Risk Factors and Clinical Predictors of Suicidal Behaviors and Non-Suicidal Self-Injury Among Pediatric Psychiatry Emergency Admissions Pre- and Post-Pandemic: A Retrospective Coho... by Roxana Șipoș, Tudor Văidean, Elena Predescu

“…The random forest model featured a slightly different order of the main predictors and highlighted the importance of additional predictors, such as prior suicide attempts, gender, and past non-suicidal self-injury. NSSI was mainly predicted by a history of self-harm (OR = 52.437; <i>p</i> < 0.001), the number of comorbid psychiatric disorders (OR = 1.709; <i>p</i> = 0.003), and conduct disorder (OR = 0.184; <i>p</i> < 0.001), to which are added, according to random forest models, new predictors, such as borderline personality disorder, suicidal ideation, and school performance. …”
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Randomized Controlled Trial of Polyethylene Glycol versus Oral Sodium Phosphate for Bowel Preparation in Unsedated Colonoscopy by Dong Yang, Ke Tao, Geng Chen, Luping Zhang, Qingying He, Hong Xu

“…There were no significant differences in gender, body mass index, and history of abdominal surgery between the two groups. …”
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Gaining Insight into Operative Performance: Analysis of an Automated 360-Degree Feedback Tool Among Perioperative Staff by Stefanie J. Soelling, MD, MPH, Robert D. Sinyard, MD, Lauren Spigel, MPH, Max Riley, MD, Paul Gregory, PhD, Nick Perdomo, MS, Yves Sonnay, MScPH, Steven Yule, PhD, Steven J. Fishman, MD, Douglas S. Smink, MD, MPH, FACS

“…There was no difference in mean scores based on gender, age, or years of tenure. Six themes emerged from the interviews: initial reactions, utility, additional needs, other feedback mechanisms, reciprocal feedback, and logistical challenges. …”
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Improvement in the effective cataract surgical coverage in Malaysia: evidence of impact from a mobile cataract outreach program by Mohamad Aziz Salowi, Nyi Nyi Naing, Norasyikin Mustafa, Wan Radziah Wan Nawang, Siti Nurhuda Sharudin, Mohd Aziz Husni

“…However, there was no significant gender difference in eCSC. Comparing NES II (2014) and NES III (2023) at various levels of cataract surgical threshold, eCSC improved within the range of 13.8-19.2% and 18.6-23.8% for Eastern and Sarawak, respectively. …”
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Socio-demographic differences in the prevalence of cardiovascular diseases and the association with risk factors in the population of Serbia by Šašić Bojana M., Čanković Dušan K., Mijatović-Jovanović Vesna P., Ukropina Snežana N., Ostojić Zorana Z., Milijašević Dragana S., Stamenković Kristina D., Čanković Sonja I.

“…Results: By analyzing the data obtained from this research, it was estimated that every ninth resident of Serbia (11.2%) suffers from some form of cardiovascular diseases, with a statistically significant difference observed in the prevalence of cardiovascular diseases in relation to gender, age, income, education, self-assessment of health and attitudes towards health and risk factors, except for physical activity. …”
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Late-onset first epileptic seizure and cerebral small vessel disease: role of juxtacortical white matter lesions by Adrian Nasca, Adrian Nasca, Leo Sokolovič, Leo Sokolovič, Oliver Koprda, Patrick Haage, Patrick Haage, Thorsten Schmidt, Juraj Kukolja, Juraj Kukolja

“…A voxel-based morphometry (VBM) analysis was additionally performed on T1 weighted sequences using the automated SPM12 based CAT12 software.ResultsComparing intrapersonal volume ratios adjusted for the effects of gender and age, we found that the WML distribution was shifted to the juxtacortical compartment in LOFES patients. …”
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Digital sleep phenotype and wrist actigraphy in individuals at clinical high risk for psychosis and people with schizophrenia spectrum disorders: a systematic review and meta-analy... by Andrea Cipriani, Edoardo Giuseppe Ostinelli, John Torous, Paolo Brambilla, Philip McGuire, Dominic Oliver, Rosario Aronica, Charlotte Austin

“…Factors such as antipsychotic medications (pseudo-R²=88.14%), age (38.89%) and gender (26.29%) partially explained the heterogeneity between subgroups. …”
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Resistant Hypertension and Obstructive Sleep Apnea in the Primary-Care Setting by M. Demede, A. Pandey, F. Zizi, R. Bachmann, M. Donat, S. I. McFarlane, G. Jean-Louis, G. Ogedegbe

“…Logistic regression analysis, adjusting for effects of age, gender, and medical co morbidities, showed that patients with RH were nearly 2.5 times more likely to be at high OSA risk, relative to those with hypertension (OR = 2.46, 95% CI: 1.03–5.88, P<.05). …”
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Integration of simulation-based medical education: Student satisfaction and self-confidence at Faculty of Medicine, Jazan University, Saudi Arabia by Abuobaida Yassin

“…The participants displayed a balanced gender distribution (46.3% being male and 53.7% female). …”
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The Potential of Digital Storytelling as an Ethnographic Research Technique in Social Sciences by Oğuz Hatice Şule

“…We wanted to understand if gender differentiates the field research experiences. …”
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Perceptions of Fairness of Support Between Older Parents and Adult Children by Anna Willems, Dimitri Mortelmans, Anina Vercruyssen

