Early identification of high-risk pregnancies enables identification of those who would benefit from aspirin prophylaxis and increased surveillance for pre-eclampsia. A high body mass index (BMI) is a well-known predictor for pre-eclampsia. However, if abdominal adipose tissue distribution is associated with pre-eclampsia is limited investigated. Subcutaneous adipose tissue (SAT) thickness and visceral adipose tissue (VAT) thickness were measured by ultrasound on 3777 women at around 18 gestational weeks. SAT thickness was measured from the skin to linea alba and VAT from linea alba to the anterior aortic wall. The risk of developing pre-eclampsia  was evaluated by logistic regression and expressed as odds ratio (OR) with 95% confidence intervals (CI). The risk of pre-eclampsia increased by 79% for every cm in SAT thickness  and by 23% for every cm VAT thickness . After adjustment for maternal age, parity, BMI, smoking and country of birth, the association between SAT thickness and pre-eclampsia remained . Greater SAT thickness measured with second trimester ultrasound is associated with increased risk of developing pre-eclampsia. The measurement may improve prediction models for pre-eclampsia. Identification of women with high risk for pre-eclampsia in early pregnancy enables aspirin prophylaxis and individual surveillance, which may lead to earlier detection of the disorder4. Many risk factors for developing pre-eclampsia have been described, one of those is obesity6. Currently, about one-third of women of reproductive age in the USA are obese7 and the global obesity epidemic is a target for the United Nations third Sustainable Development Goal8. Identifying those with the highest risk of pregnancy complications among obese women is therefore important.Pre-eclampsia complicates about 3–8% of pregnancies10. However, some studies state that VAT is a stronger indicator than SAT11. In the general population VAT/SAT ratio has been shown to be a predictor for cardiac events.The obesity definition is based on body mass index (BMI), which does not consider muscle mass and adipose tissue distribution. Studies on adipose tissue distribution in the general population show that both subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) are associated with metabolic risk factors such as blood pressure, fasting plasma glucose, and high-density lipoprotein cholesterol13. Measurement of VAT and SAT with ultrasonography is a potential alternative; it is non-invasive, considered as low-risk for both mother and foetus, and compares well with the gold standard CT measurement15.Several methods can be used to estimate adipose distribution. Of those, computed tomography (CT) and magnetic resonance imaging (MRI) seem to provide the best estimation of visceral fat22. To our knowledge, only three studies have investigated the association of abdominal adipose tissue distribution estimated by ultrasound and risk of hypertensive disorders in pregnancy23, whereof only one studied pre-eclampsia specifically23 and all study populations were comparatively small.Ultrasound measurements of abdominal adipose tissue distribution during pregnancy have only been performed in small seriesOur aim in this population-based study of around 4000 women was to investigate if the ultrasonically assessed adipose tissue distribution could be used as a predictor for developing pre-eclampsia later during pregnancy.24 explained this, that as long as a register-based study is deemed ethical by committee, it is assumed that the participants do not object to the research.For this prospective cohort study we included women who did their routine second trimester foetal ultrasound scan at Uppsala University hospital between January 2015 and January 2019. We obtained ethical approval to implement SAT and VAT measurements in conjunction with the ultrasound examination and to evaluate the usefulness of the measures by linkage to standardized hospital electronic medical records on maternal, obstetric, and perinatal health care. Following linkage, the study population database was anonymized. The Regional Ethical Review Board in Uppsala approved the study on September 24th 2014 (Dnr: 2014/353). All research was performed in accordance with relevant national and international guidelines. Informed consent was waived by the Swedish Ethical Review Authority (Dnr: 2019-00391). As the study was register-based with anonymized data this was not required. In general, large register-based studies in Sweden do not require informed consent. Ludvigsson et al.All pregnant women in Sweden are invited to the routine second trimester foetal ultrasound scan at 17–19 weeks of gestation. In Uppsala County, all obstetric ultrasound scans are performed at Uppsala University Hospital, which also holds the only delivery ward within the county. Hence, the women included represent a population-based sample. Women were eligible for the study if they had an appointment with one of the certified obstetric ultra-sonographers who had been trained on the SAT and VAT measurement, see further below, and if they accepted participation (n = 4030). We excluded women where the measurements were not possible to perform because of lack of visualisation of the rectus musculature (n = 12), women we could not link with the hospital electronic medical records because of temporary or confidential medical records (n = 11), women with late miscarriage (n = 4), and 191 women who moved during the study time or did not give birth in Uppsala. Further, we excluded women with chronic hypertension (n = 9), pre-pregnancy diabetes type 1 or 2 (n = 22) or systemic lupus erythematosus (n = 4), all known risk factors for pre-eclampsia. The final study population consisted of 3777 pregnant women, Fig. 25. Additional training sessions were carried out during the study period to maximize the quality of the scans. The ultrasound measures were taken 10 cm above the level of the umbilicus. The SAT thickness was measured from the inner border of the skin down to linea alba, the midline connecting part between the abdominal rectus musculature. The VAT thickness was measured from the posterior edge of the linea alba to the anterior aortic wall, Fig. 26. The VAT and SAT thickness ratio (VAT/SAT) was then calculated from the measurements. We chose to estimate the increased risk of pre-eclampsia for every centimetre (cm) increase in adipose tissue thickness instead of every millimetre (mm) increase. Reporting in mm overstates the exactness of the ultrasound measurement and the use of cm produces a result that is understandable and communicable to physicians and patients.The SAT and VAT thickness measures were performed by certified obstetric ultra-sonographers, using Voluson E6, E8 or E10 GE ultrasound machines . The certified obstetric ultra-sonographers had been specifically trained to perform the adipose tissue measurements according to the method described by Armellini and colleaguesThe main outcome was pre-eclampsia defined as de novo hypertension after 20 weeks of gestation in combination with proteinuria, which was the clinical definition of the disorder in Sweden during the study period. Hypertension was defined as systolic blood pressure of ≥ 140 mmHg and/or diastolic blood pressure of ≥ 90 mmHg measured on two subsequent occasions, at least 6 h apart. Proteinuria was defined as ≥ 2 + on a dipstick or ≥ 300 mg/24 h in a urine collection. During the study period, women with one of the following major risk factors were recommended 75 mg aspirin from gestational week 12: history of severe or preterm pre-eclampsia in earlier pregnancy, chronic kidney disease, diabetes mellitus with known vascular complications or autoimmune disease such as systemic lupus erythematosus with anticardiolipin antibodies.2) was calculated. The women were classified as underweight (BMI < 18.5 kg/m2), normal weight (BMI 18.5–24.99 kg/m2), overweight (BMI 25–2.99 kg/m2) or obese (BMI > 30 kg/m2). Comorbid diseases included rheumatic diseases (yes/no) and inflammatory disorders (yes/no). Clinical variables and outcomes included gestational length in days at delivery. Gestational length was categorized into preterm  or term  birth. Birthweight was measured in grams. Further, we recorded if the infant was born small for gestational age (SGA), defined as birth weight below the third percentile, according to the Swedish sex-specific reference curves for gestational age27, or large for gestational age (LGA) as above the 97th percentile.Information about maternal demographic and clinical variables, pregnancy complications and perinatal outcome was obtained via linkage with the standardized hospital electronic antenatal, obstetric and neonatal medical records. Demographic data collected at the first antenatal visit included: maternal age, parity, early pregnancy BMI, self-reported smoking habits (yes/no), country of birth (born inside EU/born outside EU), pregnancy conceived by assisted reproduction, and present comorbid diseases. The women’s weight in kg and height in cm were measured and recorded at the first antenatal booking, and BMI , BMI (as a continuous variable), country of origin (born in the European Union or born outside the European Union), self-reported smoking at the beginning of pregnancy (yes/no) and parity (as a continuous variable) in our adjusted model. All of these variables are known risk factors for developing pre-eclampsia3, except smoking which is inversely associated with pre-eclampsia29, and also related to increased abdominal adipose tissue33. For all the statistical analyses, we used IBM SPSS Statistics, version 25.We determined the risk of developing pre-eclampsia by use of logistic regression analysis, with SAT and VAT thickness as well as VAT/SAT ratio expressed in centimetres as predictors. We estimated unadjusted and adjusted odds ratios (OR) with their corresponding 95% confidence intervals (CI). To identify possible confounders, we drew a directed acyclic graph (DAG), supplementary Fig. 1The study population is described in Table r = 0.68, p < 0.001, Fig. r = 0.46, p < 0.001, Fig. BMI was highly and positively correlated with SAT thickness, 2 vs. 25.0 ± 4.9 kg/m2. Women with higher BMI had an increased