Category: Statistics

Nat Commun. 2025 Dec 31. doi: 10.1038/s41467-025-67946-4. Online ahead of print.

ABSTRACT

Poleward migration of Northwest Pacific typhoons brings severe impacts on East Asian high-latitude cities, yet early typhoon climate prediction remains a long-standing scientific challenge. Here we reveal a seemingly-familiar-yet-strange climate oscillation phenomenon, which we name Tropical-leaning Atlantic Oscillation (TAO). Statistical results show that springtime TAO can explain 56% of the variance in a dominant dipole mode of typhoon track variations during July-September of 1979-2023, suggesting that it possesses a robust predictive skill of peak-season typhoon tracks four months in advance. Specifically, springtime TAO is characterized by a sea-level pressure seesaw between the tropical North Atlantic and the Hudson Bay-Davis Strait, relating to the meridional shift of North America-Atlantic subtropical jet stream. It generates cross-seasonal North Atlantic-and-Pacific surface seawater temperature anomalies, thereby triggering Northwest Pacific cyclonic steering flows that tempt (obstruct) typhoons toward East Asian high-latitude (low-latitude) cities during July-September. Climate models project an increasing frequency of positive TAO events. This may potentially contribute to a poleward migration of typhoon activity toward East Asian high-latitude cities as climate warms, yet uncertainty remains due to model biases in simulating tropical surface seawater temperature patterns. Our results highlight an overlooked impact of an emerging internal climatic oscillation on the enhancing typhoon risks toward high-latitudes.

PMID:41476152 | DOI:10.1038/s41467-025-67946-4

Sci Rep. 2025 Dec 31. doi: 10.1038/s41598-025-34244-4. Online ahead of print.

ABSTRACT

The inhibition of fibrosis in filtering blebs is indispensable for lowering intraocular pressure (IOP) after PRESERFLO MicroShunt surgery (PMS). We previously reported the anti-fibrotic effect of OBP-801 (OBP) on a filtering bleb in a rabbit glaucoma filtration surgery model using a 22-gauge cannula. In this study, we investigated the effect of OBP after PMS in rabbit eyes for the development of a new practically applicable anti-fibrotic treatment. This study involved 19 Japanese white rabbits that underwent PMS in the right eye, with those eyes divided into 3 groups: (1) intraoperative subconjunctival injection of 0.02% mitomycin-C (MMC) (n = 6), (2) postoperative instillation of 100 nM OBP eye drops (n = 7), or (3) a balanced salt solution (BSS) control (n = 6). Bleb morphology and IOP were monitored for 12 weeks postoperative, with the bleb tissues then undergoing evaluation of fibrosis and Western blot analysis. A lower postoperative IOP was maintained in the OBP-group eyes, and at 12 weeks postoperative, the IOP was significantly lower in that group than in the BSS and MMC groups (p < 0.01). OBP-treated eyes showed no adverse effects and reduced levels of alpha-smooth muscle actin and collagen deposition, thus suggesting that OBP is a promising candidate for improving surgical outcomes post PMS.

PMID:41476143 | DOI:10.1038/s41598-025-34244-4

Clin Spine Surg. 2025 Dec 30. doi: 10.1097/BSD.0000000000001928. Online ahead of print.

ABSTRACT

STUDY DESIGN: A retrospective cohort study.

OBJECTIVE: To describe the incidence, timing, and reason for ED visits following primary versus revision lumbar fusion.

SUMMARY OF BACKGROUND DATA: Emergency department (ED) presentation and misutilization place a substantial financial strain on patients and the health care system. ED visits following lumbar fusion are common and may be an overlooked target for reducing cost.

METHODS: A retrospective cohort study of patients undergoing 1-3 level primary versus revision lumbar fusion was performed. Outcomes included the incidence and characteristics (inpatient admission, discharge home, or reoperation) of ED visits at 2 weeks, 30 days, and 90 days postoperatively. Logistic regression analysis was performed to identify independent predictors of postoperative ED visits.

RESULTS: A total of 2360 patients were included (1852 primary and 508 revision). Rate of 90-day ED visits was higher in the revision group (10.2%) compared with the primary group (6.86%, P=0.014). However, breakdown by 15-day intervals revealed this was only significant between 14 and 30 days postoperatively (1.30% vs. 3.35% for revisions, P=0.004). Reasons for ED visits were similar, with both groups presenting most commonly for pain complaints. Primary patients presenting to the ED were more likely to require admission (48.0% vs. 26.9%; P=0.015). Logistic regression demonstrated that revision surgery (OR: 2.67, P<0.001), Cut-to-close time (OR: 1.003, P=0.028) and LOS (OR: 1.11, P=0.023) independently predicted postoperative ED visits.

