Objective: To explore the application effectiveness of healthcare failure mode and effect analysis (HFMEA) in optimizing intelligent blood logistics transport pathways for safety assurance. Methods: Data from 1 851 cases of intelligent blood logistics transport were collected between September 2023 and March 2025. Based on the implementation phases of HFMEA measures, the cases were divided into a control group (n=120), observation group 1 (n=219), and observation group 2 (n=1 512). Through systematic analysis of the transport processes, hazard scoring and decision tree analysis were conducted for each process, and phased optimization measures were implemented for high-risk failure modes. Results: The transport duration of intelligent blood logistics was 35.5 (20.8, 71.1) min in the control group, 25.1 (10.9, 40.7) min in observation group 1, and 9.9 (4.2, 44.5) min in observation group 2. Observation group 2 exhibited significantly shorter transport time compared to both observation group 1 and the control group, with statistically significant differences between groups (P<0.000 1). Conclusion: The implementation of HFMEA-driven measures significantly reduced intelligent blood logistics transport duration, thereby fostering the evolution of smart hospital ecosystems while enhancing healthcare service quality and operational efficiency.

To evaluate long-term survival and clinical outcomes of patients with knee osteo-arthritis undergoing total knee arthroplasty (TKA) through long-term follow-up.

Background: To identify the optimal surgical technique for single-level anterior cervical discectomy and fusion (ACDF), this study compared surgical outcomes and incidence of adjacent segment degeneration (ASD) in patients undergoing single-level ACDF using cage alone single-level fusion and plate fixation techniques. Methods: This single-center retrospective study (2003–2018) included patients who underwent single-level ACDF with either plate fixation (PLATE) or cage (CAGE) alone. The radiologic and clinical outcomes between the 2 surgical groups were compared over a 4-year follow-up period. Outcomes of interest included parameters related to range of motion, sagittal alignment, as well as fusion, subsidence, and ASD rates. Clinical outcomes were evaluated using the Neck Disability Index (NDI) and visual analog scale (VAS) for pain. Dysphagia and hoarseness rates were estimated based on medical records. Results: Forty-seven patients were included (n=17 in CAGE group). In the CAGE group, 94.1% of the patients had Bridwell grade 1 or 2, compared to 83.3% in the PLATE group (p = 0.396). Subsidence occurred in 12.5% and 3.6% of the CAGE and PLATE cases, respectively (p = 0.543). Segmental kyphosis progressed in the CAGE group compared to the PLATE group at 12, 24, and 48 months (p < 0.001). Radiographic ASD was observed in 41.2% and 30.0% of patients in the CAGE and PLATE groups, respectively, with a higher incidence in the upper segments for both groups. Preoperative NDI scores were similar between the groups; however, postoperatively, the CAGE group had significantly lower NDI scores (3.50 ± 2.74 vs. 8.00 ± 5.81) at 4 years (p = 0.020). Neck pain VAS scores also showed significant improvement in the CAGE group (2.33 ± 2.94) compared with that in the PLATE group (3.07 ± 2.31) at 4 years (p = 0.045). Both groups showed comparable arm pain VAS scores at 2 and 4 years postoperatively. Postoperative dysphagia occurred in 1 patient in the PLATE group, resolving almost completely by 1 year. Conclusions Single-level ACDF using a cage alone technique demonstrated favorable radiologic and clinical outcomes overall compared to plate-augmented ACDF. However, plate augmentation is recommended for patients with severe cervical kyphosis or those at high risk of subsidence.

Background: Given the association between nonalcoholic fatty liver disease and metabolic risks, a new term, metabolic dysfunction- associated steatotic liver disease (MASLD) has been proposed. We aimed to explore the association between MASLD and all-cause, cause-specific mortalities. Methods: We included individuals with steatotic liver disease (SLD) from the Korean National Health Insurance Service. Moreover, SLD was defined as a fatty liver index ≥30. Furthermore, MASLD, metabolic alcohol-associated liver disease (MetALD), and alcoholic liver disease (ALD) with metabolic dysfunction (MD) were categorized based on alcohol consumption and MD. We also analyzed all-cause, liver-, cancer-, hepatocellular carcinoma (HCC)- and cardiovascular (CV)-related mortalities. Results: This retrospective nationwide cohort study included 1,298,993 individuals aged 40 to 79 years for a mean follow-up duration of 9.04 years. The prevalence of MASLD, MetALD, and ALD with MD was 33.11%, 3.93%, and 1.00%, respectively. Relative to the “no SLD” group, multivariable analysis identified that MASLD (adjusted hazard ratio [aHR], 1.28; 95% confidence interval [CI], 1.26 to 1.31), MetALD (aHR, 1.38; 95% CI, 1.32 to 1.44), and ALD with MD group (aHR, 1.80; 95% CI, 1.68 to 1.93) have a significantly higher risk of all-cause mortality. Furthermore, MASLD, MetALD, ALD with MD groups showed higher liver-, cancer- and HCC-related mortality than “no SLD” group. While all-cause specific mortalities increase from MASLD to MetALD to ALD with MD, the MetALD group shows a lower risk of CV-related mortality compared to MASLD. However, ALD with MD group still have a higher risk of CV-related mortality compared to MASLD. Conclusion SLD is associated with an increased risk of all-cause, liver-, cancer-, HCC-, and CV-related mortalities.