risk of developing pre-eclampsia, OR 1.08 (95% CI 1.06–1.12), p < 0.001.Women who developed pre-eclampsia had higher BMI than those without pre-eclampsia, 27.5 ± 6.5 kg/mp < 0.001. Similarly, greater VAT thickness was noted in women with pre-eclampsia 4.75 ± 1.79 cm, compared to women without pre-eclampsia 4.16 ± 1.63 cm, p < 0.001.Women with pre-eclampsia had a SAT thickness of 2.04 ± 0.89 cm, whereas the corresponding measure in women without pre-eclampsia was 1.65 ± 0.73 cm, Women with greater SAT thickness more often developed pre-eclampsia, OR 1.79 (95% CI 1.48–2.17), i.e. with every centimetre increase in SAT thickness, the risk of pre-eclampsia increased by 79%. Greater VAT thickness was also associated with increased risk of developing pre-eclampsia, OR 1.23 (95% CI 1.11–1.35), suggesting that every extra centimetre VAT thickness increased the risk by 23%. After adjustment for confounders, the association between SAT thickness and pre-eclampsia remained, AOR 1.35 (95% CI 1.02–1.79), but no longer remained significant for VAT thickness; AOR 1.11 (95% CI 0.99–1.24), Table When the analyses were repeated after excluding all women treated with prophylactic aspirin, the estimates were only marginally changed for both SAT and VAT. The association between SAT thickness and risk of pre-eclampsia was OR 1.80 (95% CI 1.48–2.19), with AOR 1.34 (95% CI 1.00–1.79), including adjustment for BMI. The corresponding associations between VAT thickness and pre-eclampsia were OR 1.21 (95% CI 1.09–1.33), and AOR 1.09 (95% CI 0.97–1.22).Women with pre-eclampsia had a VAT/SAT ratio of 2.69 ± 1.60, whereas the corresponding ratio in women without pre-eclampsia was 2.94 ± 1.71. Greater VAT/SAT ratio was not associated with increased risk of developing pre-eclampsia, OR 0.90 (95% CI 0.80–1.02), AOR 0.99 (0.88–1.12).Our study shows that increased abdominal adipose tissue thickness in pregnancy is associated with development of pre-eclampsia. This association was stronger with SAT than VAT thickness, and the association remained significant after adjustment for confounders, including BMI.23; it included 463 pregnant women, and only VAT was measured. Their results were similar to ours, with significant association between VAT and pre-eclampsia only in unadjusted models. The studies of Nassr et al. and Kennedy et al. both studied hypertensive disorders in pregnancy as an outcome. Nassr et al.21 used another ultrasound method of estimating SAT and VAT compared to our study and included only 389 women. They found that both SAT and VAT were associated with the development of hypertensive disorders in pregnancy, using specific cut-off values for SAT and VAT. In our study, we did not find an association between VAT and pre-eclampsia. This discrepancy might depend on the different methods used to estimate VAT and to difference in risk estimation as we used continuous measurement on VAT instead of cut-off values. In the study of Nassr et al., most women developed gestational hypertension, not pre-eclampsia, two disorders with partly different pathophysiology and clinical outcomes35. Our results are consistent with the previous report of Kennedy et al.16, including 1510 pregnant women, showing that SAT thickness is a BMI-independent predictor for pregnancy hypertensive disease. Compared to all three former reports, our study population was more homogenous since we excluded women with twin pregnancies and some chronic disorders known as risk factors for pre-eclampsia.To our knowledge, there are only three earlier studies that have measured SAT or VAT thickness during the first half of pregnancy and estimated the association with risk of hypertensive disorders in pregnancy. Altogether, our results are in agreement with these reports. Only one has studied pre-eclampsia specificallyTo our knowledge, there are no studies on VAT/SAT ratio and association with pre-eclampsia. In our study VAT/SAT ratio was not associated with increased risk of pre-eclampsia, indicating that the ratio between different kinds of adipose tissue is not of great relevance, but rather that the adipose tissue thickness itself is the driving factor.6. The literature suggests that metabolic abnormalities may be a large part of the causal pathway between obesity and pre-eclampsia36. Since both SAT and VAT thickness are correlated with metabolic risk factors11, it is not unlikely that central obesity in early pregnancy can be a part of the link between obesity and risk of developing pre-eclampsia. We had anticipated that VAT thickness would be a better predictor for pre-eclampsia than SAT thickness, as studies in non-pregnant populations indicate that VAT is a stronger indicator for metabolic risk factors11. In addition, during early pregnancy, VAT seems to correlate stronger to the same metabolic risk factors than SAT21. Ageing is associated with an increase in fat deposition, especially in the visceral area37. As pregnant women are comparatively young, deposition to visceral areas may yet not have started. This might explain why SAT thickness seemed to carry stronger association with pre-eclampsia than VAT thickness.The exact causal pathway between obesity and pre-eclampsia is poorly understood, but both have several pathophysiological alterations in common, such as oxidative stress, inflammation and endothelial dysfunctionThe main strength of our study is the large homogenous study population of 3777 pregnant women and the population-based design. This is, to our knowledge, one of the largest studies with adipose tissue measurements during pregnancy. Further, in comparison with previous efforts, we specifically studied pre-eclampsia. We also measured both SAT and VAT in the same study population and estimated the ratio between the estimates, which has not been done before in pregnant women. We used a validated method to estimate SAT and VAT, a method that is easy to implement in routine ultrasound scans during the first half of pregnancy.38. According to our results, the variation in SAT and VAT measurement for any given BMI was greater than expected. Armellini et al.14 showed that the correlation between ultrasound and CT was in the range of 0.68–0-74. However, the gold standard methods for measuring abdominal adipose tissue are not acceptable during pregnancy for safety reasons. The variability can be partly explained by measurement errors, although all ultra-sonographers performing the measurements were certified and highly skilled. A possible explanation for this variation is a difference in body composition of the young study population, where some individuals have a high proportion of muscle mass, and some a greater proportion of adipose tissue, which BMI does not accurately reflect.Several limitations in our study are important to mention. Although our study population is relatively large, only 138 women developed pre-eclampsia, of whom 22 developed preterm pre-eclampsia. Therefore, we could not reach power to evaluate the association between adipose distribution in early and late pre-eclampsia. Another major limitation is that we performed the adipose tissue measurement at gestational weeks 17–19, instead of earlier in pregnancy. However it has been shown that abdominal adipose tissue distribution changes in the third trimester when compared to both first and second trimester, but those changes are not seen between first and second trimester40, but not term pre-eclampsia41. The greatest challenge is to identify women who will benefit from aspirin treatment, without over-treating. It is therefore of great importance that the identification of high-risk women for pre-eclampsia is predicted before the end of the first trimester. We also did not have information about history of pre-eclampsia in earlier pregnancies, which is one of the strongest risk factors for developing pre-eclampsia in multiparous women42. However, women with a history of severe or early pre-eclampsia were routinely recommended aspirin. In a sensitivity analysis excluding women on aspirin prophylaxis, the association between SAT and risk of pre-eclampsia remained.Today prediction and prevention of pre-eclampsia have gained great attention, both in research and clinically. Aspirin treatment starting at gestational week 16 or earlier in women at high risk for preterm pre-eclampsia, reduces the risk for preterm pre-eclampsia43. Finneran et.al. published 2019 a study on the association of obesity on platelet-derived thromboxane inhibition in high-risk women treated with low-dose aspirin. Their data suggested that an increase in aspirin dosing or frequency may be necessary in the obese population44. Other studies, such as the one by Cantu and collage, have shown no difference in the efficiency of low-dose aspirin between obese and non-obese women45. Further research is needed to evaluate if SAT and VAT measurements would contribute to risk assessment model in order to identify obese women who would benefit from prophylactic treatment with aspirin.An important issue in need of further research is aspirin prophylaxis in the obese population for pre-eclampsia prevention. Evidence suggests that aspirin may be less effective in the general obese population, and there are several potential mechanisms behind thisHigh BMI is a common risk factor in all prediction methods for pre-eclampsia, and our results show that an increase of BMI by one unit increases the risk of pre-eclampsia by 8%. Further studies are needed to investigate the potential role of SAT and VAT thickness in the first- or early second trimester. Prediction models for pre-eclampsia used today need to improve their prediction performance. Adding SAT measurement to such a model might be the next step. As most prediction models for pre-eclampsia today address risk factors as continuous measurements, we find it important to address adipose tissue measurements as a continuous variable. The method used to estimate adipose tissue thickness has the potential to be effective, quick and highly cost-effective.In conclusion, our study shows that greater SAT thickness measured with ultrasound in early second trimester is associated with an increased risk of developing pre-eclampsia later in pregnancy.Supplementary Figure 1.