CONCLUSION: Revision lumbar fusion was an independent predictor of visiting the ED, especially from 14 to 30 days postoperatively, but the absolute increase in risk was mild at 3.4%. Cut-to-close time was also statistically predictive, although with an effect size that is not clinically significant. However, visits to the ED after revision surgery were less likely to require readmission compared with visits after primary lumbar surgery. These findings may suggest that patients undergoing lumbar fusion should be appropriately counseled regarding postoperative pain expectations and appropriate acute care utilization, especially in the revision setting.

PMID:41474544 | DOI:10.1097/BSD.0000000000001928

Discov Ment Health. 2025 Dec 31. doi: 10.1007/s44192-025-00359-3. Online ahead of print.

ABSTRACT

Mental health disparities are increasingly shaped by intersecting demographic and socioeconomic conditions. Anchored in the Social Determinants of Health framework, this study investigates variations in mental well-being among adults in Abu Dhabi using data from the 5th Cycle of the Abu Dhabi Quality of Life Survey (2023-2024), which included over 100,000 respondents. Drawing on a subset of 65,203 adults, we analysed key mental health indicators-such as sadness, anxiety, loneliness, fear, difficulty concentrating, and boredom-across population groups using descriptive statistics and ANOVA. The findings reveal statistically significant disparities by age, gender, nationality, education level, household head status, and employment sector. Notably, youth aged 15-29 reported the highest emotional stress, while females and non-Emiratis exhibited higher negative mental health indicators compared to their counterparts. Non-heads of households and private-sector employees also displayed elevated distress levels, reflecting structural vulnerabilities in occupational and social roles. These results underscore the multidimensional nature of mental health and the influence of systemic inequalities on psychological well-being. The study offers timely, locally grounded evidence to inform targeted mental health interventions and inclusive policy development in Abu Dhabi’s rapidly evolving sociocultural landscape.

PMID:41474537 | DOI:10.1007/s44192-025-00359-3

EJNMMI Res. 2025 Dec 31. doi: 10.1186/s13550-025-01344-1. Online ahead of print.

ABSTRACT

BACKGROUND: Spatial filters are required to suppress the statistical noise of SPECT images but with an unavoidable smoothing effect that further decreases the SUV and contrast. This study assesses a deep-learning noise reduction (DLNR) algorithm, previously developed to further reduce bone SPECT recording time on a high-speed whole-body 360° CZT-camera, when used instead of, rather than in addition to, the conventional spatial filters (CSF) recommended for this camera.

RESULTS: The SUVmax of bone lesions (114 definite arthritis or metastasis lesions) and the resolution recovery coefficients of small and medium phantom spheres, were higher for DLNR than CSF or the combination of CSF plus DLNR (CSF-DLNR) (all p < 0.001), whereas the relative noises were lower for DLNR or CSF-DLNR, as compared with CSF (p < 0.001). Consequently, contrast-to-noise ratio (CNR) was dramatically higher for DLNR, as compared with CSF, and also CSF-DLNR, especially for small- and medium-sized structures. Compared with CSF, DLNR provided an almost two-fold CNR increase for the sphere and lesions in the range of one cm³. This dramatic CNR improvement was still documented when DLNR was compared with the median, kernel, Butterworth, or Gaussian filters used alone and set to provide an equivalent image noise reduction to DLNR on the phantom.

CONCLUSION: When used alone, this DLNR algorithm enhances the contrast-to-noise ratio and quantification of bone lesions, especially those of small or medium sizes. It outperforms conventional spatial filters and provides remarkable image quality for routine analysis of bone SPECT from the high-speed whole-body 360° CZT camera. However, further research and validation studies are still necessary before a widespread adoption in clinical practice.

KEY POINTS: Question: How does a deep-learning noise reduction algorithm, previously developed to further reduce bone SPECT recording times on a high-speed whole-body 360° CZT-camera, work when used instead of, rather than in addition to, the conventional spatial filters recommended for this camera. Pertinent findings: When used alone, this deep-learning noise reduction algorithm provides a high level of image denoising and better preserves the activities of small- to medium-sized bone structures and lesions than conventional spatial filters do, leading to a dramatic increase in the corresponding contrast-to-noise ratios.

