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Cancer prevention is a serious global challenge. We aimed to investigate the relationship between lipid-lowering drugs and cancers. We included participants based on the UK Biobank. Lipid-lowering drug use was defined as new users before enrollment and the primary outcome was cancer incidence. The Cox proportional hazards regression model was used to evaluate the association between drug use and outcome. We also performed a meta-analysis. We found that lipid-lowering drugs were associated with decreased risk of 21 types of cancers, including melanoma, skin cancer, and reproductive, hematological, urinary, digestive, nervous, and endocrine system cancers (all p  < 0.0010). Our meta-analysis documented that lipid-lowering drugs reduced the risk of prostate, liver, and gastric cancers, especially (all p  < 0.050). Overall, lipid-lowering drugs had protective associations with cancer incidence, suggesting the possible cancer prevention effects even in the general population., Competing Interests: The authors declare no competing interests., (© 2024 The Authors.)

Background: The relationship between obesity and non-Hodgkin's lymphoma (NHL) was controversial, which may be due to the crudeness definition of obesity based on body mass index (BMI). As obesity and metabolic abnormalities often coexist, we aimed to explore whether the classification of obesity based on metabolic status can help to evaluate the real impact of obesity on the readmission of NHL., Methods: In this retrospective cohort study, utilizing the 2018 Nationwide Readmissions Database, we identified NHL-related index hospitalizations and followed them for non-elective readmission. The patients with NHL were classified as metabolically healthy non-obese (MHNO) and obese (MHO) and metabolically unhealthy non-obese (MUNO) and obese (MUO). Readmission rates for each phenotype were calculated at 30-day intervals. Multiple COX regression was used to analyze the association of metabolic-defined obesity with 30-day, 90-day, and 180-day readmission rates in patients with NHL., Results: There were 22,086 index hospitalizations with NHL included. In the multivariate COX regression, MUNO was associated with increased 30-day (HR = 1.113, 95% CI 1.036-1.195), 90-day (HR = 1.148, 95% CI 1.087-1.213), and 180-day readmission rates (HR = 1.132, 95% CI 1.077-1.189), and MUO was associated with increased 30-day (HR=1.219, 95% CI: 1.081-1.374), 90-day (HR = 1.228, 95% CI 1.118-1.348), and 180-day readmission rates (HR = 1.223, 95% CI 1.124-1.33), while MHO had no associations with readmission rates., Conclusions: The presence of metabolic abnormalities with or without obesity increased the risk of non-selective readmission in patients with NHL. However, obesity alone had no associations with the risk of non-selective readmission, suggesting that interventions for metabolic abnormalities may be more important in reducing readmissions of NHL patients., (© 2023. The Author(s).)

Background: There is an inconsistent association between overweight/obesity and chronic obstructive pulmonary disease (COPD). Considering that different metabolic characteristics exist among individuals in the same body mass index (BMI) category, the classification of overweight/obesity based on metabolic status may facilitate the risk assessment of COPD. Our study aimed to explore the relationship between metabolic overweight/obesity phenotypes and unplanned readmission in patients with COPD. Methods: We conducted a retrospective cohort study using the Nationwide Readmissions Database (NRD). According to metabolic overweight/obesity phenotypes, patients were classified into four groups: metabolically healthy non-overweight/obesity (MHNO), metabolically unhealthy non-overweight/obesity (MUNO), metabolically healthy with overweight/obesity (MHO), and metabolically unhealthy with overweight/obesity (MUO). The primary outcome was unplanned readmission to hospital within 30 days of discharge from index hospitalization. Secondary outcomes included in-hospital mortality, length of stay (LOS) and total charges of readmission within 30 days. Results: Among 1,445,890 patients admitted with COPD, 167,156 individuals were unplanned readmitted within 30 days. Patients with the phenotype MUNO [hazard ratio (HR), 1.049; 95%CI, 1.038-1.061; p < 0.001] and MUO (HR, 1.061; 95%CI, 1.045-1.077; p < 0.001) had a higher readmission risk compared with patients with MHNO. But in elders (≥65yr), MHO also had a higher readmission risk (HR, 1.032; 95%CI, 1.002-1.063; p = 0.039). Besides, the readmission risk of COPD patients with hyperglycemia or hypertension regardless of overweight/obesity increased ( p < 0.001). Conclusion: In patients with COPD, overweight/obesity alone had little effect on unplanned readmission, whereas metabolic abnormalities regardless of overweight/obesity were associated with an increased risk of unplanned readmission. Among the metabolic abnormalities, particular attention should be paid to hyperglycemia and hypertension. But in elders (≥65yr) overweight/obesity and metabolic abnormalities independently exacerbated the adverse outcomes., Competing Interests: 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., (Copyright © 2023 Tian, Liu, Li, Fan, Wu, Shi, Jiang, Yuan, Dong, Li, Xuan and Xu.)

