses will inform more personalised digital interventions that better match intervention content and delivery to individual user needs, potentially helping to improve user engagement, health and well-being of participants.Participants are blinded to study allocation, but they can access similar interventions from other real-world sources. The 2×2 design involved an active control. A 2×2 plus one design including a no-intervention control would have enabled evaluation of self-tracking using Fitbit devices versus no intervention.The active control arm includes self-monitoring of physical activity and weight but the inclusion of the Fitbit devices across all arms potentially contaminates or diminishes the effect of self-regulatory components.There is a potential conflict inherent in the design of trial that seeks to allow a certain degree of personalisation of intervention content use and maintain the integrity of trial arms. For this reason, the degree of personalisation was constrained to choice in the use of available self-regulatory or contextual emotion regulatory content within respective trial arms.Social support was deliberately not part of this intervention but it is known that the degree of social support can be important for weight management.


To compare kidney size  and kidney function outcomes between patients with tuberous sclerosis complex (TSC) and rAML treated and not treated with everolimus.Medical charts of adults with TSC-associated rAML followed at a specialty medical center in the Netherlands (1990–2015). Included patients treated with everolimus  and non-treated patients .Percent change in kidney size and kidney function from the index date to the best measurement in the two years post-index date (best response) compared between patients treated and not treated with everolimus.Compared with non-treated patients, significantly more everolimus-treated patients experienced a reduction in the size of their largest kidney in the two years post-index date . Also, there was a tendency towards more improvement in the estimated glomerular filtration rate (eGFR) among the everolimus-treated patients .The study results suggest that everolimus is effective in controlling and even reversing the growth of the kidneys, used as a proxy for rAML size, as well as preserving or improving kidney function in patients with TSC and rAML treated in a real-world, observational setting. Tuberous sclerosis complex (TSC) is a disorder characterized by the growth of non-malignant tumors in various body organs . ApproxiMedical charts of patients with TSC treated from 01/01/1990 to 31/12/2015 at University Medical Center Utrecht (UMCU), a kidney tumor major specialty center in the Netherlands, were reviewed.TSC diagnosis was based on the Revised 1998 Criteria . All paOf 371 patients with TSC-associated rAML managed at UMCU, 33 everolimus-treated patients and 39 patients not treated with mTORi were included in the study . This stAll patients had kidney size and/or kidney function assessments both in the year before and two years after an index date defined as (a) date of everolimus treatment initiation for everolimus-treated patients, and (b) date with kidney size or kidney function assessment  for non-treated patients. Patients with embolization or nephrectomy after the index date were excluded from the current study as these procedures could have confounded the kidney size and kidney function measurements post-index. When multiple potential index dates were available for a given outcome, logistic regression-based propensity scores models to select a single index date corresponding to the date when the patient had the highest propensity of receiving everolimus treatment. Since everolimus was first used for TSC at UMCU in 2008, the index date had to be in 2008 or afterwards. Because everolimus use in patients with rAML stage < 4 may target non-renal TSC manifestations, patients were also required to have rAML stage ≥ 4 at the index date . Of 33 eStudy outcomes were defined as the change in kidney size and kidney function from the index date  to the best value in the two years post-index . OutcomAnalyses were performed separately for each outcome. Patient characteristics and outcomes were described using descriptive statistics. Where applicable, outcomes were compared between cohorts using Fisher, chi-square, or t-tests. Statistical analyses were performed using SAS statistical software, version 9.3 .2, and stage 1 CKD 63.0% and 72.4%, respectively , significantly more everolimus-treated patients experienced a kidney size reduction compared with non-treated patients . The average change in kidney size was -8.8 mm for everolimus-treated patients and -1.7 mm for non-treated patients (p = 0.01). Among patients with a kidney size reduction, the magnitude of the reduction was similar in the two cohorts  and there were no statistically significant differences between cohorts in the proportion of patients with CKD of different stages  compared with the non-treated patients (median observation period: 24 months) but the difference did not reach statistical significance . In 37% of the everolimus-treated patients, the kidney size reduction amounted to ≥ 10%. More everolimus-treated patients also experienced an improvement in eGFR compared with non-treated patients (55.6% vs. 33.3%). These results strongly suggest that everolimus can lead to a reduction in kidney size–and thus potentially in rAML volume–, the preservation and improvement of kidney function, and the protection of organ loss.Real-world findings from the current study substantiate the results of the phase III EXIST-2 trial, in which rAML volume was reduced in 42% of everolimus-treated patients versus 0% of placebo-controlled patients . The perIn the current study, 37.9% of non-treated patients experienced kidney size reduction. Although unexpected, this could be explained by several factors. First, measurement variations may occur between consecutive assessments in the same patient . Indeed,A distinctive feature of the present study is the assessment of kidney function following everolimus treatment, an outcome not included in the EXIST-2 trial. Findings of this study showed a tendency towards less worsening, and possibly improvement, in kidney function in everolimus-treated patients compared with non-treated patients, even though differences between the two cohorts did not reach statistical significance. However, it is very possible that the current study lacked the statistical power to detect small, but clinically meaningful differences. The results of the EXIST-2 trial  current Overall, the current study provides real-world evidence of the relationship between everolimus and kidney size reduction in patients with TSC-associated rAML in a more advanced stage than previously reported. Furthermore, it also provides evidence of a potential link between everolimus and improved kidney function. By reducing rAML volume  and kidnSeveral limitations should be considered. First, this study included patients followed at a specialty center and results might not be generalizable to the entire TSC population. Second, kidney size was used as a proxy for total rAML size and the extent to which the two measures correlate is unknown. However, rAMLs located on the upper/lower kidney poles are likely captured well by the kidney size measure. While presence of renal cysts may also influence the kidney size, current evidence shows that everolimus has no effect on cysts in patients with TSC . TherefoThe results for this longitudinal observational study suggest that everolimus is effective in controlling and even reversing kidney growth, used as a proxy for rAML size, as well as preserving or improving kidney function.


