The Effect of Chamomile Oil on Pain and Anxiety Intensity of IUD Insertion in Women Referring to Karaj Health Centers: Ridit Analysis

Introduction: Intrauterine device (IUD) is a safe, effective and reversible method of family planning. Unfortunately, IUD insertion causes anxiety and pain. The aim of study was to compare ridit analysis and Kruskal-wallis test in pain and anxiety intensity of IUD insertion in women referring to health centers of Karaj (Iran).Materials and Methods: In this randomized clinical trial study, 150 eligible women candidate intrauterine device insertion entered the study and were randomly divided into three groups: chamomile, placebo and control groups. Data was collected from women who came to health centers in Karaj (Iran) in 2017. Data collection tools included demographic information, Spiel-Berger questionnaire and pain visual analogue scale. The intensity of pain and anxiety were measured afterwards. Finally, ridit analysis and Kruskal-wallis test were used to rank the intensity of pain and anxiety in patients. The R-3.4.3 and Microsoft's Excel software were used for statistical analysis.Results: The results showed that the mean±SD of age in three groups was 29.7±7.01, 28.68±8.15 and 31.6±7.71, respectively. Ridit analysis and Kruskal-wallis test showed considerable decrease of the anxiety and pain intensity, induced by IUD insertion in Chamomile, Placebo and Control groups respectively. Ridit analysis and Kruskal-wallis test statistics are significant. The value of the ridit statistic was 15د‡2=20.23, P<0.001">  and the value of Kruskal-wallis test is 15د‡2=18.67, P<0.005">  in pain intensity. Moreover, the value of the ridit statistic is 15د‡2=3.92, P<0.001">  and the value of Kruskal-wallis test is 15د‡2=21.37, P<0.005">  in anxiety intensity.Conclusions: The results of this study suggested that, there is less significant difference in ridit analysis than Kruskal-wallis test among the three groups in decreasing pain and anxiety intensity. 

Machine learning-based classifiers to predict metastasis in colorectal cancer patients

BackgroundThe increasing prevalence of colorectal cancer (CRC) in Iran over the past three decades has made it a key public health burden. This study aimed to predict metastasis in CRC patients using machine learning (ML) approaches in terms of demographic and clinical factors.MethodsThis study focuses on 1,127 CRC patients who underwent appropriate treatments at Taleghani Hospital, a tertiary care facility. The patients were divided into training and test datasets in an 80:20 ratio. Various ML methods, including Naive Bayes (NB), random rorest (RF), support vector machine (SVM), neural network (NN), decision tree (DT), and logistic regression (LR), were used for predicting metastasis in CRC patients. Model performance was evaluated using 5-fold cross-validation, reporting sensitivity, specificity, the area under the curve (AUC), and other indexes.ResultsAmong the 1,127 patients, 183 (16%) had experienced metastasis. In the predictionof metastasis, both the NN and RF algorithms had the highest AUC, while SVM ranked third in both the original and balanced datasets. The NN and RF algorithms achieved the highest AUC (100%), sensitivity (100% and 100%, respectively), and accuracy (99.2% and 99.3%, respectively) on the balanced dataset, followed by the SVM with an AUC of 98.8%, a sensitivity of 97.5%, and an accuracy of 97%. Moreover, lower false negative rate (FNR), false positive rate (FPR), and higher negative predictive value (NPV) can be confirmed by these two methods. The results also showed that all methods exhibited good performance in the test datasets, and the balanced dataset improved the performance of most ML methods. The most important variables for predicting metastasis were the tumor stage, the number of involved lymph nodes, and the treatment type. In a separate analysis of patients with tumor stages I–III, it was identified that tumor grade, tumor size, and tumor stage are the most important features.ConclusionThis study indicated that NN and RF were the best among ML-based approaches for predicting metastasis in CRC patients. Both the tumor stage and the number of involved lymph nodes were considered the most important features

The impact of vitamin D changes during pregnancy on the development of maternal adverse events: A random forest analysis

