The potential difference in the impacts of lifestyle factors (LFs) on progression from healthy to first cardiometabolic disease (FCMD), subsequently to cardiometabolic multimorbidity (CMM), and further to death is unclear.We used data from the China Kadoorie Biobank of 461 047 adults aged 30–79 free of heart disease, stroke, and diabetes at baseline. Cardiometabolic multimorbidity was defined as the coexistence of two or three CMDs, including ischaemic heart disease (IHD), stroke, and type 2 diabetes (T2D). We used multi-state model to analyse the impacts of high-risk LFs  on the progression of CMD. During a median follow-up of 11.2 years, 87 687 participants developed at least one CMD, 14 164 developed CMM, and 17 541 died afterwards. Five high-risk LFs played crucial but different roles in all transitions from healthy to FCMD, to CMM, and then to death. The hazard ratios  per one-factor increase were 1.20  and 1.14  for transitions from healthy to FCMD, and from FCMD to CMM, and 1.21 , 1.12 , and 1.10  for mortality risk from healthy, FCMD, and CMM, respectively. When we further divided FCMDs into IHD, ischaemic stroke, haemorrhagic stroke, and T2D, we found that LFs played different roles in disease-specific transitions even within the same transition stage.Assuming causality exists, our findings emphasize the significance of integrating comprehensive lifestyle interventions into both health management and CMD management.   A pooled analysis of 16 cohorts of 120 813 European and US adults showed that the odds ratio [95% confidence interval (CI)] for CMM was 1.9 (1.8–2.3) per 5 kg/mOnly one study examined the role of LFs in the progression of CMM in a UK occupational cohort.Therefore, we aimed to examine the associations of single and combined LFs with FCMD, CMM, and death in the China Kadoorie Biobank (CKB) of 0.5 million Chinese adults. Importantly, we used multi-state model to investigate the potentially different impacts of LFs on transitions from free of CMD to FCMD, subsequently to CMM, and further to death. In line with previous studies,Figure S1). Information collected from the baseline and resurvey was directly entered into a laptop-based data entry system developed with built-in functions to avoid missing items and to minimize logic errors during the interview. Details of the study design and survey methods have been reported previously.The CKB is a large-scale prospective cohort of 512 725 participants aged 30–79 years from five urban and five rural areas. All participants provided written informed consent, completed interviewer-administered laptop-based questionnaires, and had physical measurements taken in the 2004–08 baseline survey. Besides long-term outcome follow-up for all participants, periodic resurveys were conducted in 2008 and between 2013 and 2014 in a random sample of about 5% surviving participants (n = 15 472), stroke (n = 7657), or cancer (n = 2385) at baseline. We also excluded those who had self-reported diabetes or screen-detected diabetes, defined as measured fasting blood glucose ≥7.0 mmol/L or random blood glucose ≥11.1 mmol/L at baseline (n = 26 162). Participants with missing data for BMI (n = 2) were also excluded, leaving 461 047 participants in the present analysis.We excluded participants who reported history of heart disease (Table S1).Lifestyle factors of interest were assessed by baseline questionnaires and physical measurements. We asked the frequency, type, and amount of tobacco smoked per day for ever-smokers (former and current). Former smokers were additionally asked about the years since quitting and the reason for quitting. Questions about alcohol consumption included typical drinking frequency, type of alcoholic beverage consumed habitually, and volume of alcohol consumed on a typical drinking day in the past 12 months. For physical activity, the usual type and duration of occupational, commuting, domestic, and leisure time-related activities in the past 12 months were collected. To calculate daily total physical activity level, we multiplied the metabolic equivalent of tasks (METs) for each activity by the hour spent on that activity and summed the MET-hours for all activities.A range of covariates were also assessed by the baseline questionnaire, including socio-demographic characteristics, personal and family medical history, and female reproductive information. Participants who had at least one parent suffering from chronic heart disease, stroke, or diabetes were considered as having a CMD family history. Of those, participants who reported at least one parent suffering from at least two of the CMDs were considered as having a CMM family history. Prevalent hypertension was defined as measured systolic blood pressure ≥140 mmHg, measured diastolic blood pressure ≥90 mmHg, a self-reported diagnosis of hypertension, or antihypertensive medication use at baseline.,,,We considered five LFs, including smoking, alcohol drinking, dietary habit, physical activity, and body shape according to previous studies.2 or having WC ≥90 cm (men)/85 cm (women) were considered as high risk, which emphasized avoidance of extremely high or low weight and abdominal obesity. The number of high-risk LFs was counted, ranging from 0 to 5.For smoking, we assigned current smokers and former smokers who quit because of illness to the high-risk group. For alcohol drinking, the high-risk group was defined as those who drank ≥30 g/day of pure alcohol or having stopped drinking. Former smokers and drinkers were included in the high-risk group to avoid a misleadingly elevated risk for the reference group. For physical activity, we defined the high-risk group as those who engaged in a sex- and age-  specific lower half of total physical activity. According to the Chinese dietary guidelinesIncident cases of interest and death were identified through linkages to disease and mortality registries and national health insurance claim database, supplemented with local residential records and annual active confirmation. Causes of death were ascertained chiefly by death certificates and supplemented by reviews of medical records and verbal autopsy using validated instruments. All events were coded according to the International Classification of Diseases, 10th Revision by trained staff blinded to baseline information.In the present analysis, IHD, IS, and HS were defined by code I20 to I25, I63, and I61. For T2D, after excluding cases with a definitive diagnosis of insulin-dependent, malnutrition-related, or other specified diabetes , we included cases coded as E11 or E14 in the analysis. Because participants in our study were aged mostly over 40 years at baseline, it was reasonable to assume that incident cases of unspecified diabetes (E14) were mostly T2D. Since 2014, medical records of incident IHD and stroke cases were retrieved and reviewed by qualified cardiovascular specialists blinded to baseline exposures of patients. By October 2018, of 33 515 retrieved medical records of IHD cases and 40 465 retrieved medical records of stroke cases, the diagnosis was confirmed in 87.9% of IHD cases and 91.8% of stroke cases. The medical records of a random sample of 831 diabetes cases were retrieved and reviewed, and 98.6% were confirmed for diagnosis. Therefore, we did not conduct further adjudication for diabetes.Methods).Participants were considered at risk from enrolment to death, loss to follow-up, or 31 December 2017, whichever came first. Changes in dichotomized LFs by the number of CMDs that occurred between 2004–08 baseline and 2013–14 resurvey were analysed with adjustment for age, sex, and study area, as appropriate , and parental family history of CMM. We first used Cox proportional hazards model to estimate the hazard ratios (HRs) and 95% CIs of high-risk LFs  with FCMD, CMM, and all-cause death. In the analyses of individual LFs, the model included five LFs simultaneously. The number of high-risk LFs entered the model as a categorical variable, with 0–1 high-risk LFs being the reference group; this variable also entered a separate model as an ordinal variable to assess the HR of events of interest per one-factor increase in the number of LFs.Figure 1): (i) baseline healthy to FCMD; (ii) FCMD to CMM; (iii) baseline healthy to death from a disease other than IHD, stroke, and T2D; (iv) FCMD to death from any causes; and (v) CMM to death from any causes. For participants who entered different states on the same date (n = 8365), we calculated the entering date of the theoretically prior state as the entering date of the latter state minus 0.5 day. For example, for participants who died of FCMD, the date of FCMD occurrence equals the date of death minus 0.5 day.We further used multi-state model to assess the role of both individual and combined LFs in the temporal disease progression from free of CMD to FCMD, CMM, and death.Figure 2). In this pattern, CMM was redefined as having two of four individual diseases. Because we could not ascertain the temporal sequence of disease occurrences if a participant was diagnosed with at least two of IHD, IS, HS, and T2D on the same date, we excluded them, leaving 459 606 participants in this analysis.We also used the multi-state model with the same setting to analyse the effects of LFs on different pathways from baseline to CMM, and to the absorbing state—death. We divided the FCMDs into four individual diseases, i.e. IHD, IS, HS, and T2D, resulting in 14 transitions  calculating the entering date of the prior state using different time intervals  for participants who entered different states on the same day; (ii) excluding participants who entered different states on the same date; (iii) additionally adjusting for hypertension, usage of blood pressure medicine, and statin at baseline; (iv) including participants who had previously diagnosed heart disease, stroke, or diabetes, and assigning them to FCMD or CMM state according to their CMD status at baseline; (v) excluding the events occurring in the first 2 years of follow-up; and (vi) in addition to the predefined five transitions, adding another transition from the baseline directly to CMM.The multistate analyses of the transition pattern A were further stratified according to sex, age, residence area, family history of CMD, and hypertension. The interactions were tested by using the likelihood ratio test comparing models with and without a cross-product term.P < 0.05 indicated statistical significance.The multi-state model was performed using ‘mstate’ package of R (version 3.6.3), and all other analyses were performed using Stata . Two-tailed Figure 1). Of all incident CMD patients, 14 164  developed CMM, and afterward, 3184  died from any causes; 19 852  died without experiencing CMM. The primary cause of death in transition C was cancer (ICD-10: C00-C97), accounting for 54.1% of deaths. Disease of the circulatory system (ICD-10: I00-I99) was