Participants in TG-WC group had the highest BMI, WC, blood pressure (BP), insulin, Homeostatic Model Assessment of Insulin Resistance (HOMA-IR), glycosylated hemoglobin (HbA1c), low-density lipoprotein cholesterol (LDL), and fatty liver. Participants within N-WC group had a significantly higher risk of fatty liver (adjusted OR 3.50 [95% CI 2.05–5.97]), as well as TG-N (adjusted OR 2.59 [95% CI 1.61–4.16]) and TG-WC (adjusted OR 4.12 [95% CI 2.28–7.46]). The risk of elevated HOMA-IR was significantly higher in TG-N (adjusted OR 2.16 [95% CI 1.33–3.50]) and TG-WC (adjusted OR 2.04 [95% CI 1.22–3.40]). The risk of elevated HbA1c was significantly higher in the TG-WC (adjusted OR 2.79 [95% CI 1.47–5.31]). Hypertriglyceridemic waist phenotype can be a potential and cost-effective method to identify individuals with a high risk of fatty liver and glycometabolic disorders.The present study aimed to distinguish different hypertriglyceridemic waist phenotypes and relevant risks of developing fatty liver and abnormal glycometabolic profiles in overweight/obese adults. A total of 1221 Chinese adults with mean (standard deviation [SD]) age of 37 (9) years, 37.3% males and 62.7% females, body mass index (BMI) of 29.0 (4.0) kg/m It has also been speculated that there is less effectiveness and more risk following vaccination in preventing 2019 novel coronavirus among obese individuals3. These remind us that obesity and diabetes have brought pathophysiological changes to the biological systems of the human body. Therefore, there is a high priority to develop specific phenotypes of obesity and diabetes to better assess the risks and efficient screening, and to further engage patients into individualized treatments.The COVID-19 pandemic has re-focused the adverse effects of obesity and diabetes on the general health status of individuals. There are growing concerns that patients with obesity and diabetes are more likely to have severe evolution and mortality during the COVID-19 pandemic4. The complexity of phenotypes may contribute to some of the variations in symptomatic outcomes of diabetes, fatty liver, and mortalities related to obesity. Obesity, especially increases in visceral fat deposits, have been recognized as one of the leading causes of all metabolic risk factors5. However, overweight/obese individuals with similar levels of adiposity measured by body mass index (BMI) or waist circumference (WC) can display different metabolic profiles characterized by lipid, insulin, and glucose concentrations6. Insulin resistance has elucidated most of the pathophysiology of the metabolic syndrome with a significant contribution to hyperglycemia7. Furthermore, a major contributor to the development of insulin resistance is an overabundance of circulating fatty acids mainly derived from triglyceride8. Hence, the main factors to identify high risks of obesity and diabetes are visceral fat and abnormality in triglyceride concentrations.Heterogeneous subgroups among the overweight/obese based on phenotypic differences for metabolic risk factors have been observed previously9. Previous studies conducted with overweight/obese populations, found a higher risk of diabetes in such phenotype among the elderly12. It was also suggested that hypertriglyceridemic waist was more prevalent in young and middle-aged adults10. Fatty liver is considered to be a hepatic injury associated with the metabolic syndrome in parallel with obesity and diabetes13. The prevalence of fatty liver has continued to grow in recent years. Most of the patients with fatty liver disease are asymptomatic and ignored. The diagnosis of fatty liver is complicated and is depended on abnormal imaging results and liver enzyme activity following biopsy examinations, which are also expensive and invasive14. The association between the hypertriglyceridemic waist phenotype and fatty liver disease needs further scientific investigation.The hypertriglyceridemic waist phenotype is characterized by the simultaneous presence of elevated serum triglyceride (TG) levels with an increased WC. Hypertriglyceridemic waist phenotype has been proposed as a cost-effective method of screening in clinical practice to overcome the major barriers of the high cost of measuring visceral adiposity and insulinThe purpose of this study was to distinguish the relationships between the hypertriglyceridemic waist phenotype and the risk of developing fatty liver and associated abnormal glycometabolic profiles in overweight/obese adults. It was hypothesized that the hypertriglyceridemic waist phenotype could be associated with a high prevalence of fatty liver and glycometabolic disorders.2)15; (4) no history of severe diseases in the major organs  and no secondary obesity by self-report; (5) not using medications that might impact the measurements obtained in the current study. These included lipid-lowering drugs, hypoglycemic agents, and antihypertensive medications.Participants were recruited by convenient sampling via fliers posted and distributed in local urban communities of the Haidian District, Beijing, China, from April to May 2014. Inclusion criteria were: (1) resided locally for a continuous period of not less than 1 year; (2) 20–55 years; (3) a nutritional status of overweight  by self-report. Physical activity and sedentary time  were also recorded for all participants. The study was approved by the Ethical Committee for the Use of Human and Animal Subjects in Research by the local university ethics committee (IRB00001052-130 86). Subjects were fully informed about the purpose and constraints of this study prior to data collection, and all participants provided their written informed consent.Following initial screening, every participant underwent a physical examination including anthropometric measurement, assessment of biomarkers (lipids and glycometabolic profile) from venous blood samples, and ultrasonography to diagnosis fatty liver. The protocol used has been outlined previously in detail2, obesity as BMI ≥ 28.0 kg/m215.Participants were instructed to stand up-right in a vertical position in bare feet, wearing light clothing for all anthropometric measures. Weight was measured with a lever scale  to the nearest 0.1 kg; height with a stadiometer  to the nearest 0.1 cm. BMI was calculated as weight in kilograms divided by height in meters squared. Overweight was defined as 24.0 ≤ BMI < 28.0kg/m18.WC was measured at the midpoint between the lowest rib and iliac crest with a Myo Tape measuring tape  to the nearest 0.1 cm, at the hipline at the widest part of hips. High WC was defined as ≥ 102.0 for males and ≥ 88.0 cm for femalesBP was measured in a seated position following 5 min of rest with a clinical sphygmomanometer  and a stethoscope  to the nearest 1 mm Hg. High BP was defined as systolic BP (SBP) ≥ 140 and/or diastolic BP (DBP) ≥ 90 mmHg.18, high glucose as ≥ 5.6 mmol/L19 and high HbA1c as ≥ 6.5%21.All participants were overnight fasted for 8–12 h prior to a venous blood draw in the morning. TG, total cholesterol (TC), high-density lipoprotein cholesterol (HDL), low-density lipoprotein cholesterol (LDL), and glucose were measured using commercial assay kits  by a spectrophotometer , as well as glycosylated hemoglobin . High TG was defined as ≥ 1.71 mmol/L22. Briefly the calculation was HOMA-IR = blood glucose (mmol/L) × insulin (mU/L)/22.5.Insulin was measured using the radioimmunoassay technique . The Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) index was calculated as outlined previously23.High HOMA-IR was defined as ≥ 3.1924.Real-time ultrasonography  was used to identify fatty liver. Fatty liver was diagnosed according to the criteria of the presence of at least 2 of 3 abnormal findings in the abdominal area: (1) diffusely increased echogenicity liver (bright liver with its echogenicity greater than the kidney); (2) vascular blurring; (3) gradual attenuation of ultrasound echoParticipants were classified into four phenotypes (1) G1: N-N, normal TG & normal WC; (2) G2: N-WC, normal TG & high WC; (3) G3: TG-N, high TG & normal WC; (4) G4: TG-W, high TG & high WC.p < 0.05 was the level set for statistical significance.Data were analyzed using IBM SPSS for Windows . Continuous variables were expressed as mean (standard deviation [SD]) and categorical variables as n (percent%). One-way analysis of variance and chi-square tests were used for the comparison of continuous variables and categorical variables among the four phenotypes. Logistic regression models were used to analyze the association between phenotypes and risk of fatty liver or glycometabolic profiles, while odds ratio (OR) with 95% confidence intervals (95% CI) in different models were calculated. Model 1 was a crude model without adjustment, Model 2 was adjusted for age, sex, and BMI, and Model 3 was further adjusted for smoking, alcohol consumption, physical activity, and sedentary time. Following control of potential confounders, the association was further explored by subgroup analysis, which was stratified based on sex , BMI (overweight or obesity), and BP , using the normal TG and WC group as a reference. Two-tailed All procedures performed in the present study were in accordance with the Declaration of Helsinki and were approved by the Medical Ethical Committee of the Peking University Health Science Center (IRB00001052-13086). The author obtained permission to use the dataset from Institute of Child and Adolescent health, Peking University and the secondary analysis of the dataset without identifiable information was approved by the Ethical Committee of Hunan Normal University (NO.2019-88). Before the formal investigation, written informed consent to participate in the study was obtained from all participants. Also, all participants had the right to withdraw from the study at any time and for any reason.2, TG 2.04 (1.45) mmol/L, WC 95.8 (10.7) cm, and the prevalence of fatty liver was 74.3% totally. Table Finally, 1221 participants were involved in the current study. General characteristics were as follows: mean (SD) age of 37 (9) years, n (percent%) of 455 (37.3%) males and 766 (62.7%) females, BMI 29.0 (4.0) kg/mAs shown in Table As shown in Fig. In the current cross-sectional study, we found that the hypertriglyceridemic waist phenotype was independently associated with a 4.1-fold higher risk to develop fatty liver, twofold increased insulin resistance, and 2.8-fold elevated HbA1c than those with normal TG and WC in Chinese overweight/obese adults. We further observed that the relevant risks associated with the hypertriglyceridemic waist phenotype could be 1.9- to 6.4-fold higher especially in females, the overweight, and non-hypertensive subgroups. The phenotype for high TG but normal WC, was associated with 2.6- and 2.2-fold high prevalence of fatty liver and insulin resistance. The strength and novelty of this study was the finding that the hypertriglyceridemic waist phenotype was a cost-effective screening tool for fatty liver and diabetes identification among overweight/obese adults.9. This phenotype has been widely accepted in risk assessment or prediction of high visceral fat25, diabetes26, hypertension27, metabolic syndrome28, atherosclerosis29, cardiovascular diseases30, and renal dysfunction31. All these results support that the hypertriglyceridemic waist phenotype is a cost-effective screening tool that can be used in clinical practice and is an efficient and effective phenotype that can be used for health management. However, the application of this phenotype in the identification of fatty liver disease is still limited. Previously, a cross-sectional study focusing on children/adolescents found that hypertriglyceridemic waist phenotype was related to non-alcoholic fatty liver disease32. In the adult population, Liu et al. demonstrated that phenotypes combining TG and BMI were a better indicator of fatty liver disease among premenopausal women, and that WC alone was associated with the disease in postmenopausal women33. This finding was also supported by Yu et al. who observed that the hypertriglyceridemic waist phenotype was significantly associated with a higher risk of abnormal liver function in Chinese adults34. In our study population, overweight/obese adults suffered from visceral adiposity and glycometabolic disorders, that are conditions closely linked to fatty liver disease35. Interestingly, during the subgroup analysis, the identification ability of hypertriglyceridemic waist phenotype for fatty liver and abnormal glycometabolic profile was less effective in the obese and hypertension subgroups. We speculate that lower heterogeneities and small sample size may have contributed to the decrease in predictive validities.The concept of the hypertriglyceridemic waist phenotype was first proposed by Lemieux et al. based on the evidence that high TG or WC alone were inadequate to identify the metabolic triad36. In our study, following adjustment for potential confounders, the risk of high glucose was not significantly different for phenotypes. This may be the result of the regulation of β cells. At the early stage of insulin resistance, β cells can increase secretion to maintain normal glucose tolerance37. Elevated blood glucose can appear when β cells cannot release sufficient insulin. Further to this, some of the studies concentrated on the hypertriglyceridemic waist phenotype and levels of HbA1c, but there were no studies that demonstrated a specific association between phenotypes39. The findings of this study demonstrate that the hypertriglyceridemic waist phenotype was associated with a high level of HbA1c concentration especially in the overweight and normal BP populations.We also found an association between hypertriglyceridemic waist phenotype and insulin resistance, which was in agreement with some of the previous studies that investigated abnormal glucose metabolism in female, overweight, and normal subgroups. A meta-analysis concluded that participants with the hypertriglyceridemic waist phenotype had more serious insulin resistance problems and higher glucose concentrations34. Referring to the diagnosis of fatty liver, imaging results and liver enzyme activity following biopsy examinations, which are gold standard, were not used in the current study. In addition, we were not able to categorize non-alcoholic fatty liver disease which might lead to a bias in the findings. However, we included alcohol as a confounder, and the associations were persistently significant. The target population in our study was Chinese overweight/obese adults, which may not represent normal weight adults and different populations. The clinical relevance of our findings, while exciting, need further experimental investigation using larger population samples and sub group analysis.There are several limitations in the current study that need consideration. A relatively small sample size and wide confidence intervals around the estimates of associations may have resulted in low predictive ability within the subgroups of the males, the obese, and the hypertensive. It can also be speculated that there was relatively low sensitivity and specificity of the hypertriglyceridemic waist phenotype in the Chinese population sampled due to the relatively low TG and WC observedThe hypertriglyceridemic waist phenotype was associated with risks of developing fatty liver and glycometabolic disorders in overweight/obese Chinese adults especially in female, overweight, and non-hypertensive subgroups.


