Category: Statistics

Nutr J. 2025 Feb 22;24(1):28. doi: 10.1186/s12937-025-01097-6.

ABSTRACT

BACKGROUND: Cancer-related deaths and environmental issues pose significant global challenges. The Planetary Health Diet (PHD) is a healthy dietary pattern that simultaneously promotes human health and ecology. This study aims to investigate the association between the Planetary Health Diet Index (PHDI) and mortality among cancer survivors, as well as the mediating role of inflammation between PHDI and all-cause mortality.

METHODS: This study analyzed data from 3,442 cancer survivors enrolled in the United States National Health and Nutrition Examination Survey between 1999 and 2018. To investigate the association between PHDI and mortality, we applied weighted multivariate Cox proportional hazards regression, restricted cubic spline analysis, subgroup analysis, and sensitivity analysis. The mediating effects of the Systemic Immune-Inflammation Index (SII) and Neutrophil-to-Lymphocyte Ratio (NLR) were assessed using the bootstrap method with 1000 simulations.

RESULTS: In the fully adjusted model, each 10-point PHDI increase correlated with a 9% decrease in all-cause mortality (HR, 0.91; 95% CI, 0.86-0.95), a 10% decrease in cancer mortality (HR, 0.90; 95% CI, 0.83-0.99), and a 10% decrease in non-cancer mortality (HR, 0.90; 95% CI, 0.85-0.96). The PHDI was significantly inversely correlated with SII and NLR, which were positively related to all-cause mortality. The mediation proportions of SII and NLR between the PHDI and all-cause mortality were 6.52% and 8.52%, respectively.

CONCLUSIONS: Adherence to the PHD is associated with reduced all-cause, cancer, and non-cancer mortality among cancer survivors. Additionally, SII and NLR may mediate the relationship between PHDI and all-cause mortality.

PMID:39987440 | DOI:10.1186/s12937-025-01097-6

J Orthop Surg Res. 2025 Feb 22;20(1):192. doi: 10.1186/s13018-025-05585-7.

ABSTRACT

BACKGROUND: Intraoperative endplate injury (IEI) is a type of fracture and a potential complication during lumbar interbody fusion (LIF). Osteoporosis diagnosed by bone mineral density (BMD) is a well-known risk factor for fracture itself and IEI also. The bone turnover markers (BTMs) are parameters of bone qualities and have some correlations with fractures, but there is no study about the BTMs and intraoperative fractures especially IEI. This study aims to identify the correlation between IEI and BTMs, especially in misTLIF.

METHODS: We retrospectively reviewed 184 patients (230 spine levels). The IEI was diagnosed as the breakage of the endplate observed on postoperative 1 mm thin-cut CT scans. All surgical and endogenous risk factors of IEI were also checked including the bone resorption marker (serum CTX) and bone formation marker (serum P1NP) of BTMs. Additionally, the ratio (P1NP/CTX) and the subtype groups of BTMs were analyzed.

RESULTS: The rate of total IEI was 38%. The sex, osteoporosis, spine BMD, femur BMD, CTX, P1NP/CTX, preoperative disc height, and the discrepancy between preoperative disc height and cage size were risk factors in multivariate logistic regression analyses. The subtypes according to BTMs showed a different rate of IEI, resulting in subtype 2 A (low CTX and P1NP and high P1NP/CTX ratio) having the lowest incidence and statistically significant odds ratios compared to other subtype groups.

CONCLUSION: This study demonstrated that the IEI is related to BTMs regardless of BMD in misTLIF. In addition, the P1NP/CTX ratio or subtypes could be helpful in predicting the risk of IEI due to the parallel dynamics of BTMs.

PMID:39987433 | DOI:10.1186/s13018-025-05585-7

BMC Med Res Methodol. 2025 Feb 22;25(1):50. doi: 10.1186/s12874-025-02489-2.

ABSTRACT

BACKGROUND: Classical approaches to subgroup analysis in randomised controlled trials (RCTs) to identify heterogeneous treatment effects (HTEs) involve testing the interaction between each pre-specified possible treatment effect modifier and the treatment effect. However, individual significant interactions may not always yield clinically actionable subgroups, particularly for continuous covariates. Non-parametric causal machine learning approaches are flexible alternatives for estimating HTEs across many possible treatment effect modifiers in a single analysis.

