MHGCL: Multimodal heterogeneous graph contrastive learning for cancer patient classification.

This study examines how the Science of Reading is represented in Twitter discourse and compares these representations to contemporary models of reading development. Although the Science of Reading is frequently positioned as an equity-oriented reform, little is known about how related ideas circulate in public discourse, particularly across social media platforms that increasingly shape teacher learning, policymaking, and public opinion. This content analysis study analyzed a sample of 14,165 tweets containing the hashtag #scienceofreading from 2020–2021 and 2022–2023. It explores two primary questions investigating (1) the extent to which essential literacy skills (e.g., phonological awareness, phonics, comprehension, vocabulary) are referenced in tweets or linked content and (2) the extent to which specific subgroup classifications identified by the National Assessment of Educational Progress (e.g., Black, Hispanic, students with disabilities, low-income, and other populations) are mentioned in the same sample of discourse on Twitter. Findings demonstrate that online discourse on Twitter (now X) includes more references to decoding-related skills such as phonological awareness and phonics, with far fewer mentions of language-related skills such as comprehension or vocabulary. Mentions of subgroups were minimal, while references to students with disabilities with explicit mention of dyslexia occurred at four times the frequency of race- or income-related subgroups. These distributions contrast with persistent national achievement disparities and suggest that contemporary Science of Reading discourse is more strongly oriented toward decoding-related skills than toward equity-focused concerns. Implications for teacher preparation, policy enactment, and critical media literacy are discussed.

This study aimed to identify the core symptoms in patients following glioma surgery by constructing a symptom network model and to classify patient subgroups exhibiting heterogeneity through latent profile analysis. A cross-sectional survey was conducted on 357 adult patients with glioma one week after surgery, utilizing the Chinese version of the Anderson Brain Tumor Symptom Scale. Core symptoms were identified via network analysis, and distinct subgroups were delineated using latent profile analysis. "Weakness" emerged as a core symptom. Three subgroups with distinct characteristics were identified: (1) "Digestive & Emotional Disturbance Predominant - Low Incidence, High Symptom Burden" Cluster (2) "Sleep and Functional Impairment Predominant - High Incidence, High Symptom Burden Cluster" (3) "High Incidence, Low Symptom Burden Cluster". These findings provide a scientific foundation for targeted symptom management. From a population perspective, interventions should prioritize core symptoms following glioma surgery. From an individual perspective, heterogeneous glioma patients require tailored treatment and management based on subgroup classification. The results of this study are helpful for medical staff to make judgments on the postoperative prognosis symptoms of glioma patients and carry out precise intervention, and at the same time can improve the symptom education of postoperative glioma patients.

Severity-dependent alterations of EEG microstate dynamics in obsessive-compulsive disorder.

Accurate identification of medulloblastoma molecular subgroups is essential, particularly in settings lacking advanced genomic tools. Conventional markers, such as β-catenin, present significant challenges in reliably detecting the WNT-activated subgroup (WNT-AG). To evaluate the utility of lymphoid enhancer-binding factor 1 (LEF1), Cyclin D1, and receptor tyrosine kinase-like orphan receptor 2 (ROR2) as immunohistochemical (IHC) markers for molecular subgroup classification and to assess their prognostic significance. Retrospective cohort study. IHC analysis was performed using LEF1, Cyclin D1, and ROR2. Two distinct LEF1 staining patterns were identified: nuclear (nLEF1) and punctate (pLEF1). A subset of 29 cases, selected based on predefined criteria, underwent EPIC array Methylation analysis. Findings were correlated with recurrence and survival outcomes. Among the 94 cases, 12.8% were WNT-AG, 54.3% were sonic hedgehog-activated subgroup (SHH-AG), and 33.0% were Groups 3 and 4 (G3/4). nLEF1 demonstrated higher specificity and sensitivity for WNT-AG than β-catenin, identifying it as a more reliable diagnostic marker. High pLEF1 expression was strongly associated with SHH-AG. Cyclin D1 positivity was predominantly observed in WNT-AG. While ROR2 did not identify WNT-AG effectively, its absence in Group 3 cases was notable. Prognostic analysis revealed that LEF1 expression patterns correlated with favorable survival outcomes: total LEF1 (tLEF1) and nLEF1 were associated with improved overall survival, whereas pLEF1 and tLEF1 were linked to better progression-free survival. Nuclear LEF1 (nLEF1) is at least as effective as β-catenin in identifying WNT-AG and may serve as a superior diagnostic marker. Cyclin D1 can be used as a complementary marker in WNT-AG detection. ROR2 negativity may indicate G3 tumors, though further studies are warranted to confirm its prognostic value.