the primary cause of death in both transitions D and E, accounting for more than 70% of deaths.The mean age of 461 047 participants was 51.2 ± 10.5 years. Of those, 41.0% were male, and 42.3% resided in urban areas. During a median follow-up of 11.2 years , 87 687 participants experienced at least one CMD, with a crude incidence rate of 187.59 per 10 000 PYs . Compared with cases whose FCMD was IHD, IS, or T2D, cases whose FCMD was HS were more likely to die afterwards, with 3671 (54.7%) died during follow-up.In the separate analysis for individual diseases , 34 304  participants’ FCMDs were IHD, 31 012 (6.7%) were IS, 6715 (1.5%) were HS, and 14 215 (3.1%) were T2D (Table S2 and S3). Among 22 965 participants who participated in both the 2004–08 baseline and 2013–14 resurvey, most had not changed their risk level of lifestyles. Participants between different CMD status groups exhibited no distinct differences in the changes in lifestyles (Table S4).Overall, men were more likely than women to have high-risk lifestyles, with 55.4% of men and 17.1% of women having three or more high-risk LFs. Cardiometabolic multimorbidity survivors and participants who died with CMM were more likely to be older, urban resident, and to have hypertension and more high-risk LFs than others (Table S5). Body shape defined by BMI and WC showed the strongest associations with both FCMD and CMM [HRs (95% CIs): 1.40  and 1.63 ]. Smoking showed the strongest association with death, with an HR (95% CI) of 1.35 . Upward trends were observed for risks of FCMD, CMD, and death with an increasing number of high-risk LFs; the corresponding HRs (95% CIs) per one-factor increase was 1.20 , 1.29 , and 1.23 , respectively. Generally, the effect estimates for associations were slightly stronger for transition to CMM than that for transition to FCMD.All five high-risk LFs were associated with an increased risk of FCMD, CMM, and all-cause death . The impacts of smoking, unhealthy dietary habits, and unhealthy body shape on the transition to FCMD were stronger than those on the transition to subsequent CMM. The effect estimates of four LFs, except for physical inactivity, were similar for the transition from FCMD to death and from CMM to death. Besides, the strength of associations of smoking, excessive drinking, and physical inactivity with mortality outcome  was greater than that of morbidity outcome. In contrast, the opposite was observed for unhealthy body shape.Multi-state analyses showed the same result for the transition from baseline (free of CMD) to FCMD as the Cox regression analyses, but further distinguished the roles of high-risk LFs in the temporal trajectories of CMM . Also, we observed a stronger association of the number of LFs with the transition from healthy to FCMD vs. the subsequent transition to CMM, and a similar magnitude of the associations with mortality outcome (either from FCMD or CMM). The adjusted HRs (95% CIs) per one-factor increase were 1.20 , 1.14 , 1.21 , 1.12 , and 1.10  for transitions A–E, respectively.When LFs were combined, gradients in the associations were observed between the number of high-risk LFs and all five transitions (Table 1). Smoking was more likely to be associated with mortality risk and incidence of IHD and IS than with HS and T2D. Unhealthy body shape had fewer impacts on transitions from FCMD or CMM to death than other transitions. We also observed gradients in associations of combined LFs with all transitions except for the transition from HS to CMM (Table 2).After dividing FCMDs into four specific CMDs , we found that physical inactivity was significantly associated with basically all possible transitions . In contrast, having five high-risk LFs approximately doubled the risk of developing CMD (31.9%), tripled the risk of CMM (5.8%), and tripled the risk of death with CMD (5.0%).At the longest follow-up of 13.5 years, given the average level of covariates in the CKB population, 16.2%, 1.8%, and 1.7% of participants with 0–1 high-risk LFs at baseline were predicted to develop at least one CMD , CMM , and die with CMD (including FCMD and CMM) (Tables S6 and S7). Although several statistically significant interactions were found in the stratified analyses, most of them seemed clinically meaningless . When the analysis was stratified by residence area or family history of CMD, statistically significant modification effects were only found on one of the five transitions. Prevalent hypertension modified the associations of the number of high-risk LFs with three stages of transition, but with a different direction. In contrast, we observed similar impacts of age on the transitions between high-risk LFs and morbidity transitions. Taking those with 0–1 high-risk LFs as the reference, the associations of having 4–5 factors with incidence transitions were stronger among younger participants.The results were not substantially altered in the sensitivity analyses .The present prospective study of 0.5 million Chinese adults found that five high-risk LFs played important roles in all disease transition stages from healthy to FCMD, to CMM, and then to death, but to different extents. The associations of LFs with the transition from healthy to FCMD were stronger than those with the transition from FCMD to CMM. Also, a stronger impact of LFs on morbidity outcomes  was observed among middle-aged than older participants. When we further divided FCMDs into four individual CMDs, we found that single LFs had different impacts on disease-specific transitions even within the same transition stage   for those with four high-risk LFs (except for BMI) were 1.64 (1.26–2.13) and 3.09 (1.83–5.22) for FCMD and CMM, respectively.2 increment.Three prior studies conducted in European, US, and Australian populations estimated the associations of LFs with FCMD and CMM among participants free of CMD at baseline.Using the same analysis strategy as the above studies, we also observed a slightly stronger association of LFs with CMM than FCMD. Although this analysis strategy is conventional for studies on risk factors for multimorbidity,Hence, we used the multi-state model, an extension of the competing risk model, to distinguish the difference in impacts of LFs on the five transitions between healthy, FCMD, CMM, and death. We observed that LFs had influences on each transition, but to different extents. The only study using a similar analytic method was based on the Whitehall II cohort in which the authors found that LFs had a relatively greater role in the transition from FCMD to CMM than from healthy to FCMD.,Besides LFs, several other factors affect the progression from FCMD to CMM. They may cover up the relative importance of LFs in determining the risk of developing CMM, to some extent. A systematic analysis from the Global Burden of Disease 2016 concluded that health-care access and quality in China was relatively lower than that in UK.,,Our previous studies in the CKB population estimated that 43.2% IHD, 39.1% IS, and 78.8% T2D were preventable by adherence to a healthy lifestyle.Limited by sample size, no previous study was able to further detail the progression of four specific CMDs and examined the role of LFs in all possible transitions between healthy and individual CMDs, as well as individual CMDs to CMM and death as our study. We found that single LFs had distinct impacts on different transition stages. For example, an unhealthy body shape was associated with increased risks of almost all morbidity outcomes (i.e. baseline to FCMD and FCMD to CMM) but was not associated with the risk of death among CMD patients. And even within a certain transition stage, single LFs had different impacts on disease-specific transitions. For example, smoking was more specifically related to the risk of ischaemic cardiovascular disease (i.e. IHD and IS) than to HS and T2D. In contrast, our study observed that total physical activity  played roles in basically all transitions of progression of CMDs, suggesting a universal benefit of being physically active.The present study provides evidence from a uniquely only Chinese cohort living in China, an underrepresented population under a health-care system different from that of developed countries where most previous studies were conducted. The chief strength of our study lies in the use of the multi-state model, yielding less biased estimates than the conventional Cox model and distinguishing the impact of LFs on each transition in the progression trajectory of CMD. It is also one of the largest prospective studies on associations of LFs with CMM worldwide. The large number of cases recorded during more than 10 years of follow-up allowed us to model all possible transitions from baseline healthy to one of the four FCMDs, and then to CMM and death. Also, the study includes a nationwide geographically spread population, with a broad range of ages and diverse socio-demographic characteristics. By performing thorough investigation of LFs and covariates and extensive sensitivity analyses, the study’s internal validity was also enhanced.,,,Some limitations characterize the present study. First, we used LFs collected at baseline and did not account for possible changes during follow-up. However, we conducted a separate analysis in participants attending both the baseline survey and 2013–14 resurvey. During a median interval of around 8 years, most of them had not changed their risk level of lifestyles. The change in LFs was similar between those who developed CMD or CMM during the follow-up and those who did not. The use of baseline LFs may also help avoid reverse causation resulted from lifestyle change after disease onset. Second, we did not collect information on the treatment for CMD, of which medication adherence and compliance might correlate to the adherence to a healthy lifestyle. However, education, as a surrogate for several health-related behaviours, has been adjusted. The residual confounding from treatment is less likely to completely explain the relative risk of LFs with the transition from FCMD to CMM and subsequent death observed in the current study.In conclusion, this large-scale prospective cohort of Chinese adults revealed that LFs differently influenced the progression from healthy to FCMD, to CMM, and further to death, and also had diverse impacts on disease-specific transitions. Our findings further add to the evidence that it is of great significance to integrate comprehensive lifestyle interventions into both health management and cardiometabolic disease management programmes if observed associations are causal. Further studies are warranted on whether genetic susceptibility modifies the effects of LFs on the development and prognosis of CMM and which cardiometabolic biomarkers may mediate the effect of LFs. European Heart Journal online.ehab413_Supplementary_MaterialsClick here for additional data file.


