Comprehensive Evaluation of Reference Values of Parametric and Non-Parametric Effect Size Methods for Two Independent Groups

In the field of health and other sciences, effect size (ES) provides a scientific approach to the effectiveness of treatment or intervention. The p-value indicates whether the statistical difference depends on chance, while ES gives information about the effectiveness of the treatment or intervention, even if the difference is not significant. For this reason, ES has become a very popular measure in recent years. It depends on which ES will be used based on the distribution of data and the number of groups. In this study, parametric and non-parametric ES were evaluated for two independent groups. When the literature was examined, there were no studies aimed at evaluating the reference values of the parametric and non-parametric ES methods used for two independent groups. In this study, the reference values of parametric and non-parametric ES methods for two independent groups were re-evaluated by a simulation study. As a result, the very small reference value of parametric ES methods was determined differently from the literature. It has been seen that the reference values of non-parametric ES methods are valid in cases where the skewness is low, and new reference values have been proposed at the varying skewness level

Working from home during the COVID-19 pandemic and its effects on diet, sedentary lifestyle, and stress

Many companies switched to working from home (WFH) after the COVID-19 pandemic. This paper aimed to examine the changes in dietary behavior, body weight, sedentary lifestyle, and stress in individuals who practice WFH. A cross-sectional, web-based questionnaire was administered between March and May 2021 and included socio-demographic characteristics, anthropometric measurements, WFH arrangement, changes in diet, sedentary lifestyle, and stress status. A total of 328 individuals (260 women, 68 men), aged 31.3 +/- 8.3 years with a BMI of 24.9 +/- 4.6 kg/m(2), participated in the study. The questionnaire revealed that the daily working time increased with WFH. The majority of the individuals (59.1%) gained weight. The average daily sedentary time and the Perceived Stress Scale score increased significantly. The daily sedentary time and Non-Healthy Diet Index scores were higher in individuals who gained weight (p < 0.05). A multinominal regression model revealed that increased body weight was less likely in individuals with underweight and normal BMI classifications. Normal BMI, stable work shifts, and no physical activity were positive predictors for gaining weight. These results suggest that WFH may have significant negative effects on physical and mental status of individuals

One-year follow-up evaluation of radiological and respiratory findings and functional capacity in COVID-19 survivors without comorbidities

The aim of this study was to assess clinical findings, radiological data, pulmonary functions and physical capacity change over time and to investigate factors associated with radiological abnormalities after coronavirus disease 2019 (COVID-19) in non-comorbid patients. This prospective cohort study was conducted between April 2020 and June 2020. A total of 62 symptomatic in non-comorbid patients with COVID-19 pneumonia were included in the study. At baseline and the 2nd, 5th and 12th months, patients were scheduled for follow-up. Males represented 51.6% of the participants and overall mean age was 51.60 ± 12.45 years. The percentage of patients with radiological abnormalities at 2 months was significantly higher than at 5 months (P < .001). At 12 months, dyspnea frequency (P = .008), 6-minute walk test (6MWT) distance (P = .045), BORG-dyspnea (P < .001) and BORG-fatigue (P < .001) scores was significantly lower, while median SpO2 after 6MWT (P < .001) was significantly higher compared to results at 2 months. The presence of radiological abnormalities at 2 months was associated with the following values measured at 5 months: advanced age (P = .006), lung involvement at baseline (P = .046), low forced expiratory volume in 1 second (P = .018) and low forced vital capacity (P = .006). Even in COVID-19 patients without comorbidities, control computed tomography at 2 months and pulmonary rehabilitation may be beneficial, especially in COVID-19 patients with advanced age and greater baseline lung involvement

