Required Sample Size Research Articles

Methodologies for the Emulation of Biomarker-Guided Trials Using Observational Data: A Systematic Review

Background: Target trial emulation involves the application of design principles from randomised controlled trials (RCTs) to observational data, and is particularly useful in situations where an RCT would be unfeasible. Biomarker-guided trials, which incorporate biomarkers within their design to either guide treatment and/or determine eligibility, are often unfeasible in practice due to sample size requirements or ethical concerns. Here, we undertake a systematic review of methodologies used in target trial emulations, comparing treatment effectiveness, critically appraising them, and considering their applicability to the emulation of biomarker-guided trials. Methods: A comprehensive search strategy was developed to identify studies reporting on methods for target trial emulation comparing the effectiveness of treatments using observational data, and applied to the following bibliographic databases: PubMed, Scopus, Web of Science, and Ovid MEDLINE. A narrative description of methods identified in the review was undertaken alongside a critique of their relative strengths and limitations. Results: We identified a total of 59 papers: 47 emulating a target trial (‘application’ studies), and 12 detailing methods to emulate a target trial (‘methods’ studies). A total of 25 papers were identified as emulating a biomarker-guided trial (42%). While all papers reported methods to adjust for baseline confounding, 40% of application papers did not specify methods to adjust for time-varying confounding. Conclusions: This systematic review has identified a range of methods used to control for baseline, time-varying, and residual/unmeasured confounding within target trial emulation and provides a guide for researchers interested in emulation of biomarker-guided trials.

Overcoming methodological barriers in electronic nose clinical studies, a simulation data-based approach

Analysis of volatile organic compounds by electronic nose (e-nose) may address gaps in non-invasive screening for neoplasia. Machine learning impacts study design and sample size requirements, but guidance on clinical study design is limited. This study evaluates how neoplasia prevalence, augmented data, and the number of e-nose devices impact sample size requirements. Simulated e-nose breath test data were created using real-world study data. We examined the effect of varying neoplasia prevalence (50%-5%) and data augmentation on model performance, as well as the impact of using multiple devices. Prediction models were developed using single value decomposition and random forest, and convolutional neural networks. Model performance was displayed as area under the receiver operating characteristics curve and F1-score. Stable model performance was defined as the phase where additional data no longer increases model performance. We found that lower neoplasia prevalence significantly increased sample size requirements, with low-prevalence settings (5%) requiring up to five times more data than high-prevalence settings (50%) for stable model performance. Model performance varied between devices, and integrating data from multiple devices required larger sample sizes. Approximately 400 data points per device at 50% prevalence, and 2100 data points at 5% prevalence, were necessary to reach stable model performance. Concluding, sample size requirements for e-nose studies are heavily influenced by disease prevalence and the number of devices used. Limiting device variability and ensuring sufficient case and control samples per device are crucial for achieving reliable predictive performance. Specific requirements will vary based on sensor and disease characteristics.ClinicalTrials.gov Identifier:Clinicaltrials.gov Identifier NCT03346005 (model study) and NCT04357158 (validation study).

The impact of learner background variables on academic burnout in online vs. face-to-face classes among students of Shiraz University of Medical Sciences having English courses