ABSTRACT This study examined the characteristics, developmental trajectories, and associated factors of adolescent anxiety and depression using a longitudinal design. A total of 736 high school students in Gansu Province, China, were followed across a two-month interval. Latent transition analysis (LTA) was used to identify changes in latent symptom profiles over time, and multinomial logistic regression analyses examined associations of internal (neuroticism) and external (negative life events) factors with subgroup membership and transitions. Three distinct latent classes were identified: a low-depression group, a low-symptom group, and a comorbid group. LTA quantified transition probabilities between these classes from Time 1 to Time 2. Overall, class membership showed high stability, although both symptom progression (e.g., transitions from the low-depression group to the low-symptom group) and symptom recovery (e.g., transitions from the comorbid group to lower-symptom groups) were observed. Further analyses indicated that neuroticism and negative life events correlated with baseline subgroup classification, with negative life events additionally related to transitions between groups. Gender had no significant effect on the occurrence and development of short-term anxiety and depression. These findings highlight the heterogeneity and dynamic nature of adolescent anxiety and depression and underscore the role of contextual stressors in short-term symptom development.

Objective: To identify potential clinical subgroups among parents who lost their only child and compare inter-subgroup differences in brain structure and function. Methods: Parents who lost their only child and participated in a psychological assistance program organized by the local civil affairs department in Southern Jiangsu, China, between April 2021 and June 2022 were retrospectively recruited. They were randomly divided into a discovery set and a validation set in a 1∶1 ratio using a random number table. Assessments included the Clinician Administered Post-Traumatic Stress Disorder Scale (CAPS), the 24-item Hamilton Depression Rating Scale (HAMD-24), and the Hamilton Anxiety Rating Scale (HAMA). Seven symptom dimension factors were extracted: re-experiencing, avoidance, hyperarousal, depressive mood, somatic/anxiety, psychic anxiety, and somatic anxiety. Hierarchical clustering was applied in the discovery set to identify clinical subgroups. The stability of this classification was verified in the validation set. Cranial MRI scans were conducted to compare differences in fractional anisotropy (FA) from diffusion tensor imaging, as well as degree centrality (DC) and regional homogeneity (ReHo) from functional MRI among the different subgroups. Pearson correlation analysis was used to assess the correlations between neuroimaging metrics and scale scores. Results: A total of 154 parents who lost their only child were enrolled, with an average age of (57.6±5.2) years, including 68 males (44.2%), and a mean trauma duration of (15.1±5.1) months. The discovery set and the validation set each comprised 77 participants. Hierarchical clustering and cross-validation consistently identified two stable subgroups. Subgroup A was characterized by core features of traumatic re-experiencing, cognitive avoidance, and depressive mood, while subgroup B was dominated by somatization symptoms and anxiety. Neuroimaging results showed that compared with subgroup B, subgroup A exhibited significantly higher FA values in multiple white matter tracts closely associated with emotion regulation and cognitive processing (P<0.05, corrected with threshold-free cluster enhancement). Compared with subgroup A, subgroup B demonstrated higher DC in the left precentral gyrus (t=-3.02, Gaussian random field-corrected P=0.003) and lower ReHo in the left middle frontal gyrus (t=3.90, Gaussian random field-corrected P=0.001). Correlation analyses indicated that FA values in white matter tracts were positively correlated with total CAPS score, total HAMD-24 score, and specific CAPS factors (avoidance, re-experiencing) (r=0.30-0.36, false discovery rate-corrected P<0.05). DC values in the left precentral gyrus were positively correlated with total HAMA score and the somatic anxiety factor (r=0.32-0.37, false discovery rate-corrected P<0.05). Conclusions: Parents who lost their only child can be categorized into two clinical subgroups: one dominated by emotional disturbances and the other by somatic anxiety. The observed differences in brain structure and function provide neurobiological evidence for this subgroup classification and may suggest potential targets for precise neuromodulation interventions.

