Medicine & Health

456 items

Frontiers in Medicine Sep 28, 2026
This retrospective study of 494 patients (145 with complete discoid lateral meniscus, CDLM; 64 with incomplete discoid lateral meniscus, ICDLM; 285 normal lateral meniscus controls) measured multiple tibial plateau radiographic anatomical parameters, used LASSO to select six features (gender, lateral joint space, height of lateral tibial spine, lateral slope of the lateral tibial spine, lateral slope of the medial tibial spine, and tibial eminence width/tibial plateau width ratio), built seven machine-learning models, and evaluated them in a held-out validation set, where the best CDLM model (support vector machine) reached an AUC of 0.885 and the best ICDLM model (gradient boosting) reached an AUC of 0.861.
This retrospective study of 494 patients (145 with complete discoid lateral meniscus, CDLM; 64 with incomplete discoid lateral meniscus, ICDLM; 285 normal lateral meniscus controls) measured multiple tibial plateau radiographic anatomical parameters, used LASSO to select six features (gender, lateral joint space, height of lateral tibial spine, lateral slope of the lateral tibial spine, lateral slope of the medial tibial spine, and tibial eminence width/tibial plateau width ratio), built seven machine-learning models, and evaluated them in a held-out validation set, where the best CDLM model (support vector machine) reached an AUC of 0.885 and the best ICDLM model (gradient boosting) reached an AUC of 0.861.
Suzhou University team uses tibial plateau X-ray parameters plus machine learning to identify complete and incomplete discoid lateral meniscus, reaching validation AUCs of 0.885 and 0.861
This retrospective study of 494 patients (145 with complete discoid lateral meniscus, CDLM; 64 with incomplete discoid lateral meniscus, ICDLM; 285 normal lateral meniscus controls) measured multiple tibial plateau radiographic anatomical parameters, used LASSO to select six features (gender, lateral joint space, height of lateral tibial spine, lateral slope of the lateral tibial spine, lateral slope of the medial tibial spine, and tibial eminence width/tibial plateau width ratio), built seven machine-learning models, and evaluated them in a held-out validation set, where the best CDLM model (support vector machine) reached an AUC of 0.885 and the best ICDLM model (gradient boosting) reached an AUC of 0.861.
This retrospective study of 494 patients (145 with complete discoid lateral meniscus, CDLM; 64 with incomplete discoid lateral meniscus, ICDLM; 285 normal lateral meniscus controls) measured multiple tibial plateau radiographic anatomical parameters, used LASSO to select six features (gender, lateral joint space, height of lateral tibial spine, lateral slope of the lateral tibial spine, lateral slope of the medial tibial spine, and tibial eminence width/tibial plateau width ratio), built seven machine-learning models, and evaluated them in a held-out validation set, where the best CDLM model (support vector machine) reached an AUC of 0.885 and the best ICDLM model (gradient boosting) reached an AUC of 0.861.
Research Square Sep 28, 2026
Using COPD-related datasets from a public database, this study applied differential expression analysis, machine learning, and gene expression analysis to identify APRT and S100A8 as lipotoxicity-related COPD biomarkers (APRT notably lower and S100A8 notably higher in COPD samples), supported by RT-qPCR, built and validated a nomogram for predicting COPD risk (P = 0.395 in the Hosmer-Lemeshow test), found both biomarkers co-enriched in the "focal adhesion" pathway and significantly correlated with neutrophils, predicted 27 drugs targeting APRT (such as alteplase and relaxin) and methotrexate targeting S100A8, and used scRNA-seq to identify macrophages as a key cell type in COPD with dynamic expression patterns of both biomarkers during macrophage differentiation.
