International Journal of General Medicine最新文献

Objective: Circulating tumor cell (CTC) has been used to assist in the diagnosis and progression assessment of solid tumors, but the relationship between preoperative CTCs levels and central lymph node metastasis (CLNM) of papillary thyroid carcinoma (PTC) needs to be clarified.

Methods: Data on clinical features (age, gender, Hashimoto's thyroiditis, multifocal, maximum lesion diameter, invaded capsule, clinical stage, and status of lymph node metastasis) of PTC patients treated at our hospital between June 2021 and April 2023 were retrospectively collected. The relationship between the CTCs level and these clinical features was analyzed, especially the relationship between the CTCs level and CLNM.

Results: A total of 705 PTC patients were included, and there were 333 (47.2%) patients with CLNM. Patients with a high CTCs level had higher proportions of multifocality, maximum lesion diameter >1cm, and CLNM than those in patients with a low CTCs level. Tumor size was connected to CTCs level, patients with a high CTCs level had a higher proportion of CLNM than those with a low CTCs level in PTC with maximum lesion diameter ≤1cm (45.3% vs 29.7%) (p=0.001). Logistic regression analysis showed that age <55 years old (odds ratio (OR): 2.612, 95% confidence interval (CI): 1.565-4.361, p<0.001), invaded capsule (OR: 1.662, 95% CI: 1.098-2.517, p=0.016), and high CTCs level (≥8.7 FU/3mL, OR: 2.141, 95% CI: 1.431-3.203, p<0.001) were associated with CLNM in PTC with maximum lesion diameter ≤1cm.

Conclusion: In PTC patients with maximum lesion diameter ≤1cm, patients with high preoperative CTCs level (≥ 8.7FU/3mL), age <55 years old, and capsular invasion were prone to CLNM. However, similar results were not observed in patients with maximum lesion diameter >1cm.

Background and aims: In coronavirus disease 2019 (COVID-19) patients, several serum biomarkers have been identified. Upon intensive care unit (ICU) admission, these laboratory markers become more crucial to distinguish between patients with severe cases of COVID-19. It might assist doctors in predicting the course of illnesses and treating patients appropriately. This work was to investigate the role of biomarkers in patients with COVID-19 classification admitted to the hospital and identified by reverse transcription polymerase chain reaction (RT-PCR).

Methods: Peripheral blood sample was taken from COVID-19 cases isolated on admission to determine C-reactive protein (CRP), D-dimer, Fibrinogen, neutrophil-lymphocyte ratio (NLR), leukocytes CRP ratio (LeCR), lymphocyte-CRP ratio (LCR), interleukin-6 (IL6), leukocytes interleukin 6 ratio (LeIL6), systemic inflammatory index (SII), platelet-to-lymphocyte ratio (PLR), and tissue plasminogen activator inhibitor one (tPAI-1). Follow-up for IL6, Ferritin, D-dimer, and tPAI-1 were determined on the 3^rd and 7^th days.

Results: Comparisons of severity revealed that hypertension, chronic obstructive pulmonary disease (COPD), and Ischemia were major risk factors in COVID-19 patients. There was a statistically significant difference between the test groups for fibrinogen (p < 0.000), IL6 (p < 0.009), LeCR (p < 0.006), and LCR (p < 0.011).

Conclusion: Based on laboratory test findings at the time of ICU admission, we can distinguish severe cases of COVID-19.

Insulin resistance (IR) and non-alcoholic fatty liver disease (NAFLD) are representative metabolic diseases, and no pharmacological therapeutic strategies have been developed worldwide. In recent studies, acupuncture has increasingly been used as an integrative or complementary therapy for IR and NAFLD. In this review, we summarized 18 clinical trials and 25 animal studies to reveal the function and potential molecular mechanisms of acupuncture for IR and NAFLD treatment. We found that acupuncture can be a first-line treatment strategy for IR and has a positive therapeutic effect on NAFLD. Thus, this review provides clinicians with a deeper understanding of the scientific evidence for acupuncture treatment of IR and NAFLD. Finally, we highlighted three potential limitations of existing studies on acupuncture for the treatment of IR and NAFLD, including small sample sizes and inconsistent operating techniques.