Background: Maternal vitamin D deficiency during pregnancy has been associated with various maternal adverse events (MAE). However, the evidence regarding the effect of vitamin D supplementation on these outcomes is still inconclusive. Methods: This secondary analysis utilized a case–control design. 403 samples with MAE and 403 samples without any outcomes were selected from the Khuzestan Vitamin D Deficiency Screening Program in Pregnancy study. Random forest (RF) analysis was used to evaluate the effect of maternal vitamin D changes during pregnancy on MAE. Results: The results showed that women who remained deficient (35.2%) or who worsened from sufficient to deficient (30.0%) had more MAE than women who improved (16.4%) or stayed sufficient (11.8%). The RF model had an AUC of 0.74, sensitivity of 72.6%, and specificity of 69%, which indicate a moderate to high performance for predicting MAE. The ranked variables revealed that systolic blood pressure is the most important variable for MAE, followed by diastolic blood pressure and vitamin D changes during pregnancy. Conclusion: This study provides evidence that maternal vitamin D changes during pregnancy have a significant impact on MAE. Our findings suggest that monitoring and treatment of vitamin D deficiency during pregnancy may be a potential preventive strategy for reducing the risk of MAE. The presented RF model had a moderate to high performance for predicting MAE

Biological and Clinical Relevance of Long Non-Coding RNA PCAT-1 in Cancer, A Systematic Review and Meta-Analysis

Long non-coding RNA (lncRNA) prostate cancer associated transcript 1 (PCAT-1) has been identified as a potential biomarker for the diagnosis and prognosis of various cancers. We performed this systematic review and meta-analysis to evaluate the role of dysregulation as well as the biological and clinical significance of lnc-PCAT-1 for predicting the malignancy status in several cancers. Two independent reviewers conducted an extensive search in electronic databases of Medline, Embase, Scopus, Web of Science and PubMed until the December of 2017. Five articles investigating the clinical significance of lncRNA PCAT-1, including 996 patients, were analyzed. Our results revealed that the increased PCAT-1 expression was related to overall survival (OS) (HR = 1.9, 95%CI: 1.13-3.18, P=0.015). Also, pooled results of the diagnostic data analysis demonstrated that PCAT-1 has a sensitivity of 0.59 and specificity of 0.66 for cancer diagnosis. Moreover, pooled area under curve was 0.62 (95% CI: 0.58–0.69). This meta-analysis revealed that lncRNA PCAT-1 could be served as a potential diagnostic and prognostic biomarker in various solid tumors

Lifestyle and occupational risks assessment of bladder cancer using machine learning‐based prediction models

Background: Bladder cancer, one of the most prevalent cancers globally, can be regarded as considerable morbidity and mortality for patients. The bladder is an organ that comes in constant exposure to the environment and other risk factors such as inflammation. Aims: In the current study, we used machine learning (ML) methods and developed risk prediction models for bladder cancer. Methods: This population‐based case–control study is focused on 692 cases of bladder cancer and 692 healthy people. The ML, including Neural Network (NN), Random Forest (RF), Decision Tree (DT), Naive Bayes (NB), Gradient Boosting (GB), and Logistic Regression (LR), were applied, and the model performance was evaluated. Results: The RF (AUC = .86, precision = 79%) had the best performance, and the RT (AUC = .78, precision = 73%) was in the next rank. Based on variable importance analysis in RF, recurrent infection, bladder stone history, neurogenic bladder, smoking and opium use, chronic renal failure, spinal cord paralysis, analgesic, family history of bladder cancer, diabetic mellitus, low dietary intake of fruit and vegetable, high dietary intake of ham, sausage, can and pickles were respectively the most important factors, which effect on the probability of bladder cancer. Conclusion: Machine learning approaches can predict the probability of bladder cancer according to medical history, occupational risk factors, and dietary and demographical characteristics

A study of depression, partnership and sexual satisfaction in patients with post-traumatic olfactory disorders