IntroductionAcademic burnout is a universal phenomenon that has impacted many students in different educational settings. The present study attempted to compare the academic burnout that students of Shiraz University of Medical Sciences (SUMs) faced in online vs. face-to-face environments. It also sought to determine the effects of learner background variables of age, academic achievement, and degree programs on selected students’ academic burnout.MethodsThe power analysis was performed using gpower to determine the required sample size, and 257 participants taking their General English courses were involved in the study. Then, cluster sampling was used to select a random sample from the students taking an English course at SUMS. An online modified version of the Maslach Burnout Inventory (MBI), measuring participants’ academic burnout, was used to represent students’ reported burnout.ResultsA paired samples t-test was performed to compare reported academic burnout in online classes vs. face-to-face environments, indicating significant differences in academic burnout between the two modalities (online vs. face-to-face), with lower levels of burnout reported for online environments. Moreover, a multivariate analysis of variance (MANOVA) was performed to determine the effects of the learner background variables of academic achievement and age on academic burnout, which manifested significant differences in burnout in face-to-face learning environments for students of different age groups. Likewise, it was illuminated that academic achievement influenced students’ burnout in face-to-face environments, as high achievers experienced significantly lower academic burnout than moderate achievers. A robust MANOVA of Pillai’s trace also indicated no significant differences between Bachelor of Science and Professional Doctorate students across the dependent variables of academic burnout in online vs. face-to-face environments.DiscussionEducators must balance workload, seek regular student feedback about lesson pace and delivery, and avoid overloading students with overdemanding assignments and projects or setting unrealistic goals and expectations. The present study has cast light on the multifaceted nature of burnout and the factors that impact academic burnout in educational settings. It can pave the way for education practitioners to follow appropriate strategies and macro-level policies to mitigate learner burnout.

Comparison of Sodium Imbalance in Diabetics and Non-Diabetics Presenting with Sepsis

Background: Patients with diabetes are more likely to get infection and, as a result, sepsis. Sepsis is the largest cause of intensive care unit (ICU) admissions, resulting in a huge healthcare burden. Despite extensive research on sepsis and electrolyte disturbances, in diabetic individuals there is a notable gap in studies comparing sodium imbalances in diabetic versus non-diabetic patients with sepsis. Therefore, the current study aims to explore these differences in sodium level in diagnosed patients of sepsis with and without diabetes. Methodology: It was a cross-sectional study conducted at Department of Medicine, Dr. Ruth K.M. Pfau Civil Hospital, Karachi from January to March 2025. The required sample size for this study after calculation was 113 patients however, the data was gathered for 120 patients 60 patients with diabetes and sepsis and other 60 without diabetes with sepsis. The study participants were recruited via non-probability consecutive sampling. The set inclusion criteria was patient of age between 18-70 years, either gender and patients presenting within 24–72 hours of sepsis onset. A 5 cc blood sample was drawn by a trained phlebotomist using aseptic techniques for serum sodium level assessment. Serum sodium levels were analyzed using flame spectrometry. All patients with sepsis were managed according to the hospital's standard treatment protocol. Data was recorded on a predesigned proforma, including the occurrence and type of sodium imbalance (hyponatremia or hypernatremia). Results: There was a significant difference (p-value <0.001) between the sodium level of diabetic and non-diabetic patients with sepsis. Most of the diabetic patients had hyponatremia (sodium level < 135 mEq/L). There was no significant difference (p-value = 0.221) in development of symptoms of sepsis among study participants of both the groups. Conclusion: Patients with sepsis and diabetes were presented with hyponatremia (sodium level < 135 mEq/L) in our study setting.

Patterns of intra-cluster correlation coefficients in school-based cluster randomised controlled trials of interventions for improving social-emotional functioning outcomes in pupils: a secondary data analysis of five UK-based studies

