International Journal of General Medicine最新文献

Purpose: The objective of this study was to identify the sonographic and clinical predictors of drainage procedure failure using small-caliber catheters under ultrasound guidance for complex septated pleural effusions.

Materials and methods: In this retrospective cohort study, we analyzed 145 consecutive patients who underwent ultrasound-guided small-caliber (6- or 8-Fr) catheter drainage for complex septated pleural effusion at a single tertiary center. Demographic, clinical, and pleural fluid data were collected. Sonographic images were reviewed to classify septation complexity (widespread vs few) and to quantitatively measure septal thickness. Multivariable logistic regression was used to identify independent predictors of drainage failure.

Results: Unsuccessful drainage occurred in 79 patients (54.5%). Widespread septations (72.2% vs 36.4%, P<0.001) and greater septal thickness (3.3 vs 2.1 mm, P<0.001) were more common in the unsuccessful group. Multivariable analysis identified widespread septations (adjusted odds ratio [aOR]=2.94, P=0.033) and septal thickness (aOR=3.39 per mm, P<0.001) as independent predictors of failure. The optimal cut-off for septal thickness was >2.4 mm (sensitivity 82.3%, specificity 69.7%). An alternative cut-off of >1.8 mm provided high sensitivity (93.7%) and a negative likelihood ratio (LR-) of 0.1 for ruling out failure.

Conclusion: Quantitative sonographic assessment of septation complexity and thickness independently predicts small-caliber catheter drainage failure in complex septated pleural effusions. Incorporating these parameters into pre-procedural evaluation can aid in risk stratification and guide individualized management, potentially facilitating timely escalation to advanced therapies when indicated.

Purpose: Arterial blood gas (ABG) analysis is a widespread, low-cost diagnostic tool routinely used to assess the metabolic status of patients in internal medicine wards, a population characterized by a high burden of chronic comorbidities. However, its prognostic value for collectively predicting adverse outcomes such as ICU transfer and mortality remains insufficiently investigated. This study aimed to evaluate the ability of ABG parameters to predict the composite outcome of ICU transfer and in-hospital mortality in this patient population.

Patients and methods: This retrospective cohort study was conducted at Haseki Training and Research Hospital and included 15,698 patients hospitalized in the Department of Internal Medicine between January 2020 and January 2025. Demographic data, medical history, laboratory parameters (including hemoglobin, white blood cell count, creatinine, albumin, procalcitonin, and blood gas analysis), and outcomes (ICU transfer and in-hospital mortality) were retrieved from the electronic hospital information system. Patients were stratified based on ICU transfer status and in-hospital mortality for comparative analysis.

Results: The study included 9057 patients (mean age 63.5±18.1 years; 51% female). The overall ICU admission and mortality rates were 6.2% (n=564) and 1.9% (n=168), respectively. The ICU and non-survivor groups were significantly older and exhibited a more pronounced inflammatory response (elevated CRP, neutrophils; decreased lymphocytes, albumin) along with more severe metabolic disturbances (elevated lactate; decreased bicarbonate) compared to their counterparts. Multivariate analysis identified age, neutrophil count, CRP, albumin, and lactate levels as independent predictors for both ICU admission and mortality.

Conclusion: This study established that current blood gas parameters, particularly lactate and pCO₂, were useful in stratifying the risk for both intensive care unit transfer and in-hospital mortality.

Objective: To investigate the influencing factors of new-onset atrial fibrillation (AF) in patients with sepsis and to construct a nomogram prediction model.

Methods: A retrospective analysis of 245 sepsis patients admitted to our hospital from March 2021 to March 2024 was used as the training set. An additional 107 sepsis patients admitted to our hospital from April 2024 to April 2025 were included as the validation set. The training and validation sets were divided into an AF group and a non-AF group based on the occurrence of new-onset AF.

Results: In the training set, there were significant differences between the two groups in terms of age, mechanical ventilation, APACHE II score, acute kidney injury, metabolic disorders, theophylline medication, TNF-α, E/e', and NT-proBNP (P < 0.05). LASSO regression analysis was used to screen for 7 predictive factors. Logistic regression analysis identified age, mechanical ventilation, APACHE II score, theophylline medication, TNF-α, E/e', and NT-proBNP as risk factors for new-onset AF in sepsis patients (P < 0.05). The area under the curve (AUC) of the ROC curve for the training set was 0.869, and the Hosmer-Lemeshow test yielded χ2=7.346 (P=0.713). The decision curve analysis (DCA) showed that the model has high clinical application value when the threshold probability is between 0.10 and 0.89. For external validation, the AUC of the ROC curve was 0.875, the Hosmer-Lemeshow test yielded χ2=6.992 (P=0.703), and the DCA curve showed that the model has high clinical application value when the threshold probability is between 0.12 and 0.83.