Background and Aim: Obesity is a potentially modifiable factor for reducing readmissions, with heterogeneity that varies according to the metabolic status. Our objective was to examine the independent or mutual relationship between obesity and metabolic abnormalities and diabetic kidney disease (DKD)-related hospitalizations., Methods: 493,570 subjects with DKD were enrolled in the 2018 Nationwide Readmission Database (NRD, United States). The at-risk population was reclassified into refined obesity subtypes based on the body mass index (BMI) classification of metabolic abnormalities (hypertension and/or dyslipidemia) to investigate the 180 d readmission risk and hospitalization costs related to DKD., Results: The overall readmission rate was 34.1%. Patients with metabolic abnormalities, regardless of obesity, had a significantly higher risk of readmission compared to non-obese counterparts (adjusted HR, 1.11 [95% CI, 1.07-1.14]; 1.12 [95% CI, 1.08-1.15]). Hypertension appeared to be the only metabolic factor associated with readmission among individuals with DKD. Obesity without metabolic abnormalities was independently associated with readmission (adjusted HR,1.08 [1.01,1.14]), especially among males and those >65 years (adjusted HR,1.10 [1.01-1.21]; 1.20 [1.10-1.31]). Women or those ≤65 years with metabolic abnormalities (all p <0.050) had elevated readmission rates, regardless of obesity; however, no such trend was observed in obese subjects without metabolic abnormalities (adjusted HR, 1.06 [0.98,1.16]). Additionally, obesity and metabolic abnormalities were associated with elevated hospitalization costs (all p <0.0001)., Conclusions: Increased BMI and hypertension are positively associated with readmissions and related costs among patients with DKD, which should be considered in future studies., Competing Interests: Conflict of Interest The authors declared that they have no conflict of interest., (Copyright © 2023. Published by Elsevier Inc.)

Background: Little is known about the association between abnormal metabolic obesity states and the outcomes of chronic myeloid leukemia (CML), especially in patients with obesity with different metabolic status. Here, we used the Nationwide Readmissions Database to assess the effects of metabolically defined obesity on adverse outcomes of CML., Methods: Of the 35 460 557 (weighted) patients, we included 7931 adults with discharge diagnoses of CML from January 1, 2018 to June 30, 2018. The study population was observed until December 31, 2018 and divided into four groups based on body mass index and metabolic status. The primary outcome was the adverse outcomes of CML, including nonremission (NR)/relapse and severe mortality risk. Multivariate logistic regression analysis was performed to analyze data., Results: Metabolically unhealthy normal weight and metabolically unhealthy obesity were all risk factors for adverse outcomes of CML compared with metabolically healthy normal weight (all p < 0.01), and a significant difference was not found in the metabolically healthy obese. Female patients with metabolically unhealthy normal weight and metabolically unhealthy obesity had 1.23-fold and 1.40-fold increased NR/relapse risk, while male patients did not have this risk. Moreover, patients with a higher number of metabolic risk factors or with dyslipidemia were at higher risk of adverse outcomes, regardless of obesity status., Conclusions: Metabolic abnormalities were associated with adverse outcomes in patients with CML, irrespective of obesity status. Future treatment of patients with CML should consider the effects of obesity on their adverse outcomes under different metabolic status, especially in female patients., (© 2023 The Authors. Journal of Diabetes published by Ruijin Hospital, Shanghai Jiaotong University School of Medicine and John Wiley & Sons Australia, Ltd.)