Traditional cardiovascular disease (CVD) risk models may fail to adequately capture the interactions among metabolic factors. We evaluated the combined and mediating associations of the triglyceride-glucose (TyG) index and uric acid (UA) with incident CVD in Chinese adults. Using data from the nationally representative China Health and Retirement Longitudinal Study, we included 9,353 participants aged ≥ 45 years without baseline CVD or cancer, whose fasting triglycerides, glucose, and UA were measured in 2011, and who were followed up through 2020. TyG was calculated as ln [triglycerides (mg/dL) × glucose (mg/dL)/2]. Incident CVD (including myocardial infarction, coronary heart disease, angina pectoris, congestive heart failure, or stroke) was ascertained via standardized self-reported questionnaires. Cox proportional hazards models were used to quantify the relationship between TyG index/UA level, their combination categories and CVD events. Kaplan-Meier curves were used to illustrate the time-dependent association and synergistic effect of TyG index and UA on CVD-related outcomes. Age subgroup classification was used to analyze the effects of two biomarkers on CVD at different ages. Mediation analysis was conducted to assess the direct and indirect associations between two biomarkers and CVD events. During the 9-year follow-up, 2505 (26.8%) individuals developed CVD, including 1745 (18.7%) cases of CHD and760 (8.1%) cases of stroke. Compared with TyG < median (8.59) and UA 4-5 mg/dL, higher TyG and higher UA were each associated with greater CVD risk (fully adjusted HR = 1.146 for TyG ≥ median and HR = 1.167 for UA > 6 mg/dL, all P < 0.05). The joint category of TyG ≥ median and UA > 6 mg/dL showed the strongest association, especially for stroke (fully adjusted HR = 2.193). Elevated TyG and UA levels jointly increased the cumulative incidence of CVD (41.1%), coronary heart disease (31.5%), and stroke (119.3%) relative to the reference group. Synergy was most evident at ages 45-59 and was not significant at ≥ 70 years. Mediation analyses supported a bidirectional pathway: TyG affected CVD via UA and UA affected CVD via TyG. The TyG index and UA levels independently and synergistically increase CVD risk in middle-aged and elderly Chinese adults, with the strongest synergistic effect observed in middle-aged individuals (45-59 years). A bidirectional mediating relationship exists between the TyG index and UA in their effects on CVD. Combined assessment of the TyG index and UA may improve CVD risk stratification, supporting more refined clinical and public health interventions for CVD prevention.

Global patterns and knowledge gaps in rare earth element bioaccumulation in wildlife: A systematic review.

Introns are generally considered rare in bacteria, yet they are frequently observed in Patescibacteria, which have highly reduced genomes. To systematically explore the diversity, roles, and evolution of introns in Patescibacteria, we first focused on the tRNA introns. Using 95 complete genomes, we identified tRNAAsn and tRNAAsp genes previously undetected by standard annotation tools due to group I introns inserted at an unusual position, 35/36, in the anticodon loop. In vitro splicing assays confirmed that these introns catalyze precise self-splicing, validating our computational approach. A large-scale survey of complete bacterial genomes revealed that intron insertions at position 35/36 are highly enriched in Patescibacteria but rare in other phyla. Subgroup classification indicated that 81% of all tRNA introns belong to the IC subgroup, whereas nearly all Patescibacteria introns were classified as IA. As most tRNA introns lack homing endonuclease genes, horizontal transfer appears limited. Comparative analysis across bacterial phyla showed that Patescibacteria and Cyanobacteriota exhibit the highest prevalence of group I introns (~40% of genomes). In contrast, group II introns, which require protein cofactors for activity, were more common in other bacteria, including Cyanobacteriota, but absent in Patescibacteria. Collectively, these findings suggest that Patescibacteria harbor introns with phylum-specific trends in abundance, structure, and evolutionary lineage. The coexistence of extensive genome reduction and persistent group I introns may reflect an adaptive strategy, where introns serve as efficient RNA-based regulatory elements, potentially substituting for complex protein-mediated systems.IMPORTANCEIntrons were traditionally thought to be rare in bacteria, yet their occurrence and diversity may have been underestimated. Here, we present the first comprehensive overview of group I and group II introns in Patescibacteria. While most introns are readily identified, group I introns inserted at position 35/36 within the anticodon loop often escape detection by standard annotation tools; through experimental verification, we demonstrate that these introns are accurately spliced despite their unusual insertion site. Notably, approximately 40% of genomes in both Patescibacteria and Cyanobacteriota harbor group I introns; however, while around 20% of Cyanobacteriota genomes also contain group II introns, none were detected in Patescibacteria. These results illustrate a previously overlooked phylogenetic distribution of group I and group II introns across the bacterial domain.

