Tag: pubmed

Breast Cancer Res. 2026 Jan 16. doi: 10.1186/s13058-025-02204-5. Online ahead of print.

ABSTRACT

BACKGROUND: In the years following pregnancy, breast cancer risk is elevated, particularly for hormone receptor negative (HR-) tumors. Exposure to high maternal circulating estrogens, when the breast is vastly remodeling in structure and morphology, has been associated with HR- tumor risk. Estrogen metabolite profiles in nonpregnant women, notably the ratio of 2:16 hydroxylation (OH) pathway metabolites, are associated with postmenopausal breast cancer development; whether estrogen metabolism during pregnancy influences subsequent HR- breast cancer risk is unknown.

METHODS: We conducted a population-based case-control study in women 19-39 years identified in the Finnish Maternity Cohort Biobank and linked with the Finnish Cancer Registry to identify breast cancer diagnoses within 20 years of pregnancy. Estrogens and metabolites were measured using highly reliable and sensitive LC-MS/MS methods in serum collected during the first and second trimesters of pregnancy. Included were invasive, ER-/PR- breast cancer cases (n = 449) and controls (n = 449) matched on maternal age at index pregnancy, parity, calendar year of serum collection, gestational week of blood collection, and number of sample freeze/thaw cycles. Associations between the estrogens and breast cancer risk were estimated using odds ratios (ORs) with 95% confidence intervals (CIs) from conditional logistic regression models.

RESULTS: The median years of follow-up between blood collection and breast cancer diagnosis/control selection was 9 (range 0-19). Ninety-three percent of cases were < 50 years of age at breast cancer diagnosis. Total estrogens were positively associated with ER-/PR- breast cancer (OR associated with a doubling of total estrogens 1.16; 95% CI 1.02-1.32), as were metabolites in the 16-pathway including estriol [OR 1.11; 95% CI 1.01-1.22], 16-epiestriol [OR 1.11; 95% CI 1.01-1.21)], 17-epiestriol [OR 1.06; 95% CI 1.01-1.13], and total 16-hydroxylation pathway metabolites [OR 1.11; 95% CI 1.00-1.24]. There was no clear association with the ratio of 2:16 hydroxylation pathway metabolites. Some associations differed by parity, age at diagnosis, and gestational timing of blood collection, but interactions were not statistically significant. Results were similar when restricted to cases occurring within 15 years since pregnancy.

CONCLUSION: This prospective study demonstrated positive associations of estrogen metabolites in pregnancy and risk of mostly premenopausal ER-/PR- breast cancer, but the magnitudes varied by metabolite. No strong or consistent pattern for one metabolic pathway emerged suggesting that total estrogen concentrations during pregnancy are associated with subsequent HR- breast cancer development, regardless of how they are metabolized.

PMID:41546058 | DOI:10.1186/s13058-025-02204-5

Scand J Trauma Resusc Emerg Med. 2026 Jan 17. doi: 10.1186/s13049-025-01542-9. Online ahead of print.

ABSTRACT

INTRODUCTION: In situ simulation (ISS) is a popular teaching method which uses simulated scenarios occurring in the actual clinical work environment of the learners. Our study aimed to compare the feasibility, safety, and identification of latent safety threats (LSTs) of two types of ISS in the Emergency Department (ED): announced and unannounced.

METHODS: We conducted a mixed method study at a Level-1 trauma center ED, using announced and unannounced ISS sessions. Research Assistants conducted semi-structured individual interviews to measure acceptability, implementation, and practicality. We also assessed implementation and patient safety using quantitative parameters (number of cancelled ISS sessions, ED wait times, patients who left without being seen, latent safety threats). We performed thematic content analyses for the qualitative data. Quantitative data were analysed using descriptive statistics and linear mixed-effects modelling.

RESULTS: In total, 84 emergency professionals participated in 18 simulations; 5 were unannounced and 13 were announced. Three main themes emerged from the interviews: the positive impact of ISS on patient safety, the preference for announced ISS, and the stress induced by ISS. The comparison of safety parameters showed no differences between both ISS modalities except for an increased number of patients leaving without being seen after unannounced ISS.

