CM Hospital

To understand the current status and influencing factors of self-management ability in peritoneal dialysis (PD) patients. This study employed an interpretive sequential mixed-methods approach and followed the STROBE and CONDITION guidelines. From June 2024 to February 2025, convenience sampling was used to survey 507 PD patients from three tertiary hospitals. Quantitative data were collected using five scales. Concurrently,purposesampling was used to conduct semi-structured interviews with 13 patients until data saturation was reached. Quantitative data were analyzed using SPSS 26.0, and qualitative data were analyzed thematically using Nvivo15. The results were integrated to provide a comprehensive understanding. The quantitative results showed that PD patients had a self-management ability score of [55.00 (45.00, 60.00)] out of a possible 96, indicating a moderately low level. Multiple linear regression identified age, educational attainment, monthly household income, dialysis age, understanding of the disease, mastery of health education content, frequency of follow-up, and self-efficacy as significant influencing factors. The qualitative interviews identified two themes (obstructive and promoting factors) and nine sub-themes. The integration of results showed that qualitative findings confirmed and complemented the quantitative associations. The self-management ability of PD patients is moderately low. Medical staff should enhance the self-efficacy and social support of PD patients based on the influencing factors of their self-management ability, increase the frequency of follow-up, pay attention to PD patients with low education, advanced age and other types, strengthen training and monitoring for complications, and carry out targeted intervention to improve the self-management ability of PD patients.

Dear Editor, We greatly appreciate Liu et al’s study on perioperative metabolomics and surgical outcomes in colorectal cancer (CRC) patients, recently published in the International Journal of Surgery[1]. This work effectively integrates clinical data with high-throughput nuclear magnetic resonance (NMR)-based metabolomic profiling, identifying key metabolic predictors of postoperative complications and hospital stay in 243 CRC patients, and bridges basic research and clinical practice. As researchers in surgical metabolomics and outcome prediction, we admire the rigorous design and impactful findings, and offer suggestions to enhance reproducibility, clinical relevance, and translational potential. First, standardizing metabolomic methodologies is critical for cross-study validation. While NMR ensures quantitative precision, metabolomic results are sensitive to technical variables (sample collection, extraction, detection, and modeling) that may cause heterogeneity. Gas chromatography-mass spectrometry (GC-MS) and ultra-high-performance liquid chromatography (UPLC)-based techniques – well-validated in CRC metabolomics[2] – complement NMR in metabolite coverage and sensitivity for specific compound classes (e.g., amino acids, fatty acids). A brief comparison of NMR results with UPLC-validated markers (e.g., guanosine, sphingosine) or pathway overlaps (e.g., arginine biosynthesis, pyrimidine metabolism) identified in prior CRC studies[2] would contextualize findings. Aligning sample collection timelines with international guidelines and disclosing detailed protocols (as in studies analyzing perioperative metabolomic trajectories[3]) will minimize bias and boost biomarker reproducibility. Second, refined clinical stratification can optimize predictive precision. Perioperative metabolic responses vary by surgical approach (laparoscopic vs open) and tumor characteristics (stage, location, and differentiation), which may yield subtype-specific metabolic signatures – consistent with findings that minimally invasive surgery correlates with distinct metabolic and inflammatory profiles[4]. Additionally, models integrating metabolomic markers with clinical factors (e.g., cortisol, C-reactive protein) have shown strong performance in predicting surgical outcomes[1], similar to the integrated frameworks previously proposed. Incorporating such clinical-metabolic integration, alongside perioperative management details [e.g., Enhanced Recovery After Surgery (ERAS) adherence], will enhance adaptability to individual differences in clinical practice. Third, applying the GRADE framework and extending follow-up strengthens evidence quality. The GRADE framework[5] systematically evaluates bias risk, consistency, and precision – key for clinical translation, as demonstrated in metabolomic studies of CRC prognosis[2]. While short-term outcomes (complications, hospital stay) are relevant, long-term outcomes (delayed anastomotic leakage, sustained gastrointestinal function) matter equally: recent work shows postoperative metabolic alterations persist for up to 1 year and correlate with recovery trajectories[3]. Extending follow-up to 6–12 months will validate biomarker durability and uncover long-term recovery-related targets. Finally, exploring mechanistic pathways bridges prediction and intervention. Markers like 2-aminobutyric acid (linked to inflammation) and Very-Long-Chain Polyunsaturated Lipid (V3PL) ratio (reflecting lipid transport) lack clear biological mechanisms, but prior CRC metabolomic studies offer clues: for example, postoperative restoration of specific metabolites to healthy levels correlates with improved tissue repair[2], and metabolic pathway modulation enhances recovery[4]. Elucidating such pathways – similar to how metabolome traits were linked to postoperative CRC recovery[3] – will transform predictors into therapeutic targets, enabling interventions like nutritional modulation to improve outcomes. In conclusion, Liu et al’s study[1] advances perioperative metabolomic research for CRC. Our suggestions aim to complement their valuable work. We believe refined biomarkers could play a pivotal role in personalized perioperative care, and eagerly anticipate the authors’ responses and future breakthroughs. Ethical approval Not applicable. Consent Not applicable.