This study aimed to investigate whether pre-operative dexamethasone could ameliorate transient hypoparathyroidism outcome through total thyroidectomy.This randomized clinical trial study was conducted on 128 patients underwent total thyroidectomy from March 2014 to April 2015. Patients were randomly assigned to two groups of experimental receiving 8 mg IV of intravenous dexamethasone (n=45) 45 min before skin incision treatment and control (n=83). After the surgery, all patients were evaluated for clinical and laboratory hypocalcaemia.Post-operative transient biochemical hypoparathyroidism and hypocalcaemia did not occur more often in the control group, compared to the dexamethasone group while controlling for the baseline variables. However, there was a significant difference in phosphorus level between the dexamethasone and control groups (P=0.028). A total of 50 (39.1%) patients developed hypocalcaemia after surgery. Moreover, post-operative symptomatic hypocalcemia occurred more frequently in the control group (68%) compared to the dexamethasone group (32%); however, this difference was not statistically significant (P=0.54).The pre-operative administration of dexamethasone reduced post-operative hypocalcemia rate. It is essential to conduct future studies with validated means for better results. Total thyroidectomy is currently an accepted surgical method for benign and malignant thyroidal disorders -3. However, it might enhance the risk of post-operative complications following an extensive resection . The comTherefore, an appropriate surgical technique during total thyroidectomy could easily prevent surgery complications, particularly related to parathyroid glands . On the However, other effects of glucocorticoids, including analgesic, immune-modulating, and antiemetic properties, are well-known . DexametRecently, a double-blinded randomized trial revealed that the administration of dexamethasone could decrease the incidence and severity of a post-operative sore throat during swallowing after thyroidectomy . HoweverStudy Design:This randomized clinical trial study was conducted from March 2014 to April 2015 at the surgery ward in Alzahra Hospital, Isfahan, Iran (IRCT2017011329726N3). A total of 128 patients were admitted to the hospital, and consequently underwent total thyroidectomy. Almost most cases had thyroid tumor but approximately 10% (n=15) of patients were selected for thyroidectomy due to other causes, such as multinodular goiter and hyperthyroidism resistant to treatment. Patients with a history of the parathyroid disease, renal failure, and unilateral thyroid lobectomy were excluded from the study. All operations were carried out by an experienced surgeon in the high-volume center for thyroid surgery. The study protocol was sanctioned by the Ethics Committee of the Faculty of Medicine of the University of Medical Sciences, Isfahan, Iran, and all patients filled out a written informed consent in order to participate in the study. This consent form was designed according to the Declaration of Helsinki.Demographic data, including age, gender, histological diagnosis, and pathology results (data regarding the observation of any parathyroid tissues in the specimen) were collected from all patients. Total thyroidectomy was performed by a capsular dissection technique. The indication for surgery was determined by an endocrine subspecialty internist and an experienced surgeon. The determination for surgery was based on clinical findings and thyroid surgery reference guidelines. During this prospective study, subjects were randomized and divided into two groups of treatment (n=45) and control (n=83). The individuals who attended the two groups were matched for age and gender.Patients were randomized to obtain intravenous dexamethasone, 8mg IV  45 min before skin incision ,20. All Instances of symptomatic hypocalcemia were defined as patients developing any of the symptoms, such as circumoral numbness, tingling of the fingers and toes, paresthesia or muscle irritability or a positive Chvostek sign. Replacement therapy with oral calcium supplements and vitamin D analog  began in patients with clinical hypocalcemia. Laboratory hypocalcemia was described as at least 1 serum calcium determination below 8.1 mg/dL (reference range of 8.1-10.4 mg/dL). If patients progressed to symptomatic hypocalcemia or when the serum calcium level was less than 8.1 mg/dL, it was better to administrate oral calcium supplementation with or without vitamin D analog. An intravenous calcium gluconate 10% infusion was prescribed for significant hypocalcemic symptoms or until oral therapy was ineffective. Patients were discharged when the serum calcium level was higher than 8.1 mg/dL.Analysis of Laboratory Concentrations Furthermore, laboratory data, such as serum calcium, serum phosphorus, vitamin D level and serum parathyroid hormone (PTH) levels before surgery, post-operative calcium, and PTH levels, were measured at 1, 6, and 24 h of operation. Patients were followed-up daily from the day before the operation until the end of the first post-operative