Sample size, power and effect size revisited: simplified and practical approaches in pre-clinical, clinical and laboratory studies

Calculating the sample size in scientific studies is one of the critical issues as regards the scientific contribution of the study. The sample size critically affects the hypothesis and the study design, and there is no straightforward way of calculating the effective sample size for reaching an accurate conclusion. Use of a statistically incorrect sample size may lead to inadequate results in both clinical and laboratory studies as well as resulting in time loss, cost, and ethical problems. This review holds two main aims. The first aim is to explain the importance of sample size and its relationship to effect size (ES) and statistical significance. The second aim is to assist researchers planning to perform sample size estimations by suggesting and elucidating available alternative software, guidelines and references that will serve different scientific purposes

Association of serum ADMA, SDMA and L-NMMA concentrations with disease progression in COVID-19 patients

IntroductionThis study determines and compares the concentrations of arginine and methylated arginine products ((asymmetric dimethylarginine (ADMA), symmetric dimethylarginine (SDMA), n-monomethyl-1-arginine (L-NMMA) and homoarginine (HA)) for assessment of their association with disease severity in serum samples of COVID-19 patients. Materials and methodsSerum arginine and methylated arginine products of 57 mild-moderate and 29 severe (N = 86) COVID-19 patients and 21 controls were determined by tandem mass spectrometry. Moreover, the concentrations of some of the routine clinical laboratory parameters -neutrophil lymphocyte ratio (NLR), C-reactive protein, ferritin, D-dimer, and fibrinogen measured during COVID-19 follow-up were also taken into consideration and compared with the concentrations of arginine and methylated arginine products. ResultsSerum ADMA, SDMA and L-NMMA were found to be significantly higher in severe COVID-19 patients, than in both mild-moderate patients and the control group (P < 0.001 for each). In addition, multiple logistic regression analysis indicated L-NMMA (cut-off =120 nmol/L OR = 34, 95% confidence interval (CI) = 3.5-302.0, P= 0.002), CRP (cut-off = 32 mg/L, OR = 37, 95% CI = 4.8-287.0, P < 0.001), and NLR (cut-off = 7, OR = 22, 95% CI = 1.4-335.0, P = 0.020) as independent risk factors for identification of severe patients. ConclusionsThe concentration of methylated arginine metabolites are significantly altered in COVID-19 disease. The results of this study indicate a significant correlation between the severity of COVID-19 disease and concentrations of CRP, NLR and L-NMMA

Investigation of the relationship between cord clamping time and risk of hyperbilirubinemia

Background: Although the relationship between umbilical cord clamping time and various parameters such as hemoglobin (Hb) levels, iron deficiency, and risk of neonatal jaundice has previously been studied, to the best of our knowleadge there have been no studies investigating the relationship between cord clamping time and the risk of significant hyperbilirubinemia. We aimed to investigate the relationship between the time of umbilical cord clamping and transcutaneous bilirubin (TcB) measurements made on various postnatal hours, Hb and serum total bilirubin (STB) levels measured on postnatal 4th day, and the risk of development of significant hyperbilirubinemia requiring phototherapy treatment. Methods: Eligible newborns were divided into two groups on the basis of the time of cord clamping: those clamped late (60 seconds or more; Group I) and those clamped early (less than 60 seconds; Group II). Groups were compared with respect to the parameters of cord Hb, postnatal TcB measurements at 6th, 48th, 96th and 168th hours, and 96th hour Hb, STB and direct bilirubin levels. Results: TcB levels at the 96th and 168th hour were significantly higher in Group I when compared to Group II (p < 0.001 and p < 0.001, respectively). The 96th hour STB level was significantly higher in Group I when compared to Group II (p < 0.001). The need of phototherapy requirement was higher in Group I when compared to Group II (p=0.001). Increase in cord blood Hb for each 1 gr/dl caused a 3.94-fold increased risk in the requirement of phototherapy treatment. Cord clamping time showed statistically significant positive correlations with both cord blood and 96th hour venous Hb levels, with both 96th hour and 168th hour TcB levels, and with 96th hour STB levels. Conclusions: Newborns whose cords are clamped late should be followed up closely with respect to high postnatal bilirubin levels and other risks associated with significant hyperbilirubinemia requiring phototherapy treatment

Exposure to Perchlorate in Lactating Women and Its Associations With Newborn Thyroid Stimulating Hormone