Tapering or stopping biological disease-modifying anti-rheumatic drugs has been proposed for patients with rheumatoid arthritis (RA) in remission, but it frequently results in high rates of recurrence. This study evaluates the efficacy and safety of tacrolimus (TAC) as maintenance therapy in patients with established RA in remission after receiving combination therapy with tumor necrosis factor inhibitor (TNFi) and methotrexate (MTX).This 24-week, prospective, open-label trial included patients who received TNFi and MTX at stable doses for ≥24 weeks and had low disease activity (LDA), measured by Disease Activity Score-28 for ≥12 weeks. Patients selected one of two arms: maintenance (TNFi plus MTX) or switched (TAC plus MTX). The primary outcome was the difference in the proportion of patients maintaining LDA at week 24, which was assessed using a logistic regression model. Adverse events were monitored throughout the study period.In efficacy analysis, 80 and 34 patients were included in the maintenance and switched arms, respectively. At week 24, LDA was maintained in 99% and 91% of patients in the maintenance and switched arms, respectively . Drug-related adverse effects tended to be more common in the switched arm than in the maintenance arm  but were well-tolerated.This controlled study tested a novel treatment strategy of switching from TNFi to TAC in RA patients with sustained LDA, and the findings suggested that TNFi can be replaced with TAC in most patients without the patients experiencing flare-ups for at least 24 weeks.KCT0005868. Registered 4 February 2021—retrospectively registeredKorea CDC CRIS, The online version contains supplementary material available at 10.1186/s13075-021-02566-z. Rheumatoid arthritis (RA) is an autoimmune disease with progressive joint damage and deformities, eventually resulting in functional disability . Due to Given the recent updates on RA management, we can consider tapering TNFi by dose reduction or prolonged intervals when the treatment is combined with conventional synthetic DMARDs (csDMARDs) . The lonIt is unclear whether TNFi can be discontinued when RA flare-ups can be prevented by adding csDMARDs. Tacrolimus (TAC) is an immunosuppressant previously used to prevent rejection following organ transplantation and to treat autoimmune diseases, such as lupus nephritis and myasthenia gravis . It is eTNF agents versus tacrolimus as maintenance therapy in rheumatoid arthritis patients of inactive state receiving methotrexate concomitantly” (TROPHY) study was a prospective, multicenter, non-randomized, active control, parallel group, 24-week trial. The study compared two therapeutic strategies, maintaining TNFi and switching to TAC following sustained LDA with TNFi (at least 6 months), at nine institutes in South Korea between November 18, 2012, and November 20, 2017. The primary objective was to evaluate the feasibility of switching from TNFi to TAC as maintenance therapy in RA patients with stable LDA following combination therapy with TNFi and methotrexate (MTX). The study protocol was approved by the Institutional Review Board of each participating institution. The study was conducted in accordance with the Korean Good Clinical Practice guidelines and the Helsinki Declaration. Written informed consent was obtained from all participants.The “Anti-Eligible patients were 20–70 years of age with established RA (≥ 12-month duration) according to 2010 American College of Rheumatology (ACR)/European League Against Rheumatism (EULAR) criteria . The folPatients who received DMARDs other than MTX and three TNFi within 4 weeks of screening were excluded. The use of oral glucocorticoids ≤10 mg/day was acceptable unless the dose was changed within 4 weeks before screening. Non-steroidal anti-inflammatory drugs were also allowed at the same dose if they were in use before baseline evaluation and the dosage was unchanged within 14 days prior to screening. Additionally, patients who had received intra-articular, intravenous, or intramuscular glucocorticoid injections or intra-articular hyaluronic acid injections within 4 weeks preceding screening were excluded. Patients with conditions such as cytopenia, transaminitis , abnormal serum creatinine level , hyperbilirubinemia , and fasting glucose > 110 mg/dL or postprandial glucose > 200 mg/dL were excluded. Patients with a history of infection within 24 weeks prior to screening, patients with a history of malignancy , pregnant or breastfeeding women, and women of childbearing age who were not using appropriate contraception were also excluded.This trial was designed to detect equivalence of the proportion of patients who maintained LDA for 24 weeks between the two therapies. Based on historical data, 90% of patients on maintenance therapy maintain LDA after 24 weeks. For a priori sample-size estimation, it was assumed that the maintenance rate of switched therapy would be 70%. The expected difference between the two arms was fixed at 20%. The ratio of patients was set to 1:2 . With α = 5% and power = 80%, the required sample size was 48 and 96 patients in the switched and maintenance arms, respectively.Patients chose to either change from TNFi to TAC  or maintain TNFi  after understanding the differences between the treatments. In the switched arm, TNFi was switched to TAC , which was increased to 3 mg/day at the investigator’s discretion. The maintenance arm continued to receive TNFi at the standard dose  or reduced dose for 24 weeks. In both arms, MTX was maintained at a constant dose throughout the study but dose reduction was permitted for adverse events (AEs). The patients were evaluated at baseline, 8, 16, and 24 weeks. The switched arm included additional visits at 2 and 4 weeks  at week 24. Functional ability was measured using HAQ-DI every 8 weeks. Additionally, the progression of structural damage was assessed using the method of Larsen et al. , which rExploratory outcomes included tender joint count in 68 joints (TJC68), swollen joint count in 66 joints (SJC66), serum ESR and CRP, Physician’s Global Assessment of Disease Activity (PhGA), and Patient Global Assessment of Disease Activity (PGA) based on a visual analog scale (VAS) of 0–100.Safety data were obtained through interviews, physical examinations, and laboratory tests at each visit. Safety variables included all treatment-emergent adverse events (TEAEs) that occurred after administration of TAC or TNFi, serious AEs, AEs of special interest , and laboratory parameters. The association of AEs and laboratory abnormalities with the drugs was entirely based on the clinical judgment of the investigator.Demographic and efficacy analyses included patients who received at least one dose of TAC or TNFi and were evaluated for efficacy. Safety analyses included all patients who received at least one dose of TAC or TNFi irrespective of efficacy evaluation Fig. . BaselinP-values < 0.05 were considered statistically significant.For the primary and secondary endpoints, the difference in the proportion of patients in remission or LDA between the groups was compared using a logistic regression model with adjustments for baseline DAS28, with the results expressed as odds ratios (ORs) and 95% confidential intervals (CIs). Paired t-tests or Wilcoxon signed-rank tests were used to compare DAS28, HAQ-DI, and other ACR Core Data Sets from baseline scores within each group. The differences in these scores between the treatment arms at each visit were assessed using analysis of covariance (ANCOVA) with the baseline value of each parameter as a covariate. Results are summarized as least square (LS) mean differences and 95% CIs. A Kaplan–Meier plot was used to illustrate flare-ups (DAS28 > 3.2) over 24 weeks according to the allocation of the study arm. All analyses were performed using SAS 7.4  and Enrolment was lower than expected; 130 patients were screened, and 120 patients were enrolled in the switched arm (n = 35) and maintenance arm (n = 85) . The mean change in DAS28 between baseline and week 24 in the switched and maintenance arms was 0.30 ± 0.87 and 0.10 ± 0.50, respectively. The LS mean difference between the arms was 0.21 .Overall, 114 (97%) patients were evaluated for efficacy Fig. . After aThe maintenance rates of LDA at weeks 8 and 16 were 100% and 93.3% in the switched arm and 100% and 100% in the maintenance arm, respectively. The remission (DAS28 ≤ 2.6) rate was not different between the arms at weeks 8, 16, and 24  Fig. . In thisP = 0.0285)   and week 24   Fig. . HAQ-DI,85) Fig. . However98) Fig. . The cha21) Fig. .Fig. 3EP = 0.1398). The cumulative incidence curves of flare-ups are illustrated in Fig. P = 0.1685). The unadjusted mean time to flare-up was 16 and 24 weeks in the switched and maintenance arms, respectively. No radiographic changes were noted in both arms for 6 months  over 24 weeks, three in the switched arm and two in the maintenance arm P = 0.398. The P = 0.0085). Drug-related AEs were reported in 7/34 patients  in the switched arm and 6/84 patients  in the maintenance arm (P = 0.0501) (Table P > 0.999). One patient in the switched arm was diagnosed with disseminated tuberculosis, which was the only severe adverse drug reaction in this study, and four patients in the maintenance group reported upper respiratory and oral herpes simplex infections. Major hematological and biochemical abnormalities were not observed in either arm. No death or malignancy was reported in either arm.During the study, 42 cases of TEAEs occurred in 35 (29.7%) patients including 16/34 patients  in the switched arm and 19/84 patients  in the maintenance arm  than that in previously reported studies on tapering TNFi without rescue medication.The TROPHY study provides a new perspective on managing RA patients with stable LDA or those in remission. Switching to TAC and discontinuing TNFi is feasible, and most patients maintained LDA over 24 weeks.Additional file 1:. Supplemental Figure 1 and Table 1Additional file 2:. Supplementary methods and results