BackgroundThe cluster randomised trial (CRT) design is increasingly used to evaluate the impact of school-based interventions for improving social-emotional functioning outcomes in pupils. Good knowledge is required on plausible values of the intra-cluster correlation coefficient (ICC) of the outcome to calculate the required sample size in such studies. Using data from five school-based CRTs in the UK, we estimate, and describe patterns in, ICCs for social-emotional functioning outcomes.MethodsMixed effects linear regression models were fitted to estimate the ICC and variance components. Estimates for baseline data were obtained by fitting “null” models that had no predictor variables; estimates at follow-up were adjusted for trial arm status.ResultsFive hundred and twenty-nine (529) ICCs were estimated. Variation across clusters in the outcomes was present at the school, year group and classroom levels. Overall, the ICCs were not markedly different between the primary and secondary school settings. Most of the school- and classroom-level ICCs were less than 0.04 for pupil-reported outcomes and less than 0.035 for parent-reported outcomes; a notable exception for pupil-reported outcomes was for outcomes that reflect a common experience shared by children, such as school climate, where the ICCs were as large as 0.1. The ICCs for teacher-reported outcomes (up to 0.1 at the school level and 0.2 at the classroom level) were larger than for pupil- and parent-reported outcomes. In the CRT that allocated schools to trial arms and only sampled one classroom from each school, the nominal school-level ICCs for teacher-reported outcomes took values up to 0.25. ICCs for teacher-reported measures of internalising behaviour problems and pro-social behaviour were larger than for externalising behaviour problems.ConclusionsWhen randomising school clusters, sub-sampling of lower-level clusters such as classrooms should be accounted for in the sample size calculation. Teacher-reported ICCs are likely to be greater than those for pupil- and parent-reported outcomes as teachers will often provide data for many or all pupils in a given school or classroom. Differences across reporter type and across outcomes need to be considered when specifying plausible values of the ICC to calculate sample size.Trial registrationSTARS study (ISRCTN84130388); KiVa study (ISRCTN23999021); PACES study (ISRCTN23563048); PROMISE study (ISRCTN19083628); MYRIAD study (ISRCTN86619085).

Radical antegrade modular pancreatosplenectomy: Myth or reality? A systematic review and trial sequential meta-analysis.

Radical antegrade modular pancreatosplenectomy: Myth or reality? A systematic review and trial sequential meta-analysis.

ARL‐Unbiased Exponential Control Charts With Estimated Parameters: Statistical Design and Implementation

ABSTRACTThe bias of a control chart is an important factor in practical applications. Average run length (ARL)‐biased control charts have their out‐of‐control (OOC) ARL (ARLOOC) greater than the in‐control (IC) ARL (ARLin) for some values of the monitored parameter. This may cause a delayed detection of a true alarm (than a false alarm) and thus can have serious negative consequences in practice. To remedy this problem, ARL‐unbiased charts have been considered in literature but mostly in the known IC parameters case (case K). In this paper, Shewhart‐type conditional ARL‐unbiased (CARLU) charts are considered for the more practical problem of unknown IC parameters case (case U), with a focus on a deteriorating process. The popular exponential time between events (TBE) chart is considered for illustration of the ideas. Other charts can be considered along the same lines. The proposed charts are designed using both the unconditional and the conditional perspective, respectively. The required chart design constants are calculated. A published dataset is used to illustrate the methodology in a case study. Chart performance is examined via various metrics. Interestingly, it is found that tuning the chart design parameters can lead to substantial savings in the Phase I sample size requirement under the conditional perspective. To this end, some recommendations on minimum sample size are given. A summary and some concluding remarks are provided.

Exploring number of response categories in factor analysis: Implications for sample size

Factor analysis is a statistical method to explore the relationships among observed variables and identify latent structures. It is crucial in scale development and validity analysis. Key factors affecting the accuracy of factor analysis results include the type of data, sample size, and the number of response categories. While some studies suggest that reliability improves with more response categories, others find no significant relationship between the number of response categories and reliability. A key consideration is that increasing the number of response categories can introduce measurement errors, especially when there are too many categories for participants to respond accurately. The study examines how different numbers of response categories affect sample size requirements in factor analysis, particularly under misspecified and correctly specified models. MonteCarloSEM package in R was used to simulate data sets based on sample size, number of response categories, model specification, and test length. Results show that a higher number of categories helps reduce bias and improve model fit, especially in smaller samples. However, when sample sizes are small or when fewer categories are used, increasing the number of items or the number of categories can improve parameter estimation. The findings suggest that for optimal results, researchers should carefully balance sample size, number of items, and response categories, particularly in studies with categorical data.