Conclusion: Age, mechanical ventilation, APACHE II score, theophylline medication, TNF-α, E/e', and NT-proBNP are influencing factors for new-onset AF in patients with sepsis. The nomogram prediction model constructed on the basis of these factors has good clinical applicability.

Objective:  Emerging evidence substantiates the cardiometabolic index (CMI) as a pivotal indicator demonstrating robust associations with an array of cardiovascular pathologies. However, its specific link to coronary heart disease (CHD) remains insufficiently explored. This study aimed to investigate both the association and the predictive value of CMI for CHD in a clinical cohort.

Methods: This retrospective study included patients with suspected CHD who underwent coronary angiography at the Cardiology Department of Chengde Central Hospital between October 2023 and December 2024. Participants were stratified into CHD and non-CHD groups based on angiographic results. A LASSO regression and a logistic regression framework was implemented to examine the influence of age, sex, hypertension, diabetes, smoking, WBC, CK, CMI, and LDL-C on CHD. The association between CMI and CHD was explored using restricted cubic spline (RCS) methodology. The diagnostic efficacy of the model was scrutinized through the utilization of the area under the curve (AUC).

Results: CMI exhibits an independent predictor for CHD, particularly in individuals with high CMI values (Q4 group), where the risk of CHD is markedly elevated. Furthermore, a linear relationship exists between CMI and CHD. Calibration curves demonstrate a strong alignment correlation linking predicted to observed probabilities. Decision curve analysis (DCA) reveals that the model provides substantial clinical benefit within a threshold probability range of 0.13 to 0.72. Receiver operating characteristic (ROC) curve analysis indicates that CMI possesses certain predictive merit for the occurrence of CHD.

Conclusion: A positive association exists between CMI and incidence of CHD. Additionally, CMI serves as an independent risk factor, demonstrating certain predictive power in clinical settings, thereby effectively forecasting the risk of CHD occurrence.

Background: Acute pancreatitis (AP) is a common gastrointestinal emergency that may rapidly progress to severe disease. Acute respiratory distress syndrome (ARDS) is one of the most fatal complications of AP, yet reliable early prediction tools remain limited. Early identification of high-risk patients may improve clinical outcomes.

Purpose: To develop and validate a nomogram prediction model for AP complicated by ARDS based on clinical data.

Methods: A total of 280 AP patients admitted to our hospital between February 2022 and March 2024 were retrospectively enrolled as the training set, and 129 patients admitted between April 2024 and June 2025 served as the validation set. Patients were divided into ARDS and non-ARDS groups according to whether ARDS occurred within 14 days of admission. Clinical and laboratory data were collected and analyzed.

Results: In the training set, 74 patients (26.43%) developed ARDS. Multivariate analysis identified age, history of alcohol consumption, lactate (Lac), red cell distribution width (RDW), fasting blood glucose (FBG), and procalcitonin (PCT) as independent risk factors, while albumin (ALB) was a protective factor. These variables were incorporated into the nomogram. The area under the ROC curve (AUC) was 0.899 in internal validation and 0.927 in external validation. Hosmer-Lemeshow tests demonstrated good calibration in both cohorts (P > 0.05). Decision curve analysis indicated favorable clinical net benefit across a wide range of threshold probabilities.

Conclusion: Age, alcohol consumption history, Lac, RDW, ALB, FBG, and PCT are key predictors of ARDS in patients with AP. The proposed nomogram demonstrates good discrimination, calibration, and clinical utility, and may assist clinicians in early risk stratification.

Purpose: Gastric cancer (GC) represents a malignant neoplasm with high global incidence and mortality rates. The limited efficacy of current clinical treatment regimens underscores the urgent need for novel and more effective therapeutic targets.