Purpose: This study aims to investigate the influence of the Global Leadership Initiative on Malnutrition (GLIM) on diagnosing malnutrition in acute pancreatitis (AP) based on various inflammatory criteria.

Patients and methods: A total of 258 AP patients admitted to a large medical center between June 2019 and January 2022 were retrospectively analyzed. All patients underwent evaluation using the original GLIM and GLIM criteria based on C-reactive protein (CRP), albumin, neutrophil/lymphocyte ratio, and CRP/albumin ratio (CAR). The study explored the impact of malnutrition diagnosis using different GLIM criteria on various clinical outcomes of AP patients and assessed the agreement of different GLIM criteria compared to the original GLIM.

Results: Thirty-seven (14.34%) patients were malnourished according to the original GLIM criteria. Using the other four criteria, malnutrition rates ranged from 6.59% to 12.40%. Malnutrition diagnosed by all GLIM criteria was associated with local complications. Malnutrition identified by the original, CRP-based, and CAR-based GLIM criteria was also associated with infectious complications and composite outcomes. Meanwhile, albumin-based malnutrition was associated with all adverse outcomes except organ failure. When considering all four GLIM criteria except the original one, malnourished patients exhibited longer lengths of stay than non-malnourished patients. Under the CRP- and albumin-based GLIM criteria, hospitalization costs were higher for malnourished patients. The sensitivity analyses demonstrated the robustness of the results. The agreement of the four GLIM criteria with the original GLIM criteria were consistent with the corresponding incidence of malnutrition.

Conclusion: This study validated the GLIM criteria for the first time in AP. Malnourished patients were more likely to experience local complications than non-malnourished AP patients. However, the inconsistency between GLIM criteria based on disease burden and various inflammatory markers was significant. The inflammatory marker-based GLIM criteria demonstrated a stronger predictive value than the original GLIM criteria in assessing prognosis in AP patients.

Background: Lymph node metastasis (LNM) is an important prognostic factor for breast cancer. Inflammatory stimulation can change tumor microenvironment and lead to LNM, but the relationship between LNM and peripheral immunoinflammatory indices has not been clarified in breast cancer.

Methods: The clinical information of 1918 patients with breast cancer admitted to Meizhou People's Hospital from October 2017 to December 2023 were retrospectively analyzed. The relationship of clinicopathological features (age, body mass index (BMI), ABO blood types, family history of cancer, tumor site, disease stage, LNM, distant metastasis, and molecular subtypes) and peripheral immunoinflammatory indices (pan-immune inflammation value (PIV), systemic immune inflammation index (SII), and system inflammation response index (SIRI)) were analyzed.

Results: There were 935 (48.7%) patients had no LNM and 983 (51.3%) had LNM. There were statistically significant differences in the distributions of ABO blood groups (p=0.022) and molecular subtypes (p<0.001) between the two groups. PIV, SII, and SIRI levels in patients with LNM were significantly higher than those without LNM (all p<0.05). The proportions of LNM in patients with high PIV, SII, and SIRI levels were higher than those with low PIV, SII, and SIRI levels, respectively. Logistic regression analysis showed that non-O blood type (non-O blood type vs O blood type, odds ratio (OR): 1.327, 95% confidence interval (CI): 1.056-1.667, p=0.015), luminal B subtype (luminal B vs luminal A, OR: 2.939, 95% CI: 2.147-4.022, p<0.001), HER2+ subtype (HER2+ vs luminal A, OR: 2.044, 95% CI: 1.388-3.009, p<0.001), and high SIRI level (≥0.875 vs <0.875, OR: 1.572, 95% CI: 1.092-2.265, p=0.015) were independently associated with LNM.

Conclusion: Non-O blood type, luminal B and HER2+ subtypes, and high SIRI level (≥0.875) have potential role in predicting the status of LNM in breast cancer patients.

Objective: To explore the value of the systemic immune-inflammatory index (SII) and the systemic inflammatory response index (SIRI) in patients with severe hemorrhagic fever with renal syndrome (HFRS) upon admission.