Hearing loss is among the top three non-fatal disabling conditions in low- and middle-income countries (LMICs), where cochlear implantation (CI), the gold standard for severe-to-profound sensorineural hearing loss, remains underused. Conventionally, device activation occurs 2–4 weeks postoperatively; however, early activation (EA) within days of surgery has shown promising benefits. Literature reveals inconsistencies in defining EA and late activation (LA). Some studies report device activation as early as 1 to 7 days postoperatively, while others classify activation within 8 to 14 days as either EA or LA. Traditionally, activation has been reported between 9 and 46 days postoperatively. This lack of consensus complicates the development of standardized postoperative activation timelines and impedes evidence-based clinical guidelines. This narrative review aims to compare the outcomes, feasibility, and safety of EA versus traditional activation in CI patients while highlighting the variability in definitions and activation timelines across studies. A thorough literature search was conducted using PubMed, Scopus, Google Scholar, and Google. Seventeen studies were included, comprising 3 systematic reviews, 2 literature reviews, and 12 primary studies. Most studies reported EA on the first postoperative day, demonstrating benefits such as faster auditory rehabilitation, improved speech recognition, reduced anxiety, and higher patient satisfaction. EA was not associated with increased complications and was cost-effective, particularly for patients from remote areas. However, long-term impedance outcomes were similar between EA and LA. In conclusion, first-day EA appears feasible, safe, and beneficial. Still, large-scale prospective studies are needed to establish optimal activation timing and support standardized CI care protocols.

Đặt vấn đề: Viêm phổi cộng đồng là một trong những bệnh truyền nhiễm thường gặp và gây ra tỷ lệ tử vong đáng kể. Tỷ lệ viêm phổi cộng đồng ngày càng tăng ở những người cao tuổi với tỷ lệ nhập viện và tử vong nội viện cao hơn so với các bệnh lý khác. Mục tiêu: Xác định tỷ lệ tử vong nội viện và các yếu tố liên quan ở bệnh nhân cao tuổi mắc viêm phổi cộng đồng. Đối tượng và phương pháp nghiên cứu: Nghiên cứu cắt ngang được tiến hành trên 293 bệnh nhân ≥ 60 tuổi được chẩn đoán viêm phổi cộng đồng điều trị nội trú tại khoa Nội Hô Hấp, Bệnh viện Thống Nhất từ tháng 3 đến tháng 9 năm 2023. Sử dụng hồi quy đa biến để xác định các yếu tố liên quan với tỷ lệ tử vong nội viện, với ngưỡng có ý nghĩa thống kê khi p < 0,05. Kết quả: Có 293 bệnh nhân tham gia nghiên cứu với tỷ lệ tử vong nội viện là 11,9%. Các bệnh nhân tử vong có tuổi, mức suy yếu lâm sàng (CFS), chỉ số bệnh kèm theo Charlson (CCI), ure máu, protein phản ứng C (CRP) và độ nặng bệnh viêm phổi (CURB-65) cao hơn so với nhóm bệnh nhân xuất viện. Ngược lại, bệnh nhân tử vong có điểm đánh giá tình trạng dinh dưỡng MNA-SF thấp hơn. Qua phân tích đa biến, mức suy yếu lâm sàng CFS trước nhập viện (OR=2,17), MNA-SF (OR = 0,77) và CURB-65 (OR = 3,71) có tương quan độc lập với tử vong nội viện ở bệnh nhân cao tuổi nhập viện vì viêm phổi cộng đồng. Kết luận: Tỷ lệ bệnh nhân cao tuổi mắc viêm phổi cộng đồng tử vong nội viện không quá cao. Mức suy yếu lâm sàng CFS trước nhập viện và CURB-65 là hai yếu tố nguy cơ liên quan tử vong nội viện. Do đó, tình trạng suy yếu và độ nặng bệnh viêm phổi trước nhập viện ở bệnh nhân cao tuổi mắc viêm phổi cộng đồng cần được đánh giá đầy đủ nhằm tiên lượng nguy cơ tử vong và đưa ra kế hoạch điều trị phù hợp.