“…Besides general contrasts and similarities between child–parent support perspectives, the analysis looked into differences regarding gender and legal relationships. Our findings only found gendered care expectations. …”
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Change of Body Composition and Adipokines and Their Relationship with Insulin Resistance across Pubertal Development in Obese and Nonobese Chinese Children: The BCAMS Study by Lu Xu, Ming Li, Jinhua Yin, Hong Cheng, Miao Yu, Xiaoyuan Zhao, Xinhua Xiao, Jie Mi

“…Our results demonstrated that gender-specific FAT% and leptin changed with pubertal development. …”
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Mycological Profile and Associated Factors Among Patients with Dermatophytosis in Astana, Kazakhstan by Alma Aimoldina, Ainura Smagulova, Gulnar Batpenova, Nellie Konnikov, Togzhan Algazina, Zulfiya Jetpisbayeva, Dinara Azanbayeva, Darkhan Amantayev, Vladimir Kiyan

“…Several factors were significantly associated with an increased risk of dermatophytosis, including the following: male gender (AOR = 1.97), age 1–10 years (AOR = 3.80), living in rural areas (AOR = 2.30), visiting public bathhouses (AOR = 2.32), visiting massage parlors (AOR = 1.39), contact with cats (AOR = 2.32), family history of dermatophytosis (AOR = 3.04), and sexual contact with an infected or unknown partner (AOR = 3.08). …”
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Influence of Type 1 Diabetes Mellitus on the Ocular Biometry of Chinese Children by Ying Xiao, Tao Li, Yan Jia, Shanshan Wang, Chenhao Yang, Haidong Zou

“…The mean age of T1DM group and control group was 10.59 ± 3.40 years and 9.55 ± 1.89 years, respectively, and the differences between age and gender were not significant (p=0.052, p=0.700). The mean LT in T1DM group (3.49 ± 0.18 mm) was thicker than that in the control group (3.40 ± 0.16 mm) (p=0.018), the mean ACD in T1DM group (3.52 ± 0.26 mm) was shallower than that in the control group (3.72 ± 0.26 mm) (p<0.001), and there were no significant differences of CCT, K1, K2, AL, and SE (p=0.088, p=0.672, p=0.821, p=0.094, and p=0.306, respectively). …”
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Endocrinopathies after Allogeneic and Autologous Transplantation of Hematopoietic Stem Cells by Francesco Orio, Giovanna Muscogiuri, Stefano Palomba, Bianca Serio, Mariarosaria Sessa, Valentina Giudice, Idalucia Ferrara, Libuse Tauchmanovà, Annamaria Colao, Carmine Selleri

“…Our analysis further provides evidence that main recognized risk factors for endocrine complications after HSCT are the underlying disease, previous pretransplant therapies, the age at HSCT, gender, total body irradiation, posttransplant derangement of immune system, and in the allogeneic setting, the presence of graft-versus-host disease requiring prolonged steroid treatment. …”
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A Comparison of Urine Dilution Ability between Adult Dominant Polycystic Kidney Disease, Other Chronic Kidney Diseases, and Healthy Control Subjects: A Case-Control Study by M. H. Malmberg, F. H. Mose, E. B. Pedersen, J. N. Bech

“…The three groups were age and gender matched, and the patient groups had similar renal function. …”
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Intentional saccadic eye movements in patients with vestibular migraine by Pan Gu, Jing Feng, Lipeng Cai, Huimin Fan, Hailing Wang, Xiaokun Geng, Yuchuan Ding

“…The VM group and control group matched for age and gender were collected from Beijing Luhe Hospital affiliated with Capital Medical University, between June 2021 and May 2022. …”
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Factors Associated with Midterm Visual Field Variability in Patients with Stable Glaucoma by Maria Emília V. Guimarães, Carolina P. B. Gracitelli, Syril Dorairaj, Fábio N. Kanadani, Tiago S. Prata

“…Baseline data assessed were age, gender, educational level, intraocular pressure (IOP), central corneal thickness, best-corrected visual acuity, spherical equivalent, number of hypotensive eye drops, type of glaucoma, number of VFs performed, follow-up in years, lens status, visual field index (VFI) values from the last 5 VF (standard automated perimetry (SAP)) tests, the presence or absence of central scotoma in the VF test, and the level of glaucomatous damage according to the VF mean deviation (MD) index of the last VFs. …”
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Pulse Wave Velocity as Marker of Preclinical Arterial Disease: Reference Levels in a Uruguayan Population Considering Wave Detection Algorithms, Path Lengths, Aging, and Blood Pres... by Ignacio Farro, Daniel Bia, Yanina Zócalo, Juan Torrado, Federico Farro, Lucía Florio, Alicia Olascoaga, Walter Alallón, Ricardo Lluberas, Ricardo L. Armentano

“…A conservative approach was used, and we excluded symptomatic subjects; subjects with history of cardiovascular (CV) disease, diabetes mellitus or renal failure; subjects with traditional CV risk factors (other than age and gender); asymptomatic subjects with atherosclerotic plaques in carotid arteries; patients taking anti-hypertensives or lipid-lowering medications. …”
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What are the important factors influencing the physical activity level of junior high school students: a cross-sectional survey by Huijun Ma, Xuefeng Li, Chengliang Ma, Da Teng

“…Schools should develop and implement tailored physical education curricula addressing gender and grade differences. Furthermore, schools and local governments should invest in high-quality sports equipment and facilities.…”
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