METHODS: We conducted a secondary analysis of the VANISH RCT, which compared the early use of vasopressin with norepinephrine on renal failure-free survival for patients with septic shock at 28 days. We used classical (separate tests for interaction with Bonferroni correction), data-adaptive (hierarchical lasso regression), and non-parametric causal machine learning (causal forest) methods to analyse HTEs for the primary outcome of being alive at 28 days. Causal forests comprise honest causal trees, which use sample splitting to determine tree splits and estimate treatment effects separately. The modal initial (root) splits of the causal forest were extracted, and the mean value was used as a threshold to partition the population into subgroups with different treatment effects.

RESULTS: All three models found evidence of HTE with serum potassium levels. Univariable logistic regression OR 0.435 (95%CI [0.270, 0.683]. p = 0.0004), hierarchical lasso logistic regression standardised OR: 0.604 (95% CI 0.259, 0.701), lambda = 0.0049. Hierarchical lasso kept the interaction between the treatment and serum potassium, sodium level, minimum temperature, platelet count and presence of ischemic heart disease. The causal forest approach found some evidence of HTE (p = 0.124). When extracting root splits, the modal split was on serum potassium (mean applied threshold of 4.68 mmol/L). When dividing the patient population into subgroups based on the mean initial root threshold, risk differences in being alive at 28 days were 0.069 (95%CI [-0.032, 0.169]) and – 0.257 (95%CI [-0.368, -0.146]) with serum potassium ≤ 4.68 and > 4.68 respectively.

CONCLUSIONS: The causal forest agreed with the data-adaptive and classical method of subgroup analysis in identifying HTE by serum potassium. Whilst classical and data-adaptive methods may identify sources of HTE, they do not immediately suggest subgroup splits which are clinically actionable. The extraction of root splits in causal forests is a novel approach to obtaining data-derived subgroups, to be further investigated.

PMID:39987431 | DOI:10.1186/s12874-025-02489-2

Eur Arch Paediatr Dent. 2025 Feb 22. doi: 10.1007/s40368-025-01012-x. Online ahead of print.

ABSTRACT

PURPOSE: The use of large language models (LLMs) in generative artificial intelligence (AI) is rapidly increasing in dentistry. However, their reliability is yet to be fully founded. This study aims to evaluate the diagnostic accuracy, clinical applicability, and patient education potential of LLMs in paediatric dentistry, by evaluating the responses of six LLMs: Google AI’s Gemini and Gemini Advanced, OpenAI’s ChatGPT-3.5, -4o and -4, and Microsoft’s Copilot.

METHODS: Ten open-type clinical questions, relevant to paediatric dentistry were posed to the LLMs. The responses were graded by two independent evaluators from 0 to 10 using a detailed rubric. After 4 weeks, answers were reevaluated to assess intra-evaluator reliability. Statistical comparisons used Friedman’s and Wilcoxon’s and Kruskal-Wallis tests to assess the model that provided the most comprehensive, accurate, explicit and relevant answers.

RESULTS: Variations of results were noted. Chat GPT 4 answers were scored as the best (average score 8.08), followed by the answers of Gemini Advanced (8.06), ChatGPT 4o (8.01), ChatGPT 3.5 (7.61), Gemini (7,32) and Copilot (5.41). Statistical analysis revealed that Chat GPT 4 outperformed all other LLMs, and the difference was statistically significant. Despite variations and different responses to the same queries, remarkable similarities were observed. Except for Copilot, all chatbots managed to achieve a score level above 6.5 on all queries.

CONCLUSION: This study demonstrates the potential use of language models (LLMs) in supporting evidence-based paediatric dentistry. Nevertheless, they cannot be regarded as completely trustworthy. Dental professionals should critically use AI models as supportive tools and not as a substitute of overall scientific knowledge and critical thinking.

PMID:39987420 | DOI:10.1007/s40368-025-01012-x

Commun Biol. 2025 Feb 22;8(1):277. doi: 10.1038/s42003-025-07666-z.

