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Abstract Introduction Emerging infectious diseases (EIDs) can disrupt the healthcare system, causing regulatory changes that affect the healthcare-seeking process and potentially increase patient-physician dissatisfaction. This study aimed to collect and analyze patients’ and physicians’ complaints during an EID outbreak to inform potential clues regarding medical quality and patient safety enhancement in future dealing with EIDs, employing text mining methodologies. Methods In this descriptive study, complaint records from January 2020 to February 2023 at West China Hospital, a national medical facility in China, were analyzed. Patient and physician complaints have been retrospectively retrieved from the record from the medical department, and then categorized into distinct groups based on reporting reasons, encompassing COVID-19-related policies, healthcare access, availability of medical resources, and financial concerns. Results During the COVID-19 pandemic, 541 COVID-19-related complaints were identified: 330 (61.00%) from patients and 211 (39.00%) from physicians. The monthly volume of complaints fluctuated, starting at 10 in 2020, peaking at 21 in 2022, and dropping to 14 in 2023. Most complaints from inpatients were expressed by older males aged 40 to 65 (38.82%, 210/541). The primary source of complaints was related to mandatory COVID-19 policies (79.30%, 429/541), followed by concerns regarding timely healthcare services (31.61%, 171/541). Few complaints were expressed regarding the insufficiency of medical resources (2.77%, 15/541) and the high costs (4.25%, 23/541). The frequency of complaints expressed by doctors and patients in the emergency department was higher compared with other departments (24.58%, 133/541). Conclusions Increased complaints may serve as a primitive and timely resource for investigating the potential hazards and drawbacks associated with policies pertaining to EIDs. Prompt collection and systematical analysis of patient and physician feedback could help us accurately evaluate the efficacy and repercussions of these policies. Implementing complaints-based assessment might improve care standards in forthcoming healthcare environments grappling with EIDs.

Abstract Background Surgery in geriatric patients often poses risk of major postoperative complications. Acute kidney injury (AKI) is a common complication following noncardiac surgery and is associated with increased mortality. Early identification of geriatric patients at high risk of AKI could facilitate preventive measures and improve patient prognosis. This study used machine learning methods to identify important features and predict AKI following noncardiac surgery in geriatric patients. Methods The data for this study were obtained from a prospective cohort. Patients aged ≥ 65 years who received noncardiac surgery from June 2019 to December 2021 were enrolled. Data were split into training set (from June 2019 to March 2021) and internal validation set (from April 2021 to December 2021) by time. The least absolute shrinkage and selection operator (LASSO) regularization algorithm and the random forest recursive feature elimination algorithm (RF-RFE) were used to screen important predictors. Models were trained through extreme gradient boosting (XGBoost), random forest, and LASSO. The SHapley Additive exPlanations (SHAP) package was used to interpret the machine learning model. Results The training set included 6753 geriatric patients. Of these, 250 (3.70%) patients developed AKI. The XGBoost model with RF-RFE selected features outperformed other models with an area under the precision-recall curve (AUPRC) of 0.505 (95% confidence interval [CI]: 0.369–0.626) and an area under the receiver operating characteristic curve (AUROC) of 0.806 (95%CI: 0.733–0.875). The model incorporated ten predictors, including operation site and hypertension. The internal validation set included 3808 geriatric patients, and 96 (2.52%) patients developed AKI. The model maintained good predictive performance with an AUPRC of 0.431 (95%CI: 0.331–0.524) and an AUROC of 0.845 (95%CI: 0.796–0.888) in the internal validation. Conclusions This study developed a simple machine learning model and a web calculator for predicting AKI following noncardiac surgery in geriatric patients. This model may be a valuable tool for guiding preventive measures and improving patient prognosis. Trial registration The protocol of this study was approved by the Committee of Ethics from West China Hospital of Sichuan University (2019–473) with a waiver of informed consent and registered at www.chictr.org.cn (ChiCTR1900025160, 15/08/2019).