Mean diffusivity (MD), which is the average diffusion across all directions, has been considered as a marker of WM tract degeneration or extracellular space enlargement in GM. Recent lines of evidence suggest that cortical MD can better identify early-stage Alzheimer’s disease than structural morphometric parameters in magnetic resonance imaging. However, knowledge of the relationships between cortical MD and other biological factors in the same cortical region, e.g. metabolites, is still limited.Diffusion tensor imaging (DTI), which is a technique for measuring the degree and direction of movement of water molecules in tissue, has been widely used to noninvasively assess white matter (WM) or gray matter (GM) microstructures Thirty-three healthy elderly individuals  were enrolled. We estimated the associations between cortical MD and neurotransmitter levels. Specifically, we measured levels of γ-aminobutyric acid (GABA) and glutamate + glutamine (Glx), which are inhibitory and excitatory neurotransmitters, respectively, in medial prefrontal cortex (mPFC) and posterior cingulate cortex (PCC) using MEGA-PRESS magnetic resonance spectroscopy, and we measured regional cortical MD using DTI.Cortical MD was significantly negatively associated with Glx levels in both mPFC and PCC. No significant association was observed between cortical MD and GABA levels in either GM region.Our findings suggest that degeneration of microstructural organization in GM, as determined on the basis of cortical MD measured by DTI, is accompanied by the decline of Glx metabolism within the same GM region. In the directions of refocusing pulses , the chemical shift displacement between GABA and Glx was 1.67 mm. The VOI in mPFC was defined as follows. After drawing “line a” exactly on the rostral margin of the corpus callosum as the perpendicular axis to the anterior commissure–posterior commissure (AC–PC) line  peaks in the MEGA-PRESS spectra to determine the quality of shimming. The means ± standard deviations (SDs) were 6.864 ± 2.272 Hz in mPFC and 5.201± 2.203 Hz in PCC. We excluded the samples whose FWHM values of NAA peaks were large (i.e. FWHM > mean ± 2 SD). Although data from PCC were successfully collected from all the participants, those from mPFC of one participant were excluded from the analysis because the FWHM of the NAA peak was larger than the cut-off value. In addition, we evaluated motion artifacts by visual inspection of superimposed spectra for all the excitations during scanning using MEGA-PRESS. As a result, two samples obtained from mPFC were also excluded owing to motion artifacts.We measured the full-width at half-maximum (FWHM) of 2 and 5 T2-weighted b = 0 images. The acquisition parameters for the DTI scan were as follows: TE = 84 ms, TR = 6500 ms, 50 axial slices, slice thickness = 3 mm, field of view = 23 × 23 cm2, and matrix size = 128 × 128 (i.e. voxel size = 1.8 × 1.8 × 3.0 mm3). To improve signal-to-noise ratio, the scanning was repeated twice [number of excitation (NEX) = 2].DTI data of the participants were acquired using a clinical 3.0 Tesla Prisma MRI scanner  with a 12-channel head coil. The entire brain was scanned by echo-planar imaging with 30 noncolinear motion probing gradients at a b-value of 1000 sec/mm3.We also obtained high-resolution T1-weighted images for GM morphometry. MP-RAGE sequencing yielding 176 continuous slices of 1.0 mm thickness was carried out along the sagittal plane. The acquisition parameters were as follows: echo time = 2 ms; repetition time = 2000 ms; inversion time = 990 ms; flip angle = 9°; field of view = 256 mm; matrix size = 256 × 256; voxel size = 1 × 1 × 1 mmet al., https://github.com/cic-methods/fid-a) in MATLAB  to minimize the effects of frequency and phase drifts. Motion-corrupted averages were removed as described previously . The data were preprocessed using FMRIB Software Library (FSL) version 4.1.5 (http://www.fmrib.ox.ac.uk/fsl). This procedure included the following: (1) eddy current correction, (2) motion correction by registering all the diffusion-weighted data to the b = 0 images, which were corrected first, (3) brain extraction, (4) calculation of diffusion tensor and diagonalization, and (5) transformation to the MNI space. After these processes, the MD map in the MNI space was automatically constructed using FSL.Diffusion tensor data were converted into the NIfTI format using MRI Convert   was used to coregister different spaces between the binary GM masks and the MD map in each subject. The threshold of GM mask was set to the default SPM parameter of 0.8. Because MD is markedly higher in CSF than in the brain tissue, the map of MDs lower than, 0.102 × 10−2 mm2/s was generated to attenuate the CSF effect on MD measurement within MRS VOIs, in accordance with the previous method described by Albrecht et al.  using FAST (FMRIB’s automated segmentation tool) . The GM corrected Glx/Cr levels in mPFC and PCC were also significantly negatively correlated with MD in each VOI  . Also, the GM corrected Glx/Cr in mPFC and PCC could predict MD in each VOI . To control further for possible effects of GM, WM and CSF fractions were used in separate regression models for raw Glx/Cr, as reported by Fujihara et al. . These regression models showed that only raw Glx/Cr has a predictive effect on MD in each VOI . Also, GM corrected Glx/Cr has a predictive effect on MD in each VOI .In regression analysis, the raw Glx/Cr in mPFC and PCC could predict MD in each VOI (a et al.  and Yild (et al. . All theThe results of this study show that cortical MD is significantly negatively correlated with Glx levels in both mPFC and PCC in healthy elderly individuals. On the other hand, no significant association was found between GABA level and cortical MD in both VOIs.et al., et al., et al., et al., et al., et al., et al., et al., et al., et al., et al., et al., et al., et al., et al., et al., et al., et al., et al., et al., Glx level is very likely related to excitatory neurotransmission, because glutamate is considered to be the major component of the Glx signal (Bauer et al., et al., et al., et al., et al., et al., In this study, no significant association was found between GABA levels and cortical MD in both mPFC and PCC. Similarly to Glx levels, previous MRS studies have shown that the GABA levels in mPFC and PCC are lower in healthy elderly people and patients with Alzheimer’s disease and mild cognitive impairments than in controls (Bai et al., et al., A major limitation in this study is its small sample size, which may have influenced our statistical results. In addition, owing to the lack of data from subjects with age-related neurodegenerative disorders, i.e. mild cognitive impairment or Alzheimer’s disease, there are some limitations in this study. Although some previous MRS studies have shown the significant associations between cognitive function test scores and the levels of several cortical metabolites, i.e. NAA, GABA or Glx (Jessen In conclusion, the level of Glx, which reflects excitatory neurotransmission, was associated with cortical MD in mPFC and PCC in GM. These findings might support a hypothesis, i.e. neuronal loss detected on the basis of cortical MD in DTI can cause a decline of Glx metabolism in these GM regions in elderly people. The results of this study can lead to a better understanding of the association between microstructural organization and neuronal metabolism in GM during aging.