ABSTRACT

ZBTB48 (also known as TZAP) is a transcription factor that has previously been reported to bind to telomeres and act as a negative regulator of telomere length in human cell lines. To explore whether transcription factor activity and telomere length regulation are conserved at the organismal level in vertebrates, we generate a zbtb48^-/- zebrafish line via CRISPR‒Cas genome editing. The zbtb48^-/- mutants display no obvious physical or behavioral abnormalities in the first two generations. We find no statistically significant changes in telomere length in first-generation adults. However, for the gene regulatory aspect of Zbtb48, similar to that in human cancer cell lines, we observe downregulation of mtfp1 at both the mRNA and protein levels in the zbtb48^-/- mutants. This suggests that mtfp1 is an evolutionarily conserved regulatory target of Zbtb48. Further investigation of the spatiotemporal expression of zbtb48 in previously published zebrafish data reveals low transcript expression in diverse tissues, except in germline stem cells and gametocytes of the gonads. Notably, Mtfp1 protein downregulation is detected in the ovaries of 40 dpf zbtb48^-/- mutants and in the testes of both 40 dpf and 10.5-month-old zbtb48^-/- mutants.

PMID:39987415 | DOI:10.1038/s42003-025-07666-z

Metabolomics. 2025 Feb 22;21(2):33. doi: 10.1007/s11306-025-02231-5.

ABSTRACT

INTRODUCTION: Extracranial and intracranial tumors are a diverse group of malignant and benign neoplasms, influenced by multiple factors. Given the complex nature of these tumors and usually late or accidental diagnosis, minimally invasive, rapid, early, and accurate diagnostic methods are urgently required. Metabolomics offers promising insights into central nervous system tumors by uncovering distinctive metabolic changes linked to tumor development.

OBJECTIVES: This study aimed to elucidate the role of altered metabolites and the associated biological pathways implicated in the development of gliomas and meningiomas.

METHODS: The study was conducted on 95 patients with gliomas, 68 patients with meningiomas, and 71 subjects as a control group. The metabolic profiling of gliomas and meningiomas achieved by integrating untargeted metabolomic analysis based on GC-MS and targeted analysis performed using LC-MS/MS represents the first comprehensive study. Three comparisons (gliomas or meningiomas vs. controls as well as gliomas vs. meningiomas) were performed to reveal statistically significant metabolites.

RESULTS: Comparative analysis revealed 97, 56, and 27 significant metabolites for gliomas vs. controls, meningiomas vs. controls and gliomas vs. meningiomas comparison, respectively. Moreover, among above mentioned comparisons unique metabolites involved in arginine biosynthesis and metabolism, the Krebs cycle, and lysine degradation pathways were found. Notably, 2-aminoadipic acid has been identified as a metabolite that can be used in distinguishing two tumor types.

CONCLUSIONS: Our results provide a deeper understanding of the metabolic changes associated with brain tumor development and progression.

PMID:39987409 | DOI:10.1007/s11306-025-02231-5

Arch Dermatol Res. 2025 Feb 22;317(1):452. doi: 10.1007/s00403-025-03981-x.

ABSTRACT

Endocrine-disrupting chemicals such as phenols and parabens can promote allergic conditions including eczema. We aimed to analyze the association between exposure to environmental phenols and parabens and allergic biomarkers-including total serum Immunoglobulin E (IgE), C-reactive protein (CRP), and eosinophils-in individuals with eczema, using the dataset from NHANES 2005-2006. This analysis was based on urinary biomarker levels of phenols and parabens, including bisphenol A, benzophenone-3, 4-tert-octylphenol, triclosan, as well as methyl, ethyl, propyl, and butyl parabens. The urinary biomarkers of phenols and parabens were quantified using online SPE-HPLC-MS/MS, while IgE, CRP, and eosinophil levels were analyzed using fluorescent-enzyme immunoassay, the ImmunoCAP 1000 system, latex-enhanced nephelometry, and the Beckman Coulter method, respectively. Following data extraction, we obtained 159 individuals with a history of eczema and categorized them by age for analysis. Our findings showed positive correlations between bisphenol A, triclosan, butyl paraben, methyl paraben, and propyl paraben and allergic biomarkers in children with eczema aged 6 to 8 years. Notably, a significant positive correlation was observed between methyl paraben exposure and IgE levels. In adults with eczema, 4-tert-octylphenol demonstrated a significant positive association with both IgE levels and eosinophil counts. These findings suggest that exposure to these chemicals may exacerbate eczema symptoms.

PMID:39987402 | DOI:10.1007/s00403-025-03981-x

Commun Psychol. 2025 Feb 22;3(1):29. doi: 10.1038/s44271-025-00212-x.