Methods: This study included a total of 165 patients with HFRS, who were divided into mild and severe groups based on the severity of the disease. By reviewing medical records, we collected the white blood cell (WBC), SII, and SIRI values of patients upon admission. Univariate and multivariate logistics regression analyses were performed to identify risk factors for severe HFRS. The receiver operating characteristic (ROC) curve was applied to calculate the area under the ROC curve (AUC) to analyze the predictive value of SII and SIRI for severe HFRS, and the results were compared with WBC and SIRI.

Results: Compared with the mild HFRS group, patients in the severe HFRS group had a longer duration of illness (P < 0.05), higher levels of WBC, neutrophil (NEUT), lymphocyte (LYMP), monocyte (MONO), procalcitonin (PCT), SIRI, alanine transaminase (ALT), and creatinine (Scr) (P < 0.05), while lower levels of ALB, platelet (PLT), platelet-to-lymphocyte rate (PLR), and SII, with statistically significant differences (P < 0.05). Binary logistics regression analysis indicated that WBC (OR: 1.190, 95% CI: 1.032-1.371), SII (OR: 0.967, 95% CI: 0.951-0.984), and SIRI (OR: 4.743, 95% CI: 2.077-10.830) were risk factors for severe HFRS. The AUCs of WBC, SII, and SIRI for predicting severe HFRS were 0.765, 0.803, and 0.785, respectively.

Conclusion: Low levels of SII and high levels of WBC and SIRI upon admission are risk factors for severe HFRS and have certain value in predicting the progression of HFRS to severe cases, among which SII exhibits the best predictive value.

Purpose: Cathepsin V (CTSV) is a cysteine protease peptidase, which is typically upregulated in cancer and is associated with various oncogenic processes, such as angiogenesis, proliferation, apoptosis, and invasion. The study explored the role of CTSV in hepatocellular carcinoma (HCC) and its potential as a potential biomarker.

Patients and methods: This study collected tumor and peritumoral archived specimens from 180 HCC patients who underwent surgical resection at Zhongshan Hospital, Fudan University (Shanghai, China) between 2009 and 2010. We extracted data from the TCGA and GEO databases and conducted differential expression analysis, univariate Cox regression, and Kaplan-Meier analysis. Ultimately, we determined that CTSV may emerge as a potential biomarker. Then, immunohistochemical staining for CTSV was performed on tumors and adjacent tissues of HCC patients, and a Cox proportional hazards model was constructed to evaluate the prognostic significance of CTSV expression levels. Applied functional enrichment analysis to reveal the underlying molecular mechanisms. Utilized ssGSEA enrichment analysis and TIMER2.0 algorithm to explore the correlation between CTSV expression and immune cells in HCC. In vitro and in vivo experiments were conducted using human liver cancer cell lines to further validate the clinical application value of CTSV.

Results: In this study, we observed that CTSV expression was notably elevated in HCC (P < 0.001), and identified a significant association between elevated CTSV expression and reduced overall survival rates in patients. In vitro and in vivo experiments indicated that CTSV knockdown could significantly inhibit the proliferation, migration, and invasion of liver cancer cells, and it was found that the combination of CTSV knockdown with PD-1 inhibitors might enhance the therapeutic effect of PD-1 inhibitors in HCC.

Conclusion: CTSV serves as a standalone negative prognostic indicator and possesses clinical significance in HCC.

Introduction: Sepsis remains a significant global health challenge due to its high morbidity and mortality rates. Disseminated Intravascular Coagulopathy (DIC) represents a critical complication of sepsis, contributing to increased mortality and economic burden. Despite various prognostic scoring systems, there is a lack of a specific model for DIC prediction in sepsis patients.

Methods: This observational study included 336 sepsis patients. Clinical and laboratory data were collected, and prognoses were defined according to established criteria.

Results: We enrolled 336 patients, with 304 in the non-DIC group and 32 in the DIC group. Patients with DIC had notably lower platelet (PLT) and higher levels of prothrombin time (PT), lactate (LAC), and procalcitonin (PCT) compared to those without DIC. Univariate and multivariate analyses identified risk factors associated with the DIC, showing that PLT (OR = 0.985, 95% CI 0.978-0.993, p < 0.001), PT level (OR = 1.140, 95% CI 1.004-1.295, p = 0.044), and LAC (OR = 1.101, 95% CI 0.989-1.226, p = 0.078) were related factors. A risk model was established, and its sensitivity and specificity in predicting DIC among sepsis patients were assessed by comparing it to the SOFA score. The area under the ROC curve for the model was 0.850, while the SOFA score was 0.813. With a model score >-2.12, the sensitivity for predicting DIC was 84.4%, and the specificity was 75.0%.