Work of Bourdon–Clark–Pollack shows that the set of degrees d ∈ Z + for which the classification of torsion subgroups of CM elliptic curves over all number fields of degree d is the same as the classification of CM torsion of elliptic curves over Q has positive asymptotic density. Based on this, I conjectured that for every d 0 ∈ Z + , the set of d ∈ Z + such that the classification of CM torsion in degree d as the same as in degree d 0 has positive density. This was proven for all odd d 0 by Bourdon–Pollack in 2017. Here we give the first results on even d 0 : the conjecture holds for d 0 = 2 and for d 0 = 2 p 0 for a set of primes p 0 of relative density one. However, we will also explain why the conjecture seems likely to be false for d 0 = 2 p 0 where p 0 lies in an infinite set of prime numbers, including p 0 = 3 .

Acute respiratory distress syndrome (ARDS) is a highly heterogeneous disease with clinical manifestations that may overlap with severe pneumonia, posing challenges for accurate differentiation. Therefore, early prediction and bedside rapid subtype clustering of ARDS patients are urgently needed. This study aims to develop a web-based system, which includes validated models of early bedside diagnosis and clinical subgroup classification, for predicting the development and phenotypes of pneumonia-associated ARDS. Diagnostic and subgroup models were developed and validated from the two large databases, Medical Information Mart for Intensive Care IV (MIMIC-IV) and Telehealth Intensive Care Unit (eICU) and were incorporated into a web-based prediction system. Data from patients with pneumonia hospitalized for more than 24 h between 2008 and 2019 were analyzed. The MIMIC-IV derivation cohort included 24,987 patients with pneumonia (14,121 with pneumonia-associated ARDS); the eICU verification cohort included 20,676 patients with pneumonia (9946 with pneumonia-associated ARDS). In diagnosis, the stacking method of machine learning performed best with an AUC of 0.919, an accuracy of 70.00%, a precision of 69.88% and a recall of 82.27% in the MIMIC-IV derivation cohort. The AUC, accuracy, precision, and recall of the eICU validation cohort were 0.915, 70.87%, 69.70% and 69.70% respectively. Pneumonia-associated ARDS was classified into three clinical phenotypes with different clinical characteristics and outcomes, all of which responded differently to treatment. Among patients in clusters 0 and 1, the in-hospital mortality rates were higher among those who received early corticosteroid treatment than among those who did not, whereas among patients in cluster 2, the in-hospital mortality rate was lower among those who received corticosteroids than among those who did not. We performed a web transformation of the diagnosis prediction and clinical subgroup classification of pneumonia-associated ARDS.Our web-based models of early bedside diagnosis and clinical subgroup classification of pneumonia-associated ARDS may assist clinicians in diagnosing and treating the disease and in promoting individualized precision treatment.

ABSTRACT Clustering is a fundamental problem in many scientific applications. This paper introduces the concept of K -regression, which divides a random sample of size n into K clusters such that the observations within each cluster exhibit an identical linear pattern of dependence, and the observations in different clusters exhibit distinctive structures of linear dependence. We estimate the coefficients of the clustering regressions through minimizing the within cluster ℓ 1 and ℓ 2 loss functions. From the asymptotic perspective, the resulting estimates obtained with either the ℓ 1 or the ℓ 2 loss are strongly consistent and asymptotically normal. From the non-asymptotic perspective, we further explore the conditions under which the models are identifiable and the algorithms are convergent. Furthermore, we propose a tailored Bayesian Information Criterion (BIC) designed specifically for regression-based clustering. Through extensive simulations and an application to clinical trial subgroup analysis, we demonstrate the effectiveness of K -regression. Numerical results highlight that, in the presence of heterogeneity, ℓ 1 K -regression outperforms alternative methods (including ℓ 2 K -regression) in coefficient estimation, cluster number determination, and subgroup classification while maintaining computational efficiency. These advantages make ℓ 1 K -regression particularly appealing for large-scale data analysis, especially when heterogeneous subpopulations are present.

