Category: Statistics

BMC Oral Health. 2026 Jan 29. doi: 10.1186/s12903-026-07765-1. Online ahead of print.

ABSTRACT

OBJECTIVE: To assess the diagnostic performance of photon-counting detector computed tomography (PCD-CT) and cone-beam computed tomography (CBCT) at dose-matched radiation levels (high, standard, and low) for detecting and evaluating simulated endodontic conditions, treatments, and associated complications.

METHODS: Sixteen extracted third molars with eight endodontic tasks were imaged using PCD-CT and CBCT. Qualitative (image quality, artifact susceptibility, diagnostic interpretability) and quantitative (endodontic working length) parameters were assessed by two observers using a five-point Likert scale. Descriptive statistics and weighted kappa (κ) were used for data analysis.

RESULTS: High- and standard-dose PCD-CT demonstrated superior image quality and anatomical visualization compared to CBCT (median 5, IQR 5-5; κ = 1.0; all p < 0.001). Low-dose PCD-CT remained diagnostically robust, outperforming CBCT, except in root canal visualization, where both performed similarly. Diagnostic accuracy of pathologies and complications was slightly higher with PCD-CT (80-88%) than with CBCT (75-88%). Endodontic working length measurements were consistently accurate across all protocols, with near-perfect inter-observer agreement (κ = 0.84-0.86, all p < 0.001).

CONCLUSIONS: PCD-CT demonstrated superior diagnostic performance over CBCT across multiple endodontic tasks, particularly at high and standard doses. Even at low doses, PCD-CT maintained robust accuracy and image quality, outperforming dose-matched CBCT in most parameters. Endodontic working length assessment was equally reliable across both modalities. Overall, PCD-CT offers diagnostic advantages over CBCT, particularly in challenging cases involving complex anatomy or high-density materials. Its effective performance at lower radiation levels emphasizes its clinical potential and supports broader implementation in dentomaxillofacial diagnostics.

PMID:41612315 | DOI:10.1186/s12903-026-07765-1

Biomed Eng Online. 2026 Jan 29. doi: 10.1186/s12938-026-01516-7. Online ahead of print.

ABSTRACT

Heart failure is a leading cause of morbidity and mortality, and fluid congestion complicates its management. Conventional home-monitoring methods, such as daily weight measurements, are insufficiently sensitive, while invasive techniques are impractical for routine use. This paper introduces a novel, non-invasive approach using textile-based dry electrodes for bio-impedance spectroscopy to detect subtle changes in thoracic fluid volume in a mouse model. Twenty-three mice underwent controlled fluid infusion into the thoracic cavity following a six-stage protocol. Bio-impedance data were collected over 256 frequencies ($3–1000$ kHz) and analyzed to extract $R_0$ and $R_{\infty }$, from which total ($V_T$), extra-cellular ($V_E$), and intra-cellular ($V_I$) fluid volumes were calculated and normalized to baseline. Statistical analyses included two-way ANOVA and multiple linear regression to correlate impedance measurements with animal length and weight. No statistically significant differences in normalized fluid volumes ($V_T$, $V_E$, $V_I$) were observed across infusion stages ($p>0.05$), though there was an anecdotal increase in $V_T$ ($\Delta V_T=1.16\pm 1.79$ mL) and $V_I$ ($\Delta V_I=1.80\pm 2.91$ mL) after fluid infusion. Multiple linear regression revealed moderate correlations between impedance measurements and weight ($r^2=0.33$, $p=0.035$, RMSE $=19.34$ g) as well as length ($r^2=0.34$, $p=0.0066$, RMSE $=1.00$ cm). Additionally, a strong correlation was found between length and weight ($r^2=0.81$, $p=5.65\times {10}^{–8}$). The results indicate that textile-based dry electrodes can non-invasively measure thoracic fluid volume in mice, although the sensor’s sensitivity to small changes is limited. Further refinement is needed to enhance sensitivity and determine sensitivity threshold. These findings support the continued development of textile-based bio-impedance sensors as a practical tool for non-invasive heart failure monitoring.

PMID:41612308 | DOI:10.1186/s12938-026-01516-7

BMC Public Health. 2026 Jan 29. doi: 10.1186/s12889-026-26297-5. Online ahead of print.

NO ABSTRACT

PMID:41612281 | DOI:10.1186/s12889-026-26297-5

BMC Ophthalmol. 2026 Jan 29. doi: 10.1186/s12886-026-04641-y. Online ahead of print.

