Tag: statistics

BMC Pediatr. 2026 Jun 22. doi: 10.1186/s12887-026-07208-4. Online ahead of print.

ABSTRACT

BACKGROUND: Antibiotic-resistant bloodstream infections are a major public health concern, particularly in children under five years of age. The objective of this study was to determine the prevalence of bloodstream infections and assess the antimicrobial resistance profiles and their associated factors among febrile children under five years of age in Bahir Dar, northwest Ethiopia.

METHODS: A cross-sectional study was conducted from November to December 2025 among 281 children under five years of age who attended the pediatric clinic of Felege Hiwot Comprehensive Specialized Hospital in Bahir Dar. Sociodemographic and clinical data were collected using a structured questionnaire through face-to-face interviews with the parents or guardians. Approximately 3 mL of venous blood was aseptically collected and cultured using standard microbiological techniques. Bacterial identification was performed based on colony characteristics and biochemical tests. Antimicrobial susceptibility testing was performed using the Kirby-Bauer disk diffusion method. Data were entered into EpiData version 3.1 and analyzed using SPSS version 26. Logistic regression analysis was used to identify factors associated with bloodstream infections, and statistical significance was set at p < 0.05.

RESULTS: The prevalence of bloodstream infection was 19.2% (54/281; 95% CI: 14.0%-24.4%). The most common isolate was Klebsiella pneumoniae (31%), followed by Enterobacter cloacae (11%), Escherichia coli (9%), and Acinetobacter baumannii (9) %. Gram-negative bacteria accounted for 80% of the isolates. Antimicrobial susceptibility testing revealed high resistance rates to commonly used antibiotics, particularly ampicillin (87.0%, 40/46), trimethoprim-sulfamethoxazole (86.3%, 44/51), and cefepime 42/54 (77.8). Resistance was also high to ciprofloxacin (68.5%, 37/54), tobramycin (68.6%, 35/51), amoxicillin-clavulanic acid (66.0%, 31/47), gentamicin (63.3%, 31/49), tetracycline (61.1%, 33/54), and chloramphenicol (60.5%, 26/43). In contrast, lower resistance rates were observed for cefotaxime (37.0%, 20/54) and meropenem (20.4%, 11/54). Significant associated factors of blood stream infections included age < 1 year (AOR = 2.11; 95% CI: 1.46-2.86), fever duration > 7 days (AOR = 2.74; 95% CI: 1.22-6.15), partially immunized children (AOR = 3.21; 95% CI: 1.08-9.51; p = 0.036), and non-immunized children (AOR = 9.87; 95% CI: 3.61-26.9; p < 0.001).

CONCLUSION: The prevalence of bloodstream infections among febrile children under five years of age was high. Younger age, fever duration > 7 days, and partially immunization and non-immunization were significant predictors of bloodstream infection. Strengthening antimicrobial stewardship, improving immunization coverage, and enhancing early diagnosis are essential to reduce the burden of bloodstream infections and combat antimicrobial resistance.

PMID:42324521 | DOI:10.1186/s12887-026-07208-4

BMC Psychiatry. 2026 Jun 21. doi: 10.1186/s12888-026-08317-1. Online ahead of print.

ABSTRACT

BACKGROUND: Schizophrenia is a severe mental disorder characterized by complex clinical presentations and marked impairments in social and occupational functioning. While antipsychotic medications are effective in managing positive symptoms, their efficacy in addressing negative symptoms, cognitive deficits, and overall improvements in social functioning and quality of life remains substantially limited.This study aims to evaluate the effects of Baduanjin combined with Computerized Cognitive Remediation Therapy (CCRT) on patients with schizophrenia, thereby contributing to the evidence base for its clinical management.

METHODS: A total of 120 hospitalized patients with schizophrenia (aged 29-64 years; 66.67% male) were recruited and randomly allocated to either an intervention group (n = 60) or a control group (n = 60). Participants in the intervention group received a combined 85-minute session (45 min of CCRT plus 40 min of Baduanjin training) five times per week, whereas the control group received CCRT alone for the same duration. Assessments of psychiatric symptoms, cognitive function, social functioning, and quality of life were conducted at baseline and post-intervention.