To develop a risk stratification system that can predict axillary lymph node (LN) metastasis in invasive breast cancer based on the combination of shear wave elastography (SWE) and conventional ultrasound.A total of 619 participants pathologically diagnosed with invasive breast cancer underwent breast ultrasound examinations were recruited from a multicenter of 17 hospitals in China from August 2016 to August 2017. Conventional ultrasound and SWE features were compared between positive and negative LN metastasis groups. The regression equation, the weighting, and the counting methods were used to predict axillary LN metastasis. The sensitivity, specificity, and the areas under the receiver operating characteristic curve (AUC) were calculated.p < 0.05 for all). There was no significant difference in the diagnostic performance of the regression equation, the weighting, and the counting methods . Using the counting method, a 0–4 grade risk stratification system based on the four characteristics was established, which yielded an AUC of 0.656 , a sensitivity of 54.60% , and a specificity of 68.99%  in predicting axillary LN metastasis.A significant difference was found in the Breast Imaging Reporting and Data System (BI-RADS) category, the “stiff rim” sign, minimum elastic modulus of the internal tumor and peritumor region of 3 mm between positive and negative LN groups (A 0–4 grade risk stratification system was developed based on SWE characteristics and BI-RADS categories, and this system has the potential to predict axillary LN metastases in invasive breast cancer. Female breast cancer, the first cause of the death in malignant tumors , is the For breast ultrasound examinations, as the suspicious imaging features increase, the Breast Imaging Reporting and Data System (BI-RADS) categories of the breast tumor increase accordingly. Tumors in BI-RADS category 4 or 5 indicate a risk of malignancy, and a detailed assessment of the SLN status is required . Shear wHence, our study aims at assessing the risk of breast cancer LN metastasis in ultrasound examination by combining quantitative and qualitative SWE features, as well as BI-RADS categories.in situ, 11 solid papillary carcinoma, 6 intraductal papillary carcinoma, 2 cases with neoadjuvant chemotherapy before surgery, 6 cases of secondary tumor, and 11 cases without LN pathology. According to the rules established by the study, only one lesion was evaluated per patient, i.e., the most suspicious lesion in ultrasound examination or the largest one among the same BI-RADS category was selected in patients with multiple masses. Finally, our study included 619 invasive breast cancer participants , including 1 male and 618 female patients.This prospective study was approved by the institutional ethics committee, and written informed consent to participate was acquired before examinations. From August 2016 to August 2017, there were a total of 689 patients with malignant breast tumors from a multicenter consisting of 17 hospitals in China diagnosed by surgical pathology enrollment, with conventional ultrasound and SWE images acquired before treatment. The pathology of LNs from SLNB or axillary LN dissection was acquired. All macrometastases, micrometastases, and isolated tumor cells were counted as node positive. The exclusion criteria were set as follows: (1) patients with non-invasive malignant tumors according to the pathology; (2) patients who accepted chemotherapy before surgery; and (3) patients who accepted chemotherapy or biopsy before ultrasound examination. In total, we have excluded 70 patients, including 34 ductal carcinoma All the ultrasound examinations of patients from 17 hospitals used the Resona 7 ultrasound system  equipped with an L11-3 high-frequency probe. Prior to collecting data, all participating radiologists received systematic training in conventional ultrasound and SWE breast examination. Moreover, all radiologists from the multicenter had more than 3 years of experience in breast ultrasound elastography. Following standard conventional ultrasound examination, SWE was performed according to the already well-established method . The SWEmeanE), maximum elasticity (maxE), minimum elastic modulus (minE), standard deviation (sdE) evaluating both internal tumors and peritumoral tissues as well as intratumor ratio between mean elastic modulus of breast lesions, and normal fatty tissue (ratioE) were acquired and recorded. In assessing the location of the breast tumor, it is based on the location of the center of the lump in the 4 quadrants of the breast (upper/lower outer/inner quadrants). Upon completion of the evaluation, both B-mode images and SWE images of each patient were stored in a hard disk of the ultrasound system and subsequently sent to the study center , then it is judged as positive for the “stiff rim” sign .Statistical analyses were performed using SPSS Version 23.0  and SAS 9.4. A p value less than 0.05 was considered for significant differences. The Mann–Whitney U test was used to compare the statistical difference in continuous variables between positive and negative LN groups, and the chi-square test was used to verify whether there was a statistical difference in categorical variables between the two groups. Significant variables were included in the final logistic regression analysis. The selection criteria alpha was set to 0.05. The odds ratio (OR) and 95% confidence interval (CI) for each feature were obtained from the logistic regression model. To predict axillary LN metastasis, the regression equation, the weighting, and the counting methods were used. The OR for the BI-RADS category and each SWE feature from the final logistic regression model was used in the weighting and counting methods. In the weighting method, the ORs were standardized using rounding to ensure appropriate application. In the counting method, the number of features with OR >1 was counted . The areA total of 619 invasive breast cancers included 508 cases of invasive ductal carcinoma and 111 cases of other types Table 1.p < 0.001). In the 619 masses, 481 lesions were defined as BI-RADS 3-4C, with about 25% (ranging from 22.4% to 27.3%) cases in positive metastasis LN, while in 138 masses of BI-RADS 5, patients with positive LN metastasis were up to 43.5%. There was no significant difference in tumor staging (p = 0.340) and location (p = 0.390) in the two groups.Features of categorical variables including staging of tumor, tumor location, and tumor BI-RADS categories were compared between negative and positive LN groups, as shown in p < 0.001). In patients with negative LN metastasis, 68.3% (304/445) cases presented a “stiff rim” sign in SWE images, while in positive LN groups, up to 82.2% (143/174) cases presented a “stiff rim” sign, significantly higher than that of negative LN groups.For the qualitative SWE feature, i.e., the “stiff rim” sign, there was a significant difference between the positive and negative groups for lymph node metastasis . The meanE, maxE, and sdE of shell 1, 2, and 3 mm as well as minE of shell 1 and 2 mm showed no significant difference between the two groups . However, the minE of internal tumor (p = 0.005) and shell 3 mm (p = 0.007) was significantly lower in positive LN groups than that in the negative group. The AUC, sensitivity, specificity, 95% CI, and cutoff values are shown in minE of internal tumor (p <0.01) and shell 3 mm (p < 0.01) could predict axillary LN metastasis, with cutoff values of 3.31 and 3.52, respectively.The characteristics of continuous SWE parameters in internal tumors and peritumor tissues between the two groups are shown in minE of intrinsic tumor was no more than 3.31 kPa; (3) the minE of shell 3 mm was no more than 3.52 kPa; and (4) the tumor showed a positive “stiff rim” sign in SWE. The OR values of the four features were 2.155, 1.654, 1.564, and 1.900, respectively . In the weighting method, the weight values of all four features were 2 based on the OR values of the above four features  the breast tumor was assessed as BI-RADS 5; (2) the Following the principle of balancing the diagnostic performance and ease of use, the counting method was used to establish the risk system for predicting axillary LN metastases. Thus, a 0–4 grade risk stratification system was established based on the four suspicious features mentioned above: The LN metastasis risk grade of the breast cancer is defined from 0 to 4 according to the number of suspicious features, i.e., the mass was judged to be risk grade 4 when all suspicious features were present and grade 0 when no suspicious features were present. The risk grade of LN metastasis for the 619 patients was determined according to the above rule.p < 0.001). The percentage of patients with positive LNs from grades 0 to 4 was constantly increased, with 7.1% (3/42) for grade 0, 19.2% (30/156) for grade 1, 24.5% (46/188) for grade 2, 35.6% (64/180) for grade 3, and 58.5% (31/53) for grade 4, respectively, which is shown in p < 0.0001). Results of the logistic analysis of the comprehensive grade showed that the OR of axillary LN metastasis was increased progressively with rising grade. The risk of axillary LN metastasis was 3.095 times higher in patients with risk grade 1 than in patients with risk grade 0 (p = 0.074), and 4.211–18.318 times higher in patients with risk grades 2–4 . The risk grade model predicted axillary LN metastasis with an AUC of 0.656 , a sensitivity of 54.60% , a specificity of 68.99% , and a cutoff value of grade 2.Subsequently, we compared the difference of risk grade between patients with positive and negative metastasis LNs Table 7,Since risk category 1 was not different from category 0, we also compared the difference of OR values between grade 1 vs. grades 2, 3, and 4 and grades 0–1 vs. grades 2, 3, and 4 in the risk system. Results showed that the risk of axillary LN metastasis was higher in patients with risk grades 3 and 4 than in patients with risk grades 0–1 and grade 1  Table 8.maxE and meanE of primary tumors were higher in LN metastasis cases , indicating that these SWE parameters of intrinsic tumor and peritumor tissues might not provide sufficient information in predicting LN metastasis for our research group. The difference between the results of this study and previous studies may be due to the difference of the study sample and the difference of the ultrasound instruments used.The risk of LN metastasis constantly exists in breast cancer patients, and it is expected to be provided in an early stage in order to guide the clinical decision and improve the tumor survival. SWE has been used to predict axillary LN metastasis in invasive breast cancer. Previous studies have reported that higher elasticity of the tumor was related to lymph node metastasis of breast cancer , 23, andis cases . In our minE of internal tumor and shell 3 mm and the “stiff rim” sign showed a significant difference between patients with positive and negative LN metastasis groups . Zhou et al. have reported that the “stiff rim” sign could select the malignant breast lesions, and possible reasons may contribute to cancer cell infiltration into interstitial tissues or a desmoplastic reaction . In the 619 masses, 481 lesions were defined as BI-RADS 3-4C, with about 25% (ranging from 22.4% to 27.3%) cases in positive metastasis LN, while in 138 masses of BI-RADS 5, patients with positive LN metastasis were up to 43.5%. Guo et al. revealed that irregular shape and higher color Doppler flow imaging grades were associated with axillary LN metastasis of breast cancer . Previoup = 0.340), which was similar to the results of the previous study; that is, tumor size on ultrasound was not an independent predictor of axillary LN metastasis (p = 0.390) in LN-positive and -negative groups in our study.A previous study revealed that tumor staging was an independent predictor of breast cancer LN metastasis . A tumortastasis . Breast tastasis . HoweverminE of internal tumor, and shell 3 mm). A patient with a BI-RADS 5 breast tumor exhibiting the “stiff rim” sign  was assessed as grade 4 in our risk system. The OR of each grade in the risk system gradually increased as the increasing levels were 3.095  for grade 1, 4.211  for grade 2, 7.172  for grade 3, and 18.318  for grade 4, respectively, compared with grade 0, indicating that patients with a higher risk grade were more likely to have LN metastasis. The diagnostic performance of this risk grade system is significant in assessing the risk grade of LN metastasis, although the AUC is not excellent .The grade system has been extensively used in categorical variables of clinical and imaging data analysis , 33. In The merit of our research is that this is a multicenter study covering 17 hospitals, which effectively improves the reliability of the research data. However, the study still has some limitations. Firstly, the evaluation of the BI-RADS category and the SWE features of breast lesions were influenced by the experience of the radiologist. However, previous studies have confirmed that the reproducibility ranged from moderate to substantial for the BI-RADS category and ranged from substantial to almost perfect for both the quantitative SWE features and the “stiff rim” sign , 34, 35.A 0–4 grade risk stratification system, based on quantitative and qualitative SWE features as well as BI-RADS category, for predicting axillary LN metastasis in invasive breast cancer was established in this study. Although the diagnostic performance of this risk system was not excellent, there is no doubt that it has the potential to predict axillary LN metastasis by the combination of SWE and conventional ultrasound.zhousu30@126.com.The datasets presented in this article are not readily available because the generated datasets belong to department of ultrasound, Ruijin Hospital, Shanghai Jiaotong University School of Medicine. Requests to access the datasets should be directed to JQZ, The studies involving human participants were reviewed and approved by the Ethics Committee of Ruijin Hospital, Shanghai Jiaotong University School of Medicine. The patients/participants provided their written informed consent to participate in this study.JWZ drafted and edited the manuscript. HTZ, YJD, XHJ, JWZ, ZYL, ZRC, YJX, BH, YXH, CC, JFX, FJD, XNX, CRW, WJH, GW, QYL, QC, WYD, QCJ, YLM, HNY, XJX, HJY, PZ, YS, LGC, PH, LXQ, JPL, LYS, YNZ, and YYX collected the clinical and ultrasound data. YJD and WWZ analyzed the images. XHJ collected the ultrasound images. XHJ and JWZ collected the autopsy and pathology data. HTZ prepared for the literature. YYS and HTZ completed the statistical analysis. All authors contributed to the article and approved the submitted version.This study was supported by the National Natural Science Foundation of China (grant no. 82071928).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