BackgroundMental health challenges are encountered by frail older adults as the population ages. The extant literature is scant regarding the correlation between depressive symptoms and social participation among frail older adults.MethodsThis study is based on an analysis of data from China Health and Retirement Longitudinal Study (CHARLS) participants aged 60 and older who are frail. A frailty index (FI) was developed for the purpose of assessing the frailty level of the participants. Additionally, latent class analysis (LCA) was employed to classify the participants’ social engagement patterns in 2015 and 2018. The study used ordered logistic regression to examine the relationship between social participation type and depressive symptoms. We also used Latent Transition Analysis (LTA) methods to explore the impact of changes in social activity types on depressive symptoms after three years of follow-up in 2018. In addition, the response surface analysis (RSM) investigation explored the relationship among FI, depression, and social participation.ResultsA total of 4,384 participants completed the baseline survey; three years later, 3,483 were included in the follow-up cohort. The baseline survey indicates that female older adults in rural areas who are single, have lower incomes, shorter sleep durations, and lighter weights exhibited more severe depressive symptoms. Social participation patterns were categorized into five subgroups by LCA. The findings indicate that individuals classified as “board game enthusiasts” (OR, 0.62; 95% CI, 0.47-0.82) and those as “extensive social interaction” (OR,0.67; 95% CI, 0.49-0.90) have a significantly lower likelihood of developing depressive symptoms compared to the “socially isolated” group. We also discovered that “socially isolated” baseline participants who transitioned to the “helpful individual” group after three years had significantly greater depressed symptoms (OR, 1.56; 95% CI, 1.00-2.44). More social activity types and less FI are linked to lower depression in our study.ConclusionThe results of the study emphasize the importance of social participation patterns and the number of social participation types in relation to the severity of depression among frail older adults individuals. This study’s findings may provide important insights for addressing depressive symptoms in frail older adults person.

Abstract The swift advancement of technology has led to the widespread utilization of artificial intelligence (AI) in the diagnosis of diseases and prediction of prognoses, particularly in the field of intensive care unit (ICU) and Anesthesia. Numerous evidential data have demonstrated the extensive potential of AI in monitoring and predicting patient outcomes in these fields. Using bibliometric analysis, this study provides an overview of the current state of knowledge regarding the application of AI in ICU and Anesthesia and investigates prospective avenues for future research. Web of Science Core Collection was queried on May 6, 2023, to select articles and reviews regarding AI in ICU and Anesthesia. Subsequently, various analytical tools including Microsoft Excel 2022, VOSviewer (version 1.6.16), Citespace (version 6.2.R2), and an online bibliometric platform were employed to examine the publication year, citations, authors, countries, institutions, journals, and keywords associated with this subject area. This study selected 2196 articles from the literature. focusing on AI-related research within the fields of ICU and Anesthesia, which has increased exponentially over the past decade. Among them, the USA ranked first with 634 publications and had close international cooperation. Harvard Medical School was the most productive institution. In terms of publications, Scientific Reports (impact factor (IF) 4.996) had the most, while Critical Care Medicine (IF 9.296) had the most citations. According to numerous references, researchers may focus on the following research hotspots: “Early Warning Scores”, “Covid-19″, “Sepsis” and “Neural Networks”. “Procalcitonin” and “Convolutional Neural Networks” were the hottest burst keywords. The potential applications of AI in the fields of ICU and Anesthesia have garnered significant attention from scholars, prompting an increase in research endeavors. In addition, it is imperative for various countries and institutions to enhance their collaborative efforts in this area. The research focus in the upcoming years will center on sepsis and coronavirus, as well as the development of predictive models utilizing neural network algorithms to improve well-being and quality of life in surviving patients. Graphical Abstract

Abstract Aim This study aimed to explore a novel subtype classification method based on the stemness characteristics of patients with non-small cell lung cancer (NSCLC). Methods Based on the Cancer Genome Atlas database to calculate the stemness index (mRNAsi) of NSCLC patients, an unsupervised consensus clustering method was used to classify patients into two subtypes and analyze the survival differences, somatic mutational load, copy number variation, and immune characteristics differences between them. Subsequently, four machine learning methods were used to construct and validate a stemness subtype classification model, and cell function experiments were performed to verify the effect of the signature gene ARTN on NSCLC. Results Patients with Stemness Subtype I had better PFS and a higher somatic mutational burden and copy number alteration than patients with Stemness Subtype II. In addition, the two stemness subtypes have different patterns of tumor immune microenvironment. The immune score and stromal score and overall score of Stemness Subtype II were higher than those of Stemness Subtype I, suggesting a relatively small benefit to immune checkpoints. Four machine learning methods constructed and validated classification model for stemness subtypes and obtained multiple logistic regression equations for 22 characteristic genes. The results of cell function experiments showed that ARTN can promote the proliferation, invasion, and migration of NSCLC and is closely related to cancer stem cell properties. Conclusion This new classification method based on stemness characteristics can effectively distinguish patients' characteristics and thus provide possible directions for the selection and optimization of clinical treatment plans.