Background: We aimed to investigate the predictive values of plasma C-peptide levels and the continuous glucose monitoring (CGM)-defined coefficient of variation (CV) in risk prediction for hypoglycemia in Korean people with diabetes with normal and impaired kidney function. Methods: We analyzed data from 1,185 participants diagnosed with type 1 and type 2 diabetes who underwent blinded professional CGM between January 2009 and May 2021 at outpatient clinics. We explored correlations among CGM-defined CV, plasma C-peptide levels, and time below range at <70 and 54 mg/dL across different kidney function categories. Results: In patients with chronic kidney disease (CKD) stages 1–2 (n=934), 89.3% who had a random plasma C-peptide level higher than 600 pmol/L exhibited a CV of ≤36%. Among those in CKD stage 3 (n=161) with a random plasma C-peptide level exceeding 600 pmol/L, 66.7% showed a CV of ≤36%. In stages 4–5 of CKD (n=90), the correlation between random C-peptide levels and CV was not significant (r=–0.05, P=0.640), including cases with a CV greater than 36% despite very high random plasma C-peptide levels. Random plasma C-peptide levels and CGM-assessed CV significantly predicted hypoglycemia in CKD stages 1–2 and 1–5, respectively. Conclusion The established C-peptide criteria in Western populations are applicable to Korean people with diabetes for hypoglycemic risk prediction, unless kidney function is impaired equivalent to CKD stage 3–5. The CGM-defined CV is informative for hypoglycemic risk prediction regardless of kidney function.

Background: The World Health Organization has declared the end of the coronavirus disease 2019 (COVID-19) public health emergency. However, this did not indicate the end of COVID-19. Several months after the infection, numerous patients complain of respiratory or nonspecific symptoms; this condition is called long COVID. Even patients with mild COVID-19 can experience long COVID, thus the burden of long COVID remains considerable. Therefore, we conducted this study to comprehensively analyze the effects of long COVID using multi-faceted assessments. Materials and Methods: We conducted a prospective cohort study involving patients diagnosed with COVID-19 between February 2020 and September 2021 in six tertiary hospitals in Korea. Patients were followed up at 1, 3, 6, 12, 18, and 24 months after discharge. Long COVID was defined as the persistence of three or more COVID-19-related symptoms. The primary outcome of this study was the prevalence of long COVID after the period of COVID-19. Results: During the study period, 290 patients were enrolled. Among them, 54.5 and 34.6% experienced long COVID within 6 months and after more than 18 months, respectively. Several patients showed abnormal results when tested for post-traumatic stress disorder (17.4%) and anxiety (31.9%) after 18 months. In patients who underwent follow-up chest computed tomography 18 months after COVID-19, abnormal findings remained at 51.9%. Males (odds ratio [OR], 0.17; 95% confidence interval [CI], 0.05–0.53; P=0.004) and elderly (OR, 1.04; 95% CI, 1.00–1.09; P=0.04) showed a significant association with long COVID after 12–18 months in a multivariable logistic regression analysis. Conclusion Many patients still showed long COVID after 18 months post SARS-CoV-2 infection. When managing these patients, the assessment of multiple aspects is necessary.