TMPRSS3 and MYH14). These data highlight for the first time the high prevalence of dual molecular diagnoses in HL patients and suggest that they should be considered especially for those cases that depart from the expected clinical manifestation or those characterized by a significant intra-familiar variability.Hearing loss (HL) is the most common sensory impairment, and it is characterized by a high clinical/genetic heterogeneity. Here we report the identification of dual molecular diagnoses  in a series of families affected by non-syndromic and syndromic HL. Eighty-two patients who displayed HL as a major clinical feature have been recruited during the last year. After an accurate clinical evaluation, individuals have been analyzed through whole-exome sequencing (WES). This protocol led to the identification of seven families characterized by the presence of a dual diagnosis. In particular, based on the clinical and genetic findings, patients have been classified into two groups: (a) patients with HL and distinct phenotypes not fitting in a known syndrome due to mutations at two loci  and (b) patients with two genes involved in HL phenotype (e.g.,  The identification of the molecular basis of a genetic disorder is the central goal of modern medical genetics. In fact, the definition of the correct molecular diagnosis offers a series of benefits that have a tremendous impact on human life, such as understanding the pathological mechanisms, the implementation of preventive strategies, the development of personalized treatments, etc.Recently, next-generation sequencing (NGS) technologies, and in particular whole-exome sequencing (WES), have been introduced in the diagnostic routine of Mendelian diseases, revolutionizing the approach of the study of genetic disorders. The possibility to screen multiple genes simultaneously in an unbiased method allowed the identification of the molecular cause of many rare diseases, especially those characterized by high genetic heterogeneity.The pathologies that benefited the most from the introduction of NGS technologies are those characterized by high genetic heterogeneity and different models of inheritance such as hearing loss (HL).https://www.who.int/news-room/fact-sheets/detail/deafness-and-hearing-loss, accessed on 24 November 2021). It is extremely heterogeneous both from the clinical and genetic point of view and can be classified in many categories according to different parameters, such as (1) the degree and configuration of loss, (2) the location of the damage causing the impairment, and (3) the age of onset. At least 50% of congenital or childhood HL is attributable to genetic causes, leading to hereditary hearing loss (HHL) [HL is the most prevalent sensory impairment in both childhood and adulthood . Accordihttp://hereditaryhearingloss.org/, accessed on 24 November 2021), and more than 400 syndromes associated with HL [HHL can be further classified as syndromic (SHL), when HL is accompanied by other clinical features and non-syndromic (NSHL) ; it is e with HL .Thanks to the application of a multi-step approach, here we describe the identification of an additional peculiar scenario, the one of dual molecular diagnosis in patients affected by HHL, i.e., the presence of pathogenic variations at two distinct loci that lead to the expression of two Mendelian conditions, which segregate independently.During the last year, a total of 82 subjects affected by HL have been recruited at the IRCCS “Burlo Garofolo” in Trieste and at the Policlinico S.Orsola-Malpighi in Bologna .All the participants underwent an accurate clinical evaluation. In particular, a complete medical history has been collected to exclude HL due to infections, trauma, or other non-genetic causes. All the patients underwent pure tone audiometric testing (PTA) or auditory brainstem response (ABR) (based on the probands’ age) to define the degree of HL according to the international guidelines described by Clark (1981) . NeuroloBased on the clinical findings, patients have been classified as likely NSHL (N = 67) or likely SHL (N = 15). Moreover, based on the inheritance pattern, familial cases were further categorized as: presumed autosomal recessive (N = 4), presumed autosomal dominant (N = 14), or sporadic cases (N = 64).Written informed consent was obtained from all the participants; in the case of minors, their next of kin provided written informed consent. The study was conducted in accordance with the tenets of the Helsinki Declaration and was approved by the Ethics Committee of IRCCS-Burlo Garofolo of Trieste and of Policlinico S.Orsola-Malpighi of Bologna  .All the patients underwent a multi-step approach for the molecular diagnosis of HHL, summarized in GJB2, GJB6, and MT-RNR1 genes were previously excluded. In particular, the entire coding region of the GJB2 gene was sequenced by the Sanger method (primers available upon request). DNA was analyzed on a 3500 Dx Genetic Analyzer , using ABI PRISM 3.1 Big Dye terminator chemistry (Thermo Fisher) according to the manufacturer’s instructions. Subsequently, GJB6 deletions  were screened by multiplex PCR, as previously described [For all the patients enrolled in the study, the presence of mutations in the STRC, CATSPER2, and OTOA genes. The SALSA® MLPA® probe mixes P461-A1 DIS  were employed, according to the manufacturer’s instructions. Coffalyser. Net software was used for data analysis in combination with the lot-specific MLPA Coffalyser sheet. The following cutoff values for the dosage quotient (DQ) of the probes were used to interpret MLPA results: 0.80 < DQ < 1.20 (no deletion/duplication), DQ  =  0 (deletion), and 1.75 < DQ < 2.15 (duplication).MLPA analysis was performed for the identification of deletion/duplication in WES was completed on an Illumina NextSeq 550 instrument  using the Twist Human Core Exome + Human RefSeq Panel kit , according to the manufacturer’s protocol.Briefly, 50 ng of genomic DNA was enzymatically fragmented. After an end repair and dA-tailing reaction, each fragment was ligated to a universal adapter and then amplified using the Unique Dual Index primers . Afterward, the samples were hybridized with the Twist Human Core Exome and the Human RefSeq Panel, which allows covering 99% of the protein-coding genes. Finally, the hybridized fragments have been captured, amplified, and sequenced.https://www.engenome.com/, accessed on 24 November 2021). This workflow has been designed for Illumina paired-end sequencing data and allows the identification of germline variants such as single-nucleotide variants (SNVs), short insertion/deletions (INDELs), exon-level copy number variations (CNVs) starting from sequence reads. The pipeline includes a series of steps, such as FASTQ trimming, FASTQ quality check, FASTQ mapping, mark of duplicates, base quality score recalibration, and variant calling.FASTQ files have been processed through a custom pipeline, called Germline-Pipeline, developed by enGenome s.r.l.  software (evai.engenome.com), which allows variant annotation and interpretation. In particular, eVai combines artificial intelligence with the American College of Medical Genetics (ACMG) guidelines  to classSNVs leading to synonymous amino acids substitutions not predicted as damaging, not affecting splicing, or highly conserved residues were excluded, as well as SNVs/INDELs with quality score (QUAL) < 20 and called in off-target regions.http://www.ncbi.nlm.nih.gov/SNP/, accessed on 24 November 2021) as well as in gnomAD , led to the exclusion of those variants previously reported as polymorphism. In particular, a minor allele frequency (MAF) cutoff of 0.005 for recessive forms and 0.001 for the dominant ones was used.A comparison between the identified genetic variants and data reported in NCBI dbSNP build153 , Deafness Variation Database , and The Human Gene Mutation Database .The pathogenicity of known genetic variants was evaluated using ClinVar . Based on both the genetic and clinical findings, patients have been classified into two main categories: (1) those with distinct phenotypes, i.e., HL plus other clinical features due to mutations in different genes, (2) patients with overlapping phenotypes, i.e., HL due to the contribution of two distinct loci.In particular, five families belong to the first class of patients , while the remaining two belong to the second one .Fam 1 A, an ItaThe audiometric evaluation revealed a mild-moderate HL across all frequencies and normal hearing in both parents . Family STRC, CATSPER2, and OTOA genes through MLPA revealed the presence of a homozygous STRC (NM_153700.2) deletion in the proband   , Table 1Fam 2 B, an ItaIn particular, both the proband, a 10-year-old girl, and the mother showed a series of clinical features attributable to Marfan syndrome . In addition, an accurate clinical evaluation that included hematological and biochemical tests revealed the presence of metabolic acidosis (pH 7.25), hyperchloremia, and hypokalemia in the proband, suggesting a clinical diagnosis of distal renal tubular acidosis (dRTA). Furthermore, the proband displayed a congenital progressive asymmetric HL (moderate to severe in the right ear and severe to profound in the left one) .FBN1 (NM_000138.5) ), at the heterozygous state both in the proband and the mother, and (2) two compound heterozygous mutations already described as causative of dRTA and HL  [ATP6V1B1 gene (NM_001692.4) in the proband  a nonsense mutation already described as causative of Marfan syndrome  [ T, p.Arg44*), at PHA: 18) , the c.2 proband , Table 1Fam 3 C came toMYO15A gene (NM_016239.3)  , Table 1KLHL7 (NM_001031710.2) ) ) , Table 1GJB2 (coding for connexin-26) and analysis for the deletion involving delGJB6-DS13S1830 of GJB6, coding for connexin 30, were negative. Despite implantation of the bilateral external prosthesis, her developmental milestones were characterized by a cognitive delay with predominant language impairment. When she was nine years old, she presented with seizures with sudden arousal, eye opening, diffuse rigidity, and limbs jerks arising from sleep. Based on EEG pattern and video-polysomnography (which documented up to 40 motor events/night mainly characterized by asymmetric tonic posturing), a diagnosis of sleep-related hypermotor epilepsy was made. In the hypothesis of a syndrome associating HL and epileptic encephalopathy, arrayCGH analysis was performed without identifying any copy number variation. WES was then performed on the family trio. Data analysis revealed the presence in the proband of a de novo heterozygous mutation in KCNT1 (NM_020822.3) ) [). KCNT1 mutations are a known cause of dominant epileptic encephalopathy (MIM#: 614959), and the same mutation was previously described as pathogenic [The proband of Fam 4 D is a 27934Thr))  (Supplem1 NM_0208.3 (c.280TMPRSS3 (NM_024022.2), a gene known for being causative of autosomal recessive deafness , were identified in the proband. In particular, the proband carried a pathogenic frameshift deletion ) inherited from her father and a pathogenic missense mutation ) on the maternal allele  showed a similar audio profile, despite being diagnosed later (concomitantly with the proband). The mother (46 years old) displayed a milder phenotype, with a moderate HL at the medium and high frequencies, diagnosed at the age of 25 . MoreoveFurther clinical assessments did not reveal any other relevant features.STRC, CATSPER2, and OTOA genes, with negative results.The proband was first screened for mutations in connexin genes, for the mitochondrial mutation A1555G, and for the presence of CNV in TMPRSS3 gene, known for being causative of autosomal recessive deafness , together with a likely pathogenic variant in MYH14, a gene described for causing autosomal dominant HL   .TMPRSS3 (NM_024022.2), the c.413C > A, p.