Comparison of effect size methods

Etki büyüklüğü, istatistiksel anlamlılıktan ziyade bir müdahalenin büyüklüğüne daha bilimsel bir yaklaşım sağlamaktadır. Etki büyüklüğünün üç farklı yönü vardır. İlk yönü, ilgilenilen bilgi türü; ikinci yönü, istatistik veya parametreleri etki büyüklüğüne bağlayan denklem aracılığıyla etki büyüklüğünün işlevselleştirilmesi ve üçüncü yönü ise etki büyüklüğünün değeridir. İki bağımsız grubun normal dağılım varsayımı altında Cohen d, Glass delta ve Hedge g olmak üzere üç standart etki büyüklüğü tahmincisi vardır. Normallik varsayımı olduğu sürece Cohen d, Glass delta ve Hedge g etki büyüklüğü tahmincileri tutarlı ve asimptotik tahmincilerdir. Popülasyonların normal dağılıma sahip olmadığı durumda iki bağımsız grup için parametrik olmayan etki büyüklüğü ölçüleri önerilmiştir. Bu etki büyüklüğü ölçüleri Cliff delta, Glass Rank Biserial Korelasyon Katsayısı ve Vargha ve Delanay A (VDA)’dır. Bu çalışmada Cohen d, Hedge g, Glass delta, Cliff delta, VDA ve Rank-Biserial Korelasyon Katsayısı etki büyüklüğü yöntemleri açıklanmış ve simülasyon çalışması ile referans aralıkları değerlendirilmiştir. Parametrik olmayan etki büyüklüğü yöntemleri için değişen çarpıklık ve basıklık değerlerinde yöntemlerin performansları ve referans aralıkları değerlendirilmiştir. Varsayımlardan bağımsız olan ve iki bağımsız grup için kullanılan parametrik ve parametrik olmayan etki büyüklüğü yöntemlerinin birleştirilmesi ile Meta Bulanık Etki Büyüklüğü Fonksiyonu (MBEBF) olarak adlandırılan yeni bir etki büyüklüğü yaklaşımı önerilmiştir. Simülasyon çalışmasından elde edilen sonuçlara göre parametrik ve parametrik olmayan etki büyüklüğü yöntemlerinin referans değerleri literatüre göre farklılık göstermiştir. Bu tez çalışmasında önerilen MBEBF etki büyüklüğü yaklaşımı ise değerlendirilen yöntemlere göre en düşük ortalama mutlak yüzde hata ile en iyi performansı göstermiştir.Effect size provides a more scientific approach to the size of an intervention rather than statistical significance. There are three different aspects of effect size. The first aspect is the type of information of interest; The second aspect is the functionalization of the effect size through the equation linking statistics or parameters to the effect size, and the third aspect is the value of the effect size. There are three standard effect size estimators, namely Cohen d, Glass delta and Hedge g, under the assumption of normal distribution of two independent groups. Effect size estimators Cohen d, Glass delta, and Hedge g are consistent and asymptotic as long as the assumption of normality is present. Non-parametric effect size measures have been proposed for two independent groups in cases where the populations are not normally distributed. These effect size measures are Cliff delta, Glass Rank Biserial Correlation Coefficient, and Vargha and Delanay A (VDA). In this study, Cohen d, Hedge g, Glass delta, Cliff delta, VDA and Rank-Biserial Correlation Coefficient effect size methods were explained and reference intervals were evaluated with simulation study. For non-parametric effect size methods, the performances and reference intervals of the methods were evaluated at varying skewness and kurtosis values. A new effect size approach called the Meta Fuzzy Effect Size Function (MBEBF) has been proposed by combining the parametric and non-parametric effect size methods used for two independent groups, which are independent of the assumptions. According to the results obtained from the simulation study, the reference values of the parametric and non-parametric effect size methods differed according to the literature. The MBEBF effect size approach proposed in this thesis study showed the best performance with the lowest mean absolute percentage error according to the methods evaluated

