The metabolic and inflammatory burden of cardiac surgery results in increased protein catabolism, elevated energy expenditure and thereby a consequent increased risk of postoperative complications. Therefore, it is imperative to optimise nutritional status preoperatively and postoperatively to ameliorate these effects on wound healing, immune function, and recovery of the myocardium, in addition to other clinical outcomes. Despite its benefits, structured perioperative nutritional care is rarely undertaken. In this narrative review, we will summarise contemporary literature (2017-2026) and international guideline recommendations to outline phase-specific nutritional strategies for patients undergoing cardiac surgery. In the early postoperative period, early initiation of enteral nutrition, adequate protein provision (1.2-2.0 g/kg/day), and careful fluid and glycaemic management are critical to attenuate catabolic stress and reduce complications. During hospital recovery and discharge to home, emphasis should shift towards caloric adequacy, micronutrient optimisation-particularly vitamins C and D, zinc, and iron-and management of medication-related gastrointestinal effects. In the long-term phase, adoption of cardioprotective dietary patterns such as the Mediterranean and Dietary Approaches to Stop Hypertension (DASH) diets supports secondary prevention and cardiovascular risk reduction. Elderly patients who are sarcopenic, individuals with diabetes mellitus or chronic kidney disease (CKD), overweight individuals and people on anticoagulation warrant special consideration. Integrating nutritional assessment and intervention into Enhanced Recovery After Cardiac Surgery (ERACS) pathways may help improve recovery trajectories and reduce morbidity. Further high-quality research should be conducted to define procedure-specific and individualised nutritional protocols in the cardiac surgical population.
AIMS/BACKGROUND:Whole-body computed tomography (WBCT) is central to major trauma assessment, but appropriate justification and reporting depend on adequate clinical information at the time of request. The Royal College of Radiologists (RCR) 2024 major trauma guidance recommends six minimum data elements for trauma WBCT requests. This quality improvement project aimed to improve documentation compliance and reduce inappropriate WBCT requests at a district general hospital. METHODS:A completed audit cycle was undertaken. Consecutive adult trauma patients undergoing WBCT were identified in a baseline audit (Cycle 1; n = 100, September-December 2024) and a post-intervention re-audit (Cycle 2; n = 100, September-December 2025). Three interventions were introduced: educational feedback to Department of Radiology and Department of Emergency Medicine staff, an RCR-derived electronic request proforma embedded within CareFlow Electronic Patient Record (EPR), and real-time radiologist feedback. Primary outcomes were compliance with the six RCR minimum dataset standards and the proportion of requests meeting RCR WBCT criteria. RESULTS:Baseline compliance varied across documentation domains. In Cycle 1, documentation rates were 74% for mechanism of injury, 94% for primary survey findings, 7% for haemodynamic status, 5% for preceding investigations, 13% for past medical history, and 0% for trauma team leader contact details. Following intervention, mechanism documentation improved to 100% (p < 0.001), haemodynamic status to 93% (p < 0.001), and trauma team leader contact details to 92% (p < 0.001). Primary survey documentation remained high at 97% (p = 0.306). Past medical history increased to 18% (p = 0.329), while preceding investigations remained low at 4% (p = 1.000). Requests meeting RCR WBCT criteria increased from 57% to 96% (p < 0.001), while non-compliant requests fell from 43% to 4%. This represented 39 potentially avoidable scans and approximately 780 mSv of theoretically avoided radiation exposure per 100 requests. CONCLUSION:A theory-informed intervention combining education, a mandatory electronic proforma, and real-time radiologist feedback substantially improved trauma WBCT request documentation and reduced inappropriate requests. Embedding minimum datasets into electronic requesting systems is a low-cost, scalable strategy to support compliance with the Ionising Radiation (Medical Exposure) Regulations [IR(ME)R] 2017, as amended in 2020, and radiation stewardship.