The objective of this study was the development and validation of a clinical investigation protocol for tinnitus and the analysis of its applicability. The research was conducted in eight stages: Stage 1: Literature review and development of the pilot protocol; Stage 2: Expert judges I - first analysis/evaluation; Stage 3: Elaboration of the unified investigation protocol and the application guide; Stage 4: Expert judges II - second analysis/evaluation of the instruments from the previous stage; Stage 5: Refinement of materials; Stage 6: Application of the protocol by expert and non-expert clinicians; Stage 7: Final construction; Stage 8: Pilot study - convenience sample. The results of each stage were compiled into an Excel spreadsheet for specific analyses (content validity ratio calculation and suggestions). The structure of the protocol was successfully developed, resulting in a unified instrument subdivided into: tinnitus-focused anamnesis, audiological, emotional, metabolic, somatosensory, and vascular history, assessment results, a framework for subgroup classification, clinical decision tree, and complementary evaluations. The protocol was applied to a sample of 83 adults and older individuals. The clinical investigation protocol for tinnitus was finalized and its content validated, demonstrating applicability for adult and elderly individuals with tinnitus.

ABSTRACT Purpose The objective of this study was the development and validation of a clinical investigation protocol for tinnitus and the analysis of its applicability. Methods The research was conducted in eight stages: Stage 1: Literature review and development of the pilot protocol; Stage 2: Expert judges I – first analysis/evaluation; Stage 3: Elaboration of the unified investigation protocol and the application guide; Stage 4: Expert judges II – second analysis/evaluation of the instruments from the previous stage; Stage 5: Refinement of materials; Stage 6: Application of the protocol by expert and non-expert clinicians; Stage 7: Final construction; Stage 8: Pilot study – convenience sample. The results of each stage were compiled into an Excel spreadsheet for specific analyses (content validity ratio calculation and suggestions). Results The structure of the protocol was successfully developed, resulting in a unified instrument subdivided into: tinnitus-focused anamnesis, audiological, emotional, metabolic, somatosensory, and vascular history, assessment results, a framework for subgroup classification, clinical decision tree, and complementary evaluations. The protocol was applied to a sample of 83 adults and older individuals. Conclusion The clinical investigation protocol for tinnitus was finalized and its content validated, demonstrating applicability for adult and elderly individuals with tinnitus.

Objectives: Previous research has primarily focused on typical error patterns, with limited attention to atypical error patterns in children with speech sound disorders (SSDs). This study aimed to investigate both typical and atypical error patterns in children with SSDs and to explore their clinical implications. Methods: Fifty children aged 4–6 years with SSDs of unknown origin were assessed using the Urimal Test of Articulation and Phonology 2 (UTAP2) word and sentence tasks. Error patterns were classified as typical or atypical, and the number of children and the frequency of occurrence for each pattern were carefully analyzed. Results: A majority of children exhibited most of the typical error patterns with high frequency. In addition, several atypical error patterns that may be frequently encountered in clinical practice were identified. Interestingly, several atypical error patterns were repeatedly observed within a small subset of children, indicating potential subgroup-specific characteristics. Conclusion: This study identified both common and rare error patterns in children with SSDs, providing empirical evidence that may inform clinical goal setting and intervention prioritization. Moreover, the atypical error patterns observed may reflect the heterogeneous characteristics of SSDs, thereby providing a solid foundation for future research on subgroup classification and for developing consistent analytic frameworks that can be effectively applied to the diagnosis and intervention planning for children with SSDs.

BACKGROUND:Cardiovascular disease (CVD) is a leading cause of diabetes-related mortality in Mexico. Although diabetes subgroups capture underlying disease heterogeneity, their association and utility for risk prediction for fatal CVD in Mexican adults remain unclear.METHODS:We analyzed 24,943 adults with diabetes from the Mexico City Prospective Study. Participants were classified into mild obesity-related (MOD), severe insulin-deficient (SIDD), severe insulin-resistant (SIRD), and mild age-related (MARD) diabetes using a self-normalizing neural network algorithm. Fatal CVD was defined as death from ischemic heart disease or stroke (ICD-10 I20–I25, I60–I69). SCORE2-Diabetes was recalibrated and validated overall and by diabetes subgroup. Cox proportional hazards models were used to estimate subgroup-specific risk, and sequential models evaluated the incremental predictive value of diabetes subgroups combined with SCORE2-Diabetes and traditional risk factors.RESULTS:Over a median follow-up of 19.3 years (IQR 12.7–20.6), 2,223 fatal CVD events (8.9%) were recorded. SIDD was the most prevalent subgroup (50.6%), followed by SIRD (17.3%), MARD (16.8%), and MOD (15.4%). SIDD and MARD showed the highest adjusted risk of fatal CVD (RR 1.58 [95%CI 1.38–1.81] and 1.35 [1.13–1.60]), whereas MOD and SIRD had lower risk. Recalibrated SCORE2-Diabetes demonstrated adequate discrimination overall (c-statistic 0.759, 95%CI 0.745–0.773) and for most subgroups but underperformed in MARD, with recalibration improving risk assessment. The combination of diabetes subgroups and SCORE2-Diabetes improved prediction for fatal CVD outcomes.CONCLUSIONS:Diabetes subgroups show heterogeneity in fatal CVD risk in Mexican adults. SIDD and MARD identify high-risk individuals and integration subgroup classification with SCORE2-Diabetes enhances risk prediction.