Using COPD-related datasets from a public database, this study applied differential expression analysis, machine learning, and gene expression analysis to identify APRT and S100A8 as lipotoxicity-related COPD biomarkers (APRT notably lower and S100A8 notably higher in COPD samples), supported by RT-qPCR, built and validated a nomogram for predicting COPD risk (P = 0.395 in the Hosmer-Lemeshow test), found both biomarkers co-enriched in the "focal adhesion" pathway and significantly correlated with neutrophils, predicted 27 drugs targeting APRT (such as alteplase and relaxin) and methotrexate targeting S100A8, and used scRNA-seq to identify macrophages as a key cell type in COPD with dynamic expression patterns of both biomarkers during macrophage differentiation.
Transcriptomic and single-cell sequencing identify lipotoxicity-related COPD biomarkers APRT and S100A8, validated by RT-qPCR and a nomogram
Using COPD-related datasets from a public database, this study applied differential expression analysis, machine learning, and gene expression analysis to identify APRT and S100A8 as lipotoxicity-related COPD biomarkers (APRT notably lower and S100A8 notably higher in COPD samples), supported by RT-qPCR, built and validated a nomogram for predicting COPD risk (P = 0.395 in the Hosmer-Lemeshow test), found both biomarkers co-enriched in the "focal adhesion" pathway and significantly correlated with neutrophils, predicted 27 drugs targeting APRT (such as alteplase and relaxin) and methotrexate targeting S100A8, and used scRNA-seq to identify macrophages as a key cell type in COPD with dynamic expression patterns of both biomarkers during macrophage differentiation.
Using COPD-related datasets from a public database, this study applied differential expression analysis, machine learning, and gene expression analysis to identify APRT and S100A8 as lipotoxicity-related COPD biomarkers (APRT notably lower and S100A8 notably higher in COPD samples), supported by RT-qPCR, built and validated a nomogram for predicting COPD risk (P = 0.395 in the Hosmer-Lemeshow test), found both biomarkers co-enriched in the "focal adhesion" pathway and significantly correlated with neutrophils, predicted 27 drugs targeting APRT (such as alteplase and relaxin) and methotrexate targeting S100A8, and used scRNA-seq to identify macrophages as a key cell type in COPD with dynamic expression patterns of both biomarkers during macrophage differentiation.
Research Square Sep 28, 2026
This work presents an end-to-end comparative medical imaging framework that evaluates ResNet50, EfficientNet-B0, DenseNet121, DeiT-Small, and Swin-Tiny across three heterogeneous tasks—chest X-ray pneumonia classification, brain MRI tumor detection, and dermoscopic skin cancer classification—integrating transfer learning, class-imbalance handling, model calibration, bootstrap confidence intervals, robustness evaluation, failure-case analysis, Grad-CAM explainability, ensemble learning, and extensive performance metrics, together with an LLM-driven reporting component constrained to research-oriented assistance that generates structured model-comparison summaries, explainability interpretations, and decision-support reports; results indicate that CNNs remain highly effective for structured
This work presents an end-to-end comparative medical imaging framework that evaluates ResNet50, EfficientNet-B0, DenseNet121, DeiT-Small, and Swin-Tiny across three heterogeneous tasks—chest X-ray pneumonia classification, brain MRI tumor detection, and dermoscopic skin cancer classification—integrating transfer learning, class-imbalance handling, model calibration, bootstrap confidence intervals, robustness evaluation, failure-case analysis, Grad-CAM explainability, ensemble learning, and extensive performance metrics, together with an LLM-driven reporting component constrained to research-oriented assistance that generates structured model-comparison summaries, explainability interpretations, and decision-support reports; results indicate that CNNs remain highly effective for structured
An end-to-end agentic framework compares CNNs and vision transformers across three medical imaging tasks and adds LLM-generated structured reports
This work presents an end-to-end comparative medical imaging framework that evaluates ResNet50, EfficientNet-B0, DenseNet121, DeiT-Small, and Swin-Tiny across three heterogeneous tasks—chest X-ray pneumonia classification, brain MRI tumor detection, and dermoscopic skin cancer classification—integrating transfer learning, class-imbalance handling, model calibration, bootstrap confidence intervals, robustness evaluation, failure-case analysis, Grad-CAM explainability, ensemble learning, and extensive performance metrics, together with an LLM-driven reporting component constrained to research-oriented assistance that generates structured model-comparison summaries, explainability interpretations, and decision-support reports; results indicate that CNNs remain highly effective for structured