AIMS/BACKGROUND:The Central Sterile Supply Department (CSSD) is a critical component of hospital infection control, and the quality of its work directly impacts patient safety. Given that traditional training models struggle to accommodate differences in staff competency levels, this study aimed to investigate the effectiveness of a tiered training model in CSSD personnel management. METHODS:A retrospective analysis was conducted using the same group of staff members. Traditional standardized training was implemented during the control period (2024), while tiered training based on job competency was implemented during the observation period (2025). Based on competency assessments, staff were categorized into basic, proficient, core, and management & guidance levels, and targeted training courses were implemented accordingly. The effectiveness of the tiered training model was evaluated by comparing knowledge levels, core skills, work quality indicators (including process quality, outcome quality, and service efficiency), as well as internal and external satisfaction between the two periods. RESULTS:During the observation period, staff knowledge scores were significantly higher than those in the control period (81.86 ± 5.23 vs. 70.71 ± 8.52, p < 0.001), and scores for various operational skills also improved significantly (p < 0.001). Process and outcome quality indicators, including cleaning qualification rate and sterilization qualification rate, showed significant improvements (p < 0.05). Service efficiency indicators, including retrieval time, preparation, and replenishment times, were also significantly reduced (p < 0.001). Additionally, internal and external training and service satisfaction scores were significantly higher during the observation period (p < 0.05). CONCLUSION:The tiered training model can effectively improve the knowledge and technical competencies of CSSD staff, enhance work quality and service efficiency, and increase internal and external satisfaction. This model represents a precise and efficient personnel training and management strategy that accommodates differences in staff capabilities and may have potential for widespread application in the future.
AIMS/BACKGROUND:The coexistence of gestational diabetes mellitus (GDM) and preeclampsia (PE) significantly increases the risk of adverse neonatal outcomes. However, effective predictive tools for this high-risk population remain limited. This study aimed to evaluate the predictive value of inflammatory and placental-related biomarkers for adverse neonatal outcomes in pregnant women with GDM and PE. METHODS:This retrospective observational study enrolled 230 pregnant women with GDM and PE between February 2022 and February 2025. Participants were divided into an event group (n = 53) and a non-event group (n = 177) based on the occurrence of adverse neonatal outcomes. Baseline characteristics, inflammatory markers, and placental growth factor (PlGF) levels were collected. Independent predictive factors were identified using univariate and multivariate logistic regression analyses, with collinearity diagnostics performed. Receiver operating characteristic (ROC) curves were plotted to evaluate the discriminative performance of individual markers and combined predictive models. RESULTS:Univariate analysis indicated that fasting blood glucose, PlGF, glycated hemoglobin (HbA1c), neutrophil-lymphocyte ratio (NLR), systemic immune-inflammatory index (SII), and systemic inflammatory response index (SIRI) were significantly associated with adverse neonatal outcomes (all p < 0.05). Multivariate logistic regression, after adjustment for collinearity, identified elevated fasting blood glucose, reduced PlGF, increased HbA1c, and elevated SII as independent risk factors for adverse neonatal outcomes (all p < 0.001). ROC curve analysis demonstrated that the combined model incorporating these four variables achieved the highest predictive accuracy, with an area under the curve (AUC) of 0.944 (95% confidence interval [CI]: 0.902-0.986), sensitivity of 94.3%, and specificity of 84.7%, significantly outperforming individual markers. CONCLUSION:In pregnant women with GDM and PE, fasting blood glucose, PlGF, HbA1c, and SII represent independent predictors of adverse neonatal outcomes. A composite panel integrating metabolic, placental, and inflammatory biomarkers exhibits strong discriminative value and may provide objective evidence for neonatal risk stratification in this high-risk population, thereby informing targeted clinical management.