RESULTS: Baseline characteristics were comparable between the two groups for all outcome measures (P > 0.05). Following the 8-week intervention, within-group analyses showed significant improvements from baseline in The Neurobehavioral Cognitive Status Examination(NCSE), The Scale of Social Function in Psychosis Inpatients( SSPI), and The Schizophrenia Quality of Life Scale(SQLS) scores for both groups (all P < 0.05). In contrast, a statistically significant reduction in The Positive and Negative Syndrome Scale(PANSS) total scores was only observed in the intervention group (P < 0.05). Moreover, intergroup analysis revealed that the intervention group demonstrated significantly greater improvements across all outcome measures (NCSE, SSPI, SQLS, and PANSS) compared to the control group post-intervention (all P < 0.05).

CONCLUSION: Patients with schizophrenia showed significantly better overall efficacy with an 8-week combined treatment of Baduanjin and CCRT compared to CCRT alone, particularly in improving psychiatric symptoms (especially negative symptoms), enhancing cognitive function, restoring social functioning, and improving quality of life.

CLINICAL TRIAL REGISTRATION INFORMATION: The study protocol of this investigator-initiated randomised controlled trial was formally registered with the ISRCTN registry (registration number: ISRCTN14037337) on 12 May 2026.

PMID:42324517 | DOI:10.1186/s12888-026-08317-1

Head Face Med. 2026 Jun 22. doi: 10.1186/s13005-026-00632-y. Online ahead of print.

ABSTRACT

BACKGROUND: Dentin-cement interface can be considered a critical point in fiber post cementation. Post-space preparation may leave a smear layer and sodium hypochlorite remnants on root dentin, which can compromise bonding between fiber posts and self-adhesive resin cement. This study evaluated the effect of different post-space dentin pretreatment modalities on dentin surface characteristics and push-out bond strength of fiber posts.

METHODS: Forty-five extracted single-rooted mandibular second premolars were endodontically treated and assigned to five groups according to post-space dentin pretreatment (n = 9): 2.5% chitosan (CH), 5% apple vinegar (AV), Er,Cr:YSGG laser (ErCr), 970 nm diode laser (DL), and 0.9% saline as control group (CG). Fiber posts were cemented using self-adhesive resin cement. Specimens were sectioned into coronal, middle, and apical slices for push-out bond strength testing and failure mode analysis. One additional specimen from each group was examined by scanning electron microscopy (SEM).

RESULTS: Push-out bond strength was significantly influenced by surface treatment. The ErCr laser group showed the highest mean bond strength, followed by the chitosan, diode laser, and apple vinegar groups, all of which demonstrated significantly higher values than the control group. Differences between root regions were not statistically significant. Mixed failure was the predominant mode in all experimental groups. SEM revealed superior smear layer removal in the ErCr laser and chitosan groups, whereas the diode laser and apple vinegar groups showed only partial dentinal tubules exposure, and the control group retained a dense smear layer.

CONCLUSIONS: Post-space dentin pretreatment improved fiber post bond strength and interfacial adaptation compared with saline treatment. ErCr laser and 2.5% chitosan showed the most favorable outcomes and may represent promising conditioning strategies before fiber post cementation.

PMID:42324516 | DOI:10.1186/s13005-026-00632-y

BMC Pediatr. 2026 Jun 22. doi: 10.1186/s12887-026-07050-8. Online ahead of print.

ABSTRACT

BACKGROUND: Type 1 diabetes is a common chronic disease in adolescents, requiring continuous self-care and attention to quality of life. With the rise of digital health technologies, eHealth literacy may play a key role in promoting self-care behaviors and well-being. This study aimed to investigate the relationships between eHealth literacy, self-care behaviors, and quality of life in adolescents with type 1 diabetes.

METHODS: In this descriptive-analytical cross-sectional study, 250 adolescents with type 1 diabetes completed validated questionnaires assessing Electronic Health Literacy (eHEALS), diabetes-specific self-care behaviors (SMOD-A), and health-related quality of life (Diabetes Quality of Life for Youth [DQOLY]). Data were analyzed using descriptive statistics, Spearman’s correlation, and multiple linear regression.