Abstract Background The association between anemia and depression has been demonstrated in previous studies, but it's still unclear whether depressive symptoms as a hazard factor for anemia. The findings of a large-scale cross-sectional and longitudinal examination of such an association of among the middle-aged and elderly individuals in China were presented in our study. Methods The data from China Health and Retirement Longitudinal Study in 2011 and 2015 were evaluated. 10,179 and 5,887 participants were included in cross-sectional and longitudinal study, respectively. According to the World Health Organization, hemoglobin concentrations below 13 g/dL for males and 12 g/dL for females are considered anemia. The research population was separated into two groups based on scores of the 10-item short form of the Center for Epidemiologic Studies Depression Scale (CES-D-10): the group with depressed symptoms had a score of more than 10 points, and the group with depressive disorder had a score of more than 20 points. Multilevel logistic regression analyses were conducted to explore the relationship between anemia and varying degrees of depressive symptoms, utilizing three models based on adjusting for different types of covariates. Results In our cross-sectional investigation, depression disorders were more likely to link to the occurrence of anemia (OR, 1.34; 95% CI, 1.02–1.77; P = 0.035). Additionally, there seems a linear connection between depression questionnaire scores and hemoglobin concentrations (r = - 0.053, P

AbstractStudy objective This study was undertaken to compare the effect of the modified ultrasound-guided anterior superior laryngeal nerve block (SLNB) with the traditional ultrasound-guided posterior SLNB in providing intubation conditions during awake tracheal intubation (ATI) in patients without difficult airway.Design Randomized, assessor-blind. Registration number: ChiCTR2200058086.Setting West China Hospital of Sichuan University, Chengdu, China.Patients 104 patients aged 18–65 years, of American Society of Anesthesiologists status I-III, posted for elective general surgery with general endotracheal anesthesia.Interventions The patients were randomized into two groups (modified group, n = 52; traditional group, n = 52). Modified anterior SLNB or traditional posterior SLNB was performed under ultrasound guidance.Measurements The primary outcome was the proportion of acceptable intubation condition (AIC), which was analyzed in both per-protocol (PP) and intention-to-treat (ITT) populations. The prespecified non-inferiority margin was −4.8%. Secondary outcomes included intubation success rate on the first attempt, hemodynamic parameters during ATI, time taken for airway anesthesia and intubation, recall of intubation, patient perception of comfort, and incidence and severity of postoperative complications.Main results In the PP population, the proportion of AIC in the modified group was 49/49 (100%) and that in the traditional group was 49/49 (100%), absolute difference 0, lower limit of 1-sided 95% CI, −0.3%. In the ITT population, the primary outcomes in the modified and traditional group were 52/52 (100%) and 51/52 (98.1%), respectively, with an absolute difference of 1.9% and a lower limit of 1-sided 95% CI of −1.2%. The non-inferiority of modified ultrasound-guided anterior SLNB was confirmed in both populations.Conclusions Among adults without difficult airways during videolaryngoscope-assisted ATI, the modified ultrasound-guided anterior SLNB, compared to the traditional posterior approach, showed a statistically non-inferior effect in terms of providing AIC.