Klebsiella pneumoniae (hvKP) is a high-risk subtype of pneumonia with high mortality and disability rates. An in-depth understanding of hvKP's pathogenic process and mechanism of action is the focus of achieving early disease diagnosis and early symptomatic treatment. This study conducted a preliminary analysis on the influence of lncRNA NKILA (NKILA) on hvKP, aiming at providing a new approach to the diagnosis and treatment of hvKP and laying a reliable foundation for subsequent NKILA-related studies.  Pneumonia due to hypervirulent κB) p65 protein.  Selected from our hospital from October 2016 to February 2018, 67 patients who were examined for the pathogenic microorganisms of alveolar lavage fluid were selected as the research subjects. Among them, 29 were diagnosed as hvKP (research group), and the other 38 had no pathogenic bacteria (control group). Serum and bronchoalveolar lavage fluid (BALF) NKILA and inflammatory factors were detected, and the clinical significance of NKILA was analyzed. In addition, neutrophils from research group were extracted and NKILA expression was increased to observe the alterations in cell apoptosis, respiratory burst intensity, and NF-kappa B inhibitor alpha (NF-P < 0.05). NKILA had an excellent predictive effect on the occurrence of hvKP (P < 0.001) and was positively correlated with inflammatory factors (P < 0.05). Prognostic follow-up revealed that NKILA also had a good predictive value for death in hvKP patients (P < 0.05), and increased posttreatment levels predicted an increased risk of death (P < 0.05). In vitro, increased NKILA hindered the delayed apoptosis rate, decreased respiratory burst intensity of hvKP neutrophils, and activated NF-κB p65 protein (P < 0.05).  Serum and BALF levels of NKILA and inflammatory factors were higher in research group than in control group, and NKILA decreased in both cohorts after treatment (κB p65. With an elevated expression profile in hvKP, NKILA can induce the delayed apoptosis of neutrophils, enhance the ability of releasing inflammatory mediators, and promote the progression of hvKP via activating NF- Klebsiella pneumoniae (hvKP), a subtype of Klebsiella pneumoniae (KP), is one of the rarest bacterial pneumoniae in all cases, accounting for about 3%–8% of all pneumoniae [Pneumonia is the most common pulmonary infectious disease derived from infections of pathogens such as bacteria and viruses, presenting clinical symptoms such as fever and cough . Accordieumoniae . hvKP caeumoniae . Althougeumoniae . MoreoveClinically, an in-depth understanding of the pathogenic process and mechanism of hvKP is not only the focus of early diagnosis and early symptomatic treatment but also the key link to ensure the safety of patients . ReferriSelected from Zhongshan People's Hospital, The Affiliated Hospital of Sun Yat-Sen University from October 2016 to February 2018, 67 patients who were examined for the pathogenic microorganisms of alveolar lavage fluid were selected as the research subjects. Among them, 29 were diagnosed as hvKP (research group), and the other 38 had no pathogenic bacteria (control group). All subjects signed an informed consent after the study was approved by the hospital Ethics Committee.Research Group. Inclusion criteria: (1) patients over 18 years old with etiological diagnosis of hvKP and Klebsiella, (2) bloodstream infection, (3) mild pneumonia, and (4) complete case data. Exclusion criteria: (1) those with other pathogenic bacteria infection, (2) organ dysfunction, (3) cardiovascular disease, (4) immune deficiency, and (5) infectious disease or drug allergy. Control group: age >18 years old, clinical manifestations of cough, no pathogenic bacteria after alveolar lavage fluid examination, diagnosed as allergic pneumonia, and no major medical history.2 and 37°C incubator with RPMI1640 medium added with 10% fetal bovine serum.Human neutrophils infected with hvKP were extracted from the peripheral blood of hvKP patients. Dextran was used to accelerate the sedimentation of red blood cells. The upper layer rich in white blood cells was centrifuged with lymphocyte layering liquid to separate granulocytes from the lymphocytes and monocytes by sinking to the bottom of the tube . The cell were cultivated in a 5% COPatients were fasted and deprived of water before collection. The patient was placed in a supine position, administered with nasal drops of Furoma and sedated with midazolam injection. The bronchoscope was entered through one nostril, and lidocaine was inhaled through the nose for anesthesia. At the same time, the bronchoscope gradually entered until it reached the lesion site. Sodium chloride solution (0.9%) was used for bronchoalveolar lavage for 3 times with a total amount of lavage fluid ≤10 mL/kg. Then, a sterile sputum collector was used to recover the lavage fluid (negative pressure 100–150 mmHg). After centrifugation, the BALF was divided into lower sediment and supernatant to be stored for measurement.β-lactamase inhibitor mixture, colistin, and other drugs were used according to the drug resistance, and the specific medication was carried out in accordance with the doctor's advice.After admission, hvKP patients were given routine treatment such as monitoring care, respiratory support treatment, and nutrition intervention, and according to the pathogenic bacteria and infection, they were treated with conservative antimicrobial therapy, including broad-spectrum antibiotics and cephalosporins. For drug-resistant patients, cephamycin, Fasting venous blood (4 mL) was extracted upon admission (before treatment) and discharge (after treatment) into the procoagulant tube, which was placed for 30 min at room temperature and centrifuged to obtain serum for subsequent detection.−ΔΔCt method, ΔCt (n) = Ct target gene (n)-Ct internal reference gene (n); ΔΔCT (n) = ΔCt (n) − ΔCt (1).Total RNA extracted from serum and BALF by TRIzol was reverse transcribed into cDNA according to the reverse transcription kit for amplification. Primer sequences were designed and constructed by Thermo Fisher Scientific Searle . Expressα (TNF-α) in serum and supernatant of BALF employed ELISA, with kits all offered by Beijing Solarbio Science & Technology Co., Ltd.Strictly following the kits instructions, measurements of interleukin-6 (IL-6), interleukin-8 (IL-8), and tumor necrosis factor-The prognosis of hvKP patients was followed up via hospital reexamination for 3 years to record the prognosis and survival.According to the instructions of Lipofectamine 2000 kit, the targeted elevated NKILA vector (pcDNA-NKILA) and the corresponding empty vector control (pcDNA-NC) were transfected into neutrophils. Transfection effects were verified by PCR.κB p65 protein was measured by western blot. Neutrophil suspension was incubated with dihydrorhodamine at 37°C for 2 min, and the intensity of cell respiratory burst at 0, 60, 120, and 180 min was detected.Neutrophil apoptosis was determined by flow cytometry 12, 24, and 48 h after transfection, and NF-t test, one-way analysis of variance, and LSD postmortem test were used for statistical calculation. The diagnostic value was analyzed by ROC curves, and the correlation analysis was made by Pearson correlation coefficient. The significance level was assumed at P < 0.05.Data analysis and processing employed statistical software SPSS 23.0. Categorical variables were recorded in percentages, and the statistical calculation adopted the chi-square test; continuous variables were described as mean ± standard deviation, and P > 0.05).As shown in P < 0.05). After treatment, serum NKILA declined in both cohorts (P < 0.05).As shown in P < 0.001). However, when NKILA > 2.55 in BALF, the sensitivity and specificity of predicting the occurrence of hvKP were 85.71% and 87.18% (P < 0.001).ROC analysis was carried out on NKILA of the research group and control group before treatment, as shown in α levels were higher in research group than in control group before treatment (P < 0.05).As shown in α (P < 0.05).As shown in P < 0.05). ROC analysis of posttreatment serum NKILA in hvKP patients identified that when NKILA > 3.42, the sensitivity and specificity of predicting the 3-year mortality were 87.50% and 72.22%, respectively (P < 0.05). Then, according to the cut-off value, hvKP patients were allocated into high  and low NKILA expression groups . By comparing the prognosis, it was found that the prognostic mortality was higher in high NKILA expression group compared with low expression group (P < 0.05).During the 3-year follow-up, 27 hvKP cases were successfully followed up, of which 8 died, with an overall mortality rate of 29.63%. As shown in As shown in P > 0.05) but was lower at 60, 120, and 180 min after treatment versus pcDNA-NC group (P < 0.05).As shown in κB p65 protein was higher in pcDNA-NKILA group at 12, 24, and 48 h compared with pcDNA-NC group (P < 0.05), and its protein expression elevated with transfection time (P < 0.05).As shown in With similar clinical manifestations, both hvKP and KP belong to the high-risk subtype of pneumonia , and theα in patients with hvKP increased, indicating that the inflammatory reaction process of hvKP was more serious, which was also in agreement with the disease reports of hvKP in previous studies [Herein, we first conducted a preliminary analysis on the clinical implications of NKILA in hvKP. It determined elevated NKILA in both serum and BALF of hvKP patients, suggesting that NKILA interfered with the onset and development of hvKP, which was consistent with the previous research , 20 and  studies , 22. As  studies . Therefoin vitro experiment. It was found that the apoptosis rate and respiratory burst intensity of neutrophils infected with hvKP decreased dramatically after NKILA was inhibited in vitro. Neutrophils belong to terminally differentiated cells and do not have the ability to differentiate and proliferate; the decrease in their apoptotic ability indicates that the cell's active cycle is enhanced, leading to an increase in the release of inflammatory mediators and toxic substances [κB p65, as a regulatory protein with important reference significance in neutrophils, can activate its protease release when stimulated by external signals, accelerate phosphorylation and degradation to release p65 into the nucleus, and induce the transcription of target genes, thus increasing the cell's functional capacity [κB p65 protein, suggesting that NKILA caused delayed apoptosis through activating NF-κB p65 in neutrophils, which also preliminarily revealed the preliminary pathway of NKILA action in hvKP.Finally, in order to further understand the mechanism of NKILA's influence on hvKP, we conducted an bstances . Respirabstances , is obvicapacity . In thisκB p65, it can induce the delayed apoptosis of neutrophils, enhance its ability to release inflammatory mediators, and promote the progression of hvKP. This study provides a new way for the diagnosis and treatment of hvKP and lays a reliable foundation for follow-up NKILA-related research. Follow-up can explore and analyze other related genes of hvKP to find the fastest and safest diagnosis and treatment method.To sum up, NKILA is elevated in hvKP and via activating NF-