Patients and methods: Through the utilization of public databases, we identified circadian rhythm genes associated with GC and conducted an analysis of their expression profiles. Enrichment analysis was performed using the KEGG/GO pathways via the "clusterProfiler" package, immune correlation was assessed through ssGSEA (GSVA), tumor mutations were analyzed using TCGA somatic data, and drug sensitivity was evaluated using the "pRRophetic" package. The biological functions of RORC in GC cells were investigated through CCK8, colony formation, and Transwell assays.

Results: RORC has been identified as a pivotal gene associated with circadian modulation in gastric cancer. Its expression is markedly reduced in gastric cancer tissues compared to adjacent normal tissues. Enrichment analysis indicates a significant correlation between RORC and the regulation of circadian rhythms. Immunocorrelation analysis demonstrates a significant association between RORC gene expression and T follicular helper cells (Tfh), T cell co-stimulation, and activated dendritic cells (aDCs). Analysis of mutations related to the RORC gene reveals that missense mutations are the predominant type. Notably, key genes such as TP53 and ARID1A show relatively high mutation frequencies in both high and low RORC expression groups. Drug sensitivity analysis indicates that the RORC gene is responsive to agents such as VX-680, MG-132, and Sunitinib. Cell biology experiments have confirmed that RORC overexpression significantly diminishes the proliferation, invasion, and migration capabilities of gastric cancer cells.

Conclusion: Integrating bioinformatics and cell biology experiments suggests that RORC, a gene associated with rhythm regulation, acts as a tumor suppressor gene that is underexpressed in gastric cancer, thereby serving as a potential biomarker and therapeutic target for this malignancy.

Background: Disruption of circadian blood pressure (BP) rhythms-manifested as non-dipper or reverse-dipper patterns-is associated with increased cardiovascular risk, especially in patients with primary hypertension (PH) and concomitant coronary artery disease (CAD). The ambulatory arterial pressure index (AAPI), a novel parameter derived from 24-hour ambulatory BP monitoring (ABPM), reflects the cumulative hemodynamic burden and may provide insight into circadian BP abnormalities. However, its relationship with BP rhythm patterns in this high-risk population remains unclear.

Methods: This retrospective observational study included 430 hospitalized patients with PH and CAD who underwent 24-hour ABPM between January 2022 and December 2023. Patients were classified into dipper (n = 51), non-dipper (n = 266), and reverse-dipper (n = 113) groups based on the nocturnal decline in systolic BP. AAPI was calculated as the ratio of diastolic to systolic pressure load over a 24-hour period. Baseline demographic, biochemical, and hemodynamic variables were compared across groups, and correlations between AAPI and BP rhythm categories were analyzed.

Results: The mean age was 69.1 ± 17.8 years, and 63.5% of patients were male. There were no significant differences in age, sex, renal function, or lipid profiles across circadian BP rhythm subgroups. Patients with disrupted BP rhythms (non-dipper or reverse-dipper) had significantly higher AAPI values than those with a dipper pattern (0.396 ± 0.041 vs 0.387 ± 0.043, p = 0.022). AAPI values showed a significant positive correlation with rhythm severity (r = 0.18, p = 0.004).

Conclusion: AAPI is significantly associated with abnormal circadian BP patterns in patients with PH and CAD. As a simple, integrative hemodynamic index, AAPI may aid in the early identification of patients with rhythm disruption and provide added value for personalized cardiovascular risk stratification.

Background: Sarcopenia is increasingly recognized as a host-related prognostic factor in gastric cancer; however, its relationship with early postoperative outcomes remains inconsistent. The psoas muscle index (PMI) is a practical CT-based surrogate of skeletal muscle reserves.

Methods: This retrospective cohort from two university-based tertiary referral centers included patients who underwent curative-intent upfront gastrectomy for gastric cancer between 2015 and 2020. Patients who received neoadjuvant chemotherapy, or who presented with radiologically bulky lymph nodes or distant metastasis, were excluded. Bilateral psoas muscle areas at L3 were summed and normalized to height squared (mm²/m²). Sex-specific Turkish cut-offs defined low PMI (<530 mm²/m² men; <360 mm²/m² women). Early postoperative outcomes and time-specific OS (1-, 3-, 5-year) were compared across PMI-defined categories.

