The effect of smoking on latent hazard classes of metabolic syndrome using latent class causal analysis method in the Iranian population.

BACKGROUND: The prevalence of metabolic syndrome is increasing worldwide. Clinical guidelines consider metabolic syndrome as an all or none medical condition. One proposed method for classifying metabolic syndrome is latent class analysis (LCA). One approach to causal inference in LCA is using propensity score (PS) methods. The aim of this study was to investigate the causal effect of smoking on latent hazard classes of metabolic syndrome using the method of latent class causal analysis. METHODS: In this study, we used data from the Tehran Lipid and Glucose Cohort Study (TLGS). 4857 participants aged over 20 years with complete information on exposure (smoking) and confounders in the third phase (2005-2008) were included. Metabolic syndrome was evaluated as outcome and latent variable in LCA in the data of the fifth phase (2014-2015). The step-by-step procedure for conducting causal inference in LCA included: (1) PS estimation and evaluation of overlap, (2) calculation of inverse probability-of-treatment weighting (IPTW), (3) PS matching, (4) evaluating balance of confounding variables between exposure groups, and (5) conducting LCA using the weighted or matched data set. RESULTS: Based on the results of IPTW which compared the low, medium and high risk classes of metabolic syndrome (compared to a class without metabolic syndrome), no association was found between smoking and the metabolic syndrome latent classes. PS matching which compared low and moderate risk classes compared to class without metabolic syndrome, showed that smoking increases the probability of being in the low-risk class of metabolic syndrome (OR: 2.19; 95% CI: 1.32, 3.63). In the unadjusted analysis, smoking increased the chances of being in the low-risk (OR: 1.45; 95% CI: 1.01, 2.08) and moderate-risk (OR: 1.68; 95% CI: 1.18, 2.40) classes of metabolic syndrome compared to the class without metabolic syndrome. CONCLUSIONS: Based on the results, the causal effect of smoking on latent hazard classes of metabolic syndrome can be different based on the type of PS method. In adjusted analysis, no relationship was observed between smoking and moderate-risk and high-risk classes of metabolic syndrome.

Hospital length of stay for COVID-19 patients: a systematic review and meta-analysis.

The length of stay in the hospital for COVID-19 can aid in understanding the disease's prognosis. Thus, the goal of this study was to collectively estimate the hospital length of stay (LoS) in COVID-19 hospitalized individuals. To locate related studies, international databases (including Google Scholar, Science Direct, PubMed, and Scopus) were searched. The I2 index, the Cochran Q test, and T2 were used to analyze study heterogeneity. The mean LoS in COVID- 19 hospitalized patients was estimated using a random-effects model. COVID-19's total pooled estimated hospital LoS was 15.35, 95%CI:13.47-17.23; p<0.001, I2 = 80.0). South America had the highest pooled estimated hospital LoS of COVID-19 among the continents, at 20.85 (95%CI: 14.80-26.91; p<0.001, I2 = 0.01), whereas Africa had the lowest at 8.56 8 (95%CI: 1.00-22.76). The >60 age group had the highest pooled estimated COVID-19 hospital LoS of 16.60 (95%CI: 12.94-20.25; p<0.001, I2 = 82.6), while the 40 age group had the lowest hospital LoS of 10.15 (95% CI: 4.90-15.39, p<0.001, I2 = 22.1). The metanalysis revealed that COVID-19's hospital LoS was more than 10 days. However, it appears that this duration varies depending on a number of factors, including the patient's age and the availability of resources.

The relationship between metabolic syndrome and its components with bladder cancer: a systematic review and meta-analysis of cohort studies.

A previous meta-analysis, entitled "The association between metabolic syndrome and bladder cancer susceptibility and prognosis: an updated comprehensive evidence synthesis of 95 observational studies involving 97,795,299 subjects," focused on all observational studies, whereas in the present meta-analysis, we focused on cohort studies to obtain more accurate and stronger evidence to evaluate the association between metabolic syndrome and its components with bladder cancer. PubMed, Embase, Scopus, and Web of Science were searched to identify studies on the association between metabolic syndrome and its components with bladder cancer from January 1, 2000 through May 23, 2021. The pooled relative risk (RR) and 95% confidence intervals (CI) were used to measure this relationship using a random-effects meta-analytic model. Quality appraisal was undertaken using the Newcastle-Ottawa Scale. In total, 56 studies were included. A statistically significant relationship was found between metabolic syndrome and bladder cancer 1.09 (95% CI, 1.02 to 1.17), and there was evidence of moderate heterogeneity among these studies. Our findings also indicated statistically significant relationships between diabetes (RR, 1.23; 95% CI, 1.16 to 1.31) and hypertension (RR, 1.07; 95% CI, 1.01 to 1.13) with bladder cancer, but obesity and overweight did not present a statistically significant relationship with bladder cancer. We found no evidence of publication bias. Our analysis demonstrated statistically significant relationships between metabolic syndrome and the risk of bladder cancer. Furthermore, diabetes and hypertension were associated with the risk of bladder cancer.

The association between migraine and breast cancer risk: A systematic review and meta-analysis.

BACKGROUND: Migraines is likely to play a protective role in the risk of breast cancer. Some studies have shown that there is an inverse relationship between migraine and breast cancer, and some studies have not found an association; therefore, results from previous studies have been inconclusive and we conducted a meta-analysis to evaluate association between migraine and breast cancer. METHODS: PubMed, EMBASE, Scopus and Web of Science were searched to identify studies on the association between migraine and breast cancer from January 1, 2000 through March 12, 2021. The pooled relative risk (RR) and the 95% confidence intervals (CI) was used to measure this relationship by assuming a random effects meta-analytic model. RESULTS: A total of 10 studies were included. Our study revealed that there was statistically significant inverse relationship between migraine and breast cancer in case-control studies 0.68 [95% CI: 0.56, 0.82], but no significant relationship was found in cohort studies 0.98 [95% CI: 0.91, 1.06]. Also, migraine reduced the risk of ductal carcinoma 0.84 [95% CI: 0.73, 0.96], and lobular carcinoma 0.83 [95% CI: 0.73, 0.96]. With respect to ER_PR status no association between migraine and breast cancer was found. We found no evidence of publication bias. CONCLUSION: Our analysis demonstrated a statistically significantly inverse relationship between migraine and total risk of breast cancer only in case-control studies. In summary, cohort studies do not support an inverse association between migraine and incident breast cancer. While in case-control studies, migraine has an inverse association with ductal carcinoma and lobular carcinoma of breast.