This work presents an end-to-end comparative medical imaging framework that evaluates ResNet50, EfficientNet-B0, DenseNet121, DeiT-Small, and Swin-Tiny across three heterogeneous tasks—chest X-ray pneumonia classification, brain MRI tumor detection, and dermoscopic skin cancer classification—integrating transfer learning, class-imbalance handling, model calibration, bootstrap confidence intervals, robustness evaluation, failure-case analysis, Grad-CAM explainability, ensemble learning, and extensive performance metrics, together with an LLM-driven reporting component constrained to research-oriented assistance that generates structured model-comparison summaries, explainability interpretations, and decision-support reports; results indicate that CNNs remain highly effective for structured
Frontiers in Cellular and Infection Microbiology Sep 28, 2026
The authors built unmarked single- and double-knockout Mycobacterium tuberculosis strains lacking MTS0997, MTS1338, or both, profiled whole-genome expression during culture growth, in IFN-γ-activated and non-activated murine bone marrow-derived macrophages, and in infection of highly TB-susceptible I/St mice, and found that MTS0997 deletion had the larger impact on bacterial biology (altered succinate/fumarate respiration, up-regulated ESX-1 secretion genes, increased virulence in mice, reduced lung pro-inflammatory cytokine production), that all three knockout strains killed mice significantly faster than wild type while lung CFU counts at 6 weeks did not differ, and that B-cell and MHC-II-expressing lung cell populations differed between single- and double-knockout infections, suggesting
The authors built unmarked single- and double-knockout Mycobacterium tuberculosis strains lacking MTS0997, MTS1338, or both, profiled whole-genome expression during culture growth, in IFN-γ-activated and non-activated murine bone marrow-derived macrophages, and in infection of highly TB-susceptible I/St mice, and found that MTS0997 deletion had the larger impact on bacterial biology (altered succinate/fumarate respiration, up-regulated ESX-1 secretion genes, increased virulence in mice, reduced lung pro-inflammatory cytokine production), that all three knockout strains killed mice significantly faster than wild type while lung CFU counts at 6 weeks did not differ, and that B-cell and MHC-II-expressing lung cell populations differed between single- and double-knockout infections, suggesting
Knocking out M. tuberculosis small RNAs MTS0997 and MTS1338 shortens mouse survival without changing lung bacterial burden
The authors built unmarked single- and double-knockout Mycobacterium tuberculosis strains lacking MTS0997, MTS1338, or both, profiled whole-genome expression during culture growth, in IFN-γ-activated and non-activated murine bone marrow-derived macrophages, and in infection of highly TB-susceptible I/St mice, and found that MTS0997 deletion had the larger impact on bacterial biology (altered succinate/fumarate respiration, up-regulated ESX-1 secretion genes, increased virulence in mice, reduced lung pro-inflammatory cytokine production), that all three knockout strains killed mice significantly faster than wild type while lung CFU counts at 6 weeks did not differ, and that B-cell and MHC-II-expressing lung cell populations differed between single- and double-knockout infections, suggesting
The authors built unmarked single- and double-knockout Mycobacterium tuberculosis strains lacking MTS0997, MTS1338, or both, profiled whole-genome expression during culture growth, in IFN-γ-activated and non-activated murine bone marrow-derived macrophages, and in infection of highly TB-susceptible I/St mice, and found that MTS0997 deletion had the larger impact on bacterial biology (altered succinate/fumarate respiration, up-regulated ESX-1 secretion genes, increased virulence in mice, reduced lung pro-inflammatory cytokine production), that all three knockout strains killed mice significantly faster than wild type while lung CFU counts at 6 weeks did not differ, and that B-cell and MHC-II-expressing lung cell populations differed between single- and double-knockout infections, suggesting
Frontiers in Oncology Sep 28, 2026
This network meta-analysis pooled 10 phase III randomized controlled trials with over 8,000 patients with unresectable advanced gastric cancer, ranked first-line immune checkpoint inhibitors and targeted agents by SUCRA on time to deterioration across EORTC QLQ-C30, EORTC QLQ-STO22 and EQ-5D domains, and used an exploratory minimum distance criterion to integrate overall survival with health-related quality of life, finding that trastuzumab (HER2-positive population) and tislelizumab (largely biomarker-unselected population) ranked most favorably across most quality-of-life domains, while the composite metric remains exploratory, lacks uncertainty estimates, and should not serve as primary evidence for clinical decision-making.