Results: A total of 184 patients were included (106 low-PMI; 57.6% and 78 high-PMI; 42.4%). Low PMI was not associated with higher postoperative morbidity: anastomotic leak 4.72% vs 3.85% (p=1.000), surgical-site infection 11.3% vs 10.3% (p=1.000), transfusion requirement 31.1% vs 30.8% (p=1.000), median hospital stay 13 vs 13 days (p=0.379). In contrast, survival clearly diverged: 1-year OS was not significant (80.19% vs 91.03%; p=0.060), whereas 3-year OS (54.72% vs 79.49%; p<0.001) and 5-year OS (43.40% vs 74.36%; p<0.001) were markedly inferior in low-PMI patients. In multivariable Cox regression, PMI independently predicted mortality (HR 0.996; p<0.001).

Conclusion: Low PMI was not associated with early morbidity, but it independently identified patients at substantially higher long-term mortality risk, supporting the concept that diminished muscle mass reflects impaired long-term biological reserve rather than short-term surgical vulnerability, and may be incorporated into routine preoperative risk stratification.

Objective: This study aims to assess the predictive value of interleukin-6 (IL-6) as a biomarker in patients with rheumatoid arthritis-associated interstitial lung disease (RA-ILD).

Methods: A total of 361 RA patients (236 RA non-ILD and 125 RA-ILD patients) are included in the study, and stratified analysis is performed according to age and gender. The RA-ILD group is divided into mild ILD, moderate ILD, and severe ILD groups based on HRCT score. Using logistic regression analysis to investigate the risk association between IL-6 and rheumatoid arthritis-associated interstitial lung disease (RA-ILD), and employing receiver operating characteristic (ROC) to determine the value of IL-6 for distinguishing RA-ILD. Pearson's analysis and linear regression are used to analyze the association between IL-6 and RA disease activity, High-Resolution Computed Tomography (HRCT) scores, and Krebs Von den Lungen-6 (KL-6).

Results: The level of IL-6 in the RA-ILD group is higher than that in the RA non-ILD group (p < 0.001). The OR of IL-6 associated with the risk of ILD is 1.03 (p < 0.001). IL-6 demonstrated significant diagnostic utility in distinguishing RA-ILD patients from RA patients without ILD, with an area under the receiver operating characteristic curve (AUC) of 0.810 (95% CI: 0.767-0.854; p < 0.001). At the best cutoff value of 8.87 pg/mL, IL-6 exhibited a sensitivity of 94.4% and specificity of 63.6%. There is no statistically significant difference in IL-6 among the ILD subgroups (p > 0.05). Pearson correlation analysis and multiple linear regression analysis show that IL-6 is significantly positively correlated with Disease Activity Score-28 (DAS28), but does not significantly correlate with HRCT score and KL-6.

Conclusion: IL-6 may be used as a new peripheral blood biomarker to predict RA-ILD.

Objective: To investigate the knowledge, attitudes, and practices (KAP) of caregivers of stroke patients regarding the risk factors and management of post-stroke delirium.

Methods: This multicenter, cross-sectional study was conducted among caregivers of stroke patients who visited two tertiary hospitals and three community health service centers between November 2023 and January 2024. In this study, knowledge, attitude, and practice were assessed using structured scoring systems, with knowledge scored from 0-24, attitudes from 7-35, and practices from 9-45.

Results: A total of 484 valid questionnaires were included, with 325 (67.1%) females respondents. The median (25th, 75th percentile) KAP scores were 9.00 (2.00, 12.00) (possible range: 0-24), 24.00 (23.00, 26.00) (possible range: 7-35), and 33.00 (27.00, 36.00) (possible range: 9-45), respectively. Multivariate logistic regression analysis showed that knowledge score (OR = 1.11, 95% CI: 1.07, 1.16), attitude score (OR = 1.48, 95% CI: 1.32, 1.67), duration of stroke diagnosis > 2 years (OR = 0.47, 95% CI: 0.26, 0.83), and lack of participation in related education (OR = 0.43, 95% CI: 0.26, 0.72) were independently associated with practices. Structural equation modeling revealed that knowledge directly influenced attitudes (β = -0.39, P < 0.001) and practice (β = 0.30, P < 0.001), while attitudes also directly influenced practices (β = -0.51, P < 0.001). Knowledge indirectly affected practices through its effect on attitudes (β = 0.20, P < 0.001).

Conclusion: Caregivers of stroke patients exhibited inadequate knowledge, neutral attitudes and moderate practices regarding risk factors and management of post-stroke delirium. Targeted educational interventions should be implemented for caregivers, emphasizing the importance of recognizing and effectively managing post-stroke delirium.