IMPLICATIONS FOR PATIENT CARE: Such a deep-learning noise reduction algorithm could be used not only to reduce SPECT recording time when added to conventional spatial filters, but also to improve image quality and resolution when used alone.

TRIAL REGISTRATION: clinicaltrials.gov, NCT06782438, Registered 27 February 2025,https://clinicaltrials.gov/search?id=NCT06782438.

PMID:41474536 | DOI:10.1186/s13550-025-01344-1

Clin Spine Surg. 2025 Dec 30. doi: 10.1097/BSD.0000000000002003. Online ahead of print.

ABSTRACT

STUDY DESIGN: A case-series study.

OBJECTIVES: To acquire diagnostic insights to distinguish between intradural extramedullary spinal metastases (IESM) and benign spinal tumors by comparing patients with IESM and those with schwannoma or spinal meningioma.

SUMMARY OF BACKGROUND DATA: IESM constitute a rare category of spinal metastases. As the outcome of IESM is usually poor without intervention, early diagnosis and treatment are particularly important for better prognosis. As few studies have clearly addressed the features of IESM, it is necessary to gain comprehensive diagnostic insights into the characteristics of the disease.

METHODS: Included in this study were 14 IESM patients who underwent gross total tumor resection. IESM and schwannoma or meningioma were compared in a ratio of 1:2. Differences in clinical and imaging presentations between them were analyzed statistically, and survival curves were plotted using the Kaplan-Meier method.

RESULTS: IESM presented an unclear boundary (P=0.005), an irregular shape (P=0.035), and A low probability of cystic degeneration (P=0.028) as compared with schwannoma. Compared with IESM, meningioma tended to have a clear boundary (P=0.001), a wide base (P=0.047), high calcification possibility (P=0.040), and homogeneous enhancement on MRI (P=0.016). The estimated mean overall survival of IESM patients was 16.80±3.94 months.

CONCLUSION: This study demonstrated the characteristics of IESM and clarified the distinguishing points between IESM and intradural extramedullary benign tumors. Early warning features drawn from this study may be able to help clinicians to identify patients with IESM.

PMID:41474520 | DOI:10.1097/BSD.0000000000002003

Assessment. 2025 Dec 31:10731911251406404. doi: 10.1177/10731911251406404. Online ahead of print.

ABSTRACT

Existing diagnosis instruments for developmental dyslexia (DD) in mainland China are limited in generalizability and typically rely on traditional norming approaches, which require large sample sizes to achieve precision. This study aims to develop and validate the Beijing Normal University Diagnostic Tool for Chinese Mandarin Developmental Dyslexia (BNU-DTCMDD), a DD diagnostic tool with regression-based norms for elementary school students in mainland China. A nationally representative sample of 3,782 first-to-sixth-grade students and a clinical sample of 84 first-to-sixth-grade students diagnosed with specific learning disabilities (SLD) were administered the BNU-DTCMDD, comprising six tasks that measure reading abilities and related cognitive skills. The tool demonstrated high internal consistency (Cronbach’s α .73-.99), good test-retest reliability (Pearson’s r .68-.99), good structural validity, and reasonable criterion validity (Cohen’s d 0.27-0.63). Norms were established using generalized additive models for location, scale, and shape (GAMLSS), yielding percentile curves and Z-scores. Based on the norms, the prevalence of DD was 6.08% in the normative sample and 73.81% in the clinical sample with SLD. The BNU-DTCMDD can diagnose DD in elementary school students in mainland China with good reliability and validity, and its regression-based norms overcome the statistical constraints of traditional norming and support timely diagnosis and intervention for DD.

PMID:41474507 | DOI:10.1177/10731911251406404

Adv Neonatal Care. 2025 Dec 30. doi: 10.1097/ANC.0000000000001329. Online ahead of print.

ABSTRACT

BACKGROUND: The experience of having newborn admitted to the neonatal intensive care unit (NICU) is one that can be incredibly challenging for parents, particularly mothers.

PURPOSE: To assess the effectiveness of supportive nursing interventions defined as structured emotional support, informational counseling, and parent‑education sessions delivered by NICU nursing staff on anxiety, depression, and stress among mothers of NICU infants.