Post-traumatic olfactory dysfunction (PTOD) is associated with a significant decrease in quality of life. The present study aimed to explore whether PTOD is associated with depression and changes in sexuality. There were two groups in this case-control study. The patient group consisted of patients with PTOD (n = 55), and the control group comprised healthy individuals without the olfactory disorder (n = 115). Olfactory function, depression, partnership, and sexual satisfaction were assessed using the Iranian version of the Sniffin' Sticks test (Ir-SST), Beck Depression Inventory (BDI), Enrich Couple Scale (ECS) and Sexual Satisfaction Scale for Women (SSSW). The BDI scores were higher in the patient group than in the control group (p < 0.001). The SSSW score was lower in the patient group than in controls (p < 0.01), although the ECS score was not significantly different between patients and controls. Also, there was no significant difference in the severity of trauma between marital satisfaction and sexual satisfaction. However, the analysis showed a statistically significant difference in depression scores in connection with the head trauma severity. In the PTOD group, depression was increased and sexual satisfaction declined. Understanding the association of olfactory dysfunction with depression and sexuality allows patients and doctors to deal with less notable consequences of this disorder

Dapagliflozin and Days of Full Health Lost in the DAPA-HF Trial

Background: Conventional time-to-first-event analyses cannot incorporate recurrent hospitalizations and patient well-being in a single outcome. Objectives: To overcome this limitation, we tested an integrated measure that includes days lost from death and hospitalization, and additional days of full health lost through diminished well-being. Methods: The effect of dapagliflozin on this integrated measure was assessed in the DAPA-HF (Dapagliflozin and Prevention of Adverse Outcomes in Heart Failure) trial, which examined the efficacy of dapagliflozin, compared with placebo, in patients with NYHA functional class II to IV heart failure and a left ventricular ejection fraction ≤40%. Results: Over 360 days, patients in the dapagliflozin group (n = 2,127) lost 10.6 ± 1.0 (2.9%) of potential follow-up days through cardiovascular death and heart failure hospitalization, compared with 14.4 ± 1.0 days (4.0%) in the placebo group (n = 2,108), and this component of all measures of days lost accounted for the greatest between-treatment difference (−3.8 days [95% CI: −6.6 to −1.0 days]). Patients receiving dapagliflozin also had fewer days lost to death and hospitalization from all causes vs placebo (15.5 ± 1.1 days [4.3%] vs 20.3 ± 1.1 days [5.6%]). When additional days of full health lost (ie, adjusted for Kansas City Cardiomyopathy Questionnaire–overall summary score) were added, total days lost were 110.6 ± 1.6 days (30.7%) with dapagliflozin vs 116.9 ± 1.6 days (32.5%) with placebo. The difference in all measures between the 2 groups increased over time (ie, days lost by death and hospitalization −0.9 days [−0.7%] at 120 days, −2.3 days [−1.0%] at 240 days, and −4.8 days [−1.3%] at 360 days). Conclusions: Dapagliflozin reduced the total days of potential full health lost due to death, hospitalizations, and impaired well-being, and this benefit increased over time during the first year.</p

Adherence to dietary recommendations by socioeconomic status in the United Kingdom biobank cohort study

Understanding how socioeconomic markers interact could inform future policies aimed at increasing adherence to a healthy diet. This cross-sectional study included 437,860 participants from the UK Biobank. Dietary intake was self-reported. Were used as measures socioeconomic education level, income and Townsend deprivation index. A healthy diet score was defined using current dietary recommendations for nine food items and one point was assigned for meeting the recommendation for each. Good adherence to a healthy diet was defined as the top 75th percentile, while poor adherence was defined as the lowest 25th percentile. Poisson regression was used to investigate adherence to dietary recommendations. There were significant trends whereby diet scores tended to be less healthy as deprivation markers increased. The diet score trends were greater for education compared to area deprivation and income. Compared to participants with the highest level of education, those with the lowest education were found to be 48% less likely to adhere to a healthy diet (95% Confidence Interval [CI]: 0.60-0.64). Additionally, participants with the lowest income level were 33% less likely to maintain a healthy diet (95% CI: 0.73-0.81), and those in the most deprived areas were 13% less likely (95% CI: 0.84-0.91). Among the three measured proxies of socioeconomic statuseducation, income, and area deprivationlow education emerged as the strongest factor associated with lower adherence to a healthy diet

Association between walking pace and incident type 2 diabetes by adiposity levels – a prospective cohort study from the UK Biobank