Conclusion: Our study introduces a predictive model for DIC detection in sepsis patients, emphasizing the need for clinicians to focus on patients with high model scores for timely intervention.

Background: This study explores risk determinants for participants' lower extremities deep vein thrombosis (DVT) in the perioperative phase after spontaneous intracerebral hemorrhage (SICH), thereby informing more effective clinical prevention and treatment strategies.

Methods: During the period spanning October 2021 to March 2024, clinical data from 96 participants who received surgical treatment for spontaneous cerebral hemorrhage was analyzed in a retrospective study. Participants were classified into DVT and negative-DVT groups within the first week post-surgery. We used univariate logistic regression and multivariate logistic regression analyses to assess the impact of various clinical variables on DVT. A nomogram model was constructed to forecast the occurrence of early DVT following SICH surgery. The model's performance was assessed and validated using receiver operating characteristic (ROC) curves and bootstrap resampling.

Results: Among the 96 participants, 46 developed DVT. Significant differences were noted in age, D-dimer levels, fibrinogen degradation products, Caprini scores, and total surgical bleeding volume between the groups. Multivariate analysis revealed that Caprini score (the values of OR, 95% CI, and P are 1.962, 1.124-3.424, and 0.018, respectively) and total surgical bleeding volume (the values of OR, 95% CI, and P are 1.010, 1.002-1.018, and 0.017, respectively) were risk variables contributing to DVT occurrence. The area under the receiver operating characteristic curve was 0.918 (95% CI, 0.821-0.988). The calibration curve showed good prediction accuracy.

Conclusion: The Caprini score and total surgical bleeding volume are meaningful self-reliant risk variables contributing to DVT occurrence in postoperative participants with SICH. We have created a straightforward and efficient model to predict early DVT post-SICH surgery. This model serves as a valuable clinical tool for evaluating individual risk and enhancing decision-making processes.

Objective: To investigate the correlation between background factors and blood pressure variability (BPV), and the prognostic value of intra-dialytic BPV metrics for cardiovascular death and all-cause mortality in hemodialysis (HD) patients.

Methods: A retrospective study of 264 hD patients was followed up for 36 months. The intra-dialytic BP during the 3-month period for each patient was used to calculate BPV metrics, including standard deviation (SD), coefficient of variation (CV), average real variability (ARV), blood pressure change (ΔBP), and percent change in blood pressure (ΔBP/pre-BP). The primary outcomes were CVD death and all-cause mortality.

Results: Age, body mass index (BMI), predialysis blood pressure, inter-dialytic weight gain rate (IDWG%), α- blockers, and cholesterol levels were positively correlated with intra-dialytic BPV. Hemoglobin and albumin are negatively associated with intra-dialytic BPV. In Cox regression analysis, SBP-ARV, ΔSBP, and ΔSBP/pre-SBP were independent risk factors for CVD death (HR: 1.087, 95% CI: 1.001-1.181, p = 0.047; HR: 1.072, 95% CI: 1.016-1.131, p = 0.011; HR: 1.107, 95% CI: 1.011-1.211, p = 0.028). SBP-ARV showed the largest AUC of 0.593 (p = 0.022) in predicting all-cause death. SBP-ARV, ΔSBP, and ΔSBP/pre-SBP showed relatively large area (AUC = 0.631, 0.639, and 0.620; p = 0.007, 0.004, and 0.013 respectively) in predicting CVD death.

Conclusion: Age, BMI, IDWG%, predialysis blood pressure, albumin, hemoglobin, α- blockers, and total cholesterol were significantly correlated with intra-dialytic BPV. SBP-ARV, ΔSBP, and ΔSBP/pre-SBP were independent risk factors for CVD mortality, and there were no differences in prognostic value among various BPV metrics.