(Ala138Glu) mutation in exon 5 and the c.977C > T, p.(Pro326Leu) variant in exon 10 have been identified. The first mutation, inherited from the father, is already described as causative of childhood NSHL by both the HGMD Professional database [in silico tools used during the tertiary analysis.As regards database  and DeafMYH14 (NM_024729.3), the c.160C > A, p.(Arg54Ser) variant in exon 2 was detected at the heterozygous state in both the proband and the affected mother. The variant affects a highly conserved residue, is predicted as damaging, and is not described in any public database.Concerning Sanger sequencing confirmed the presence of all the variants also in the affected brother.Furthermore, two additional families, Family 5 (FLNA gene (NM_001456.3) , in 01456.3) , a gene The second family, Family 7, was characterized by a likely dominant NSHL, with the presence of HL in the proband, in the mother, in the maternal uncle, and maternal grandfather.EYA4 (NM_004100.5) ), a gene known for being causative of autosomal dominant NSHL , and (2) two pathogenic mutations in USH2A gene (NM_206933.2) at the compound heterozygous state  and c.2276G > T, p.(Cys759Phe)), which is known for being causative of Usher syndrome type 2A  in the proband, a girl of three years old  a nonsense variant segregating in all the affected family members in ears old .The presence of dual molecular diagnoses is becoming a more and more frequent finding in all genetic conditions. In fact, several reports demonstrated that this scenario occurs in a relatively large percentage of cases, ranging from 4.6% to 8.9% of the patients who received a molecular diagnosis ,28,29. MGJB2-positive patients, and dual diagnoses might be more frequent in individuals displaying a variety of clinical features. In this light, to clearly define the contribution of dual diagnosis in the etiopathogenesis of HHL, it is necessary to expand the number of analyzed samples. However, these results point out the complexity of the molecular basis of HHL, highlighting that the identification of a single molecular diagnosis might not be conclusive for all the cases, thus requiring a deeper data evaluation.Data here presented confirmed the presence of dual molecular diagnoses also in HL patients suggesting they can occur in a large percentage of cases. In particular, among the 82 families recruited during the last year, seven display a dual diagnosis, for an overall percentage of 8.5% of the total cases and 17.9% of all the patients who received a molecular diagnosis. Of course, we should take into account that these results have been obtained from a small sample size, which might be enriched by complex scenarios. All the cases have been selected from a larger group of patients enrolled in our institute, excluding Based on this evidence, it appears clear that even in the genomic era, it is still fundamental to have extensive knowledge of the investigated phenotype in order to critically interpret the sequencing findings. For this reason, sequencing data analysis should be performed by a multidisciplinary team of geneticists, clinicians, radiologists, and otolaryngologists that altogether cooperate with the final aim of defining the correct molecular diagnosis.(1)in the presence of patients with clinical features that do not fit into a known model/syndrome. In this case, the possible scenarios include the identification of a novel syndrome, with a new gene involved, or, as shown in patients of Fam 1, 2, 3, 4, 5, the presence of dual independent genetic causes;(2)in the presence of families with a high intra-familial phenotypic variability. As shown for the probands of Family 6 and 7, the differences in the degree or onset of HL might be the consequence of concomitant genetic causes that modulate and worsen the clinical manifestation.The examples mentioned above suggest that possibility of a dual molecular diagnosis in HHL families should be taken into consideration in the following cases:The knowledge of the genetic background responsible for HL is extremely valuable in many ways: it helps in elucidating the biology of the hearing system, and, more importantly, has relevant practical outcomes, influencing the clinical management of the patients, providing recurrence risk estimation and paving the way for the development of future personalized therapeutic approaches.Overall, the examples described here point out the emerging role of dual molecular diagnosis in patients affected by both SHL and NSHL, suggesting that alternative inheritance scenarios should be taken into account, especially for those cases that depart from the expected clinical manifestation. Moreover, given the high proportion of dual diagnosis here detected, the recommended approach for the study of the genetics of HL should include NGS technologies, which are able to provide an unbiased screen of our genome.We conclude that, once the most common forms of SHL are excluded, the frequency of dual molecular diagnosis can be as high as 10% in the remaining cases. Furthermore, dual molecular diagnosis can explain a small but relevant proportion of families with clinically heterogeneous NSHL thus should be carefully considered for the early diagnosis and the clinical management of the patients.


Rimicaris exoculata, which are endemic to the hydrothermal vents of the Mid-Atlantic Ridge. However, only a few studies have examined intestinal symbiosis. Here, we studied the intestinal fauna in juvenile and adult Rimicaris kairei, another species in the Rimicaris genus that was originally discovered at the Kairei and Edmond hydrothermal vent fields in the Central Indian Ridge. The results showed that there were significant differences between juvenile and adult gut microbiota in terms of species richness, diversity, and evenness. The values of Chao1, observed species, and ASV rarefaction curves indicated almost four times the number of species in adults compared to juveniles. In juveniles, the most abundant phylum was Deferribacterota, at 80%, while in adults, Campilobacterota was the most abundant, at 49%. Beta diversity showed that the intestinal communities of juveniles and adults were clearly classified into two clusters based on the evaluations of Bray–Curtis and weighted UniFrac distance matrices. Deferribacteraceae and Sulfurovum were the main featured bacteria contributing to the difference. Moreover, functional prediction for all of the intestinal microbiota showed that the pathways related to ansamycin synthesis, branched-chain amino acid biosynthesis, lipid metabolism, and cell motility appeared highly abundant in juveniles. However, for adults, the most abundant pathways were those of sulfur transfer, carbohydrate, and biotin metabolism. Taken together, these results indicated large differences in intestinal microbial composition and potential functions between juvenile and adult vent shrimp (R. kairei), which may be related to their physiological needs at different stages of development.Despite extreme physical and chemical characteristics, deep-sea hydrothermal vents provide a place for fauna survival and reproduction. The symbiotic relationship of chemotrophic microorganisms has been investigated in the gill of  Rimicaris exoculata is one of the dominant macroorganisms in the hydrothermal vents of the Mid-Atlantic Ridge (MAR) and can reach densities of up to 3,000 individuals per square meter in the mixing zone of hydrothermal fluid and the surrounding cold, oxygenated seawater  and Kairei , during the cruises on February 2019 by the research ship “Tan Suo Yi Hao.” All shrimps were obtained using the suction sampler from a manned submersible (“Shen Hai Yong Shi”). Once onboard, specimens were immediately frozen at −80°C or stored in 75% ethanol at −20°C.c oxidase subunit I (COI). We identified the species as R. kairei (COI sequence and the phylogenetic tree constructed through MEGA-X (64-bit) , and adults (>6 cm in length) . Ten ind. kairei , based o(64-bit)  and NeigCOI sequence) and whole gut samples were isolated under sterile conditions. The gut before the fourth body segment is the foregut, while the rest constitute the hindgut  database under accession numbers Analysis of the V3–V4 sequence was conducted with QIIME2 v2021.8 along with the built-in plugins . First, Alpha diversities  and beta diversities  were estimated using q2-diversity after normalization to 16,714 sequences per sample according to the minimum number of sequences in the samples. Kruskal–Wallis rank-sum tests were used to detect significant differences in alpha diversity. Beta diversities were visualized using non-metric multidimensional scaling (NMDS) and principal coordinate analysis (PCoA) plots. ANOSIM  was used to analyze the similarities of the microbial community compositions of the two groups.To identify the discriminative microbes of juvenile and adult groups, two methods were used: Random Forest and STAMP (v2.1.3). Random Forest is a machine learning classification algorithm that creates predictions by parallel learning of multiple tree predictors built randomly and trained on different subsets of data . The ASVThe Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) 2.0 pipeline was used to predict the potential functions of the bacterial communities based on 16S rRNA sequences . SequencThe rarefactions for these studied samples were saturated and are displayed in Deferribacteraceae, accounting for 80% ± 16% (mean ± SD), followed by Flavobacteriaceae, which accounted for 8% ± 7%. In adults, the top genus was Sulfurovum, accounting for 40% ± 20%. The second one was Deferribacteraceae, which accounted for 17% ± 17%. Among these 44 genera, 34 showed significant differences in abundance between the whole gut bacteria of the two developmental groups, according to Wilcoxon rank-sum tests , and Sulfurovum (juvenile vs. adult: 2% vs. 40%)  .p = 0.001). In the PCoA, principal coordinate 1(PCo1) explained 79.1% of the variance   .Deferribacteraceae) was more abundant in juveniles than in adults; the other 19 genera were lower in juveniles. The top five most featured microbes included Sulfurovum, Deferribacteraceae, Mycoplasmataceae, Maritinminonas, and Entomoplasmatales_type_III. Sulfurovum, the top-ranking microbe, had a mean decrease accuracy (MDA) value of approximately 8 and showed high abundance in all adult samples. Deferribacteraceae, the second-ranking microbe, had an MDA value of 7 and the highest abundance in all juvenile samples, but was almost absent in most of the adult samples. The MDA values of Mycoplasmataceae, Maritinminonas, and Entomoplasmatales_type_III ranged from 6 to 5. In the STAMP analysis, 13 genera were filtered out , the gut microbiota showed higher diversity in the larval, juvenile, and adult stages than that in fingerling and yearling stages by a culturable approach  and Calvin–Benson–Bassham (CBB) cycles were used for carbon fixation by two filamentous epibionts belonging to Campylobacteria and Gammaproteobacteria, respectively. These epibionts could couple the oxidation of reduced sulfur compounds or molecular hydrogen to oxygen or nitrate reduction  can be found in the article/LQ and L-SH conceived and designed the experiments and wrote the manuscript with input from all other authors. LQ, C-AL, F-CZ, and MS performed the experiments and analyzed the data. L-SH directed and supervised all of the research. All authors contributed to the article 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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