week. The serum levels of calcium , phosphorus  were performed by spectrophotometric methods . Other laboratory data of peripheral blood, including 25OHD (vitamin D is defined as a deficiency in this study as the 25OHD concentration of less than 20.0 ng/mL) and PTH , were analyzed by enzyme immunoassay . Statistical analysisQuantitative data were reported as mean or median (range) and categorical data as frequency (percentage). The normality of quantitative data was evaluated using Kolmogorov–Smirnov test and Q-Q plot. Nonnormal data were subjected to logarithmic transformation. Between-group comparisons based on quantitative data were conducted using independent t-test or analysis of covariance (ANCOVA)  and for categorical data using the Chi-square or Fisher exact test. Within-group comparisons were employed using paired samples t-test. All the statistical calculations were carried out with SPSS software .A total of 128 patients were available for the analysis. There were 45 patients in the dexamethasone group and 83 were in the control group (without receiving any treatment). The comparison of calcium and PTH levels in pre-operative and post-operative status revealed a significant difference between the two groups . The PTH level in the pre-operative state had a significant difference between the control group (58.2±26.31) and the dexamethasone group  but after adjusting for baseline values there was no significant difference between the two groups (P=0.0601).A total of 50 patients (39.1%) developed hypocalcaemia after surgery. Post-operative symptomatic hypocalcemia occurred more often in the control group (68%), compared to the dexamethasone group (32%); however, this difference was not statistically significant (P=0.54); .In addition, subgroup analysis was performed in dexamethasone treatment based on the existence or lack of symptomatic hypocalcemia. In patients with or without symptomatic hypocalcaemia, a significant difference was observed in calcium and PTH levels between pre- and post-operative levels .It was found that declining in only post-operative serum calcium level in patients who developed symptomatic hypocalcaemia more frequently happened than the patients without symptomatic hypocalcaemia with (P=0.05) or without adjusting for baseline calcium level P=0.02; . In the present study, post-operative transient biochemical hypoparathyroidism and hypocalcaemia did not occur more often in the control group, compared to the dexamethasone group. However, a non-significant lower occurrence rate in post-operative symptomatic hypocalcemia was observed in the dexamethasone group when compared with the control group.A major and occasionally severe complication after total thyroidectomy is the clinically manifested post-operative hypoparathyroidism ,10,21,22It is obvious that the sensitive predictor of post-operative hypocalcaemia is a significant reduction in post-operative blood calcium. The early diagnosis and prophylaxis treatment of hypocalcaemia is the avoidance of symptomatic hypocalcaemia and a significant reduction of hospital stay and hospitalization costs .There arHowever, in one study, it was revealed that prophylactic treatment with single-dose dexamethasone (8mg IV) could influence post-operative transient hypoparathyroidism . To the In other words, glucocorticoids act as physiologic modifiers of the post-operative inflammatory response by reducing both vascular reactivities to vasoconstrictors and the induced cellular immune response mainly regulated by cytokine functions,24. Cytokines play a major role in immunological function following the surgery . In the Moreover, we measured calcium and PTH several times both in the pre-operative and post-operative stage. The comparison of calcium and PTH levels in pre-operative and post-operative status revealed a significant difference between the control and dexamethasone groups without adjusting for baseline values. In patients who developed hypoparathyroidism, PTH levels decreased more rapidly when compared with the decline in serum calcium level . Four hoA recent meta-analysis presented there was no specific correlation between pre-operative serum calcium levels and post-operative hypocalcaemia . On one On the other hand, it is essential to consider the time of administration. One meta-analysis in 2015 presented that the effectiveness of a single dose of pre-operative dexamethasone and time of administration are still unknown . HoweverIn conclusion, according to previous studies, based on the effectiveness and safety of dexamethasone (8 mg IV) for pain, fatigue, vomiting, and vocal dysfunction, we evaluated transient hypoparathyroidism in patients undergoing total thyroidectomy ,20,30,32A non-significant post-operative symptomatic hypocalcemia was less observed in the dexamethasone group, compared to the control group. It seems that precise care during surgery is more important than dexamethasone administration.  The pre-operative administration of dexamethasone reduced post-operative hypocalcemia rate. It is suggested to further the study with validated means for better results.