To validate a subgroup classification tool designed to support clinical decision-making in vestibular physiotherapy. A structured instrument was developed based on the main vestibular disorders commonly treated by physiotherapists. The tool was applied by professionals to simulated clinical cases. Content validation was performed by expert judges using the Delphi technique. The Content Validity Index was calculated for each item. The tool obtained a Content Validity Index of 0.78 or more across all domains in the first round and reached 100 per cent agreement among experts in the second round, confirming its content validity. The tool demonstrated clarity, coherence and clinical relevance for decision-making in vestibular rehabilitation. The validated tool presents evidence of content validity and clinical applicability, offering support for physiotherapists in the classification and management of vestibular disorders.

BackgroundChild mortality remains a major health burden in low- and middle-income countries (LMICs), where adherence to pediatric clinical guidelines is often suboptimal. Diagnostic capacity, the availability of essential laboratory and imaging tests, is a key structural input for delivering high-quality pediatric care, yet its relationship with quality of care has received limited empirical attention. This study examines the association between diagnostic capacity and adherence to evidence-based pediatric care guidelines across eight LMICs.MethodsWe analyzed nationally representative Service Provision Assessment (SPA) data from 5311 health facilities across eight LMICs (Afghanistan, the Democratic Republic of the Congo, Ethiopia, Haiti, Malawi, Nepal, Senegal, and Tanzania) collected between 2014 and 2022. Quality of care was assessed using a 10-item adherence index derived from direct observations of outpatient consultations, aligned with the WHO Integrated Management of Childhood Illness (IMCI) protocol. Diagnostic capacity was measured using a 16-item index reflecting the availability of essential laboratory and imaging tests recommended in the WHO Essential Diagnostics List. Associations between diagnostic capacity and adherence to clinical guidelines were examined using multilevel mixed-effects generalized linear models, adjusting for facility-, provider-, and patient-level covariates.ResultsDiagnostic capacity varied substantially across countries and facility levels. Among primary care facilities, median diagnostic availability ranged from 20.1% in Malawi to 72.4% in Senegal; among hospitals, from 64.7% in the Democratic Republic of the Congo to 88.5% in Ethiopia. On a 10-point scale, pediatric care quality scores were lowest in Afghanistan (3.45) and highest in DR Congo (4.89). Higher diagnostic capacity was significantly associated with greater adherence to pediatric clinical guidelines (adjusted log-odds β = 0.138; 95% CI: 0.061–0.216; p < 0.001). Sensitivity analyses using alternative outcome definitions, exposure measures, subgroup classifications, and model specifications yielded consistent results.ConclusionsThis multi-country observational study identifies a positive association between diagnostic readiness and the quality of pediatric care in LMICs. These findings suggest that diagnostic capacity may serve as an enabling structural condition for delivering higher-quality pediatric care in LMICs, reinforcing the role of diagnostics within health system strengthening strategies.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12916-025-04517-w.

Type 2 diabetes mellitus (T2DM) is a common chronic disease, particularly affecting cross-cultural populations. These populations face socioeconomic, cultural, and health care barriers that hinder optimal disease management. Evidence suggests that culturally competent care (CCC) can improve diabetes management. To evaluate the efficacy of CCC on blood glucose and body weight in cross-cultural T2DM patients through a meta-analysis. We included 33 randomized controlled trials (RCTs) with 6,956 participants. Studies were identified from eight databases. Risk of bias was assessed, and the meta-analysis was conducted using R. CCC led to significant reductions in HbA1c, body mass index (BMI), and fasting blood glucose (FBG) (p < .05). However, the effect on low-density lipoprotein (LDL) was inconclusive (p > .05). CCC improves blood glucose and weight management in cross-cultural T2DM patients. Further research is needed to explore long-term effects, optimize strategies, and refine subgroup classifications.