In this study, we aimed to compare the effects of propofol-ketamine and propofol-fentanyl sedations on post-procedure nausea-vomiting in children undergoing magnetic resonance imaging (MRI).This study included 100 pediatric patients (2–10 years old) who had propofol-ketamine and propofol-fentanyl for sedation to undergo MRI. The patients were divided into two groups, and sedation was performed through propofol-ketamine  or propofol-fentanyl . For sedation induction, intravenous (IV) bolus of 1.2 mg/kg propofol and 1 mg/kg ketamine were administered in Group K, IV bolus of 1.2 mg/kg propofol, and 1 µg/kg fentanyl in Group F. All patients received 0.5 mg/kg IV bolus propofol in additional doses when the Ramsay Sedation Score (RSS) was below 4 for maintenance. Perioperative heart rate, systolic arterial pressure, peripheral oxygen saturation, respiratory rate, and nausea-vomiting scores were recorded for each patient. There was no difference between the groups in terms of nausea incidences at the 1st hour. However, the rate of vomiting was significantly higher in Group K.In our study, we showed that the vomiting rate was higher in the 1st hour in Group K compared to Group F.  Magnetic resonance imaging (MRI) system is a procedure that requires patients to remain motionless for a long time in a claustrophobic and noisy environment. Sedation should be performed on pediatric patients during imaging as pediatric patients cannot remain still due to severe anxiety. In anesthesia applications performed only for imaging purposes, conscious sedation, deep sedation, total intravenous anesthesia (TIVA), or inhalation anesthesia can be performed .An essential point in examinations for pediatric patients in MRI units is to increase the patient circulation rate without compromising patient safety. For this reason, combinations, of which the effect of which starts quickly and ends quickly, allowing the shortening of discharge time, are crucial.The effects of ketamine can be listed as sedation, hypnosis, dissociation, analgesia, and amnesia. The anesthetized state has been termed dissociative anesthesia because patients who receive ketamine alone appear to be in a cataleptic state, in contrast with other states of anesthesia that resemble normal sleep. Ketamine increases systolic arterial pressure, heart rate, and cardiac output in a biphasic manner. It produces a direct cardiodepressive, negative inotropic effect next to an indirect stimulatory effect due to activation of the sympathetic system [3].Fentanyl is currently the most widely used drug as the analgesic component of balanced anesthesia. It is a synthetic opioid agonist, a potent narcotic analgesic and has the same characteristics as other opioids. That is, it causes analgesia, sedation, respiratory depression, and nausea, vomiting [4]. The effect of fentanyl on the cardiovascular system is minimal. Cholinergic effects such as nausea, vomiting, myositis, and constipation may be seen [5].Propofol is used only intravenously. The onset of the effect is fast, and the duration is short. It is used in conscious sedation, general anesthesia induction, and maintenance. It does not cause a permanent effect after anesthesia. The use of propofol outside the operating room is gradually increasing. The reason for this is that it is easy to use, effective, and has a safe profile. However, it also has several other advantages, such as the rapid onset of effect, rapid metabolism, rapid separation, and showing antiemetic activity . Since propofol is hypnotic with no analgesic effect, it is recommended to be used with ketamine or a short-acting opioid in daily practice. The combination of propofol and ketamine has gained popularity in short-time procedures to provide sedo-analgesia [8].Postoperative nausea and vomiting (PONV) risk continue to be an essential problem for patients due to anesthetic methods and drugs. Nausea can be experienced alone or with vomiting. If airway reflexes are depressed because of the residual effects of anesthetic and analgesic drugs, pulmonary aspiration risk because of vomiting is high. Also, persistent vomiting may cause dehydration and electrolyte imbalance. It may delay the discharge of the patient, especially after daily procedures .In this study, we aimed to evaluate whether there is a difference in terms of nausea and vomiting between propofol/fentanyl and propofol/ketamine combination, which are two of the routine methods used in our clinic in the sedation of patients in the pediatric age group (2–10 years).This study was carried out with 100 pediatric patients in between 2 to 10 years old who underwent imaging in the Erciyes University Faculty of Medicine, Department of Anesthesiology and Reanimation, Erciyes University, Gevher Nesibe Hospital MRI unit for diagnostic purposes. After Faculty Ethics Committee approval (Decision Number: 2017 / 285) and informed consent forms from the families of these patients were obtained, these patients were included in the study as prospective randomized double-blind. Tosun et al. have reported the incidence of PONV in children undergoing strabismus surgery as 60% in their study. With respect to that study, using α = 0.05 and β = 0.2 for each comparison, the sample size in the current study was estimated at 48 evaluable patients per group [12]. Patients who were ASA physical status I or II were enrolled into the study, and the patients who had a severe hemodynamic problem (using an inotropic-vasoactive agent), partial loss of consciousness or were in a coma, who was found to have upper respiratory tract infection at the time of imaging, who had an intracranial space-occupying lesion, organ failure, who was suspected of non-adherence to the duration of fasting and had tonsillar hyperplasia causing airway obstruction were planned to exclude from the study . All patients were prevented from taking solid food 6 h before and liquid food 2 h before anesthesia.The existing comorbidities of the patient were determined, and the drugs used by the patient and their interaction with anesthetic drugs were evaluated.After establishing the vascular access, providing premedication with intravenous (IV) 0.05 mg/kg midazolam, they were taken to the MRI room with their parents 30 min before the MRI imaging process started, and the panic and fear that children felt due to a foreign environment were tried to be avoided. In order to avoid any kind of bias, 1:1 block randomization was performed. Clinical and study staff involved in recruitment, sedation, or patient care, children and their parents remained blinded until observation of the last patient completed. An anesthetist, who was not involved in patient care prepared the study medications.Patients in group K, following IV bolus of 1.2 mg/kg propofol and 1mg/kg ketamine application, received 0.5 mg/kg IV bolus propofol in additional doses when the Ramsay sedation score (RSS) was <4 for maintenance. Administration of atropine (0.015 mg/kg IV) was planned in case of the probability of hypersecretion due to ketamine.After IV bolus of 1.2 mg/kg propofol and 1 µgr/kg fentanyl administration, patients in group F received 0.5 mg/kg IV bolus propofol in additional doses when the RSS was <4 for maintenance.2) of the patients were monitored throughout the procedure, and pre-induction baseline values, 10th, 20th min and the 1st h values were recorded.Heart rate (HR), systolic arterial pressure (SAP), diastolic arterial pressure (DAP), mean arterial pressure (MAP), peripheral arterial oxygen saturation  were determined to develop hypoxia and desaturation, and tactile stimulation and airway opening maneuvers were performed. When there were coughing and suspicion of airway obstruction, the imaging was interrupted, and the airway patency was checked after pulling the patient out of the magnetic field. If the airway obstruction was partial, a position to provide head tilt was given. Overall, it was planned to ventilate with mask-ambu, and place a laryngeal mask airway (LMA), if necessary, and apply orotracheal intubation in case of failure.After completing the imaging, patients who were taken to the recovery room were kept under monitoring, and the hemodynamics, respiratory, and consciousness status of the patients were followed. It was observed whether there were nausea-vomiting and agitation. The patients were followed up in the recovery unit for 2 h, and the patients who were recovered were discharged after their parents were asked to observe the patients for 24 h for nausea and vomiting. After 24 h, the parents were called, and the 12- and 24-h results were recorded. Pre-procedure, 1st-hour, 12th-hour, and 24th-hour nausea-vomiting scores were recorded using a numeric scoring system for PONV [13]. (Table 1).Modified Aldrete scoring was used to evaluate patients’ recovery [14]. (Table 2).The time to modified Aldrete scoring ≥9 was recorded as recovery time.IBM SPSS Statistics 22.0 software package  was used for statistical analysis of the data. Independent student t-test was used to compare heart rate, Mann–Whitney U test was used to compare systolic and diastolic arterial pressure, duration of the procedure, propofol doses, and Chi-square test was used for postop nausea and vomiting score analysis. The compliance of the data to normal distribution was evaluated by histogram, q-q graphs and Shapiro–Wilk test. Variance homogeneity was tested with the Levene test. The p value <0.05 was considered statistically significant.When the demographic data of the patients were evaluated, no statistically significant difference was found between the two groups in terms of age, weight, propofol amount, and duration of the procedure (p > 0.05) (Table 3).When the patients’ HR was evaluated, no significant difference was found between Group F and Group K in the baseline, 10th-min, 20th-min, and postoperative 60th-min data (p > 0.05) .When SAP of patients was evaluated, no statistically significant difference was found between the two groups in the baseline, 10th min, 20th min, and 60th-min postoperative data (p > 0.05) .When DAP of patients was evaluated, while no significant difference was found between Group F and Group K in the baseline, 20th min, and postoperative 60th-min data (p > 0.05), a significant difference was found in 10th-min data (p < 0.05) .When postoperative nausea and vomiting scores of the patients were evaluated, there was no difference between the groups in terms of nausea rates at the 1st h (In Group K vomiting was observed once in six patients while it was not observed in Group F at the 1st h). At other hours, no significant difference was observed between the groups in terms of nausea-vomiting rates (p > 0.05) (Table 4).This study aimed to compare the effects of propofol-ketamine versus propofol-fentanyl sedations on post-procedure nausea-vomiting in children undergoing MRI. The main results were the significantly higher vomiting rate at the 1st h and significantly higher DAP at the 10th minute in Group K. PONV has been described after ketamine administration [15]. Green et al. compiled approximately 100 studies that ketamine was applied. They found that more than 11,000 patients had vomiting at a rate of 8.5%, and that vomiting was in the late recovery stages where patients generally began to wake up [16]. In the application of fentanyl, PONV has been described too [17], and concerns exist that this may also be true in combination with propofol. In our study, PONV incidences were low, which may be due to the antiemetic effect of propofol .Vomiting was seen in 6 (%12) patients in the 1sthour in Group K, but none of them required rescue medication because they vomited once within 30min. Vomiting was not observed in Group F in the 1st hour. Godambe et al. compared the effectiveness of propofol-fentanyl and ketamine-midazolam for brief orthopedic procedural sedation in 113 pediatric patients. They also observed no vomiting in the propofol-fentanyl group [21]. Bauman et al. randomly chose 64 of the total of 243 sedation procedures with analgesia for a descriptive retrospective review and analysis in pediatric patients. They reported no nausea and vomiting in the propofol-fentanyl groups. [22]Atropine, which increases HR with minimal effects on mean arterial pressure (MAP) and cardiac output (CO), is a competitive antagonist of cholinergic receptors. Atropine administration also results in a decrease in the incidence of postoperative nausea and vomiting [23]. In case of hypersecretion due to ketamine, atropine administration was planned, but none of the patients experienced hypersecretion that would require atropine administration.Green et al. detected vomiting in 12.1% of cases above five years of age and 3.5% of cases under five years of age after ketamine administration [24]. This study shows that vomiting after ketamine administration may be associated with increased age. In our study, no statistically significant difference was found between the two groups in terms of the age of the patients.When the hemodynamic parameters of the patients were evaluated, no statistically significant difference was found between the two groups in HR and SAP in our study; DAP in the 10th-min after sedation administration was found to be significantly higher in the ketamine group than in the fentanyl group. However, patients in the propofol-fentanyl group had lower HR and SAP than patients in the propofol-ketamine group. We concluded that the hypotensive effect of propofol was balanced with the use of ketamine .However, Sinner and Graf stated in their study that it is appropriate to use ketamine, especially in cases where the cardiovascular system is unstable [28]. In terms of cardiovascular stability, we can say that ketamine is an appropriate alternative to the risk of propofol-related hemodynamic depression development due to its sympathomimetic effect.In our study, it was determined that there was no statistically significant difference between the two groups in terms of recovery time.In conclusion, we showed in our study that there was no difference between the groups in terms of nausea rates; however, the vomiting rate in Group K was higher than Group F within the 1st hour. Ethical approval for this study was obtained from Faculty Ethics Committee (Decision Number: 2017 / 285). Informed consent forms were obtained from the families of patients before the study.