CONCLUSION: Our study found that both announced and unannounced in situ simulations are safe and practical for emergency medicine. They do not affect patient safety, or the number of latent safety threats. However, unannounced simulations were less feasible during a pandemic.

PMID:41546054 | DOI:10.1186/s13049-025-01542-9

BMC Surg. 2026 Jan 16. doi: 10.1186/s12893-026-03500-3. Online ahead of print.

ABSTRACT

INTRODUCTION: Firearm injuries continue to be a major cause of trauma-related morbidity and mortality worldwide. Abdominal firearm injuries are particularly critical due to the high risk of organ damage, hemorrhage, and sepsis. In trauma management, time to surgical intervention is considered one of the most decisive factors affecting survival. However, the evidence regarding the relationship between operating room (OR) access time and mortality remains inconsistent in the current literature.

AIM: This study aimed to evaluate the effect of the time to emergency surgery on mortality in patients presenting with isolated intra-abdominal firearm injuries. Additionally, it sought to identify clinical, hemodynamic, and organ-specific factors associated with early mortality.

METHODS: This retrospective study included 121 adult patients who presented to the Emergency Department of Adana City Training and Research Hospital between January 1, 2018, and July 31, 2024, with isolated intra-abdominal gunshot injuries and underwent emergency surgery. Demographics, comorbidities, vital signs, laboratory parameters, imaging findings, organ injuries, OR access times, and clinical outcomes were analyzed. Statistical comparisons were performed using appropriate parametric and non-parametric tests, with a significance threshold of p < 0.05.

RESULTS: Of the patients, 93.4% were male, and the median age was 34 years. The overall mortality rate was 6.6%. Mortality was significantly associated with chronic ischemic heart disease, colonic injury, and intra-abdominal vascular injury (p < 0.05). Non-survivors exhibited significantly lower blood pressure, hemoglobin, hematocrit, oxygen saturation, and pH levels and significantly higher heart rate, lactate, shock index, modified shock index, CK-MB, and hs-Troponin-I values (p < 0.05). Interestingly, time to the operating room was shorter in non-survivors (p = 0.002), reflecting more severe initial clinical presentation rather than improved outcomes.

CONCLUSION: In intra-abdominal firearm injuries, mortality is influenced more by the severity of organ damage and the patient’s hemodynamic condition at presentation than by OR access time alone. Early recognition of critical injuries, rapid resuscitation, and timely surgical intervention remain essential for improving survival outcomes. Clinical indicators such as lactate level, shock index, and hemodynamic parameters may serve as valuable predictors of early mortality.

PMID:41546051 | DOI:10.1186/s12893-026-03500-3

BMC Oral Health. 2026 Jan 17. doi: 10.1186/s12903-026-07660-9. Online ahead of print.

ABSTRACT

BACKGROUND: There has been a notable increase in artificial intelligence (AI) studies in dentistry. However, the inadequate use of proper validation methods has led to overly optimistic performance metrics of machine learning (ML) models. External validation provides evidence of a ML model’s performance with independent datasets and is crucial for generalizability.

METHODS: We developed Extreme Gradient Boosting (XGBoost) models to detect dental caries using easy-to-collect questionnaire data. ML model training was conducted using cross-validation nested resampling with a holdout test set, utilizing NHANES datasets (n = 6070). Performance of the trained model was tested using external data from the Northern Finland Birth Cohorts (NFBC1966 and NFBC1986; n = 3616). To enhance interpretability, beeswarm plots were constructed to visualize variable importance.