Comparison of tree-based methods used in survival data

Karar ağaçları, sınıflama ve regresyon probleminin çözümünde çok aşamalı ve ardışık bir yaklaşım ile karmaşık yapıdaki verileri aşamalı bir hale dönüştürerek basit bir karar verme işlemini gerçekleştirmektedir. Sağkalım ağaçları ve ormanları ise parametrik ve yarı parametrik modellerin popüler parametrik olmayan bir alternatifidir. Bu yöntemler diğer yöntemlere göre oldukça esnek olup daha önceden belirlenmeden etkileşimlerin otomatik olarak ortaya konulmasını sağlarlar. Koşullu çıkarsama ağaçları (KÇA) yöntemi, iyi tanımlanmış koşullu çıkarsama prosedürleri içinde ağaç tabanlı regresyon modellerinin parametrik olmayan bir sınıfıdır. Koşullu çıkarsama ağaçları yöntemi sınıflayıcı, sıralayıcı, sayısal, sansürlü ve bunlara ek olarak çoklu yanıt değişkenleri ve rasgele ölçekle ölçeklendirilmiş ortak değişkenleri içeren tüm regresyon problemlerinde uygulanabilir. Koşullu çıkarsama ormanları (KÇO), çok sayıda KÇA’nın birleştirilmesiyle gerçekleştirilen bir sağkalım ormanı yöntemidir. KÇO yöntemi, sansürlenme varlığında topluluk öğrenmesi için birleştirilmiş ve esnek bir yapı önermektedir. Bu yöntem sağdan sansürlü veriler için hastaların sağkalım zamanının tahmininde kullanılır. Rasgele sağkalım ormanları (RSO) yöntemi, rasgele ormanlar yönteminin bir uzantısıdır. Bu yöntemde rasgelelik iki şekilde tanımlanmaktadır. İlk olarak ağacın büyümesi için verinin rasgele olarak bootstrap örnekleminden çekilmesi, ikinci olarak ise ağacın her bir düğümünde ayırma için ortak değişkenlerin alt kümelere rasgele olarak seçilmesidir. RSO yöntemi, düşük genelleme hatasını sürdürürken zengin sınıf ayrımları sağlamaktadır. Bu çalışmada KÇA, KÇO ve RSO yöntemleri açıklanmış ve simülasyon çalışması ile sağkalım ormanları yöntemleri olan KÇO ve RSO’nun performansları karşılaştırılmıştır. Simülasyon çalışmasından elde edilen sonuçlara göre RSO yönteminin KÇO’ ya göre daha iyi performans gösterdiği belirlenmiştir.Decision trees, carry out a simple decision process by transforming data which are in a complex structure to a gradual form, using multi stage and sequantial approach in classification and regression problems. Survival trees and forests are popular non parametric alternatives of parametric and semi-parametric survival models. These methods are more flexible than the other methods and provide putting forward the interactions automatically which have not been determined before. Conditional inference trees (Ctree) is a non-parametric class of regression trees embedding tree-structured regression models into a well defined theory of conditional inference procedures. It is applicable to all kinds of regression problems, including nominal, ordinal, numeric, censored as well as multivariate response variables and arbitrary measurement scales of the covariates. Conditional inference forests (Cforest) is a survival forest method which is conducted by combining a large number of Ctrees. Cforest propose an unified and flexible framework for ensemble learning in the presence of censoring. The methodology is utilized for predicting the survival time of patients for right cencored data. Random survival forests (RSF) methodology extends Breiman’s random forests (RF) method. In RF, randomization is introduced in two forms. First, a randomly drawn bootstrap sample of the data is used to grow a tree. Second, at each node of the tree, a randomly selected subset of covariates are chosen as candidate variables for splitting. In addition, RSF enables to approximate rich classes of functions while maintaining low generalization error. In the present study, Ctree, Cforest and RSF methods have been explanined in detail and the performances of the survival forest methods namely Cforest and RSF have been compared with the simulation study. According to results the simulation part of the study, it is determined that the RSF method performs better than the other two tree-based method

Retrospective evaluation of the factors affecting etiology and prognosis of adult acute kidney injury