Factors Related to Obstructive Sleep Apnea in Patients with Heart Failure and Atrial Fibrillation

Introduction: Obstructive sleep apnea (OSA) causes cardiovascular disturbances due to intermittent hypoxia, oxidative stress, systemic inflammation, excessive negative intrathoracic pressure, sympathetic activation, and increased blood pressure. These factors can impair myocardial contractility, leading to the development of heart failure and atrial fibrillation (AF). Epidemiological studies have shown a significant independent association between OSA, heart failure, and AF. This study aims to identify factors associated with obstructive sleep apnea (OSA) in patients with heart failure accompanied by atrial fibrillation. Method: This study was conducted on patients diagnosed with heart failure and atrial fibrillation hospitalized at the Integrated Heart Center of Adam Malik Hospital. Data collection began in August 2023 and continued until the required sample size was reached. This is an observational analytic study with a cross-sectional design. Results: A total of 51 patients participated in this study. The majority of respondents were male (66.7%), with most being aged between 60-69 years. The study found that the degree of OSA in heart failure patients with AF was predominantly mild (30.8%), followed by moderate (25.0%) and severe (17.3%). The average AHI value was 16.78 with a standard deviation of 14.359. Multivariate analysis identified two significant variables: smoking history and functional capacity (NYHA Class) (p > 0.05). Conclusion: A significant association was found between gender and smoking history with the occurrence of OSA in patients with heart failure and atrial fibrillation. The multivariate analysis also highlighted the significance of smoking history and functional capacity (NYHA Class) (p > 0.05).

Barriers and Facilitators to Malaysian Teachers’ Mental Health Literacy: A Study on Teachers’ Experiences

This paper investigates the issue of underdeveloped mental health literacy amongst Malaysian teachers, a problematic phenomenon that leads to a school’s inability to successfully address student mental health issues. When untreated, student mental illness can manifest in aggressive or disruptive behaviours that create an unsafe educational environment. This paper explores five Malaysian teachers’ experiences of the external factors that facilitate and hinder them from developing their mental health literacy to examine the issue of underdeveloped teacher mental health literacy. The authors employed a qualitative design where data from semi-structured interviews were analysed thematically and found eleven factors—four facilitators and seven barriers—that influence the development of teachers’ mental health literacy. The four facilitators identified were school counsellors, supportive colleagues, inclusion of mental health topics in the curriculum, and Ministry of Education programmes on teacher mental health. The seven barriers identified were superstitions, societal disbelief in mental illness, unhelpful admin staff, the ignorance of older colleagues, dismissive parents, teachers’ overwhelming workload, and teachers’ lack of time. The findings suggested that developing teacher mental health literacy is possible with the necessary support and a whole-school approach. They also imply the integral role all members of the learning community play in developing teacher MHL. Future studies can expand upon the findings by examining the factors that influence the MHL development of the other members of the school community. The small sample size and narrow participant requirements limit this study's scope.

Homogeneity test and sample size of response rates for AC 1 in a stratified evaluation design.

Gwet's first-order agreement coefficient (AC 1) is widely used to evaluate the consistency between raters. Considering the existence of a certain relationship between the raters, the paper aims to test the equality of response rates and the dependency between two raters of modified AC 1's in a stratified design and estimates the sample size for a given significance level. We first establish a probability model and then estimate the unknown parameters. Further, we explore the homogeneity test of these AC 1's under the asymptotic method, such as likelihood ratio, score, and Wald-type statistics. In numerical simulation, the performance of statistics is investigated in terms of type I error rates (TIEs) and power while finding a suitable sample size under a given power. The results show that the Wald-type statistic has robust TIEs and satisfactory power and is suitable for large samples (n≥50). Under the same power, the sample size of the Wald-type test is smaller when the number of strata is large. The higher the power, the larger the required sample size. Finally, two real examples are given to illustrate these methods.