ABSTRACT

Researchers are increasingly using language measures to study emotion, yet less is known about whether language relates to other measures often used to study emotion. Building on previous work which focuses on associations between language and self-report, we test associations between language and a broader range of measures (self-report, observer report, facial cues, vocal cues). Furthermore, we examine associations across different dictionaries (LIWC-22, NRC, Lexical Suite, ANEW, VADER) used to estimate valence (i.e., positive versus negative emotion) or discrete emotions (i.e., anger, fear, sadness) in language. Associations were tested in three large, multimodal datasets (Ns = 193-1856; average word count = 316.7-2782.8). Language consistently related to observer report and consistently related to self-report in two of the three datasets. Statistically significant associations between language and facial cues emerged for language measures of valence but not for language measures of discrete emotions. Language did not consistently show significant associations with vocal cues. Results did not tend to significantly vary across dictionaries. The current research suggests that language measures (in particular, language measures of valence) are correlated with a range of other measures used to study emotion. Therefore, researchers may wish to use language to study emotion when other measures are unavailable or impractical for their research question.

PMID:39987381 | DOI:10.1038/s44271-025-00212-x

J Perinatol. 2025 Feb 22. doi: 10.1038/s41372-025-02234-z. Online ahead of print.

ABSTRACT

OBJECTIVE: Identify characteristics associated with death or tracheostomy (D/T) in preterm infants with bronchopulmonary dysplasia (BPD) predominantly managed with non-invasive respiratory support prior to 36 weeks postmenstrual age (PMA).

STUDY DESIGN: Retrospective cohort study at Children’s Hospital of Philadelphia of 134 infants meeting inclusion criteria between 2010 and 2017. Various clinical characteristics were considered as predictor variables of the primary outcome, D/T; those associated at p < 0.10 in bivariable logistic regression were evaluated in multivariable models.

RESULTS: Twenty-one (16%) infants had D/T. Treatment with pulmonary vasodilators and the presence of pulmonary hypertension (PH) on echocardiogram at 36 weeks PMA were associated with D/T in bivariable analyses. Pulmonary vasodilator use remained statistically significant in adjusted multivariable models.

CONCLUSIONS: We identified a strong association between PH and D/T in this cohort. Our findings emphasize the importance of specialized BPD management that includes early identification of PH in this high-risk population.

PMID:39987378 | DOI:10.1038/s41372-025-02234-z

Arch Dermatol Res. 2025 Feb 22;317(1):477. doi: 10.1007/s00403-025-03945-1.

ABSTRACT

reast cancer is the most common malignancy among women in the United States (American Cancer Society in Key Statistics for Breast Cancer. American Cancer Society, Atlanta, GA). Hair loss is common among women undergoing breast cancer treatment, however limited research has systematically characterized treatment-specific patterns of hair loss. The current study evaluates the distribution of alopecia, associated symptoms, and prevalence of hair loss risk factors among women undergoing breast cancer treatment. A retrospective chart review was conducted on 75 female breast cancer patients who presented for hair loss to the Dermatology Department at The Ohio State University. Patients were categorized based on chemotherapy history. Dependent variables included hair loss distribution, scalp symptoms, eyebrow or eyelash involvement, and nail findings. Among our cohort, hair loss most frequently involved the frontal scalp (52%), vertex (42.7%) and temporal scalp (26.7%). Diffuse alopecia was seen in 25.3% of patients. Eyebrow/eyelash loss was observed in 40% of patients, scalp symptoms in 28%, and nail changes in 21.3% of patients. Itching and flaking were the most common scalp symptoms, whereas onycholysis, fragility, and Beau’s lines were the most common nail changes. Results revealed that chemotherapy exposure led to significantly higher eyebrow/eyelash loss and a trend towards an increase of diffuse alopecia. Non-chemotherapy-based treatments, 98% of which were endocrine therapy-based, were characterized by more localized hair loss primarily involving the frontal and temporal scalp, suggesting these distributions may be specific to endocrine therapy-related alopecia. Understanding the adverse effects related to specific therapeutic agents enables clinicians to provide personalized care and mitigate the psychological burden associated with breast cancer therapies.

PMID:39987375 | DOI:10.1007/s00403-025-03945-1