Nonischemic cardiomyopathies with low left ventricular ejection fractions (LVEF) are eligible for an implantable cardioverter defibrillator. However, the guidelines do not specify which method should be used to assess LVEF. In our study we investigated the potential impact of performing two-dimensional echocardiography (2DE) compared to cardiovascular magnetic resonance (CMR) for LVEF regarding ICD eligibility. We found that 2DE both overestimated and especially underestimated the need for implantation, which can have serious implications in the quality of life and the prevention of death events.p < 0.001, respectively 0.65 (95% CI: 0.52–0.78), p < 0.001. The disagreement represented 7.9%/11.3% of the subjects who had EF < 35%/< 30% as observed by CMR, who would have been classified as eligible for an ICD, resulting in an additional need to use an ICD. Moreover, 2.6%/3.3% would have been deemed eligible by echocardiography for an ICD. Conclusions: These measurement problems result in incorrect assignments of eligibility that may have serious implications on the quality of life and the prevention of death events for patients assessed for eligibility of an ICD.Background: The aim of this study was to investigate the potential impact of performing two-dimensional echocardiography (2DE) compared to cardiovascular magnetic resonance (CMR) for left ventricular ejection fraction (LVEF) on implantable cardioverter defibrillator (ICD) eligibility. Methods: A prospective cohort of 166 consecutive patients with nonischemic cardiomyopathy (NICM) was designed to compare transthoracic 2DE and CMR imaging. Results: Echocardiography measurements have important differences and large limits of agreement compared to CMR, especially when assessing ventricle volumes, and smaller but relevant differences when assessing LVEF. The agreement between CMR and 2DE regarding the identification of subjects with EF <= 35, respectively <= 30, and thus eligible for an ICD measured by Cohen’s Kappa was 0.78 (95% CI: 0.68–0.88),  Cardiovascular diseases represent a main cause of death worldwide, and among European countries, Romania has a high cardiovascular disease (CVD) prevalence and mortality burden . CardiomProgression to heart failure (HF) and an increased risk of SCD are common aspects of cardiomyopathies. Studies found that the mortality decreased considerably after the implantation of an implantable cardioverter defibrillator (ICD) ,5. Current practice guidelines for the introduction of an ICD, in the primary prevention of SCD, state that left ventricular ejection fraction (LVEF) should be either <30% or 30–35%, depending on etiology and symptoms, but the technique by which it should be assessed is not specified ,7. The aNevertheless, the agreement between the two diagnostic methods, especially their utility in ICD initiation needs to be further explored.Therefore, the objectives of this study were the assessment of the agreement between two dimensional echocardiography (2DE) and CMR performed in patients with nonischemic cardiomyopathy (NICM) regarding the assessment of LVEF, end-diastolic volume (EDV) and end-systolic volume (ESV), followed by checking the agreement of the two methods to initiate an ICD based on the classical LVEF cutoffs.n = 166) consisted of clinical patients who underwent 2DE and CMR examinations during hospitalization in a tertiary regional hospital from Romania. Written informed consent was obtained for all subjects included in the study. The University Ethics Commission approved the study protocol.A prospective cohort study on consecutive patients was performed, evaluated between August 2016 and August 2019. The study cohort  between the two investigations.obesity;emphysema;related to echocardiography :claustrophobia;metallic prosthetic implants;known allergy to the contrast agents;specific to CMR:uncontrolled arrhythmias;pregnancy or lactation;high-grade valve diseases or shunts;a cardiac resynchronization or a cardiac revascularization procedure that happened between 2DE and CMR examinations.related to patient conditions:The exclusion criteria were:Patients underwent echography and CMR examinations. The examiners had access to clinical and laboratory results of the patients but did not have access to the other examination (blind assessment).All 2DE images were acquired on the same device—a Vivid S70 scanner  using a 2D matrix array transducer (M5S). The images were stored in Digital Imaging format . All stored images were obtained in the apical four- and two-chamber, respectively, standard parasternal long- and short-axis views. All cine-loops were analyzed by different experienced senior physicians unaware of the CMR results.After manual tracing of the endocardial limits from the four- and two-chamber images, left ventricle (LV) volumes and LVEF were calculated using the Simpson’s biplane method, by different senior physicians that were involved in providing the health care for their own patients. As in the CMR examination, trabeculations and papillary muscles were included in the LV volumes.Volume assessment was based on tracings of the blood–tissue interface in the apical four- and two-chamber views .Global LV function was assessed by measuring the difference between the EDV and ESV divided by EDV. End diastole was considered the image from the cardiac cycle in which the respective LV dimension or volume measurement was the largest, as in the CMR examination, which is usually at the beginning of the R wave. End systole was considered the image after aortic valve closure, or the image in which the dimension or volume of LV was the smallest . AvoidinAll subjects underwent CMR scans on the same device—a 1.5-T Avanto MRI scanner system . An eight-element phased-array surface coil device was used. Retrospective electrocardiographic (ECG) gating was used, a breath-hold of 10 to 15 s for LV volumes and LVEF assessment being needed.LVEF can be calculated when using CMR by various techniques: automated, semiautomated or manual methods . The mos2; TR 3.8 ms; TE 3.3 ms; 30 phases; flip angle 70°. A stack of SSFP images in three long-axis planes were also obtained—two-, three-, and four-chamber views.A stack of SSFP images were acquired in the short-axis plane from the level of the mitral valve annulus to the LV apex, with the following parameters: slice thickness 8 mm no gap; average in-plane resolution 1.3 × 1.3 mm2; voxel size 1.9 × 1.4 × 8 mm3; TE 3.17 msec; TR 1× RR interval; flip angle 25°.A phase-sensitive inversion recovery sequence (PSIR) for late gadolinium enhancement (LGE) was performed 10 min after the intravenous administration of 0.1 mmol/kg of Gadobutrol . A stack of left ventricle, diastolic, short-axis images was obtained, with the following settings: field of view 360 × 290 mmBefore the LGE images were obtained, an inversion time (TI) value for an optimal nulling of the normal myocardium was determined. This has been assessed on a midventricular short-axis slice, using a scout with increasing TI values.LV volumes and LVEF measurements were based on successive short-axis stacks of cine images using QMASS software . The CMR images were acquired by a senior reader. LVEF was measured by manual planimetry of the LV endocardium in short-axis cine images at ES and ED. ES and ED phases were chosen independently by each observer. Each of them took into account the maximum and minimum volume, with several phases contoured in case of doubt. At the basal slice, the LV cavity was differentiated from the atrium by the presence of ventricular myocardium, which was subsequently verified on a co-registered long-axis image. Papillary muscles were not excluded from the LV chamber tracing. LV volumes and mass were normalized to body surface area (BSA).Qualitative measurements were shown as absolute and relative frequencies. Normally distributed data were presented as means and standard deviations. Non-normally distributed data were presented as medians and quartiles. Using the Bland–Altman plot , the agrThe limits of agreement were computed classically, using the 1.96 * standard deviation of the difference between the methods, as well as using the nonparametric Harrell Davis quantile estimator , along wp-value. When assessing different classification possibilities using LVEF in the view of a future eligibility for an ICD, we considered CMR as the best method (the standard method) for measuring LVEF. A p-value beneath 0.05 was considered statistically significant, for all statistical tests.Agreement between the two methods for different thresholds of ejection fraction classification was assessed with Cohen’s Kappa, bias-adjusted Kappa, and the prevalence-and-bias-adjusted Kappa, along with the The R environment for statistical computing and graphics, version 4.1.0 , was useThe study sample consisted of 166 patients diagnosed with NICM such as dilated, hypertrophic, or myocarditis. All patients completed both echo and CMR studies. Eleven patients were excluded: three because of uncontrolled arrhythmias, six as a result of interrupted or inadequate magnetic resonance examinations, two because they had a cardiac resynchronization, or a cardiac revascularization procedure happened between 2DE and CMR examinations.The mean age was 46.35 years (16.6—standard deviation), ranging from 9 to 81 . The majThe agreement between CMR and echocardiography was evaluated for EDV LV, ESV LV, and EF . SeveralCMR, cardiac magnetic resonance imaging, EDV, end-diastolic volume; LV, left ventricle; continuous red line, bias as 50th quartile; dotted red line, bias as mean; red interval, 95% bootstrapped confidence interval for 50th quartile; straight blue lines, limits of agreement at 2.5th and 97.5th quartiles; blue interval, 95% bootstrapped confidence interval for limits of agreement at 2.5th and 97.5th quartiles; dotted blue lines, limits of agreement at 1.96 standard deviations from the mean; dashed green line, linear regression line; magenta dot-dashed line, general additive model fit with a spline.CMR, cardiac magnetic resonance imaging, ESV, end-systolic volume; LV, left ventricle; continuous red line, bias as 50th quartile; dotted red line, bias as mean; red interval, 95% bootstrapped confidence interval for 50th