Background & Purpose: Obesity and metabolic disorders were associated with increased risk of MM, a disease characterized by high risk of relapsing and require frequent hospitalizations. In this study, we conducted a retrospective cohort study to explore the association of metabolic obesity phenotypes with the readmission risk of MM., Patients & Methods: We analyzed 34,852 patients diagnosed with MM from the Nationwide Readmissions Database (NRD), a nationally representative database from US. Hospitalization diagnosis of patients were obtained using ICD-10 diagnosis codes. According to obesity and metabolic status, the population was divided into four phenotypes: metabolically healthy non-obese (MHNO), metabolically unhealthy non-obese (MUNO), metabolically healthy obese (MHO), and metabolically unhealthy obese (MUO). The patients with different phenotypes were observed for hospital readmission at days 30-day, 60-day, 90-day and 180-day. Multivariate cox regression model was used to estimate the relationship between obesity metabolic phenotypes and readmissions risk., Results: There were 5,400 (15.5%), 7,255 (22.4%), 8,025 (27.0%) and 7,839 (35.6%) unplanned readmissions within 30-day, 60-day, 90-day and 180-day follow-up, respectively. For 90-day and 180-day follow-up, compared with patients with the MHNO phenotype, those with metabolic unhealthy phenotypes MUNO (90-day: P = 0.004; 180-day: P = < 0.001) and MUO (90-day: P = 0.049; 180-day: P = 0.004) showed higher risk of readmission, while patients with only obesity phenotypes MHO (90-day: P = 0.170; 180-day: P = 0.090) experienced no higher risk. However, similar associations were not observed for 30-day and 60-day. Further analysis in 90-day follow-up revealed that, readmission risk elevated with the increase of the combined factor numbers, with aHR of 1.068 (CI: 1.002-1.137, P = 0.043, with one metabolic risk factor), 1.109 (CI: 1.038-1.184, P = 0.002, with two metabolic risk factors) and 1.125 (95% CI: 1.04-1.216, P = 0.003, with three metabolic risk factors), respectively., Conclusion: Metabolic disorders, rather than obesity, were independently associated with higher readmission risk in patients with MM, whereas the risk elevated with the increase of the number of combined metabolic factors. However, the effect of metabolic disorders on MM readmission seems to be time-dependent. For MM patient combined with metabolic disorders, more attention should be paid to advance directives to reduce readmission rate and hospitalization burden., Competing Interests: 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., (Copyright © 2023 Zhang, Fan, Zhao, Yuan, Cheng, Wu, Han, Yuan, Zhao and Lu.)

Background: The present definition of obesity based on body mass index (BMI) is not accurate and effective enough to identify hospitalized patients with a heavier burden, especially for postmenopausal hospitalized patients concomitant with osteoporosis. The link between common concomitant disorders of major chronic diseases such as osteoporosis, obesity, and metabolic syndrome (MS) remains unclear. Here, we aim to evaluate the impact of different metabolic obesity phenotypes on the burden of postmenopausal hospitalized patients concomitant with osteoporosis in view of unplanned readmissions., Methods: Data was acquired from the National Readmission Database 2018. The study population was classified into metabolically healthy non-obese (MHNO), metabolically unhealthy non-obese (MUNO), metabolically healthy obese (MHO), and metabolically unhealthy obese (MUO) patients. We estimated the associations between metabolic obesity phenotypes and 30- and 90-day unplanned readmissions. A multivariate Cox Proportional Hazards (PH) model was used to assess the effect of factors on endpoints, with results expressed as HR and 95% CI., Results: The 30-day and 90-day readmission rates for the MUNO and MUO phenotypes were higher than that of the MHNO group (all p < 0.05), whereas no significant difference was found between the MHNO and MHO groups. For 30-day readmissions, MUNO raised the risk mildly (hazard ratio [HR] = 1.110, p < 0.001), MHO had a higher risk (HR = 1.145, p = 0.002), and MUO further elevated this risk (HR = 1.238, p < 0.001). As for 90-day readmissions, both MUNO and MHO raised the risk slightly (HR = 1.134, p < 0.001; HR = 1.093, p = 0.014, respectively), and MUO had the highest risk (HR = 1.263, p < 0.001)., Conclusions: Metabolic abnormalities were associated with elevated rates and risks of 30- or 90-day readmission among postmenopausal hospitalized women complicated with osteoporosis, whereas obesity did not seem to be innocent, and the combination of these factors led to an additional burden on healthcare systems and individuals. These findings indicate that clinicians and researchers should focus not only on weight management but also metabolism intervention among patients with postmenopausal osteoporosis.