This network meta-analysis pooled 10 phase III randomized controlled trials with over 8,000 patients with unresectable advanced gastric cancer, ranked first-line immune checkpoint inhibitors and targeted agents by SUCRA on time to deterioration across EORTC QLQ-C30, EORTC QLQ-STO22 and EQ-5D domains, and used an exploratory minimum distance criterion to integrate overall survival with health-related quality of life, finding that trastuzumab (HER2-positive population) and tislelizumab (largely biomarker-unselected population) ranked most favorably across most quality-of-life domains, while the composite metric remains exploratory, lacks uncertainty estimates, and should not serve as primary evidence for clinical decision-making.
Network meta-analysis of 10 phase III trials and over 8,000 advanced gastric cancer patients ranks trastuzumab and tislelizumab highest for delaying quality-of-life deterioration
This network meta-analysis pooled 10 phase III randomized controlled trials with over 8,000 patients with unresectable advanced gastric cancer, ranked first-line immune checkpoint inhibitors and targeted agents by SUCRA on time to deterioration across EORTC QLQ-C30, EORTC QLQ-STO22 and EQ-5D domains, and used an exploratory minimum distance criterion to integrate overall survival with health-related quality of life, finding that trastuzumab (HER2-positive population) and tislelizumab (largely biomarker-unselected population) ranked most favorably across most quality-of-life domains, while the composite metric remains exploratory, lacks uncertainty estimates, and should not serve as primary evidence for clinical decision-making.
This network meta-analysis pooled 10 phase III randomized controlled trials with over 8,000 patients with unresectable advanced gastric cancer, ranked first-line immune checkpoint inhibitors and targeted agents by SUCRA on time to deterioration across EORTC QLQ-C30, EORTC QLQ-STO22 and EQ-5D domains, and used an exploratory minimum distance criterion to integrate overall survival with health-related quality of life, finding that trastuzumab (HER2-positive population) and tislelizumab (largely biomarker-unselected population) ranked most favorably across most quality-of-life domains, while the composite metric remains exploratory, lacks uncertainty estimates, and should not serve as primary evidence for clinical decision-making.
Frontiers in Pharmacology Sep 28, 2026
The study presents a non-destructive metadata-layer framework (bridge map, typed Intermediate Representation, orchestrator) that re-exposes a legacy clinical reporting library's outputs as machine-readable JSON without modifying validated SAS source, validated on a 558-component, 372,698-line industrial SAS macro library: immediate AI readiness under coexistence mode, an optional 92% reduction in proprietary code, cell-level parity of 80% or above on 11 of 14 report types from internal Phase III study PROT008-SR1 (mean 82.7%, best 99.2%), 100% parity across 5 reports and 4,764 cells on the public CDISC CDISCPilot01 benchmark, and LLM experiments covering table summarization, adverse event anomaly detection, and trial configuration generation.