Aim: Acute kidney injury (AKI) is still an important cause of morbidity and mortality. Several factors are effective in its frequency, etiology, prognosis and mortality. In our study, we aimed to demonstrate the etiology and prognostic factors of AKI.Methods: A total of 272 patients diagnosed with AKI, who were hospitalized in the nephrology department between January 2011 and December 2015, were included in the study. In addition to the demographic characteristics of patients, clinical and laboratory findings were evaluated retrospectively.Results: Forty-seven point four percent of patients were female and 52.6% were male. The mean age of the patients was 61.6 years, the mean length of hospital stay was 13.3 days, the number of hemodialysis sessions was 1.24 and the mortality rate was 4.8%. The need and number of hemodialysis sessions were significantly higher in older patients (>65 years). The need and number of hemodialysis sessions were higher in the renal AKI group (48.7%, 1.9). The length of hospital-stay was longer and mortality rate was higher in patients with renal AKI compared to the other groups (16.4 days, 8.8%). Mortality rate, length of hospital-stay, and number of hemodialysis sessions were found to be increased significantly in patients with infection (42%).Conclusion: Etiology and accompanying infection in AKI are the most important factors affecting mortality. In addition, anemia and advanced age increase the length of hospital stay and the need for hemodialysis

Comparison between sleeve gastrectomy and exenatide on type 2 diabetic patients

Background: Diabetes and obesity are major causes of mortality and morbidity that are increasing all over the world. As obesity is a major risk factor for type 2 diabetic patients, weight loss is important in the treatment of type 2 diabetic patients. In our study, our aim was to evaluate the effects of exenatide and laparoscopic sleeve gastrectomy (LSG) in obese type 2 diabetic patients on the clinical and laboratory parameters.Methods: Twenty-five LSG and 25 exenatide patients followed up in our outpatient clinic were involved in the study.Results: At the end of the 6-month follow-up, weight loss was similar to 35.4 kg in the surgery group and 11.5 kg in the exenatide group. Although postprandial glucose and hemoglobin A1c were significantly decreased in both groups, the decrease was significantly higher in LSG group compared to the exenatide group. Although there was no significant change in fasting blood glucose (FBG) in the exenatide group, there was a significant decrease in FBG in LSG group.Conclusion: LSG is a method that should be performed up on indication and much more radical compared to exenatide administration, but appears to be a more efficient application that corrects diabetes- and obesity-related metabolic parameters compared to exenatide therapy in type 2 diabetic obese patients

Short term effect of laparoscopic sleeve gastrectomy on clinical, renal parameters and urinary ngal levels in diabetic and non diabetic obesity

Background. Although diseases such as diabetes, hypertension, obstructive sleep apnea and hyperlipidemia are clearly documented as obesity associated diseases, it is not well-known whether obesity causes renal pathologies. The aim of the present study was to evaluate the effect of weight loss following laparoscopic sleeve gastrectomy on clinical, renal parameters and urinary Neutrophil gelatinase-associated lipocalin (NGAL) levels in diabetic and non-diabetic obese patients.Methods. Nineteen morbidly obese patients (10 diabetic and 9 non diabetic) who underwent laparoscopic sleeve gastrectomy were evaluated clinically (anthropometric measurements) and biochemically before surgery and at 6 months from surgery.Results. Significant decreases in weight, BMI, FPG, PPG and HbA1c levels were observed in the diabetic group when the baseline and 6th month parameters of the patients were compared. There was also a significant decrease in SBP and DBP. At 6th month following laparoscopic sleeve gastrectomy, renal parameters such as creatinine, mAlb/creatinine, NGAL/creatinine did not differ in the diabetic group. In the nondiabetic group, serum creatinine levels were significantly decreased, but other renal parameters such as mAlb/creatinine and NGAL/creatinine were not significantly different.Conclusions. Our findings revealed significant decreases in weight, body mass index and glycemic parameters after sleeve gastrectomy in diabetic and non-diabetic patients, while no significant alteration was noted in renal functions, urinary NGAL and microalbumin levels

Effects of TNF inhibitors and an IL12/23 inhibitor on changes in body weight and adipokine levels in psoriasis patients: a 48-week comparative study