Patients with congestive heart failure (CHF) are vulnerable to contrast-induced kidney injury (CI-AKI), but few prediction models are currently available. Therefore, we aimed to establish a simple nomogram for CI-AKI risk assessment for patients with CHF undergoing coronary angiography.  A total of 1876 consecutive patients with CHF  were enrolled and randomly (2:1) assigned to a development cohort and a validation cohort. The endpoint was CI-AKI defined as serum creatinine elevation of ≥0.3 mg/dL or 50% from baseline within the first 48–72 hours following the procedure. Predictors for the simple nomogram were selected by multivariable logistic regression with a stepwise approach. The discriminative power was assessed using the area under the receiver operating characteristic (ROC) curve and was compared with the classic Mehran score in the validation cohort. Calibration was assessed using the Hosmer–Lemeshow test and 1000 bootstrap samples. n = 109) in the development cohort, and 9.92% (n = 61) in the validation cohort (P=0.367). The simple nomogram including four predictors  demonstrated a similar predictive power as the Mehran score , as well as a well-fitted calibration curve.  The incidence of CI-AKI was 9.06% (170) in the total sample, 8.64% ( The present simple nomogram including four predictors is a simple and reliable tool to identify CHF patients at risk of CI-AKI, whereas further external validations are needed. Contrast-induced kidney injury (CI-AKI) is a common complication following coronary angiography (CAG) or percutaneous coronary intervention (PCI), and the occurrence of CI-AKI has been demonstrated to be related to poor outcomes –3. PubliThe current study population was based on a prospective observation cohort  which enrolled consecutive patients undergoing CAG/PCI in Guangdong Provincial People's Hospital between January 2010 and October 2012. In this study, patients with CHF (defined as New York Heart Association (NYHA) functional class II-IV or Killip class II-IV) undergoing CAG/PCI were enrolled. [The procedures were conducted by interventional cardiologists following published guidelines, institutional policy, and clinical routine.  Patients2) = 186 ∗ (SCr ^  − 1.154) ∗ (Age ^  − 0.203) ∗ 0.742 . The unit of SCr in this formula is mg/dl. CKD was defined as eGFR <60 mL/min/1.73 m2. Patients were further divided into 5 CKD stages according to the guidelines . [The endpoint of this study was CI-AKI defined as a SCr elevation of ≥0.3 mg/dL or 50% from baseline within the first 48 to 72 hours following contrast exposure.  Baseline.73 m2).  And theyt-test and are expressed as the mean ± SD or were compared through the Wilcoxon rank-sum test and are expressed as the median ± interquartile. Categorical variables were compared using the χ2 test or Fisher's exact test and are expressed as percentages. Kaplan–Meier curve and multivariable Cox proportional hazard regression adjusted for known risk factors in the context of long-term prognosis were performed to explore the association between CI-AKI and long-term mortality. [All the patients involved were randomly assigned to a development cohort and a validation cohort in a 2:1 ratio. Continuous variables were compared with an unpaired, 2-tailed rtality. , 18.P < 0.1) covariates until all the remaining variables were statistically significant. Then, we manually investigated the contribution of the remaining variables to determine the final predictors. Collinearity between variables was also evaluated. A nomogram was then formulated based on the results and by using the rms package of R. To form the nomogram, each regression coefficient in the multivariate logistic regression was proportionally converted into a 0- to 100-point scale. The variable with the highest β coefficient  was assigned 100 points. The points are added across each variable to calculate the total points, which are finally converted to predicted probabilities. The performance of the nomogram was assessed using the area under the receiver operating characteristic (ROC) curve and concordance C-statistic for discriminative ability. For validation, a bootstrap method (1000 times) was performed in both the development and validation cohorts to evaluate the stability of the C-statistic. Calibration was assessed using the Hosmer–Lemeshow test and the 1000 bootstrap samples to decrease the overfit bias [P < 0.05 was considered statistically significant. All analyses were conducted with R software  and SPSS (version 26.0).To build the nomogram, candidate variables that were imbalanced between groups in the development cohort or that are clinically important, such as risk factors included in the traditional Mehran score, were included in the univariable logistic analysis. Variables with >15% missing values were not considered candidates, i.e., low-density lipoprotein-C and HbA1c. Significant variables from the univariable logistic analysis were then included in the multivariable logistic analysis. A backward stepwise approach was performed to screen the variables by successively removal of nonsignificant  during the procedure.The details and missing data of the included patients are listed in Supplementary n = 170) in the total sample, 8.64% (109 patients) in the development cohort, and 9.92% (61 patients) in the validation cohort (P=0.367). The distribution of the SCr value within the time frame (24–72 hours after the procedure) is shown in Supplementary The incidence of CI-AKI was 9.06% .The results of univariate logistic analysis are detailed in A simple nomogram based on the selected predictors was formed . The nomP=0.061, In the validation cohort, the simple nomogram demonstrated a C-statistic of 0.80 (95% CI 0.75–0.86), which was similar to that of the Mehran score  among patients with CHF P=0.061,  and a boThe discriminative ability and calibration were also tested among patients with different stages of CHF and stages of CKD, respectively. No significant difference in discriminative ability was identified, except for the comparison between “Heart function II” and “Heart function IV.” Hosmer–Lemeshow statistic suggested a good fit in all stages of CHF and stages of CKD , 50 ≤ scores < 100 (risk = 4.71%), 100 ≤ scores < 150 (risk = 13.90%), 150 ≤ scores < 200 (risk = 39.09%), and scores ≥ 200 (risk = 65.78%). The rates of CI-AKI in the validation cohort were close to those in the development cohort inside each of the 5 score categories (Supplementary P < 0.001) and the validation cohort .The optimal cut-off value of the total nomogram scores to identify patients at risk was determined to be 100. The sensitivity and specificity used to differentiate the presence from the absence of CI-AKI were 69.7% and 75.6% in the development cohort and 70.0% and 74.5% in the validation cohort, respectively. The total nomogram scores of 100 to identify patients at risk also demonstrated a good discriminative power in both the development cohort  was constructed. In particular, the simple nomogram demonstrated a similar discriminative power as the classic Mehran score in the validation cohort, as well as good stability and calibration.To define CHF patients in this study, two classification methods (NYHA and Killip) were used interchangeably. Previous studies had already taken this method to identify CHF patients , 22. In In this study of the CHF population, the overall incidence of CI-AKI was 9.06%. The previously reported incidence of CI-AKI has not been consistent among different studies. Among the patients with a low-risk of ordinary coronary artery disease, the CI-AKI incidence was as low as 2-3%, while in the high-risk population, the CI-AKI incidence could be as high as 19% or 50% , 24, theThe present simple nomogram was constructed based on age, AMI, IABP, and CKD, which are common risk factors associated with CI-AKI, as reported by numerous previous studies , 26, 27.The nomogram developed in this study is a simple but efficient prediction model that includes only four predictors. We noticed that some important risk factors reported by previous results were not included in the current simple nomogram, such as contrast volume and diabetes . The nonThe Mehran score is one of the most classic CI-AKI risk estimating system, which was developed based on 8,357 patients undergoing PCI . CompariWe also noticed that several researches have provided nomograms to predict acute kidney injury (AKI) lately. However, these nomograms were developed for different patients specifically –39. By aOverall, in this study, we established a novel CI-AKI risk prediction nomogram specified for the CHF population. In this simple nomogram, patients with more than 100 total points are identified as at-risk patients, accounting for nearly 30% of the entire CHF cohort. The threshold of 100 points (approximately 10% risk) was also similar to the risk threshold of previous models , 29.Our study had some limitations. First, this study was an analysis of single-centre data and the nomogram we established is not a general one for CI-AKI risk evaluation in any radiological study, but specifically for coronary study/intervention. However, no relevant study had so far elucidated the specified risk factors of CI-AKI in CHF patients. Our study provided a new tool for CI-AKI risk assessment among CHF patients, prompting more attention and further studies on risk assessment of patients with comorbidities undergoing coronary catheterization. Second, the present nomogram was not externally validated, although there was a calibration with 1000 bootstrap samples to decrease the overfit bias. Third, our nomogram did not demonstrate better discriminative power than the Mehran score. However, our model has less variables, which makes it easier for clinical implement. Fourth, some other potential risk factors, especially procedural context , were not included due to the insufficient data. Finally, some patients were discharged within 72 hours after the CAG/PCI, so creatinine levels were not measured on day 3 in these patients, which might lead to the underestimation of the incidence of CI-AKI.The presented nomogram with four predictors  is a simple and reliable tool for CI-AKI risk stratification among CHF patients, which enables physicians to identify patients at risk and implement precise prevention strategies in time. However, further external validations are needed before clinical generalization.