The study presents a non-destructive metadata-layer framework (bridge map, typed Intermediate Representation, orchestrator) that re-exposes a legacy clinical reporting library's outputs as machine-readable JSON without modifying validated SAS source, validated on a 558-component, 372,698-line industrial SAS macro library: immediate AI readiness under coexistence mode, an optional 92% reduction in proprietary code, cell-level parity of 80% or above on 11 of 14 report types from internal Phase III study PROT008-SR1 (mean 82.7%, best 99.2%), 100% parity across 5 reports and 4,764 cells on the public CDISC CDISCPilot01 benchmark, and LLM experiments covering table summarization, adverse event anomaly detection, and trial configuration generation.
Without touching a line of SAS source, a metadata layer turns a 558-macro clinical reporting library into LLM-readable JSON, with 11 of 14 real reports at 80%+ cell-level parity
The study presents a non-destructive metadata-layer framework (bridge map, typed Intermediate Representation, orchestrator) that re-exposes a legacy clinical reporting library's outputs as machine-readable JSON without modifying validated SAS source, validated on a 558-component, 372,698-line industrial SAS macro library: immediate AI readiness under coexistence mode, an optional 92% reduction in proprietary code, cell-level parity of 80% or above on 11 of 14 report types from internal Phase III study PROT008-SR1 (mean 82.7%, best 99.2%), 100% parity across 5 reports and 4,764 cells on the public CDISC CDISCPilot01 benchmark, and LLM experiments covering table summarization, adverse event anomaly detection, and trial configuration generation.
The study presents a non-destructive metadata-layer framework (bridge map, typed Intermediate Representation, orchestrator) that re-exposes a legacy clinical reporting library's outputs as machine-readable JSON without modifying validated SAS source, validated on a 558-component, 372,698-line industrial SAS macro library: immediate AI readiness under coexistence mode, an optional 92% reduction in proprietary code, cell-level parity of 80% or above on 11 of 14 report types from internal Phase III study PROT008-SR1 (mean 82.7%, best 99.2%), 100% parity across 5 reports and 4,764 cells on the public CDISC CDISCPilot01 benchmark, and LLM experiments covering table summarization, adverse event anomaly detection, and trial configuration generation.
Journal of Bone and Joint Surgery Sep 28, 2026
This feasibility study trained a convolutional neural network on pre-reduction injury radiographs and combined its outputs with clinical and demographic data in a random forest model to predict whether a group of fellowship-trained hand surgeons at one institution would recommend operative intervention for distal radial fractures in 1,040 patients (884 training, 156 testing); on the test set the combined model achieved 87.14% accuracy, 97% sensitivity, 73% specificity, an area under the ROC curve of 0.96, and a Brier score of 0.10, with Grad-CAM indicating the CNN focused on clinically relevant features such as fracture displacement and SHAP highlighting age and lateral wrist radiographs as key contributors.
This feasibility study trained a convolutional neural network on pre-reduction injury radiographs and combined its outputs with clinical and demographic data in a random forest model to predict whether a group of fellowship-trained hand surgeons at one institution would recommend operative intervention for distal radial fractures in 1,040 patients (884 training, 156 testing); on the test set the combined model achieved 87.14% accuracy, 97% sensitivity, 73% specificity, an area under the ROC curve of 0.96, and a Brier score of 0.10, with Grad-CAM indicating the CNN focused on clinically relevant features such as fracture displacement and SHAP highlighting age and lateral wrist radiographs as key contributors.
A deep learning model using pre-reduction radiographs and clinical-demographic data predicted hand surgeons' surgical recommendations for distal radial fractures, reaching 87.14% accuracy and 97% sensitivity on the test set
This feasibility study trained a convolutional neural network on pre-reduction injury radiographs and combined its outputs with clinical and demographic data in a random forest model to predict whether a group of fellowship-trained hand surgeons at one institution would recommend operative intervention for distal radial fractures in 1,040 patients (884 training, 156 testing); on the test set the combined model achieved 87.14% accuracy, 97% sensitivity, 73% specificity, an area under the ROC curve of 0.96, and a Brier score of 0.10, with Grad-CAM indicating the CNN focused on clinically relevant features such as fracture displacement and SHAP highlighting age and lateral wrist radiographs as key contributors.