AIMS/BACKGROUND:Driven by global industrialization and a rapidly aging population, lung cancer and chronic obstructive pulmonary disease (COPD) increasingly co-occur, posing complex challenges for clinical management. Although the six-minute walk test (6MWT) is a well-established tool for assessing functional status in each condition, its specific role in patients with early-stage lung cancer and comorbid COPD remains unexplored. This study aimed to explore the correlations between the baseline 6MWT results and pulmonary function, COPD severity, cognitive function, and quality of life (QoL) in patients with early-stage lung cancer and comorbid COPD. METHODS:A retrospective study was conducted, enrolling 215 patients with early-stage lung cancer and COPD admitted to Hebei Provincial People's Hospital between January 2022 and December 2023. Data on patient demographics, baseline 6MWT results (six-minute walk distance [6MWD]), pulmonary function parameters (forced expiratory volume in one second [FEV1], forced vital capacity [FVC], FEV1/FVC ratio), COPD severity grade, cognitive function (Montreal Cognitive Assessment [MoCA] score), and quality of life (St. George's Respiratory Questionnaire [SGRQ] score) were collected from medical records. Patients were dichotomized into High and Low 6MWD groups based on the median 6MWD value. Spearman correlation, univariate analyses, and multivariate logistic regression were used to examine relationships and identify independent factors associated with 6MWD. RESULTS:Logistic regression identified age, FEV1, FVC, FEV1/FVC, COPD severity grade, MoCA score, and the dimensions of respiratory symptoms and activity limitation of the SGRQ scores as independent factors influencing 6MWD. Age demonstrated a significant negative correlation with 6MWD (rs = -0.666, p < 0.001). FEV1, FVC, and FEV1/FVC were each significantly positively correlated with 6MWD (rs = 0.557, p < 0.001; rs = 0.139, p = 0.041; rs = 0.598, p < 0.001, respectively). A statistically significant difference in 6MWD was observed among patients with different COPD severity levels (H = 49.283, p < 0.001). MoCA scores showed a significant positive correlation with 6MWD (rs = 0.388, p < 0.001). The respiratory symptoms, activity limitation, and impact on daily life scores of the SGRQ were each significantly negatively correlated with 6MWD (rs = -0.766, p < 0.001; rs = -0.617, p < 0.001; rs = -0.245, p < 0.001, respectively). CONCLUSION:The 6MWT results in patients with early-stage lung cancer and COPD demonstrate significant correlations with pulmonary function, COPD severity, cognitive function, and quality of life. Therefore, the 6MWT can be deployed as a comprehensive functional assessment tool in this patient population.
AIMS/BACKGROUND:Anemia is a highly prevalent and clinically significant complication in maintenance hemodialysis (MHD) patients, markedly impairing quality of life and being associated with adverse prognosis. Conventional management strategies often lack sufficient individualization, potentially leading to suboptimal therapeutic outcomes. This study aimed to investigate the impact of personalized anemia management on quality of life and albumin levels in maintenance hemodialysis patients through a retrospective analysis. METHODS:A retrospective analysis was conducted involving 353 patients who received maintenance hemodialysis at the Affiliated Hospital of North Sichuan Medical College between March 2022 and March 2025. Based on the management approaches documented in their medical records, patients were divided into two groups: Those receiving routine medical care were assigned to the control group (n = 181), while those receiving personalized anemia management strategies were assigned to the observation group (n = 172). The observation group received personalized anemia management in addition to routine dialysis. Specifically, this approach included individualized adjustment of erythropoietin and iron dosages based on a comprehensive evaluation of dynamic hemoglobin and albumin levels, as well as nutritional status. Meanwhile, a multidisciplinary team led by physicians collaboratively formulated nutritional and pharmacological management plans and provided adherence guidance. The study compared changes in hemoglobin levels, hemoglobin target achievement rate, albumin levels, body composition parameters, Self-Rating Anxiety Scale (SAS), Self-Rating Depression Scale (SDS), quality of life scores (assessed using the Kidney Disease Quality of Life 36-Item Short Form Survey, KDQOL-36), and Pittsburgh Sleep Quality Index (PSQI) between the two groups before and after treatment. RESULTS:Following the intervention, depression and anxiety scores in the observation group were significantly lower than those in the control group (p < 0.05). Regarding physiological indicators, albumin levels, body composition parameters, hemoglobin levels, and the hemoglobin target achievement rate, the observation group showed significant improvements compared with the control group (p < 0.05). Additionally, the PSQI score was significantly lower in the observation group, whereas the quality of life scores were significantly higher compared with the control group; all differences were statistically significant (p < 0.05). CONCLUSION:Personalized anemia management significantly improves quality of life and albumin levels in maintenance hemodialysis patients and demonstrates potential for clinical application.