Intention to leave the nursing profession due to mental health factors in Navarre (Spain) during the post.COVID-19 pandemic period

This study aimed to assess the intention to leave the current job or the nursing profession among nurses in the Foral Community of Navarre (Spain) during the sixth wave of the COVID-19 pandemic (October 2021-March 2022). The research also evaluated associations between this intention and nurses´ mental health status and sociodemographic characteristics. Descriptive, cross-sectional study that included nurses who worked in healthcare institutions in Navarre during the COVID-19 pandemic. A questionnaire was designed using validated scales to assess depression, anxiety, insomnia, post-traumatic stress, and the intention to leave the job or profession. The questionnaire was distributed via e-mail to all registered nurses, and data collection concluded upon reaching the required sample size. Of the 693 nurses who participated, 691 completed the questionnaire in full. Overall, 43% of respondents reported an intention to leave the nursing profession, and of these, 52% also considered leaving the current job. Nurses experiencing higher levels of anxiety and post-traumatic stress, as well as those with fewer years of professional experience, were significantly more likely to report an intention to leave. A substantial proportion of nurses in Navarre considered leaving the profession during the sixth wave of the COVID-19 pandemic, with mental health -particularly anxiety and post-traumatic stress - and limited professional experience being the key contributing factors. These findings underscore the need for targeted interventions to support nurses´ mental health, improve working conditions, and mitigate job abandonment during and after public health emergencies.

The Role of Peace Journalism in Mitigating Violence in Afghanistan: A Journalist’s Perspective

This research explores the role of peace journalism in mitigating violence in Afghanistan by examining the perspectives of Kabul’s Journalists. The study has two main objectives: to understand how peace journalism can help mitigate various forms of violence (structural, cultural, direct, ethnic, and religious) in Afghanistan and to assess the level of familiarity among journalists in Kabul with the concept of peace journalism. The study framework incorporates the theories of agenda-setting, gatekeeping, and Galtung’s peace journalism model. A survey method was employed for the research, and data were collected using a structured questionnaire. The questionnaires were distributed to 287 journalists working in Kabul's media selected through a multi-stage cluster sampling method. According to statistics provided by media support organizations, are 1,011 journalists actively working in Kabul. Using Cochran's formula, the required sample size was determined to be 278; thus, this number of questionnaires was distributed and successfully collected. The research findings indicated that employing peace journalism in media reporting can reduce violence in Afghanistan. However, the study reveals that journalists in Kabul have limited familiarity with peace journalism. Additionally, there is a significant positive relationship between journalists’ educational levels, work experience, and familiarity with peace journalism. The research further highlights that peace journalism can reduce structural, cultural, and direct violence in Afghanistan. However, it has little to no impact on mitigating ethnic and religious violence in the country.

Irrigant and intracanal medicament choices in routine endodontic practice: A cross-sectional survey of British general dentists

Abstract Introduction: Choices vary among clinicians due to personal preference or experience with disinfectants during clinical practice. Hence, the present survey aimed to evaluate the rationale behind the selection of endodontic irrigants and interappointment medications and to compare therapeutic approaches among British general dental practitioners (GDPs) with varying years of experience. Materials and Methods: A structured online questionnaire consisting of 14 questions was distributed to attendees at a dental conference in England via a QR code, along with a formal invitation to participate in the research. A sample size calculation determined the minimum required sample size of 377 GDPS from a population of 2356 British GDPs. To assess the impact of experience on disinfection protocols, clinicians were categorized by years of experience to better understand any generational differences in clinical concepts. The responses were analyzed using the Chi-square test (P < 0.05), with a 95% confidence level and a 5% margin of error. Results: Four hundred and twenty GDPs responded to the survey, representing 17.82% of the GDPs attending the conference. The results showed that sodium hypochlorite (NaOCl) is the most commonly used irrigant, with 96% (403) of respondents selecting it, and no significant differences were found between generational groups. Regarding the most important criteria for selecting an irrigant, 59.9% (243) of respondents considered NaOCl to be the most effective. Calcium hydroxide was the primary interappointment medication, used by 92.6% (389) of respondents. When grouped by years of experience, the only notable difference was in the duration for which medication remained in the root canal. Clinicians with more experience tended to leave the medication in the canal for longer periods. Conclusion: Experience was found to be the most significant factor in the choice of interappointment medication, whereas it had less influence on the selection of irrigants. The therapeutic approach varied more significantly between GDPs in different experience groups, suggesting that evolving materials and techniques in endodontics influence clinical protocols and the attitudes of practitioners.