RESULTS: Participants (mean age = 14.36 years; 54.8% male) mostly had low eHealth literacy (81.2%). eHealth literacy correlated positively with self-care (r = 0.43) and quality of life (r = 0.36), while self-care was strongly related to quality of life (r = 0.51; p < 0.01). Regression models explained 35% of the variance in self-care and 29% in quality of life. Mediation analysis confirmed a significant indirect effect of eHealth literacy on quality of life through self-care behaviors (β = 0.219, p < 0.05).

CONCLUSIONS: Enhancing eHealth literacy plays a key role in improving self-care behaviors among adolescents with type 1 diabetes, which is directly associated with better quality of life. The findings of this study clearly highlight the importance of promoting eHealth literacy as an essential component of targeted, technology-based educational interventions to improve diabetes management in this age group.

PMID:42324514 | DOI:10.1186/s12887-026-07050-8

BMC Cancer. 2026 Jun 22. doi: 10.1186/s12885-026-16365-9. Online ahead of print.

ABSTRACT

BACKGROUND: Childhood cancer represents a significant cause of morbidity and mortality among children under 15 years of age and is a growing public health concern, particularly in low- and middle-income countries, including Ethiopia.

OBJECTIVE: The purpose of this study was to assess factors Influencing delay to diagnosis and treatment initiation among pediatric cancer patients attending at Tikur Anbessa Specialized Hospital oncology unit in Addis Abeba, Ethiopia, in 2019.

METHODS: An institutional-based cross-sectional study involving 244 pediatric cancer patients was conducted between February and April of 2019. Data were collected from parents/caregivers using a structured questionnaire through face-to-face interviews and supported by review of medical records. Bivariate and multivariate analyses with adjusted odds ratios were employed to evaluate the association between dependent and independent factors. Statistical analysis was performed using STATA (Version 14) with a significance level of P < 0.05.

RESULT: A total of 244 children participated, with an average age of 6.4 (± SD 3.2 years). One hundred twenty-seven (52.0%) were reported as patient delays (> 30 days), while 179 (73%) were reported as health system delays. Children aged 5-9 years AOR:2.98; 95% CI,1.35, 6.57; three times delayed than children 0-4 years; where as children from rural areas AOR:2.28; 95% CI, 1.07, 4.88; were about 2.28 delayed as compared to children who come from urban. Furthermore, parents of children who visited traditional healers AOR: 7.85, 95% CI; 3.88,15.89 were more likely to be delayed as compared to their counter’s parts. Health system-related factors, such as lack of medical insurance AOR: 5.52, 95%CI: 2.61, 11.69 and first visit to a health institution AOR: 16.13, 95%CI: 4.00, 65.03, were identified as the cause of delay.

CONCLUSION AND RECOMMENDATIONS: In conclusion, prolonged patient and health system delays were significantly associated with age AOR: 2.98; 95% CI: 1.35-6.57), rural residence AOR: 2.28; 95% CI: 1.07-4.88, use of traditional healers AOR: 7.85; 95% CI: 3.88-15.89), low disease awareness, and lack of health insurance at diagnosis (AOR = 5.52; 95% CI: 2.61-11.69). To reduce delays, targeted health education for parents and healthcare providers, improved early detection and referral systems, strengthened multisectoral collaboration, expansion and decentralization of pediatrics oncology care facilities and further qualitative research to explore underlying causes of delay are recommended.

PMID:42324508 | DOI:10.1186/s12885-026-16365-9

BMC Ophthalmol. 2026 Jun 21. doi: 10.1186/s12886-026-05027-w. Online ahead of print.

ABSTRACT

BACKGROUND: Falls are among the most common safety concerns in people with visual impairment and can lead to serious consequences, including fractures, prolonged hospitalization, and even death. Patients with glaucoma are at increased risk of falls due to visual field loss, impaired motor coordination, and declines in cognitive function compared with the general population. Resting pulse rate is an easily obtainable measure in routine clinical practice; however, its contribution to fall risk prediction in patients with glaucoma has not been sufficiently investigated. To address this knowledge gap, we developed and compared multiple predictive approaches by incorporating a broad range of fall-related variables into prediction models, and we used explainable machine learning to quantify the contribution of resting pulse rate to fall risk prediction in glaucoma. In doing so, we aimed to explore the potential contribution of resting pulse rate as one of the model features in fall risk estimation, rather than as a standalone glaucoma-specific ophthalmic indicator.