Abstract. Background:. Managing acute postoperative pain is challenging for anesthesiologists, surgeons, and patients, leading to adverse events despite making significant progress. Patient-controlled intravenous analgesia (PCIA) is a recommended solution, where oxycodone has depicted unique advantages in recent years. However, controversy still exists in clinical practice and this study aimed to compare two drugs in PCIA. Methods:. We performed a literature search in PubMed, Embase, the Cochrane Central Register of Controlled Trials, Web of Science, Chinese National Knowledge Infrastructure, Wanfang, and VIP databases up to December 2020 to select specific randomized controlled trials (RCTs) comparing the efficacy of oxycodone with sufentanil in PCIA. The analgesic effect was the primary outcome and the secondary outcome included PCIA consumption, the Ramsay sedation scale, patients’ satisfaction and side effects. Results:. Fifteen RCTs were included in the meta-analysis. Compared with sufentanil, oxycodone showed lower Numerical Rating Scale scores (mean difference [MD] = −0.71, 95% confidence interval [CI]: −1.01 to −0.41; P

Introduction A patient record review study conducted in 2006 in a random sample of 21 Dutch hospitals found that 51%–77% of adverse events are related to perioperative care, while Centers for Disease Control and Prevention data in USA in 2013 estimated that the medical error is the third-leading cause of mortality. To capitalise on the potential of apps to enhance perioperative medical quality, there is a need for interventions developed in consultation with real-world users designed to support integrated management for perioperative adverse events (PAEs). This study aims: (1) to access the knowledge, attitude and practices for PAEs among physicians, nurses and administrators, and to identify the needs of healthcare providers for a mobile-based PAEs tool; (2) to develop a data-driven app for integrated PAE management that meets those needs and (3) to test the usability, clinical efficacy and cost-effectiveness of the developed app.Methods and analysis We will adopt an embedded mixed-methods research technique; qualitative data will be used to assess user needs and app adoption, while quantitative data will provide crucial insights to establish the demand for the app, and measure the app effects. Phase 1 will enrol surgery-related healthcare providers from the West China Hospital and identify their latent demand for mobile-based PAEs management using a self-designed questionnaire underpinned by the knowledge, attitude and practice model, as well as expert interviews. In phase 2, we will develop the app for integrated PAE management and test its effectiveness and sustainability. In phase 3, the effects on the total number and severity of reported PAEs will be evaluated using Poisson regression with interrupted time-series analysis over a 2-year period, while users’ engagement, adherence, process evaluation and cost-effectiveness will be evaluated using quarterly surveys and interviews.Ethics and dissemination The West China Hospital of Sichuan University’s Institutional Review Board authorised this study after approving the study protocol, permission forms and questionnaires (number: 2022-1364). Participants will be provided with study information, and informed written consent will be obtained. Study findings will be disseminated through peer-reviewed publications and conference presentations.

Chronic pain (CP) is an unpleasant sensory and emotional experience associated with, or resembling that associated with, actual or potential tissue damage lasting longer than 3 months. CP is the main reason why people seek medical care and exerts an enormous economic burden. Genome-wide expression analysis has revealed that diverse essential genetic elements are altered in CP patients. Although many possible mechanisms of CP have been revealed, we are still unable to meet all the analgesic needs of patients. In recent years, non-coding RNAs (ncRNAs) have been shown to play essential roles in peripheral neuropathy and axon regeneration, which is associated with CP occurrence and development. Multiple key ncRNAs have been identified in animal models of CP, such as microRNA-30c-5p, ciRS-7, and lncRNA MRAK009713. This review highlights different kinds of ncRNAs in the regulation of CP, which provides a more comprehensive understanding of the pathogenesis of the disease. It mainly focuses on the contributions of miRNAs, circRNAs, and lncRNAs to CP, specifically peripheral neuropathic pain (NP), diabetic NP, central NP associated with spinal cord injury, complex regional pain syndrome, inflammatory pain, and cancer-induced pain. In addition, we summarize some potential ncRNAs as novel biomarkers for CP and its complications. With an in-depth understanding of the mechanism of CP, ncRNAs may provide novel insight into CP and could become new therapeutic targets in the future.

Herpes zoster (HZ) is a localized, painful cutaneous eruption that occurs upon reactivation of the herpes virus. Postherpetic neuralgia (PHN) is the most common chronic complication of HZ. In this study, we examined the metabolomic and proteomic signatures of disease progression in patients with HZ and PHN. We identified differentially expressed metabolites (DEMs), differentially expressed proteins (DEPs), and key signaling pathways that transition from healthy volunteers to the acute or/and chronic phases of herpetic neuralgia. Moreover, some specific metabolites correlated with pain scores, disease duration, age, and pain in sex dimorphism. In addition, we developed and validated three optimal predictive models (AUC > 0.9) for classifying HZ and PHN from healthy individuals based on metabolic patterns and machine learning. These findings may reveal the overall metabolomics and proteomics landscapes and proposed the optimal machine learning predictive models, which provide insights into the mechanisms of HZ and PHN.