AIMS/BACKGROUND:Precise evaluation of coronary lesion severity is pivotal for the clinical management of coronary heart disease (CHD). However, because the invasive coronary angiography (ICA) method, which is considered the gold standard for diagnosis, is relatively invasive, it is not widely used in early risk stratification. This study evaluated the performance of a predictive model based on a combined triglyceride-glucose (TyG) index and ultrasound radiomics characteristics of carotid plaques for evaluating coronary artery lesion severity in patients with CHD. METHODS:From January 2020 to October 2024, 381 CHD patients were diagnosed by ICA at Yichang Central People's Hospital. Radiomics features were extracted from manually divided regions of interest (ROIs) in carotid plaque ultrasound images. A two-stage feature selection was carried out to identify the essential features, and then logistic regression was employed to construct a radiomics score (Rad score). Clinical data, such as the TyG index, were also included in the construction of the combined prediction model, and the predictive performance of this model was evaluated on both the training and test sets. RESULTS:Multivariate logistic regression shows that the TyG index (odds ratio [OR] = 3.82, 95% confidence interval [CI]: 2.13-6.84), sex (OR = 1.80, 95% CI: 1.08-3.00), and hypertension status (OR = 1.81, 95% CI: 1.14-2.87) are all independent predictors of coronary lesion severity. Based on 17 essential radiomics features, the Rad score model reached an area under the curve (AUC) of 0.673 (95% CI: 0.613-0.734) for the training set and an AUC of 0.686 (95% CI: 0.567-0.806) for the test set. The combined model including sex, TyG index, hypertension status, and Rad score performed better, with AUC values of 0.823 (95% CI: 0.777-0.870) for the training set and 0.730 (95% CI: 0.616-0.844) for the test set. CONCLUSION:The combined model of the TyG index and ultrasound radiomics features for carotid plaques can be used to predict the severity of coronary artery lesions in patients with CHD. Non-invasively, it can be used to assess the risk of coronary artery disease and tailor a plan for other treatment options.
AIMS/BACKGROUND:Post-chemotherapy infection is a major cause of treatment failure in lung cancer (LC) patients undergoing neoadjuvant chemotherapy (NAC). This study aimed to identify risk factors for post-NAC infection using the Least Absolute Shrinkage and Selection Operator (LASSO) regression and to develop and validate a corresponding risk prediction model. METHODS:Clinical data from 144 LC patients who underwent NAC at Hunan Provincial People's Hospital between January 2021 and December 2024 were retrospectively analysed. Patients were stratified into a non-infection group (n = 81) and an infection group (n = 63) based on the occurrence of infection. LASSO-logistic regression was used to identify risk factors for post-chemotherapy infection. A risk prediction nomogram was subsequently constructed and validated based on these factors. RESULTS:The optimal LASSO model was selected at lambda.1se (λ = 0.074), which retained 9 of the 15 candidate predictors. Eastern Cooperative Oncology Group Performance Status (ECOG-PS) ≥2, recent invasive procedures/catheterization, and Nutritional Risk Screening 2002 (NRS-2002) score ≥3 were identified as significant risk factors for post-chemotherapy infection, while a high cluster of differentiation 4-positive (CD4+) count served as a protective factor (p < 0.05). A nomogram incorporating these variables was subsequently developed. Internal validation using the bootstrap method (1000 iterations) demonstrated a good predictive performance with an area under the curve (AUC) of 0.831 (95% confidence interval [CI]: 0.761-0.901, p < 0.001), sensitivity of 76.2%, and specificity of 79.0% at the optimal cutoff. The calibration curve demonstrated good agreement between predicted and observed outcomes. Decision curve analysis (DCA) confirmed the clinical utility of the nomogram by showing a positive net benefit across a wide range of threshold probabilities. CONCLUSION:The LASSO-derived nomogram integrates key variables (ECOG-PS ≥2, invasive procedures/catheterization, NRS-2002 score ≥3, and CD4+ level) to enable individualised prediction of post-NAC infection risk in LC patients. Targeted interventions addressing these risk factors, together with maintenance of protective factors, may help reduce infection rates and improve treatment outcomes, providing a scientific basis for infection prevention and management.