RESULTS: The ML model demonstrated acceptable performance in predicting dental caries on the internal dataset, with an area under the operating characteristics curve (AUC) of 0.785 (95% CI 0.756-0.813). However, the model encountered difficulties in identifying participants with dental caries, as shown by its poor sensitivity of 0.391, despite achieving a high specificity of 0.919. When applied to the external dataset, the ML model encountered significant challenges, with the AUC dropping to 0.550 (95% CI 0.532-0.569), sensitivity decreasing to 0.053, and specificity slightly improving to 0.974. Important variables identified by the model were self-rated condition of teeth and gums, presence of missing teeth, financial status, and time since last dental visit.

CONCLUSION: The performance of our ML model during external validation degraded notably compared to the internal validation. However, the XAI methodology exhibited great potential to be used in the future for individualized dental caries risk assessment.

PMID:41546040 | DOI:10.1186/s12903-026-07660-9

Biomed Eng Online. 2026 Jan 16. doi: 10.1186/s12938-025-01494-2. Online ahead of print.

ABSTRACT

BACKGROUND: Diabetic foot (DF) is a severe complication of type 2 diabetes mellitus (T2DM), contributing to significant morbidity and healthcare costs globally. Early prediction and intervention are critical for preventing amputations and improving patient outcomes. However, traditional statistical methods lack the capacity to handle high-dimensional clinical data and identify optimal predictive features. This study aimed to develop and validate machine learning models for DF risk prediction using feature selection strategies based on binary logistic regression and information theory.

METHODS: A retrospective cohort of 1,179 patients (95 DF cases, 1,084 T2DM controls) was analyzed using clinical and biochemical data from 2019 to 2025. Three data sets were constructed: (1) original features; (2) features selected via binary logistic regression (F1); and (3) features selected via information-theoretic global learning (F2). Six models-extreme learning machine (ELM), kernel extreme learning machine (KELM), and their variants trained on the three data sets-were evaluated using fivefold cross-validation. Performance metrics included area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and computational efficiency.

RESULTS: Age, blood-urea-nitrogen (BUN), homocysteine (Hcy), albumin (ALB), and fasting blood glucose (FBG) were identified as independent DF risk factors. The information theory-based KELM (IT-KELM) model achieved the highest AUC of 0.799 (sensitivity: 0.792 and specificity: 0.710) on F2, outperforming other models. Feature selection improved predictive accuracy while reducing computational time, with IT-KELM requiring 0.138 s for training and 0.0023 s for testing. The SHAP summary dot plot and bar chart revealed that the top five features contributing to the model were TP, RBC, ALB, BMI and HB.

CONCLUSIONS: Integrating information theory with KELM enhances DF risk prediction by optimizing feature subsets and leveraging nonlinear kernel mapping. The IT-KELM model demonstrates robust diagnostic performance and clinical feasibility for early DF screening. Future multi-center studies are needed to validate generalizability and refine model interpretability in real-world settings. This approach provides a cost-effective tool for precision medicine in diabetes care.

PMID:41546000 | DOI:10.1186/s12938-025-01494-2

Head Face Med. 2026 Jan 16. doi: 10.1186/s13005-026-00587-0. Online ahead of print.

NO ABSTRACT

PMID:41545992 | DOI:10.1186/s13005-026-00587-0

BMC Nephrol. 2026 Jan 16. doi: 10.1186/s12882-025-04690-3. Online ahead of print.

ABSTRACT

BACKGROUND: Abnormal serum potassium levels are common among peritoneal dialysis (PD) patients. Many studies have shown hypokalemia as a risk factor for peritonitis, but most were cross-sectional and observational. We intended to analyze the longitudinal association between serum potassium levels and peritonitis in those undergoing PD.

METHODS: We included 1,288 patients undergoing regular PD at our institution. The endpoint event was peritonitis. Patients were divided into peritonitis and non-peritonitis groups. The relationship between baseline data and the emergence of peritonitis was analyzed through Cox regression analysis. Mixed-effects model was used to analyze the correlation between longitudinal serum potassium and other lab characteristics with peritonitis. Kaplan-Meier survival analysis estimated the median time to peritonitis.Independent samples t-test was used in subgroup analysis to explore the relationship between serum potassium and different pathogenic bacteria. Spearman correlation analysis and scatter plot were used to evaluate the correlation between serum potassium and magnesium. Cochran-Armitage trend chi-square test assessed the trend of peritonitis incidence.