Statistical Primer: sample size considerations for developing and validating clinical prediction models.

Clinical prediction models are statistical models or machine learning algorithms that combine information on a set of predictor variables about an individual to estimate their risk of a given clinical outcome. It is crucial to ensure that the sample size of the data used to develop or validate a clinical prediction model is large enough. If the data are inadequate, developed models can be unstable and estimates of predictive performance imprecise. This can lead to models that are unfit or even harmful for clinical practice. Recently, there have been a series of sample size formulae developed to estimate the minimum required sample size for prediction model development or external validation. The aim of this statistical primer is to overview these criteria, describe what information is required to make the calculations, and to illustrate their implementation through worked examples. The software that is available to implement the sample size criteria is reviewed and code is provided for all the worked examples.

Effects of Aerobic Exercise on The Six Minutes Walking Test and Quality of Life in EGFR Mutation Non-Small Cell Lung Cancer Patients

Background: Lung cancer reduces lung function, muscle mass, and psychological well-being, which lowers exercise capacity and quality of life. Pulmonary rehabilitation, such as aerobic exercise, can improve exercise capacity and the quality of life (QoL) in lung cancer patients. This study aimed to investigate the influence of aerobic exercise on the six-minute walking test (6MWT) and the quality of life of lung cancer patients. Methods: A clinical trial with a quasi-experimental, pretest, and post-test design was conducted on stage ≥IVa adenocarcinoma lung cancer patients who were receiving outpatient targeted therapy at the pulmonary clinic of Dr. Moewardi General Hospital for ≥1 month starting from May 2023, until the required sample size was met. The 6MWT and Functional Assessment of Cancer Therapy-Lung (FACT-L) were measured at the baseline and eight weeks ±2 weeks after aerobic exercise by walking about 15-20 minutes and breathing exercises. Results: The study included fourteen patients in the control group and fifteen patients in the aerobic group. The mean difference of 6MWT between the control and the aerobic group was 38.33 m. Functional, lung cancer subscale (LCS), total, and TOI in FACT-L showed significant differences in the increment pre-test and post-test between the control and aerobic group (P<0.05), with significant differences in pre-test and post-test of most categories in both groups, except for social. Conclusion: Aerobic exercise, psychological support, and nutrition have significantly improved the 6MWT and quality of life in lung cancer patients.

PS-SAM: propensity-score-integrated self-adapting mixture prior to dynamically and efficiently borrow information from historical data

ABSTRACT There has been growing interest in incorporating historical data to improve the efficiency of randomized controlled trials (RCTs) or reduce their required sample size. A key challenge is that the patient characteristics of the historical data may differ from those of the current RCT. To address this issue, a well-known approach is to employ propensity score matching or inverse probability weighting to adjust for baseline heterogeneity, enabling the incorporation of historical data into the inference of RCT. However, this approach is subject to bias when there are unmeasured confounders. We address this issue by incorporating a self-adapting mixture (SAM) prior with propensity score matching and inverse probability weighting to enable additional adaptation for information borrowing in the presence of unmeasured confounders. The resulting propensity score-integrated SAM (PS-SAM) priors are robust in the sense that if there are no unmeasured confounders, they result in an unbiased causal estimate of the treatment effect; and if there are unmeasured confounders, they provide a notably less biased treatment effect with better-controlled type I error. Simulation studies demonstrate that the PS-SAM prior exhibits desirable operating characteristics enabling adaptive information borrowing. The proposed methodology is freely available as the R package “SAMprior”.