AIMS/BACKGROUND:Recurrent spontaneous abortion (RSA) may contribute to intrauterine adhesions and lead to female infertility. This study aims to analyze serum lactate dehydrogenase (LDH) levels and immune-inflammatory markers in patients with recurrent abortion and to evaluate their diagnostic value in RSA. METHODS:A total of 120 patients with RSA admitted between January 2023 and December 2024 were included as the study group, and 80 pregnant women with normal prenatal examination findings during the same period were selected as controls. Serum and hematological assays were performed in both groups, and levels of LDH, immune-inflammatory markers, autoimmune antibodies, and lymphocyte subsets were compared. Factors associated with RSA were analyzed using logistic regression, and the diagnostic performance of each index was assessed using a receiver operating characteristic (ROC) curve. RESULTS:Compared with the control group, serum LDH levels, immune-inflammatory markers [interleukin (IL)-6, IL-10, and interferon gamma (IFN-γ)], antiphospholipid antibodies, and T lymphocyte subsets were significantly different in the RSA group (p < 0.05). Serum LDH, IFN-γ, antiphospholipid antibodies (APA) positive rate and cluster of differentiation (CD)4+ T-cell levels were significantly higher in the RSA group than in controls (p < 0.05), whereas IL-6, IL-10, and CD8+ T-cell levels were significantly lower (p < 0.05). Binary logistic regression analysis showed that elevated serum LDH, reduced IL-6 level, increased proportion of CD4+ cells, and decreased proportion of CD8+ cells were independent risk factors for recurrent abortion in RSA patients (all p < 0.05). ROC curve analysis showed that the combined detection of serum LDH, IL-6, CD4+, and CD8+ yielded an area under the curve (AUC) of 0.908, with a sensitivity of 0.875 and specificity of 0.823. The combined model demonstrated superior diagnostic performance compared with individual markers. CONCLUSION:Combined assessment of serum LDH and selected immune-inflammatory markers (IL-6, CD4+, CD8+) shows good predictive and diagnostic value for RSA and may facilitate early identification of high-risk patients in clinical practice.
AIMS/BACKGROUND:Postpartum depression (PPD) is a common perinatal mental health disorder that leads to adverse maternal and infant outcomes. Existing screening strategies rely on self-reported symptom presence, potentially delaying early identification. This study aims to integrate biological, psychological, and social predictive factors using an ensemble learning (EL) strategy to develop a superior early prediction machine learning (ML) model for PPD. METHODS:By integrating sociodemographic characteristics, clinical baseline data, and psychological test results of 1323 postpartum women, PPD status was classified using the Edinburgh Postnatal Depression Scale (EPDS). Eight selection methods were used, and eleven base ML models were optimized through EL strategies (Voting and Stacking) to identify the model with the optimal predictive performance. RESULTS:Twenty predictor features were selected for the model construction. The Voting top 5+XGBoost (eXtreme Gradient Boosting, Weight) model demonstrated the best overall performance (area under the curve [AUC] = 0.835) and the highest specificity (0.906), indicating that it is more suitable for differential diagnosis following an initial positive screening result. The Voting (Synthetic Minority Over-sampling Technique [SMOTE]) model performed exceptionally well in sensitivity (0.758) and clinical net benefit at low-risk thresholds, indicating its suitability for early screening for PPD. CONCLUSION:The results demonstrate that ensemble learning models outperform individual ML prediction models. Voting top 5+XGBoost (Weight) and Voting (SMOTE) show respective advantages in predictive specificity and sensitivity. This suite of models can provide distinct data-driven prediction strategies tailored to different clinical application contexts.