RESULTS: COX regression analysis found higher baseline lymphocyte count and female gender were associated with lower peritonitis risk, while older age and higher baseline uric acid levels were linked to higher risk. A mixed-effects model indicated that the peritonitis group’s serum potassium decreased more rapidly and remained low longer. Kaplan-Meier curves estimated the median time to peritonitis to be 4.09 years. The analysis of subgroups found no significant difference in serum potassium levels between the gram-positive and gram-negative bacteria groups. Spearman correlation analysis showed a very weak positive correlation between potassium and magnesium with poor trend consistency but statistical significance. Peritonitis incidence showed a significant linear downward trend from 2011 to 2023.

CONCLUSIONS: Rapid declines and long-term low levels of serum potassium after PD initiation increase peritonitis risk. Long-term potassium management in PD patients is crucial in clinic practice, with intensified monitoring advised around 4 years into PD treatment.

TRIAL REGISTRATION: 2023BA0125_GC; 2023-10-20.

PMID:41545970 | DOI:10.1186/s12882-025-04690-3

BMC Endocr Disord. 2026 Jan 16. doi: 10.1186/s12902-025-02132-7. Online ahead of print.

NO ABSTRACT

PMID:41545963 | DOI:10.1186/s12902-025-02132-7

BMC Neurol. 2026 Jan 16. doi: 10.1186/s12883-026-04636-8. Online ahead of print.

NO ABSTRACT

PMID:41545942 | DOI:10.1186/s12883-026-04636-8

BMC Anesthesiol. 2026 Jan 17. doi: 10.1186/s12871-026-03628-y. Online ahead of print.

ABSTRACT

BACKGROUND: Intranasal dexmedetomidine is commonly used preoperatively in pediatric anesthesia to reduce agitation and emergence delirium. Esketamine, with sedative and analgesic ef-fects and minimal respiratory depression at clinical doses, is also widely used in chil-dren. However, current evidence remains limited regarding the efficacy and safety of combining intranasal esketamine with dexmedetomidine versus dexmedetomidine alone in improving cooperation during anesthesia induction and reducing postoperative complications.

METHODS: This meta-analysis adhered to PRISMA guidelines and was registered in PROSPERO (CRD420251084757). A systematic search of PubMed, Embase, Cochrane Library, Web of Science, ClinicalTrials.gov, and Wanfang was conducted up to May 25, 2025. The primary outcome included the incidence of emergence delirium, emergence time, mask acceptance score (MAS), parental separation anxiety score (PSAS), and the incidence of adverse events, with pooled effect estimate reported as proportions and relative risk (RR) with 95% confidence intervals (CIs). Sensitivity analysis were performed to assess the robustness of the results and to identify sources of heterogeneity.

RESULTS: Six studies involving a total of 515 pediatric patients were included. Compared with dexmedetomidine alone, intranasal esketamine combined with dexmedetomidine significantly reduces the incidence of emergence delirium (RR = 0.27, 95% CI: [0.17-0.44], P < 0.00001, I² = 0%). The incidence of bradycardia is also significantly lower in the combination group (RR = 0.24, 95% CI: [0.08-0.72], P = 0.01). No statistically significant differences are observed between the two groups in terms of emergence time or the incidence of nausea and vomiting. The combination group shows lower parental separation anxiety scores and better mask acceptance scores, indicating improved cooperation during anesthesia induction.

CONCLUSION: Preoperative intranasal administration of esketamine combined with dexmedetomidine significantly reduces the incidence of emergence delirium and bradycardia compared with dexmedetomidine alone.Improved cooperation during anesthesia induction further supports the potential of this combination as a safe and effective alternative to dexmedetomidine monotherapy in pediatric anesthesia.

TRIAL REGISTRATION: Not applicable.

PMID:41545910 | DOI:10.1186/s12871-026-03628-y