ABSTRACT

OBJECTIVE: To evaluate whether sub-Tenon anesthesia used during cataract surgery has a potential effect on pupillary dynamics by assessing late-term pupillary responses, and to compare these outcomes with those under topical anesthesia to ensure the safety of sub-Tenon anesthesia.

METHODS: The medical records of 63 eyes of 63 patients aged 50-70 who underwent cataract surgery between January 2022 and December 2023 were retrospectively analyzed. Demographic data and medical histories were reviewed. Comprehensive eye examinations including visual acuity, biomicroscopic and detailed fundus examination, and pupillography measurements (photopic, mesopic, scotopic, and dynamic responses) were recorded preoperatively and at postoperative week 1 follow-up.

RESULTS: The mean ages of patients in the topical and sub-Tenon anesthesia groups were 67.25 ± 10.29 and 68.84 ± 9.31 years, respectively. A total of 21 patients were male and 42 were female. Topical anesthesia was applied to 31 eyes and sub-Tenon anesthesia to 32 eyes. Both groups showed significant changes in pre- and postoperative scotopic, mesopic, and dynamic 10-second pupillary responses (p < 0.05). However, there was no statistically significant difference in static and dynamic pupil diameters between the two groups (p > 0.05).

CONCLUSIONS: Sub-Tenon’s anesthesia does not cause clinically significant changes in pupillary dynamics one week postoperatively, suggesting it is a safe alternative to topical anesthesia in terms of autonomic pupillary response.

PMID:41612272 | DOI:10.1186/s12886-026-04641-y

BMC Pregnancy Childbirth. 2026 Jan 30. doi: 10.1186/s12884-026-08704-2. Online ahead of print.

ABSTRACT

BACKGROUND AND OBJECTIVES: In India, like most countries, the COVID-19 pandemic in successive waves severely hampered the emergency medical services (EMS) and the government made prompt interventions, including substantial investments in both EMS and maternal health care immediately after the first wave. The study assessed variations in EMS efficiency and critical perinatal outcomes between the pre-pandemic era and the post pandemic-resilient phase in 2023 and 2024.

DATA AND METHODS: The study analysed the key EMS metrics based on the calls related to pregnancy, including call volume, response and transfer time, hospital handoff time and ambulance travel distance, and important maternal-newborn health outcomes such as maternal and neonatal mortalities, home deliveries, institutional childbirths, C-section deliveries, miscarriages and complicated vaginal births. The data relied upon encompasses the period from January 2017 to December 2024, including eight pandemic phases in 2020-22 and the resilient period of 2023 and 2024, obtained from the Tamil Nadu 108 Ambulance Control Room. A time series analysis method evaluated the EMS metrics in various pandemic phases; a statistical comparison was made with the pre-pandemic period for maternal-newborn outcomes. The appropriate effect size metric quantified the change in both analyses.

RESULTS: In the pandemic phases, despite an increase in pregnancy related call volume, the EMS metrics such as response times, transfer times and hospital handoff times witnessed notable improvement. The maternal and childbirth outcomes, especially in the post-pandemic and resilient phases during 2023-24, were markedly superior when compared with the corresponding period in the pre-pandemic era. In particular, the maternal mortality rate reduced by 19%, with 37 deaths per 100,000 live births. This is far lower than the national average of 97 deaths per 100,000 live births. Also, the rates of infant death, neonatal death, miscarriage, difficult vaginal births, and home births went down by 19.35%, 17.03%, 28.02%, 19.23%, and 36.05%, respectively.

CONCLUSIONS: Government investments during the pandemic, along with the sustained focus on maternal health programmes, appear to have provided substantial support to pregnant women and newborns. The reproductive health of women in Tamil Nadu does not seem to have been undermined by the pandemic.

PMID:41612252 | DOI:10.1186/s12884-026-08704-2

BMC Infect Dis. 2026 Jan 29. doi: 10.1186/s12879-026-12601-6. Online ahead of print.

ABSTRACT

OBJECTIVE: A high prevalence of antiphospholipid antibodies (aPL) has been reported in patients with coronavirus disease 2019 (COVID-19). Although some studies have demonstrated roles for aPL in thrombotic events in COVID-19, findings on their association with disease development and outcomes remain heterogeneous. Therefore, this study investigated whether aPL may serve as effective markers for determining the development and outcome of COVID-19.