Cough is one of the leading causes for children and their families to seek medical advice, and it may be difficult for clinicians to determine the underlying cause. Cough is a pulmonary defence mechanism and may be acute, recurrent or defined as chronic if lasting beyond 4 weeks. Further differentiating a chronic cough into wet or dry may aid clinicians in establishing the possible cause. This article provides a framework for the assessment of chronic cough in children, signposts to the latest guidelines, explains when and how to further investigate chronic cases and considers when to refer to a tertiary respiratory service.
AIMS/BACKGROUND:Dopa-responsive dystonia (DRD) is a rare genetic disorder with complex and diverse clinical manifestations, resulting in a high rate of misdiagnosis. This case report describes an infantile case of DRD complicated by autism spectrum disorder (ASD), initially presenting with a sleep disorder. We aim to summarize its clinical manifestations, diagnostic process, treatment, and follow-up outcomes in order to improve clinical understanding of this disease. CASE PRESENTATION:A retrospective analysis was performed on a male infant who was treated at Jinhua Maternal and Child Health Care Hospital in 2020. The patient presented at one month of age with sleep disturbances, delayed motor development, and intermittent upward deviation of the eyes. Genetic testing identified two heterozygous pathogenic variants in the tyrosine hydroxylase (TH) gene. Among them, the c.738-2A>G variant was not recorded in the Exome Aggregation Consortium (ExAC), Genome Aggregation Database (gnomAD), or 1000 Genomes Asian population databases. During follow-up, the patient was also found to have comorbid ASD. RESULTS:Genetic testing confirmed biallelic TH mutations, establishing the diagnosis of infantile DRD. The patient exhibited marked clinical response to levodopa/benserazide, though dose titration was required with growth. CONCLUSION:For infants with unexplained sleep disorder accompanied by delayed motor development, genetic testing should be performed as early as possible to facilitate the identification of the root cause and implement timely treatment. In addition, close follow-up should be conducted to detect comorbid neurodevelopmental disorders.
AIMS/BACKGROUND:Cor pulmonale is characterised by right ventricular hypertrophy and dysfunction due to chronic lung disease or pulmonary vascular disease. Mortality in patients with pulmonary heart disease is influenced by a variety of factors; therefore, elucidating prognostic factors is essential to improve patient management and therapeutic strategies. The neutrophil-to-lymphocyte ratio (NLR), a marker of systemic inflammation, has been implicated in cardiovascular and pulmonary diseases. This study aims to evaluate the prognostic value of NLR in assessing all-cause mortality and survival in patients with cor pulmonale. METHODS:We conducted a retrospective analysis of data from 6681 patients in the Medical Information Mart for Intensive Care IV database, classifying them into low and high NLR groups based on the median NLR value of 8.26. Clinical indicators, including albumin levels, kidney function, and haematological results, were compared between groups. Multivariate models were used to assess the relationship between NLR and mortality risk. Subgroup analyses were conducted to validate findings across different populations. RESULTS:The high-NLR group exhibited significantly lower albumin levels, poorer kidney function, and unfavourable haematological parameters. Patients aged ≥65 years and those with high-risk medical histories were more prevalent in the high-NLR group. Model analysis demonstrated that elevated NLR was independently associated with increased risk of adverse outcomes, with hazard ratios of 1.58, 1.37, and 1.22 across three adjusted models. A strong correlation was observed between NLR and all-cause mortality, with a nonlinear relationship indicating a complex impact on mortality risk. Subgroup analyses confirmed the consistency of these findings across various patient subgroups. CONCLUSION:NLR is a significant prognostic marker for all-cause mortality in patients with cor pulmonale. Routine assessment of NLR may aid clinicians in risk assessments to enhance prognosis and management strategies. Further research is needed to explore the clinical utility of NLR in this population.