METHODS: Data were obtained from the China Health and Retirement Longitudinal Study (CHARLS). We included 249 participants with self-reported physician-diagnosed glaucoma who had no history of falls at the 2015 baseline survey and completed follow-up in 2018. The outcome was the occurrence of any fall between 2015 and 2018. To further characterize baseline differences, we also included 12,297 participants without glaucoma and without a history of falls at the 2015 baseline survey for comparative analyses.Candidate predictors comprised demographic characteristics, clinical comorbidities, medication use, self-reported vision status, and relevant laboratory measures. Self-reported near and distance vision were treated as limited visual functional information available in the database and were not considered equivalent to objective glaucoma-specific ophthalmic indicators. To compare machine learning models with a conventional statistical approach, we developed a logistic regression (LR) baseline model and trained six machine learning models: random forest, XGBoost, gradient boosting decision tree (GBDT), support vector machine (SVM), k-nearest neighbors (KNN), and AdaBoost. Feature selection was performed in the training set using recursive feature elimination with 5-fold cross-validation; within each fold, feature selection was conducted using only the fold-specific training subset and evaluated on the corresponding validation subset to reduce the risk of information leakage and overly optimistic performance estimates. After determining the final feature subset, hyperparameters were tuned and models were fitted using cross-validation within the training set. Model stability was assessed using 1,000 bootstrap resamples of the training set, and we reported the area under the receiver operating characteristic curve (AUC) with 95% confidence intervals, accuracy, and F1 score. Calibration curves and decision curve analysis were used to evaluate calibration and clinical net benefit. Finally, SHAP was applied to interpret the best-performing XGBoost model.

RESULTS: A total of 249 eligible participants with glaucoma were included. During follow-up, 36 participants reported at least one fall, yielding a fall incidence of 14.46%. In contrast, among the 12,297 non-glaucoma participants included for baseline comparison, 873 reported at least one fall (7.1%; P < 0.001).In model development, the conventional logistic regression model showed the lowest discriminative performance, with an AUC of 0.676 (95% CI, 0.628-0.724). The XGBoost model achieved the best performance, with an AUC of 0.851 (95% CI, 0.812-0.886). Decision curve analysis indicated that, within a threshold probability range of 51.5% to 67.5%, the XGBoost model provided greater net benefit than the other machine learning models. SHAP-based feature importance further identified key predictors of falls in patients with glaucoma, with resting pulse rate ranking among the top contributing features in the XGBoost model.

CONCLUSION: In this study, the XGBoost model demonstrated the best performance for estimating fall risk among participants with self-reported glaucoma. SHAP analyses indicated that resting pulse rate, creatinine, age, blood urea nitrogen, frailty status, and height made relatively large contributions within the final model. Given the absence of objective ophthalmic parameters, these findings should be regarded as exploratory and interpreted cautiously. Resting pulse rate may provide supplementary information within model-based fall risk estimation, but it should not be interpreted as a standalone glaucoma-specific indicator or as evidence of causality.

PMID:42324504 | DOI:10.1186/s12886-026-05027-w

Int Wound J. 2026 Jun;23(6):e70984. doi: 10.1111/iwj.70984.