Background: Previous observational studies have suggested the involvement of 25-hydroxyvitamin D [25(OH)D] in chronic pain. However, whether the 25(OH)D is a novel target for management, the causality remains unclear.Methods: A two-sample Mendelian randomization (MR) study was conducted to identify the causal association between 25(OH)D and low back pain (LBP). The primary analysis was revealing causality from serum 25(OH)D level (n = 417,580) on LBP (21,140 cases and 227,388 controls). The replicated analysis was performing MR estimates from circulating 25(OH)D concentration (n = 79,366) on LBP experienced last month (118,471 cases and 343,386 controls). Inverse variance weighted (IVW) was used as the main analysis. In addition, we used weighted median and MR-Egger to enhance the robustness. Sensitivity analysis was conducted to evaluate the robustness of MR results.Results: IVW estimation indicated strong evidence that higher serum 25(OH)D levels exerted a protective effect on LBP (OR = 0.89, 95% CI = 0.83–0.96, p = 0.002). Similar trends were also found in replicate analysis (OR = 0.98, 95% CI = 0.96–1.00, p = 0.07). After meta-analysis combining primary and replicated analysis, the causal effect is significant (p = 0.03). Sensitivity analysis supported that the MR estimates were robust.Conclusion: In our MR study, genetically increased serum 25(OH)D levels were associated with a reduced risk of LBP in the European population. This might have an implication for clinicians that vitamin D supplements might be effective for patients with LBP in clinical practice.

Chronic pain remains to be a clinical challenge and is recognized as a major health problem with varying impacts on quality of life. Currently, the first-line therapy for chronic pain is opioids, which are often accompanied by unwanted psychoactive side effects. Thus, new and effective treatments for chronic pain are urgently needed and eagerly pursued. Inflammatory cytokines, especially interleukin-17 (IL-17), are reportedly potential therapeutic targets owing to their pivotal role in chronic pain from the neuroinflammation perspective. Recently, substantial evidence confirmed that IL-17 and IL-17 receptors (IL-17Rs) were increased in neuropathic, inflammatory, and cancer pain models. Notably, IL-17/IL-17R antibodies also reportedly relieve or cure inflammatory- and pain-related diseases. However, existing studies have reported controversial results regarding IL-17/IL-17Rs as potential therapeutic targets in diverse animal models of chronic pain. In this review, we present a summary of published studies and discuss the evidence, from basic to clinical to research, regarding the role and mechanism of action between IL-17 and diverse kinds of chronic pain in animal models and clinical patients. Furthermore, we evaluated IL-17-based therapy as a potential therapeutic strategy for inflammatory- and pain-related disease. Importantly, we also discussed clinical trials of IL-17/IL-17R targeting monoclonal antibodies. Overall, we found that IL-17 is a potential therapeutic target for chronic pain from the perspective of neuroinflammation.

BackgroundLittle is known about the recent use of neuromuscular blocking agents (NMBAs) and monitoring in China. This paper presents the results of a nationwide survey conducted to obtain information regarding the current management of NMBAs in China.MethodsA questionnaire was sent to Chinese anesthesiologists inviting them to participate in the study. The questionnaire was available through the wenjuanxing website, and the link was sent to 1,488 anesthesiologists using the Wechat mini app.ResultsThe web-based survey consisted of 28 questions, and data were collected using an online tool. Between May 19, 2021 and June 16, 2021, 637 responses were collected (response rate = 42.8%). Only 10.2% of anesthesiologists reported using neuromuscular function monitors, and 6.59% of respondents reported that they had the relevant monitors in the operating room.ConclusionAlthough PORC is a potential safety issue, the frequency of using reversal agents and monitors remains extremely low in China. Surveys such as this are important to understand the use and application customs of NMBAs in China.