(1) Background: As the introduction of "positive" diagnostic criteria for metabolic dysfunction-associated fatty liver disease (MAFLD) does not exclude alcohol consumption, some patients originally diagnosed with alcoholic fatty liver disease (AFLD) may be diagnosed with dual- etiology fatty liver disease (AFLD&MAFLD), which requires us to urgently explore the impact of the changes in this classification of AFLD on clinical manifestations. (2) Methods: Utilizing data from the Nationwide Inpatient Sample database 2016-2018, a total of 9269 participants with AFLD were selected. With the definition of MAFLD, these patients were further categorized into two groups: single AFLD and AFLD&MAFLD. The primary outcome was the risk of comorbidities and organ failures. The secondary outcomes were the length of stay, total charges, and in-hospital all-cause mortality. (3) Results: The patients with AFLD&MAFLD were older, were predominantly male, and had more comorbidities and organ failures compared to the patients with AFLD. These comorbidities included coronary atherosclerosis, myocardial infarction, cerebrovascular disease, arrhythmia, asthma, chronic obstructive pulmonary disease, and chronic kidney disease (all p values < 0.05). The patients with AFLD&MAFLD were more likely to develop acute and chronic heart and/or kidney failures than those with single AFLD (all p < 0.05). The length of stay and total charges of the patients in the AFLD&MAFLD group were greater than the single AFLD group ( p = 0.029 and p < 0.001, respectively). No significant difference in all-cause mortality was observed. (4) Conclusions: The patients with AFLD&MAFLD have more comorbidities and organ failures, longer hospital stays, and higher hospitalization costs than the patients with single AFLD. Hence, patients with dual-etiology fatty liver disease deserve more attention from clinical staff during treatment.

Background: Increased body mass index (BMI) and metabolic abnormalities are controversial prognostic factors of lung cancer. However, the relationship between metabolic overweight/obesity phenotypes and hospital readmission in patients with lung cancer is rarely reported., Methods: We established a retrospective cohort using the United States (US) Nationwide Readmissions Database (NRD). We included adult patients diagnosed with lung cancer from January 1, 2018 to November 30, 2018 and excluded patients combined with other cancers, pregnancy, died during hospitalization, low body weight, and those with missing data. The cohort was observed for hospital readmission until December 31, 2018. We defined and distinguished four metabolic overweight/obesity phenotypes: metabolically healthy with normal weight (MHNW), metabolically unhealthy with normal weight (MUNW), metabolically healthy with overweight or obesity (MHO), and metabolically unhealthy with overweight or obesity (MUO). The relationship between metabolic overweight/obesity phenotypes and 30-day readmission risk was assessed by multivariable Cox regression analysis., Findings: Of the 115,393 patients included from the NRD 2018 (MHNW [58214, 50.4%], MUNW [44980, 39.0%], MHO [5044, 4.4%], and MUO [7155, 6.2%]), patients with the phenotype MUNW (6531, 14.5%), MHO (771, 15.3%), and MUO (1155, 16.1%) had a higher readmission rate compared to those with MHNW (7901, 13.6%). Compared with patients with the MHNW phenotype, those with the MUNW (hazard ratio [HR], 1.10; 95% CI, 1.06-1.14), MHO (HR, 1.15; 95% CI, 1.07-1.24), and MUO (HR, 1.28; 95% CI, 1.20-1.36) phenotypes had a higher risk of readmission, especially in men, those without surgical intervention, or those aged >60 years. In women, similar results with respect to readmission were observed in people aged >60 years (MUNW [HR, 1.07; 95% CI, 1.01-1.13], MHO [HR, 1.19; 95% CI, 1.06-1.35], and MUO [HR, 1.28; 95% CI, 1.16-1.41]). We also found increased costs for 30-day readmission in patients with MHO (OR, 1.18; 95% CI, 1.07-1.29) and MUO (OR, 1.11; 95% CI, 1.02-1.20)., Interpretation: Increased BMI and metabolic abnormalities are independently associated with higher readmission risks in patients with lung cancer, whereas increased BMI also increases the readmission costs. Follow-up and intervention method targeting increased BMI and metabolic abnormalities should be considered for patients with lung cancer., Funding: The National Key Research and Development Program of China (2017YFC1309800)., Competing Interests: All authors declare no competing interests., (© 2022 The Author(s).)