ABSTRACT

This study evaluated and compared the diagnostic accuracy of the Braden and Cubbin/Jackson Pressure Injury Risk Scales for predicting pressure injury development in adult ICU patients. In this prospective cohort study, 153 patients admitted to an adult ICU between September and November 2025 were assessed within 24 h using both scales and followed during their ICU stay. Diagnostic accuracy indices were calculated across cut-off points and optimal cut-offs were selected using the Youden J index. ROC curves were compared using the DeLong test. Precision-recall analysis and adjusted logistic regression analyses were also performed. Pressure injury developed in 37 patients (24.2%). The optimal Braden cut-off was ≤ 12, with sensitivity 43.2%, specificity 67.2%, PPV 29.6%, NPV 78.8%, LR+ 1.32, LR- 0.84 and Youden J 0.105. The optimal Cubbin/Jackson cut-off was ≤ 35, with sensitivity 73.0%, specificity 50.9%, PPV 32.1%, NPV 85.5%, LR+ 1.49, LR- 0.53 and Youden J 0.238. AUCs were 0.546 (95% CI: 0.439-0.653) and 0.605 (95% CI: 0.503-0.707), respectively; the difference was not statistically significant (p = 0.187). Precision-recall analysis showed limited predictive performance and adjusted logistic regression analyses indicated that neither cut-off was a statistically significant independent predictor of pressure injury development (p > 0.05). Both scales showed limited discriminatory accuracy. Cubbin/Jackson performed numerically better, but not significantly so; therefore, both scales should support, rather than replace, comprehensive clinical judgement in intensive care nursing.

PMID:42324497 | DOI:10.1111/iwj.70984

Pediatr Int. 2026 Jan-Dec;68(1):e70450. doi: 10.1111/ped.70450.

ABSTRACT

Quantitative brain magnetic resonance imaging has revolutionized pediatric neurodevelopment research by enabling noninvasive, reproducible, and high-resolution assessments of brain morphology across the entire brain. Advances in anatomical structure analysis and diffusion-weighted tractography now permit detailed characterization of gray and white matter, cortical thickness, surface area, gyrification, and fiber integrity throughout development. Automated processing pipelines, including FreeSurfer, FSL, and CIVET, have supported large-scale analyses, while harmonization frameworks and normative growth curves have facilitated clinical translation. Diffusion tensor imaging (DTI) provides complementary insights into white matter microstructure, revealing neurodevelopmental trajectories and disorder-specific connectivity alterations. These approaches have identified structural biomarkers in multiple conditions, including reduced nucleus accumbens volume and ventricular enlargement in autism spectrum disorder (ASD), as well as early amygdala overgrowth and glymphatic dysfunction that may predict ASD onset. Despite these advances, several challenges remain, such as inter-scanner variability, age-dependent processing limitations, and the lack of validated individual-level biomarkers. Standardization of imaging protocols and robust statistical harmonization will be essential to overcome these obstacles and enable longitudinal, patient-specific assessments. The incorporation of quantitative magnetic resonance imaging into clinical workflows holds promise for early diagnosis, individualized monitoring, and therapeutic stratification of neurodevelopmental and genetic disorders. Ultimately, comprehensive morphometric and diffusion-based profiling will advance understanding of brain morphogenesis and drive precision medicine in pediatric neurology.

PMID:42324486 | DOI:10.1111/ped.70450

J Ethnobiol Ethnomed. 2026 Jun 21. doi: 10.1186/s13002-026-00919-z. Online ahead of print.

ABSTRACT

BACKGROUND: Domestication and conservation research often relies on single-species frameworks, which can obscure how Indigenous management practices applied to multiple related taxa may interact to shape shared gene pools. Studies of crops such as manioc/cassava (Manihot esculenta), yam (Dioscorea spp.), sorghum (Sorghum spp.), and Amazonian treegourd (Crescentia spp.) demonstrate that domestication frequently involves interactions among multiple cultivated and wild or semi-managed relatives. However, little is known about how these dynamics operate within the genus Xanthosoma, particularly in the Ecuadorian upper Amazon, a key center of diversity and domestication history for the genus. This gap limits understanding of how Indigenous management practices may influence the maintenance, erosion, or redirection of genetic diversity, with implications for crop improvement, resilience under changing environmental conditions, and the identification of underutilized plant resources.

METHODS: We combined ethnobotanical fieldwork in the Runa community of Mondayacu-including structured and unstructured interviews, participant observation, and genus-focused walks-with a national-level syntheses of herbarium records and ethnobotanical literature to contextualize Xanthosoma diversity and use across Ecuador. Interview responses were topically coded and summarized as aggregated frequencies, with patterns visualized using bar graphs. Descriptive statistics summarized reported management, while qualitative quotations and participant observation grounded interpretation.