This feasibility study trained a convolutional neural network on pre-reduction injury radiographs and combined its outputs with clinical and demographic data in a random forest model to predict whether a group of fellowship-trained hand surgeons at one institution would recommend operative intervention for distal radial fractures in 1,040 patients (884 training, 156 testing); on the test set the combined model achieved 87.14% accuracy, 97% sensitivity, 73% specificity, an area under the ROC curve of 0.96, and a Brier score of 0.10, with Grad-CAM indicating the CNN focused on clinically relevant features such as fracture displacement and SHAP highlighting age and lateral wrist radiographs as key contributors.
CAUCHY Jurnal Matematika Murni dan Aplikasi Sep 28, 2026
Using 2024 data for 38 Indonesian provinces on stunting prevalence and nine determinants (low birth weight, safe drinking water, Human Development Index, mean years of schooling, poverty rate, exclusive breastfeeding coverage, mean maternal age at first marriage, antenatal care coverage, and pediatric health service coverage), the study jointly fitted direct and cross semivariograms under a linear model of coregionalization, selected LMC = Nug + Sph(600km), and found moderate spatial dependence of stunting (SDP = 68.
Using 2024 data for 38 Indonesian provinces on stunting prevalence and nine determinants (low birth weight, safe drinking water, Human Development Index, mean years of schooling, poverty rate, exclusive breastfeeding coverage, mean maternal age at first marriage, antenatal care coverage, and pediatric health service coverage), the study jointly fitted direct and cross semivariograms under a linear model of coregionalization, selected LMC = Nug + Sph(600km), and found moderate spatial dependence of stunting (SDP = 68.
Linear model of coregionalization and co-kriging across 38 Indonesian provinces: moderate spatial dependence (SDP = 68.78%) with the highest predicted stunting in the east
Using 2024 data for 38 Indonesian provinces on stunting prevalence and nine determinants (low birth weight, safe drinking water, Human Development Index, mean years of schooling, poverty rate, exclusive breastfeeding coverage, mean maternal age at first marriage, antenatal care coverage, and pediatric health service coverage), the study jointly fitted direct and cross semivariograms under a linear model of coregionalization, selected LMC = Nug + Sph(600km), and found moderate spatial dependence of stunting (SDP = 68.
Using 2024 data for 38 Indonesian provinces on stunting prevalence and nine determinants (low birth weight, safe drinking water, Human Development Index, mean years of schooling, poverty rate, exclusive breastfeeding coverage, mean maternal age at first marriage, antenatal care coverage, and pediatric health service coverage), the study jointly fitted direct and cross semivariograms under a linear model of coregionalization, selected LMC = Nug + Sph(600km), and found moderate spatial dependence of stunting (SDP = 68.
Frontiers in Immunology Sep 28, 2026
Using network pharmacology to predict shared targets of paeonol and rosacea, then validating in an LL-37-induced rosacea-like BALB/c mouse model, the study found that 150 mg/kg paeonol markedly lowered redness area and score, reduced inflammatory cell and CD4+ T-cell infiltration and angiogenesis, and downregulated S100A9 and p65 phosphorylation, indicating its effects correlate with suppressed S100A9-NF-κB signaling.
Using network pharmacology to predict shared targets of paeonol and rosacea, then validating in an LL-37-induced rosacea-like BALB/c mouse model, the study found that 150 mg/kg paeonol markedly lowered redness area and score, reduced inflammatory cell and CD4+ T-cell infiltration and angiogenesis, and downregulated S100A9 and p65 phosphorylation, indicating its effects correlate with suppressed S100A9-NF-κB signaling.