METHODS: Serum samples were isolated from whole blood of 95 individuals with moderate and severe COVID-19. The prevalence of lupus anticoagulant (LA), IgM/IgG antiphospholipid (aPL), IgM/IgG anti-β2-glycoprotein I (aβ2GPI), and IgM/IgG anticardiolipin (aCL) antibodies was measured by enzyme-linked immunosorbent assay. A mixing test was performed in patients with unexplained prolongation of activated partial thromboplastin time (aPTT) to distinguish coagulation factor deficiencies from factor inhibitors. The percentage of selected immune cells and values of biochemical markers were also assessed.

RESULTS: Patients with severe COVID-19 showed significant increases in IgG aβ2GPI and IgG aPL antibody levels compared with individuals with moderate COVID-19 (P < 0.05). The mixing test showed that LA had an increased prevalence in severe patients with unexplained prolongation of aPTT and prothrombin time (PT) (P < 0.01-0.05). No significant differences were observed in IgM/IgG aCL, IgM aPL, or IgM aβ2GPI antibody levels between severe and moderate cases. Additional findings revealed that severe COVID-19 patients who required intensive care unit (ICU) treatment had significant increases in IgM/IgG aPL, IgM/IgG aCL, and IgM/IgG aβ2GPI antibodies (P < 0.01-0.05). However, there was no significant change in the prevalence of LA or IgM aβ2GPI antibodies between severe patients who required ICU therapy and those who did not. IgM aCL and IgG aPL values were significantly higher in non-survivors compared with survivors (P < 0.001-0.05). A similar trend was observed for IgG aCL and IgM aPL levels in non-survivors, although these increases were not statistically significant.

CONCLUSION: Changes in aPL levels may be considered effective markers for clarifying the severity and outcome of COVID-19.

CLINICAL TRIAL: Not applicable.

PMID:41612230 | DOI:10.1186/s12879-026-12601-6

BMC Microbiol. 2026 Jan 29. doi: 10.1186/s12866-026-04786-2. Online ahead of print.

ABSTRACT

BACKGROUND: Antimicrobial resistance (AMR) is a global threat. Escherichia coli is an important reservoir of resistance genes, and the coexistence of mcr with class 1 integron (intI1) is alarming, mcr confers resistance to colistin, a last-resort antibiotic, while intI1 often carries multiple transferable resistance determinants. Although colistin use in livestock is banned in Bangladesh, data on colistin-resistant E. coli in food animals, particularly cattle, remain scarce. This study investigated multidrug-resistance patterns, biofilm formation, and the prevalence of intI1 and its association with mcr and other resistance determinants in E. coli from Bangladeshi cattle.

METHODS: A total of 254 samples (feces, rectal swabs, soil, and water) were collected from cattle farms across three divisions of Bangladesh (Dhaka, Sylhet, and Barisal). E. coli isolates were identified using culture methods and confirmed with the VITEK-2 system and PCR. Antimicrobial susceptibility testing was performed using VITEK-2 system following CLSI guidelines. The presence of class 1 integron and mcr (mcr-1 to mcr-5) genes was detected by PCR. Biofilm formation was assessed using the crystal violet assay. Statistical analysis was conducted in R using Chi-square exact test, with significance set at p < 0.05.

RESULTS: E. coli was detected in 76.4% of samples, with the highest prevalence in feces (86.8%). Antimicrobial testing revealed complete sensitivity to several antibiotics, but resistance occurred to cefuroxime (33%), ciprofloxacin (26.8%), and amoxicillin-clavulanic acid (22.2%), with all isolates showing intermediate response to colistin. Overall, 29.4% of isolates were MDR, though no XDR or PDR were detected. Class 1 integron was present in 52.6% and the mcr-1 gene in 21.7%, both significantly associated with MDR (p < 0.001). Water isolates showed the highest proportion of strong biofilm producers (25.5%).

CONCLUSION: This study reveals a high prevalence of class 1 integron and the mcr-1 gene in MDR E. coli from food animals in Bangladesh, highlighting their role in resistance dissemination and the public health risk of colistin resistance. The strong association of integron with MDR and mcr-1 underscores the need for prudent antibiotic use, routine surveillance, and stronger antimicrobial stewardship in livestock to limit the spread of resistance to humans.

PMID:41612201 | DOI:10.1186/s12866-026-04786-2

BMC Emerg Med. 2026 Jan 29. doi: 10.1186/s12873-026-01479-x. Online ahead of print.

NO ABSTRACT

PMID:41612184 | DOI:10.1186/s12873-026-01479-x

Int J Dermatol. 2026 Jan 29. doi: 10.1111/ijd.70321. Online ahead of print.