Aims: This study aims to investigate the combined association of adiposity and walking pace with incident type 2 diabetes. Methods: We undertook a prospective cohort study on 194,304 White-European participants (mean age 56.5 years, 55.9% women). Participants’ walking pace was self-reported as brisk, average, or slow. Adiposity included body mass index (BMI), waist circumference (WC) and body fat percentage (BF%). The associations were investigated using Cox proportional hazard models, with a 2-year landmark analysis. A four-way decomposition analysis was used for mediation and additive interaction. Results: The median follow-up was 5.4 years (IQR: 4.8- 6.3). During the follow-up period, 4564 participants developed type 2 diabetes. Compared to brisk walking participants with normal BMI, those with obesity who walked briskly were at a ~10-12 fold higher risk of type 2 diabetes (HR: 9.64 [95% CI: 7.24; 12.84] in women; HR: 11.91 [95% CI: 8.80; 16.12] in men), whereas those who with obese and walked slowly had ~12-15-fold higher risk (HR: 12.68 [95% CI: 9.62; 16.71] for women; and HR: 15.41 [95% CI: 11.27; 21.06] for men). There was evidence of additive interaction between WC and BF% and walking pace among women, explaining 17.8% and 47.9% excess risk respectively. Obesity mediated the association in women and men, accounting for 60.1% and 44.9%, respectively. Conclusions: Slow walking pace is a risk factor for type 2 diabetes independent of adiposity. However, promoting brisk walking as well as weight management might be an effective type 2 diabetes prevention strategy given its synergistic effect

Mineralocorticoid receptor antagonists in heart failure: an individual patient level meta-analysis

Background: Mineralocorticoid receptor antagonists (MRAs) reduce hospitalisations and death in patients with heart failure and reduced ejection fraction (HFrEF), but the benefit in patients with heart failure and mildly reduced ejection fraction (HFmrEF) or heart failure and preserved ejection fraction (HFpEF) is unclear. We evaluated the effect of MRAs in four trials that enrolled patients with heart failure across the range of ejection fraction. Methods: This is a prespecified, individual patient level meta-analysis of the RALES (spironolactone) and EMPHASIS-HF (eplerenone) trials, which enrolled patients with HFrEF, and of the TOPCAT (spironolactone) and FINEARTS-HF (finerenone) trials, which enrolled patients with HFmrEF or HFpEF. The primary outcome of this meta-analysis was a composite of time to first hospitalisation for heart failure or cardiovascular death. We also estimated the effect of MRAs on components of this composite, total (first or repeat) heart failure hospitalisations (with and without cardiovascular deaths), and all-cause death. Safety outcomes were also assessed, including serum creatinine, estimated glomerular filtration rate, serum potassium, and systolic blood pressure. An interaction between trials and treatment was tested to examine the heterogeneity of effect in these populations. This study is registered with PROSPERO, CRD42024541487. Findings: 13 846 patients were included in the four trials. MRAs reduced the risk of cardiovascular death or heart failure hospitalisation (hazard ratio 0·77 [95% CI 0·72–0·83]). There was a statistically significant interaction by trials and treatment (p for interaction=0·0012) due to the greater efficacy in HFrEF (0·66 [0·59–0·73]) compared with HFmrEF or HFpEF (0·87 [0·79–0·95]). We observed significant reductions in heart failure hospitalisation in the HFrEF trials (0·63 [0·55–0·72]) and the HFmrEF or HFpEF trials (0·82 [0·74–0·91]). The same pattern was observed for total heart failure hospitalisations with or without cardiovascular death. Cardiovascular death was reduced in the HFrEF trials (0·72 [0·63–0·82]) but not in the HFmrEF or HFpEF trials (0·92 [0·80–1·05]). All-cause death was also reduced in the HFrEF trials (0·73 [0·65–0·83]) but not in the HFmrEF or HFpEF trials (0·94 [0·85–1·03]). With an MRA, the risk of hyperkalaemia was doubled compared with placebo (odds ratio 2·27 [95% CI 2·02–2·56]), but the incidence of serious hyperkalaemia (serum potassium &gt;6·0 mmol/L) was low (2·9% vs 1·4%); the risk of hypokalaemia (potassium &lt;3·5 mmol/L) was halved (0·51 [0·45–0·57]; 7% vs 14%). Interpretation: Steroidal MRAs reduce the risk of cardiovascular death or heart failure hospitalisation in patients with HFrEF and non-steroidal MRAs reduce this risk in patients with HFmrEF or HFpEF. Funding: None