Background: Perchlorate, thiocyanate, and nitrate can block iodide transport at the sodium iodide symporter (NIS) and this can subsequently lead to decreased thyroid hormone production and hypothyroidism. NIS inhibitor exposure has been shown to reduce iodide uptake and thyroid hormone levels; therefore we hypothesized that maternal NIS inhibitor exposure will influence both maternal and newborn thyroid function.Methods: Spot urine samples were collected from 185 lactating mothers and evaluated for perchlorate, thiocyanate, and nitrate concentrations. Blood and colostrum samples were collected from the same participants in the first 48 h after delivery. Thyroid hormones and thyroid-related antibodies (TSH, fT3, fT4, anti-TPO, anti-Tg) were analyzed in maternal blood and perchlorate was analyzed in colostrum. Also, spot blood samples were collected from newborns (n = 185) between 48 and 72 postpartum hours for TSH measurement. Correlation analysis was performed to assess the effect of NIS inhibitors on thyroid hormone levels of lactating mothers and their newborns in their first 48 postpartum hours.Results: The medians of maternal urinary perchlorate (4.00 μg/g creatinine), maternal urinary thiocyanate (403 μg/g creatinine), and maternal urinary nitrate (49,117 μg/g creatinine) were determined. Higher concentrations of all three urinary NIS inhibitors (μg/g creatinine) at their 75th percentile levels were significantly correlated with newborn TSH (r = 0.21, p &lt; 0.001). Median colostrum perchlorate level concentration of all 185 participants was 2.30 μg/L. Colostrum perchlorate was not significantly correlated with newborn TSH (p &gt; 0.05); however, there was a significant correlation between colostrum perchlorate level and maternal TSH (r = 0.21, p &lt; 0.01). Similarly, there was a significant positive association between colostrum perchlorate and maternal urinary creatinine adjusted perchlorate (r = 0.32, p &lt; 0.001).Conclusion: NIS inhibitors are ubiquitous in lactating women in Turkey and are associated with increased TSH levels in newborns, thus signifying for the first time that co-exposure to maternal NIS inhibitors can have a negative effect on the newborn thyroid function

Sample size, power and effect size revisited: simplified and practical approaches in pre-clinical, clinical and laboratory studies.

Calculating the sample size in scientific studies is one of the critical issues as regards the scientific contribution of the study. The sample size critically affects the hypothesis and the study design, and there is no straightforward way of calculating the effective sample size for reaching an accurate conclusion. Use of a statistically incorrect sample size may lead to inadequate results in both clinical and laboratory studies as well as resulting in time loss, cost, and ethical problems. This review holds two main aims. The first aim is to explain the importance of sample size and its relationship to effect size (ES) and statistical significance. The second aim is to assist researchers planning to perform sample size estimations by suggesting and elucidating available alternative software, guidelines and references that will serve different scientific purposes

Eisenmenger Syndrome: Identifying The Clues For Arrhythmia

Objective: The aim of this case-controlled, cross-sectional study is to investigate the tendency towards arrhythmia using noninvasive arrhythmia markers (QT dispersion and heart rate variability) in children with Eisenmenger syndrome. Methods: We studied 23 patients, whose pulmonary-to-systemic resistance ratio was calculated to be greater than 0.75, and who were diagnosed as Eisenmenger syndrome between 1990 and 2001. Twenty healthy children were studied as the control group. Electrocardiographic recordings with calculation of (IT dispersion, Holter monitoring, echocardiographic studies and heart rate variability (HRV) analysis were performed in both groups. Catheterization records were analyzed in all the patients. Results: (IT and QTc dispersion were higher (p=0.007 and p=0.006, respectively) and PR interval was longer (p=0.009) in the patients with Eisenmenger syndrome, than those in the control group. In addition, low frequency component, high frequency component, very low frequency component, and total power, obtained from HRV analysis were significantly lower in the patients with Eisenmenger syndrome (p=0.001, p=0.006, p=0.009 and p=0.011, respectively). Evaluation of Holter recordings revealed pathologic findings in 21.7% of the patients with Eisenmenger syndrome. Pulmonary-to-systemic resistance ratio of the patients with pathologic Holter findings were higher than in the patients with normal Holter recordings (p=0.011). It was also shown that there was a positive correlation between OT dispersion and pulmonary-to-systemic resistance ratio (p=0.048, r=0.416) and between (IT dispersion and PR interval (p=0.009, r=0.532) in the patients with Eisenmenger syndrome. Conclusion: Dispersion of repolarization, being associated with high pulmonary-to-systemic resistance ratio, is increased and autonomic modulation of heart rate is impaired in patients with Eisenmenger syndrome. These findings suggest that arrhythmia risk for patients with Eisenmenger syndrome is higher than in normal controls.Wo