quartile; straight blue lines, limits of agreement at 2.5th and 97.5th quartiles; blue interval, 95% bootstrapped confidence interval for limits of agreement at 2.5th and 97.5th quartiles; dotted blue lines, limits of agreement at 1.96 standard deviations from the mean; dashed green line, linear regression line; magenta dot-dashed line, general additive model fit with a spline.CMR, cardiac magnetic resonance imaging; EF, ejection fraction; LV, left ventricle; continuous red line, bias as 50th quartile; dotted red line, bias as mean; red interval, 95% bootstrapped confidence interval for 50th quartile; straight blue lines, limits of agreement at 2.5th and 97.5th quartiles; blue interval, 95% bootstrapped confidence interval for limits of agreement at 2.5th and 97.5th quartiles; dotted blue lines, limits of agreement at 1.96 standard deviations from the mean; dashed green line, linear regression line; magenta dot-dashed line, general additive model fit with a spline.p < 0.001, while the bias-adjusted Kappa, and the prevalence-and-bias-adjusted Kappa were 0.78 and 0.79, indicating a statistically substantial agreement. Nevertheless, clinically, 10.5% of the cases were in disagreement; 7.9% of the subjects who had EF < 35% as observed by CMR would have been classified as eligible for an ICD (having EF >= 35% as observed by echocardiography), resulting in an additional need to use an ICD, according to the guidelines. Moreover, 2.6% would have been deemed eligible by echocardiography, even if, according to CMR they would not be eligible, resulting in patients receiving ICD therapy although not necessary. A sensitivity analysis for subjects with CMR EF < 50% showed an increase to 13.8% for subjects who had EF < 35% as observed by CMR, and who would have been classified as eligible for an ICD, even if according to echography they did not need it, while 4.6% would have been deemed eligible by echocardiography, even if, according to CMR they would not be eligible.The observed agreement between CMR and echocardiography regarding the identification of subjects with EF <= 35, and thus eligible for an ICD are presented in p < 0.001, while the bias-adjusted Kappa, and the prevalence-and-bias-adjusted Kappa were 0.65 and 0.71, indicating a statistically substantial agreement. As in the other threshold, 11.3% of the subjects would have been considered eligible for an ICD using CMR, even if according to echography they did not need it, while 3.3% would have received an ICD according to echography, even if they would have not need it according to CMR , g to CMR . A sensiIn the present study, we managed to assess the agreement of 2DE and CMR performed in patients with NICM regarding the assessment of LVEF, EDV and ESV, and then we compared the agreement of the two methods for initiation of ICD based on the classical LVEF cutoffs.Regarding Bland–Altman analysis, the main findings were as follows: there were important measurement differences, as observed in the bias, between CMR and echocardiography regarding EDV LV, ESV LV; there were smaller measurement differences regarding LVEF; the limits of agreement were large for EDV LV, ESV LV, and LVEF; the measurements differences had high heterogeneity for EDV LV and ESV LV, while for LVEF were homogeneous. These results imply that echocardiography measurements had important differences compared to CMR in assessing the left ventricle dimensions, even if it is the largest structure of the heart . If we cn = 12), and respectively, 11.3% (n = 17) of the subjects would have not received implantation based on echocardiography findings even they should have according to CMR findings. Moreover, 2.6% (n = 2), and respectively, 3.3% (n = 5) of the subjects would have received ICD implantation based on echocardiography findings even if it was not the case based on CMR findings. These findings are worrisome since both overestimation of the need for implantation and especially the underestimation of the need for implantation, can have serious results, in addition to problems of cost and inconvenience.To further dwell on this problem, we explored how these measurement issues of echocardiography compared to CMR would influence ICD eligibility. Thus, we checked the agreement of identifying subjects with EF at two thresholds used for ICD eligibility, namely 35% and 30%. Although the agreement was substantial , having values between 0.6 and 0.8 , the agreement was not perfect, which it is required to be for assessing the eligibility for an intervention that can increase the quality of life and also might be lifesaving . This imIn the study conducted by Joshi et al., at the EF threshold of 35%, CMR reclassified 21% of patients referred for an EF or ICD assessment. At the EF threshold of 30%, CMR reclassified 9.6% of patients. Their findings are in the same direction as our study but with higher values  in the aThere are studies that have found a similar result to our study , that atThe present study found a smaller disagreement—and thus reclassification (10.5% and 14.6%)—compared to the findings observed by Joshi et al. , who ideSince 2D echography incorrectly dictates eligibility compared to CMR, one way to continue to use it but with fewer errors might be to use a higher threshold for 2D, so that patients that need an ICD will not be incorrectly deemed as ineligible. However, several studies are arguing that the current guideline cutoff value of <= 35% should be lowered to <= 30 ,27. Thus3D echocardiography underestimates volumes in most patients because it cannot differentiate between compact myocardium and trabeculae. However, recently, a new generation of fully automated software based on an adaptive analytics algorithm has been conceived for left heart-chamber quantification. This novel technology appears feasible, fast, and reproducible. Furthermore, automated default border detection based on the compact myocardium with operator’s adjustments has shown an excellent agreement with cardiac CMR .A study conducted by Gaibazzi et al. , showed In addition, as shown in another study conducted by Gaibazzi et al. , the preThus, the future diagnostic method for ICD eligibility would be most probably debated between CMR and 3D echography, and not 2D echography.However, CMR is gradually becoming more accessible and faster, and breath-hold acquisition sequences now require significantly less time. Furthermore, there are studies  suggestiThis study is representative to the majority of hospitals that deal with various types of cardiomyopathies and that are not usually specialized centers of ICD therapy. In an ICD center, the percentage of reclassifications would be higher than those found in our study, since we had a fair number of subjects with normal EF.The present study was not designed to assess the real impact of CMR, but to explore its potential impact. Only randomized clinical trials can assess the long-term effect of using echocardiography or CMR for ICD eligibility. Nevertheless, this study signals a situation with far-reaching clinical implications for cardiomyopathy patients.Some of the inherent limitations of transthoracic 2DE are image-plane positioning errors, foreshortening of the LV long axis, geometric assumptions, and cardiac translation .The time between the two investigations was about 3 days, with a maximum of 5 days, which could explain some of the variability between the two measurements. Nevertheless, the time between the interventions was short, and there were no important treatments (coronary revascularization or cardiac resynchronization) that could have influenced the measured variables.We did not assess intra and inter-observer variability for CMR-LVEF, but other studies have shown that the interclass correlation coefficient for this measurement are very high .First, in terms of the number of subjects, this article is distinguished by a larger cohort compared to other studies that have chosen to address this topic ,24,26.Second, the present study used a more appropriate method to assess the bias and limits of agreement in the Bland–Altman framework, compared to other studies in the literature, since it used nonparametric methods for these estimations ,16.Third, LVEF assessments by 2DE were evaluated by multiple readers (the physicians that were treating their patients) who were unaware of the study objectives, a setting much closer to the common clinical practice—a pragmatic approach. This is an important point, since the results of this study are more generalizable to the current practice in hospitals, where those who perform echocardiography have different experiences.The present study provides further support for a more refined choice of ICD therapy in patients with NICM. The technique used to measure LVEF in patients being considered for ICD therapy can have paramount clinical importance in the treatment, quality of life, and outcomes of patients. The debate is still open between a growing number of candidates: CMR, 3D echography, new 2D echography techniques. Future trials can solve this dilemma, although they have to enroll large cohorts of patients in order to have enough power to observe significant differences. Still, the increase in accuracy in measuring EF is advisable due to the price associated with ICD implantation .2D echocardiography measurements have important differences when compared to CMR, especially when assessing EDV LV and ESV LV, and smaller differences when assessing LVEF. The limits of agreement are clinically important for all the four measurements. The agreement between echocardiography and CMR in recommending an ICD based on commonly used thresholds of 35% and 30% is not perfect, resulting in both overestimation of the need for implantation and especially the underestimation of the need for implantation. These can have serious implications on the outcomes of patients that are assessed for eligibility for an intervention, with implications on the quality of life and the prevention of death events. The present study suggests that 2D echocardiography is not a suitable method for the assessment of LVEF for ICD eligibility. Of course, clinical trials would be warranted to further check which assessment method will lead to improved outcomes for patients.