RESULTS: Participants reported no current cultivation of Xanthosoma sagittifolium, despite its historical importance in Mondayacu and broader global use. In contrast, participants described a spectrum of management practices for lalu (Xanthosoma purpureomaculatum), ranging from eradication to selective retention for medicinal, zootechnical, and ritual uses. Lalu was the most commonly observed Xanthosoma species during fieldwork and was perceived as highly persistent, rapidly regrowing and spreading across forests and semi-managed areas. Decisions to remove or retain plants were trait- and context-dependent, with individuals exhibiting desirable characteristics (e.g., large, deep green leaves, minimal pest damage) preferentially spared or relocated near houses or gardens. National-level herbarium and ethnobotanical synthesis documented broader Xanthosoma species diversity, multifunctional uses, and possible selection pressures across Ecuadorian Amazonian Indigenous groups.

CONCLUSIONS: Building on evidence from other crop systems, our findings suggest that domestication dynamics in Xanthosoma are not fully captured by a single-species framework. In a key center of Xanthosoma diversity and domestication history, differential management of multiple related species may contribute to shaping patterns of persistence and diversity within the genus. While this study does not directly measure genetic change, it identifies ethnobotanical processes that may influence the distribution and maintenance of diversity across related taxa, including those in secondary and less-studied gene pools. Approaches that account for genus-level diversity and Indigenous management practices may therefore improve understanding of domestication processes and support conservation of genetic diversity, crop improvement, and the identification of underutilized plant resources. These findings also contribute to decolonizing domestication research by highlighting how Indigenous knowledge systems and management practices shape the structure and future of crop diversity.

PMID:42324484 | DOI:10.1186/s13002-026-00919-z

Nutr Metab (Lond). 2026 Jun 21. doi: 10.1186/s12986-026-01160-x. Online ahead of print.

ABSTRACT

BACKGROUND: Obstructive sleep apnea (OSA) is characterized by recurrent upper airway obstruction during sleep and is frequently accompanied by dyslipidemia. However, the molecular mechanisms linking lipid metabolism to OSA remain incompletely understood. This study aimed to investigate the association between blood lipid levels and OSA and explore potential underlying molecular pathways.

METHODS: Data from the National Health and Nutrition Examination Survey (NHANES) 2005-2008 and 2015-2018 were analyzed to evaluate the associations between OSA and blood lipid parameters using multivariable regression and sensitivity analyses. Additionally, OSA-related transcriptomic data (GSE135917) were obtained from the Gene Expression Omnibus (GEO), and lipid metabolism-related genes were retrieved from the Molecular Signatures Database (MSigDB). Differentially expressed lipid metabolism-related genes (DELMRGs) were identified through data integration. Machine learning approaches, protein-protein interaction network analysis, and receiver operating characteristic analysis were applied to identify key genes. Gene set enrichment analysis (GSEA) was performed to elucidate associated biological pathways, and transcription factor-gene and gene-microRNA regulatory networks were constructed using NetworkAnalyst and Cytoscape.

RESULTS: Analysis of NHANES data showed that triglyceride (TG) and low-density lipoprotein cholesterol (LDL-C) levels were positively associated with OSA, whereas high-density lipoprotein cholesterol (HDL-C) levels was inversely associated (all p < 0.001). A nonlinear, inverted U-shaped association between TG levels and OSA risk was also observed (p for nonlinearity < 0.05). Transcriptomic analysis identified 34 DELMRGs, among which CYP3A4, CYP4A22, and MED18 emerged as key genes. GSEA revealed pathways potentially involved in lipid metabolism and OSA pathophysiology, while regulatory network analyses further supported the biological relevance of these genes.

CONCLUSIONS: This study demonstrates that dyslipidemia characterized by elevated TG and LDL-C levels and reduced HDL-C levels is associated with an increased likelihood of OSA, and identifies three DELMRGs that may be involved in OSA pathophysiology. These findings provide exploratory mechanistic insights and offer a basis for future studies to further investigate the role of lipid metabolism in OSA.

PMID:42324483 | DOI:10.1186/s12986-026-01160-x