Background Psoriasis is a chronic inflammatory disease associated with obesity and metabolic syndrome. Adipokines are thought to be a link between psoriasis and obesity. Leptin, adiponectin, and omentin are bioactive adipokines thought to play a role in both metabolic comorbidities and inflammation. Anti-tumour necrosis factor alfa (anti-TNF-α) agents are effective for psoriasis treatment, although significant weight gain has been reported during anti-TNF-α therapy. The interleukin 12/23 (IL 12/23) inhibitor ustekinumab is also effective for psoriasis treatment. We compared the effects of three anti-TNF-α drugs and an IL-12/23 inhibitor on adipokines and weight gain during treatment. Patients and methods This prospective study included 80 patients (37 women, 43 men) with moderate to severe plaque psoriasis whose age and weight were matched. The patients were divided into four equal groups: etanercept, infliximab, adalimumab, and ustekinumab treatment groups. Psoriasis Area Severity Index (PASI) score, body weight (muscle and fat compartments), and leptin, adiponectin, and omentin levels were evaluated at baseline and weeks 4, 12, 24, and 48 of treatment. Results There were no differences between drug groups in terms of weight parameters or biochemical parameters at baseline. At the end of 48 weeks, there was significant weight gain in the adalimumab group. Patients who received infliximab showed significant weight gain by week 12, but in the following weeks they returned to their initial weight. Body weight reached a maximum level by week 12 in patients using etanercept, but they lost weight in the following weeks and finished the study below their initial weight. Patients using ustekinumab did not demonstrate significant weight change during the 48 weeks except at week 12. At the end of week 48, PASI75 (improvement in PASI ≥75%) response rates were approximately 85% for the ustekinumab group, 80% for the adalimumab group, 75% for the infliximab group, and 50% for the etanercept group. Leptin, adiponectin, and omentin levels were higher in the ustekinumab group at all weeks except baseline. The lowest levels were observed in the etanercept group. The treatment response rate was also lower in the etanercept group. Limitations We did not evaluate visfatin and resistin levels, insulin sensitivity, and cardiovascular risk that may be associated with weight gain and adipokine levels. Conclusions Unlike TNF inhibitors, ustekinumab does not cause significant weight changes and it increases adipokine levels more than TNF inhibitors. Adipokine levels seem to be related to the treatment response

Investigating the diagnostic potential of IL-1β, IL-10, and IL-36γ in gingival crevicular fluid in patients with different periodontal conditions

The study aimed to analyze cytokine levels, including interleukin (IL)-1β, IL-10, and IL-36γ, to investigate the link between pro- and anti-inflammatory responses in periodontal conditions and assess their potential as diagnostic biomarkers for distinguishing between different types of periodontal conditions. 80 systemically healthy non-smokers (25 periodontally healthy, 25 with gingivitis, 30 with periodontitis) were included. Clinical periodontal parameters were recorded, and gingival crevicular fluid (GCF) samples were obtained. Receiver operating characteristic (ROC) curve analysis was applied to determine the diagnostic value of cytokines. IL-36γ had the highest sensitivity for diagnosing periodontitis, although its specificity for identifying those without periodontitis was relatively low. The combination of IL-1β and IL-36γ was the most effective in differentiating periodontitis from periodontal health. IL-10 was found to be an acceptable discriminator for distinguishing gingivitis from healthy conditions. However, its sensitivity and specificity for identifying gingivitis were lower. The combination of the three cytokines showed the highest ability to distinguish between periodontitis and gingivitis. The levels of IL-1β, IL-10, and IL-36γ in GCF may provide insights into periodontal health and disease status. Further studies are needed to validate these results and explore the potential of these cytokines in periodontal disease management. All three of these cytokines exhibit exceptional diagnostic accuracy, particularly in distinguishing between chronic periodontitis and periodontal health.Moreover, the combination of IL-1β and IL-36γ stands out as the most accurate diagnostic indicator for periodontitis. This combination could serve as a robust biomarker panel for the early detection and monitoring of periodontal disease, potentially allowing for timely interventions to prevent disease progression. All three of these cytokines exhibit exceptional diagnostic accuracy, particularly in distinguishing between chronic periodontitis and periodontal health. Moreover, the combination of IL-1β and IL-36γ stands out as the most accurate diagnostic indicator for periodontitis. This combination could serve as a robust biomarker panel for the early detection and monitoring of periodontal disease, potentially allowing for timely interventions to prevent disease progression.</p