Paeonol reduced lesions in LL-37-induced rosacea-like mice, correlating with suppressed S100A9-NF-κB signaling
Using network pharmacology to predict shared targets of paeonol and rosacea, then validating in an LL-37-induced rosacea-like BALB/c mouse model, the study found that 150 mg/kg paeonol markedly lowered redness area and score, reduced inflammatory cell and CD4+ T-cell infiltration and angiogenesis, and downregulated S100A9 and p65 phosphorylation, indicating its effects correlate with suppressed S100A9-NF-κB signaling.
Using network pharmacology to predict shared targets of paeonol and rosacea, then validating in an LL-37-induced rosacea-like BALB/c mouse model, the study found that 150 mg/kg paeonol markedly lowered redness area and score, reduced inflammatory cell and CD4+ T-cell infiltration and angiogenesis, and downregulated S100A9 and p65 phosphorylation, indicating its effects correlate with suppressed S100A9-NF-κB signaling.
Frontiers in Cardiovascular Medicine Sep 28, 2026
This cross-sectional study analyzed 165,549 users across 34 Chinese provinces and cities who completed at least one valid smartwatch-measured pulse wave velocity (SW-PWV) reading on compatible Huawei watches between December 2020 and August 2022, of whom 35,402 completed the "Vascular Health" app questionnaire; SW-PWV correlated positively with age (r=.6323), male sex and BMI (r=.1981), was significantly elevated in participants with hypertension, diabetes, dyslipidemia, coronary heart disease, stroke and carotid plaque (with hypertension and carotid plaque showing the strongest correlations), discriminated prevalent cardiovascular disease with an AUC of 0.71, and at the guideline cfPWV threshold of 10 m/s showed 13.6% sensitivity and 96.
This cross-sectional study analyzed 165,549 users across 34 Chinese provinces and cities who completed at least one valid smartwatch-measured pulse wave velocity (SW-PWV) reading on compatible Huawei watches between December 2020 and August 2022, of whom 35,402 completed the "Vascular Health" app questionnaire; SW-PWV correlated positively with age (r=.6323), male sex and BMI (r=.1981), was significantly elevated in participants with hypertension, diabetes, dyslipidemia, coronary heart disease, stroke and carotid plaque (with hypertension and carotid plaque showing the strongest correlations), discriminated prevalent cardiovascular disease with an AUC of 0.71, and at the guideline cfPWV threshold of 10 m/s showed 13.6% sensitivity and 96.
Pulse wave velocity from 165,549 smartwatches rose with age, male sex and BMI, and those at ≥10 m/s had higher cardiovascular disease prevalence
This cross-sectional study analyzed 165,549 users across 34 Chinese provinces and cities who completed at least one valid smartwatch-measured pulse wave velocity (SW-PWV) reading on compatible Huawei watches between December 2020 and August 2022, of whom 35,402 completed the "Vascular Health" app questionnaire; SW-PWV correlated positively with age (r=.6323), male sex and BMI (r=.1981), was significantly elevated in participants with hypertension, diabetes, dyslipidemia, coronary heart disease, stroke and carotid plaque (with hypertension and carotid plaque showing the strongest correlations), discriminated prevalent cardiovascular disease with an AUC of 0.71, and at the guideline cfPWV threshold of 10 m/s showed 13.6% sensitivity and 96.
This cross-sectional study analyzed 165,549 users across 34 Chinese provinces and cities who completed at least one valid smartwatch-measured pulse wave velocity (SW-PWV) reading on compatible Huawei watches between December 2020 and August 2022, of whom 35,402 completed the "Vascular Health" app questionnaire; SW-PWV correlated positively with age (r=.6323), male sex and BMI (r=.1981), was significantly elevated in participants with hypertension, diabetes, dyslipidemia, coronary heart disease, stroke and carotid plaque (with hypertension and carotid plaque showing the strongest correlations), discriminated prevalent cardiovascular disease with an AUC of 0.71, and at the guideline cfPWV threshold of 10 m/s showed 13.6% sensitivity and 96.

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