ABSTRACT

BACKGROUND: Cutaneous melanoma remains a major public health issue with increasing incidence among fair-skinned populations. Beyond well-established risk factors such as ultraviolet exposure, there is evidence suggesting female sex hormone influence in melanoma biology and prognosis. Although several epidemiological studies have explored the relationship between exogenous hormones and melanoma risk, findings remain inconsistent. This study aims to investigate the association between exogenous hormonal use and Breslow thickness assessing differences across female life stages.

METHODS: A retrospective study of 464 female patients with histologically confirmed primary superficial spreading melanoma (SSM) diagnosed from 2010 to 2021 in Andreas Sygros Hospital of Cutaneous and Venereal Diseases was conducted. Multiple linear regression models were performed to examine the association of hormonal use and thickness among females of different age groups (< 45, 45-59, and ≥ 60 years).

RESULTS: Significant inverse associations between hormone use and Breslow thickness were found for women aged 45-59 years, with oral contraceptive (OC) use being associated with a 30% reduction in thickness (95% confidence interval [CI]: -47.9, -6.4) when considering all confounders. Exposure to any exogenous hormone was found to be positively associated (percent of change [PC]: 25.6, 95% CI: -7.2, 70.1) with tumor thickness among women above 60 years, indicating an effect modified by age. No significant associations were observed in females under 45 years.

CONCLUSIONS: These results indicate that the effect of exogenous hormone use on tumor thickness may be age-related, with an inverse association observed during the peri-menopausal period, and a positive relationship found among females above 60 years. Future research is needed to explore estrogen-mediated mechanisms influencing melanoma prognosis.

PMID:41612167 | DOI:10.1111/ijd.70321

Med Phys. 2026 Feb;53(2):e70258. doi: 10.1002/mp.70258.

ABSTRACT

BACKGROUND: Radiotherapy treatment planning (TP) aims to maximize radiation dose delivered to tumors while minimizing exposure to surrounding healthy tissues. Beam angle optimization (BAO) is a crucial component of TP, characterized by high dimensionality and non-convexity, and is traditionally solved via heuristic or manual iterative approaches. These conventional methods are time-consuming and often yield suboptimal solutions due to incomplete exploration of the vast solution space.

PURPOSE: This study introduces a novel framework integrating a general-purpose large language model (LLM) within a reinforcementlearning (RL)-inspired iterative strategy to automate BAO in radiotherapy planning. Taking advantage of the inherent knowledge embedded in LLMs, the method uses visual and scalar feedback to produce clinically meaningful treatment plans without requiring any domain-specific fine-tuning or additional training.

METHODS: The proposed framework employs an off-the-shelf Generative Pre-trained Transformer, GPT-4 model (denoted GPT-4_o) in an inference-only setting. At each iteration, GPT-4_o suggests a set of gantry angles, which are subsequently input into the MatRad software to generate a dose distribution. A scalar reward is computed from this distribution using a custom reward function designed to balance target dose conformity and sparing of organs-at-risk (OARs). This reward, along with the corresponding dose maps, serves as feedback for the LLM to iteratively refine its suggestions. The refinement process consists of distinct exploration and exploitation phases inspired by classical RL paradigms. We evaluated six configurations that varied in exploration duration and in the Computed Tomography (CT) slice inputs provided to the LLM (Single-View vs. Multi-View). Performance was benchmarked against a random-angle selection baseline across three anatomical sites: prostate, head-and-neck, and liver.

RESULTS: Across the liver and head-and-neck cases, all LLM-based configurations significantly outperformed the random baseline ( ). In the prostate scenario, most strategies demonstrated statistically significant improvements, except for the Multi-View configurations with extended exploration phases (10 and 15 iterations). Rewards consistently increased during the exploitation phase, and the resulting dose-volume histograms and dose distributions exhibited improved conformity to target volumes with enhanced sparing of OARs. Notably, plans of clinically plausible quality were obtained within 20 iterative refinement steps in this proof-of-concept setting.

CONCLUSIONS: This study demonstrates that general-purpose LLMs, operating without specialized model training or fine-tuning, can effectively serve as intelligent agents for automated radiotherapy TP, specifically addressing the BAO problem. This flexible and scalable framework has the potential to enhance clinical decision-making workflows in radiotherapy. Future research directions include exploring more comprehensive and clinically nuanced reward functions and extending the methodology to other components of radiotherapy TP.

PMID:41612144 | DOI:10.1002/mp.70258