Several hematological indices have been already proposed to discriminate between iron deficiency anemia (IDA) and β‐thalassemia trait (βTT). This study compared the diagnostic performance of different hematological discrimination indices with decision trees and support vector machines, so as to discriminate IDA from βTT using multidimensional scaling and cluster analysis. In addition, decision trees were used to determine the diagnostic classification scheme of patients.Consisting of 1178 patients with hypochromic microcytic anemia (708 patients with βTT and 470 patients with IDA), this cross-sectional study compared the diagnostic performance of 43 hematological discrimination indices with classification tree algorithms and support vector machines in order to discriminate IDA from βTT. Moreover, multidimensional scaling and cluster analysis were used to identify the homogeneous subgroups of discrimination methods with similar performance.All the classification tree algorithms except the LOTUS tree algorithm showed acceptable accuracy measures for discrimination between IDA and βTT in comparison with other hematological discrimination indices. The results indicated that the CRUISE and C5.0 tree algorithms had better diagnostic performance and efficiency among other discrimination methods. Moreover, the AUC of CRUISE and C5.0 tree algorithms indicated more precise classification with values of 0.940 and 0.999, indicating excellent diagnostic accuracy of such models. Moreover, the CRUISE and C5.0 tree algorithms showed that mean corpuscular volume can be considered as the main variable in discrimination between IDA and βTT.CRUISE and C5.0 tree algorithms as powerful methods in data mining techniques can be used to develop accurate differential methods along with other laboratory parameters for the discrimination of IDA and βTT. In addition, the multidimensional scaling method and cluster analysis can be considered as the most appropriate techniques to determine the discrimination indices with similar performance for future hematological studies.The online version contains supplementary material available at 10.1186/s12911-021-01678-5. Microcytic anemia is the most common form of anemia, as a predominant hematologic disorder. IDA and βTT are the two common types of microcytic anemia disorders , 2. The The discrimination between these two hematologic disorders is necessary to prevent iron overload and its complications caused by misdiagnosis and inaccurate treatment so as to determine the prenatal causes for hemoglobin chain disorders. However, the differential diagnosis of IDA from βTT is a major challenge given that they provide similar experimental conditions , 11, 12.In addition to complete blood count (CBC), different tests have been already conducted to differentiate between IDA and βTT precisely; however, they are time-consuming and expensive. The definitive diagnostic methods for the IDA and βTT are respectively based on the increase in HbA2 (Hemoglobin A2), the increase in TIBC , and also the decrease in serum iron and serum ferritin , 13–16.Due to the importance of discriminating between these types of anemia, various studies have been conducted since 1973 to identify appropriate, rapid, and low-cost differential indices for discriminating between IDA and βTT –41. The Recently, the accessibility of powerful statistical software programs has paved the way for the application of advanced statistical models such as data mining techniques in the differential diagnosis of IDA from βTT. However, few studies have already employed such advanced statistical methods and data mining techniques for differential diagnosis of hematological data , 43–52. The tree-based methods include nonparametric methods and need no assumptions about the functional form of the data. Besides, they deal with the high-dimensional dataset, high-order interactions, and nonlinear relationships. These methods are invariant to monotone transformations of predictor variables, and are robust to outliers, missing values, and also multicollinearity. These algorithms can identify the cutoff points of important predictors to discriminate the patients. In addition, tree algorithms are easy to interpret as they display results graphically, making the results understandable without requiring statistical experience. These methods can also assist the clinician in decision making –62.CART (Classification and Regression Tree) algorithm is the best-known classic tree algorithm , though This study aimed to compare the diagnostic performance of the CART algorithm and remedial tree algorithms for solving the disadvantages of this algorithm and SVM with hematological discrimination indices to discriminate between IDA and βTT by using accuracy measures such as true positive rate (TPR or sensitivity), true negative rate (TNR or specificity), false positive rate (FPR), false negative rate (FNR), accuracy, Youden’s index, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (PLR), negative likelihood ratio (PLR), diagnostic odds ratio (DOR), F-measure, and area under the curve (AUC).Besides, the multidimensional scaling and cluster analysis were applied to extract homogeneous subgroups of hematological discriminating indices and classification tree algorithms with a similar performance according to the accuracy measures used.This study included 1178 patients with hypochromic microcytic anemia from Boghrat clinical center in Tehran, Iran. CBC analysis of EDTA-K2 anti-coagulated blood samples was performed using Sysmex kx-21 automated hematology analyzer to measure hematological parameters such as Hb (Hemoglobin), HCT (hematocrit), MCV (Mean Corpuscular Volume), MCH (Mean Corpuscular Hemoglobin), MCHC (Mean Corpuscular Hemoglobin Concentration), RBC (Red Blood Cell Count) and RDW (Red Blood Cell Distribution Width). In addition, HbA2, TIBC, serum iron and serum ferritin were measured for all patients.Patients with hypochromic microcytic anemia , Hb < 12 g.dl for women and Hb < 13 g.dl for men were included in the study. Among them, 708 patients were diagnosed as βTT with HbA2 > 3.5%, and 470 patients were diagnosed as IDA with serum ferritin < 15 ng/ml according to the World Health Organization [WHO] , 72.Patients with simultaneous presentation of both diseases, severe anemia (Hb < 8 g.dl), anemia due to chronic disease, infectious disease, chronic inflammation, pregnancy or other hemoglobinopathies were excluded.P < 0.05 was considered to be statistically significant.Descriptive statistics , median and interquartile range) were evaluated for different blood parameters. Normality of data was assessed using Shapiro–wilk test. Mann–Whitney U test was also used to compare the differences between the hematological parameters of both groups (IDA and βTT). Hematological indices for discrimination between IDA and βTT were computed for each patient according to their formula and cut off. These indices with their formula are shown in Additional file Classification tree algorithms , accuracy, PLR, NLR, DOR, F-measure and AUC. The discrimination method with sensitivity, specificity, PPV, NPV, Youden's index, accuracy, F-measure and AUC near to 1 provided better performance. Likewise, the discrimination method with PLR > 10, NLR < 0.1 and high DOR caused a good performance for discriminating between IDA from βTT , 77. RecMultidimensional scaling method was used to create a map based on the Euclidean distance for showing similarity or dissimilarity between observations. This map can be in one dimension, two dimensions, and three dimensions or in higher dimensions. Smaller distance among two observations indicates more similar and vice versa. This used a map in two dimensions for showing similarity/dissimilarity among pairs of discrimination methods through accuracy measures such as sensitivity, specificity, PPV, NPV, Youden's Index, accuracy, PLR, NLR, F-measure, and AUC .Cluster analysis is a method for extracting homogeneous subgroups of observations. Different algorithms are proposed for cluster analysis. This study used a complete-linkage hierarchical algorithm to determine homogeneous subgroups of methods with a similar diagnostic performance using accuracy measures. The optimal number of methods with a similar diagnostic performance was selected using 30 appropriate measures. Finally, the optimal number was selected based on the majority role .http://pages.stat.wisc.edu/~loh/research.html. SVM algorithm and multidimensional scaling method were fitted using package MASS and package e1071, respectively. The cluster optimal number, or homogeneous groups of diagnostic discrimination methods with a similar diagnostic performances was determined using the package of NbClust. This study was also conducted based on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: guidelines for reporting observational studies and the Standards for Reporting Studies of Diagnostic Accuracy (STARD). These checklists can be obtained from www.equator-network.org.Data analysis was done using software R 4.0.0. Package epiR and package pROC were used to compute the accuracy measures and ROC curve analysis, respectively. Classification tree algorithms like CART, J48, Ctree, Evtree, and C5.0 were fitted using packages rpart, Rweka, party, evtree, and C50, respectively. Software for tree algorithms like QUEST, CRUISE, GUIDE, and LOTUS was obtained from P < 0.001). CRUISE, C5.0, CART, and GUIDE algorithms can calculate the normalized importance (%) for each predictor variable. These algorithms indicated similar ranking of hematological parameters importance. In this study, the normalized importance of variables was reported based on the classification tree algorithms with the best diagnostic performance . This algorithm showed that MCV and HCT variables had the highest and lowest importance for discrimination between IDA and βTT, respectively  to compare the diagnostic performance of hematological discrimination indices with classification tree algorithms and SVM, so as to discriminate IDA from βTT. Data balance was, in turn, assessed using Shannon entropy , 82. AddFigures Additional file Additional file The values of accuracy measures such as Youden's index, accuracy, PLR, NLR, and DOR for each discrimination method are shown in Table P < 0.001).The value of discrimination method AUC for discrimination between IDA and βTT was shown in Table P < 0.05). In this regard, classification tree algorithms had significantly higher AUC than the mentioned hematological discrimination index. Also, CRUISE and C5.0 tree algorithms had significantly higher AUC than other classification tree algorithms, but there was no significant difference between AUC values of Ctree and CART algorithms (P > 0.05).The comparison between AUC values of classification tree algorithms and hematological discrimination index with the best diagnostic performance among hematological indices (Ehsani index) showed that there was a statistically significant difference between AUC values of tree algorithms with Ehsani index  was higher than that of CRUISE tree algorithm, these hematological indices had a high false positive rate as compared to the CRUISE tree algorithm. Moreover, with respect to the other measurements, these indices had poor performance in discriminating between IDA and βTT.Consistent with the findings of this study, other studies demonstrated that Ehsani index had good performance in discrimination between these two disorders in comparison with other hematological indices , 84. MetP < 0.001); CRUISE and C5.0 tree algorithms had significantly higher AUC than this discrimination index. Indeed, all accuracy measures indicated that CRUISE and C5.0 tree algorithms had the best diagnostic performance among the discrimination methods used.Overall, the findings showed that CRUISE tree algorithm had better performance in discrimination between IDA and βTT as compared to all hematological discrimination indices and other classification tree methods. Moreover, comparison between the AUC of CRUISE and C5.0 tree algorithms and Ehsani index  showed that there was a statistically significant difference between AUC of these discrimination methods  in comparison to the discrimination indices. In addition, tree algorithms display results graphically, making the results understandable with no statistical expertise. These algorithms can be thus useful for diagnostic classification scheme of patients in medical studies. This study thus considered the discrimination between IDA and βTT to prevent iron overload and its complications caused by misdiagnosis and inaccurate treatment, and also to determine the prenatal causes for hemoglobin chain disorders.Given its diagnostic performance, CRUISE and C5.0 tree algorithms are considered as an appropriate method for differential diagnosis of patients in comparison to other methods. Moreover, tree-based methods are useful along with other parameters for discriminating between IDA and βTT. In conclusion, considering the advantages of tree algorithms, they can help physicians make better clinical decisions. The results showed that multidimensional scaling method and cluster analysis are appropriate techniques to determine the discrimination indices with similar performance for future studies. In addition, the tree-based methods were identified as good methods for extracting homogeneous subgroups of observations in medical studies.Additional file 1. Table S1. Discrimination indices for differentiation between iron deficiency anemia (IDA) and β-thalassemia trait (βTT). Table S2. Descriptive statistics of blood parameters of the study groups and normalized importance (%) of hematological parameters based on the CRUISE tree algorithm (SD: standard deviation and IQR: interquartile range). Table S3. Sensitivity (TPR), specificity (TNR), false positive rate (FPR), false negative rate (FNR), positive predictive values (PPV) and negative predictive values (NPV) of each hematological index and classification tree algorithm for differentiation between iron deficiency anemia (IDA) and β-thalassemia trait (βTT) with their 95% confidence interval.