Application of the comprehensive complication index and Clavien–Dindo complication classification in cardiac surgery: a retrospective study

BackgroundStandardized tools are needed to accurately assess the severity of postoperative complications in cardiac surgery, which is critical for patient management and outcome evaluation. This study aims to evaluate the application of the Clavien Dindo Complications Classification (CDCC) and Comprehensive Complications Index (CCI) in cardiac surgery.Results563 patients (76.3%) had at least one complication. The mean CCI was 22.5 ± 19.3. Patients who underwent more complex surgeries had higher CDCC grades and CCI scores. Hospitalization cost and length of stay increased with increasing CDCC grade and CCI score. The ACCI (OR: 1.334 [1.109–1.606], p = 0.002) and LVEF (OR: 0.965 [0.943–0.987], p = 0.002) were associated factors for the most severe complications. The CCI may reduce the required sample size by 20.5 times and 19.6 times compared with the most severe complication or major adverse cardiovascular and cerebrovascular events, respectively, as an endpoint.ConclusionThe CCI and CDCC can help reflect the complexity of cardiac surgery and the burden of hospitalization, providing a more accurate assessment of surgical complications. This may reduce the sample size needed for clinical trials, thus facilitating research in cardiac surgery.Clinical trial registrationChinese Clinical Trial Registry (No. ChiCTR2400084925) on May 28th, 2024. https://www.chictr.org.cn/showproj.html?proj=228499.

Headache in transgender men using gender-affirming hormone therapy: A case-control study.

This study aimed to compare the frequency, characteristics, and impact of primary headaches in transgender men (TM), cisgender men (CM), and cisgender women (CW). Gender is a social construct shaped by roles and norms and influenced by cultural and environmental factors. Studies on primary headaches typically only consider sex and generally overlook gender. This was a case-control study conducted at the Hospital das Clínicas, Universidade Federal de Pernambuco, Brazil. A pilot study comparing 25 TM and 25 CM individuals was conducted to determine sample size requirements. After that, 50 TM (cases), 50 CM (controls), and 50 CW (controls) were included. The controls were age matched to cases. A semi-structured questionnaire, the six-item Headache Impact Test (HIT-6), and the Hospital Anxiety and Depression Scale were used. Data collection occurred from April 2022 to November 2023. All the TM were taking gender-affirming hormone therapy (testosterone cypionate, 41; testosterone undecanoate/undecylenate, six; testosterone esters, three). According to the sample size calculation, adequate power was only achieved for the frequency of tension-type headache (TTH) and for headache impact. No differences were observed between TM and CW in the frequency of migraine (odds ratio [OR] 1.14, 95% confidence interval [CI] 0.45-2.91), TTH (OR 0.74, 95% CI 0.28-1.96), or headache severity (frequency ≥8 days/month: OR 0.54; 95% CI 1.18-1.63; moderate/severe intensity: OR 1.24, 95% CI 0.49-3.18; HIT-6 score ≥56 points: OR 0.66, 95% CI 0.25-1.75) (OR adjusted for higher education and depression by conditional logistic regression). The TM group exhibited significantly lower rates of all types of headache (OR 0.20, 95% CI 0.05-0.85) and TTH (OR 0.18, 95% CI 0.07-0.45) and a significantly higher prevalence of any migraine (OR 3.93, 95% CI 1.60-9.63) and migraine without aura (OR 3.12, 95% CI 1.10-8.84) compared to the CM group (OR adjusted for anxiety and depression by conditional logistic regression). There were no differences between TM and CM in headache severity (frequency, intensity, and impact). There are no differences in the headache type or severity between the TM and CW groups. TM have a higher prevalence of migraine than CM, but no difference in headache severity.

Determinants of post-cesarean delivery surgical site infection in Mekelle public hospitals, Tigray, North Ethiopia, in 2024.

Determinants of post-cesarean delivery surgical site infection in Mekelle public hospitals, Tigray, North Ethiopia, in 2024.