ObjectiveExploring the formula rules of commonly used traditional Chinese medicines（TCMs） for epidemic treatment from the Qin and Han dynasties to the Qing dynasty through data mining， providing reference for the prevention and control of contemporary epidemics. MethodsThe articles on epidemic treatment in the electronic database of Chinese Medical Code V5.0 were systematically searched， and the contents such as source， dynasty， author， diagnosis， formula name， therapeutic method and efficacy， and composition of medicines from each article that met the inclusion criteria were extracted. Then， an Excel standardized database was established， and Python programs were used for data mining to summarize the frequency of commonly used medicines and perform hierarchical cluster analysis， Pearson correlation analysis， and association rule analysis. ResultsA total of 1 595 formulas were included， involving 558 TCMs. The efficacy of these medicines could be classified into two categories， namely， expeling pathogenic factors and reinforcing healthy Qi. According to the frequency deconstruction analysis， high-frequency medicines were mainly detoxification， Fu-organ dredging， aromatization and promoting blood circulation， followed by the medicines with the effect of treating the lungs， such as clearing the lungs and resolving phlegm， clearing heat and purging the lungs， relieving cough and asthma， and purging the lungs and relieving asthma. And the proportions of acrid-warm herbs and acrid-cold herbs varied in different periods. Hierarchical clustering and correlation analysis both suggested TCMs for expeling pathogenic factors and reinforcing healthy Qi often formed stable combinations with high association degrees. Association rule analysis showed that the core acrid-warm herb was mainly Ephedrae Herba， and the core acrid-cold herb was mainly Forsythiae Fructus， resulting in the core formulas of Maxing Shigantang and Yinqiaosan. ConclusionThroughout history， the prevention and control of epidemics have been based on the principle of "preserving healthy Qi and avoiding toxic Qi"， focusing on the treatment of the causes and characteristics of epidemics through detoxification， Fu-organ dredging， and aromatization， emphasizing the use of Rhei Radix et Rhizoma and other herbs to dredge Fu-organ， eliminate toxins and pathogens， and playing the role of actively intervene with symptomatic medication. And based on the external manifestations of the body's struggle between evil and righteousness， diagnose and treatment according to syndrome differentiation was performed.

ObjectiveExploring the formula rules of commonly used traditional Chinese medicines（TCMs） for epidemic treatment from the Qin and Han dynasties to the Qing dynasty through data mining， providing reference for the prevention and control of contemporary epidemics. MethodsThe articles on epidemic treatment in the electronic database of Chinese Medical Code V5.0 were systematically searched， and the contents such as source， dynasty， author， diagnosis， formula name， therapeutic method and efficacy， and composition of medicines from each article that met the inclusion criteria were extracted. Then， an Excel standardized database was established， and Python programs were used for data mining to summarize the frequency of commonly used medicines and perform hierarchical cluster analysis， Pearson correlation analysis， and association rule analysis. ResultsA total of 1 595 formulas were included， involving 558 TCMs. The efficacy of these medicines could be classified into two categories， namely， expeling pathogenic factors and reinforcing healthy Qi. According to the frequency deconstruction analysis， high-frequency medicines were mainly detoxification， Fu-organ dredging， aromatization and promoting blood circulation， followed by the medicines with the effect of treating the lungs， such as clearing the lungs and resolving phlegm， clearing heat and purging the lungs， relieving cough and asthma， and purging the lungs and relieving asthma. And the proportions of acrid-warm herbs and acrid-cold herbs varied in different periods. Hierarchical clustering and correlation analysis both suggested TCMs for expeling pathogenic factors and reinforcing healthy Qi often formed stable combinations with high association degrees. Association rule analysis showed that the core acrid-warm herb was mainly Ephedrae Herba， and the core acrid-cold herb was mainly Forsythiae Fructus， resulting in the core formulas of Maxing Shigantang and Yinqiaosan. ConclusionThroughout history， the prevention and control of epidemics have been based on the principle of "preserving healthy Qi and avoiding toxic Qi"， focusing on the treatment of the causes and characteristics of epidemics through detoxification， Fu-organ dredging， and aromatization， emphasizing the use of Rhei Radix et Rhizoma and other herbs to dredge Fu-organ， eliminate toxins and pathogens， and playing the role of actively intervene with symptomatic medication. And based on the external manifestations of the body's struggle between evil and righteousness， diagnose and treatment according to syndrome differentiation was performed.

This narrative review examines the challenges, strategies, and future directions in the development of young teachers within the pathophysiology departments of Chinese medical colleges. A thorough review of 49 studies published between 2013 and 2024 was carried out using PubMed, Web of Science, and various Chinese databases. The primary challenges identified include teaching innovation (cited in 84.2% of the studies), research pressure (91.2%), disciplinary characteristics (87.7%), and career development (80.7%). Medical schools have responded by enhancing training systems (94.7%), innovating teaching methods (93.0%), and bolstering research support (96.5%). Looking ahead, trends are shifting toward the application of new technologies, interdisciplinary integration, and international collaboration. The focus on cultivating young teachers is increasingly geared towards personalization and diversification, which are essential for advancing education in pathophysiology. High-quality young teachers are pivotal in raising teaching standards, fostering research innovation, and facilitating interdisciplinary exchanges. Based on these insights, we recommend several practical measures to enhance the quality of pathophysiology education in China. These include establishing comprehensive training programs that integrate teaching innovation and research skills; developing structured mentorship systems with clear pathways for career advancement; creating platforms that support technology-enhanced teaching and international collaboration; and implementing systematic evaluation mechanisms to assess teaching effectiveness. These targeted interventions will require a coordinated effort from department heads, educational institutions, and policymakers to ensure a sustained improvement in the quality of pathophysiology education.