METHODS: We systematically reviewed 22 studies, encompassing 1877 participants, that reported on the effects of supportive nursing interventions for stress reduction among mothers with infants in NICU. Pooled standard mean differences (SMDs) were calculated using random-effects models. Heterogeneity was assessed using the Cochran Q statistic and I2 index. Subgroup analyses were conducted based on study design and type of intervention.

RESULTS: Supportive nursing interventions produced a significant reduction in maternal NICU‑related stress (SMD = -1.285, 95% CI: -1.766 to -0.804; P < .001), indicating that mothers receiving these interventions experienced lower stress than controls. However, substantial heterogeneity was observed (I2 = 95.2%), reflecting variations in intervention format, measurement scales, and clinical settings. Subgroup analyses indicated a larger effect in nonrandomized trials (SMD = -2.16) versus randomized controlled trials (SMD = -0.99), and educational support interventions produced greater stress reduction (SMD = -1.61) than other forms of support (SMD = -0.83).

IMPLICATIONS FOR PRACTICE AND RESEARCH: Supportive nursing interventions significantly reduce stress among mothers with infants in NICU. Tailored personalized support interventions, considering individual and cultural nuances, may further enhance the efficacy of these interventions. Future research should focus on identifying the most effective components of these interventions and ensuring their broader implementation in NICU settings.

PMID:41474506 | DOI:10.1097/ANC.0000000000001329

J Clin Exp Neuropsychol. 2025 Dec 31:1-13. doi: 10.1080/13803395.2025.2609824. Online ahead of print.

ABSTRACT

OBJECTIVE: Subjective cognitive decline (SCD) is an important yet heterogeneous indicator of mild cognitive impairment (MCI) and dementia. Sex and health-related disparities in risk are well established, but differences in prevalence and conversion rates from SCD to MCI/Dementia by risk factor remain unclear.

METHOD: This preregistered study followed PRISMA guidelines to conduct a systematic review with a narrative synthesis and meta-analyses. Random-effects meta-analyses calculated the relative risk (RR) of sex, depression, hypertension, and diabetes in conversion from SCD to MCI/dementia. Q and I² statistics investigated heterogeneity. Prevalence rates were also calculated.

RESULTS: Five cross-cultural studies (N = 1136) were eligible for the meta-analyses. Participants, on average, had less than 12 years of education. Pooled analyses showed no significant differences in the RR of conversion for depression, hypertension, or diabetes. The pooled conversion rate of SCD to MCI was 17.2% and 8.7% to dementia. Evidence of heterogeneity suggested that the aggregated data may mask differences between studies; thus, unpublished conversion rates on comorbid SCD and the health conditions are reported to inform future research.

CONCLUSIONS: Relative risk estimates align with the greater literature and extend them to an inclusive cross-cultural sample with lower education. The significant heterogeneity found underscores the complexity of the interactions between cognitive decline and modifiable risk factors. This study provides novel conversion rates to MCI and dementia for individuals with comorbid SCD and depression, hypertension, and diabetes. We recommend that sex-stratified conversion rates are reported, as limited data prevented our meta-analysis from examining this important dimension of risk.

PMID:41474502 | DOI:10.1080/13803395.2025.2609824

World J Microbiol Biotechnol. 2025 Dec 31;42(1):17. doi: 10.1007/s11274-025-04755-3.

ABSTRACT

The function of the livestock gut microbiome in driving animal growth, health, and methane emissions is controlled by networks of interactions among microbes. A major challenge is to move beyond simply listing microbial members to understanding these interaction networks, which determine how the community functions as a whole. This review synthesizes how network analysis, combined with multi-omics data, can meet this challenge. We focus on the critical task of identifying keystone species, the disproportionately influential microbes that direct processes like fiber digestion and immune function, yet are often missed by standard surveys. We evaluate a progression of methods, from identifying correlated species to building models that integrate genomic, metabolic, and host data. This integration is key to separating true ecological relationships from statistical noise and to linking microbial presence to function. We highlight how computational techniques like metabolic modeling and machine learning are turning networks into predictive tools. Finally, we outline the path forward: field-ready studies that track microbiomes over time, the development of livestock-specific metabolic models, and analytical standards that will allow research to translate into practical strategies. The goal is to provide a framework for using network science to actively manage the microbiome, enhancing sustainable livestock production.

PMID:41474484 | DOI:10.1007/s11274-025-04755-3