Abstract Background This review aims to provide medical professionals with a scientific summary of evidence regarding the management of emergency cesarean sections during pregnancy. The research question is "How to provide professional cesarean section management for pregnant patients in critical condition?" Methods Relevant evidence regarding the management of perimortem cesarean delivery in pregnant patients with cardiac arrest was systematically retrieved from computerized decision support systems, guideline databases, professional association websites, and Chinese and English electronic databases. The evidence types included clinical decision-making tools, clinical practice guidelines, expert consensus statements, evidence summaries, systematic reviews, and randomized controlled trials, with the retrieval time frame ranging from database inception to August 2025. Three researchers independently assessed the quality of the included literature, followed by the extraction, collation, and synthesis of evidence from eligible studies. Results A total of 17 articles were included, including 8 expert consensuses, 8 guidelines, and 1 cohort study. 27 pieces of evidence were extracted from 6 aspects: early risk warning, indicators and timing, surgical procedures, fetal management, post-resuscitation management, and team training. Conclusion This study summarizes the best evidence for the management of pregnant patients with cardiac arrest during labor during the perioperative period, providing an evidence-based basis for healthcare professionals to conduct emergency cesarean delivery for pregnant patients with cardiac arrest. When translating into clinical practice, it is necessary to consider the clinical context and the actual situation of the patients comprehensively, and select the best evidence in a personalized manner to reduce the maternal and fetal mortality rates, improve the prognosis and quality of life. Trial registration: The study has been registered with the Evidence-Based Nursing Centre at Fudan University (ES20258777).

Gout is a chronic inflammatory disease, and cardiovascular disease (CVD) is regarded as one of its complications. The aim of our study was to explore the association between systemic inflammation response index (SIRI) and the risk of CVD in gout. Six cycles of NHANES data were analyzed. Machine learning algorithms were employed to screen covariates, followed by SHAP interpretation to assess variable importance. Participants with gout were stratified by SIRI quartiles, and logistic regression was performed to evaluate CVD risk. RCS were applied to assess nonlinear trends, while discrimination, calibration, and clinical utility were evaluated using ROC, DCA, and calibration curve. Additionally, the Framingham risk score (FRS) model was integrated with SIRI, and model improvement was quantified via net reclassification improvement and integrated discrimination improvement. Among 1260 participants with gout, 436 (weighted 28.77%) had CVD comorbidities. A linear positive association was observed between SIRI and CVD risk (P for nonlinear = 0.824), with each 1-unit increase in SIRI corresponding to 29.7% higher CVD risk (OR = 1.297, 95% CI 1.073-1.568). Participants in the highest SIRI quartile Q4 (OR = 2.060, 95% CI 1.141-3.721) exhibited increased CVD risk compared to Q1. The final model demonstrated robust discrimination (AUC = 0.755, 95% CI 0.729-0.783). Incorporating SIRI into the NHANES and clinical datasets improved the discrimination of the FRS model by 5.2% and 1.9%. A positive linear association was identified between SIRI and CVD risk in gout patients. The model constructed based on machine learning demonstrated comparable robustness to the FRS model in predicting CVD. These findings provide a theoretical and empirical foundation for early CVD identification, prevention, and management in this population. Key Points • The positive linear association between the systemic inflammation response index and cardiovascular disease, as well as its subtypes in patients with gout. • SIRI can serve as a valuable complement to the Framingham risk score model.