Construction and validation of a prediction model for the risk of citrate accumulation in patients with hepatic insufficiency receiving continuous renal replacement therapy with citrate anticoagulation.

BACKGROUND: To construct and validate a prediction model of the risk of citrate accumulation in patients with hepatic dysfunction receiving continuous renal replacement therapy with regional citrate anticoagulation (RCA-CRRT), which reduces the risk of citrate accumulation. METHODS: All patients who received RCA-CRRT from 2021 to 2022 and were hospitalized in the First Affiliated Hospital of Zhejiang University were considered for study participation. Logistic regression analysis was used to identify the risk factors for citrate accumulation, based on which a nomogram model was constructed and validated in the validation group. RESULTS: Six factors were finally identified, from which a nomogram was created to predict the risk of citrate accumulation. The area under the curve of the prediction model was 0.814 in the training group and 0.819 in the validation group, and the model showed acceptable agreement between the actual and predicted probabilities. Decision curve analysis also demonstrated that the model was clinically useful. CONCLUSIONS: The model constructed from six factors reliably predicted the risk of citrate accumulation in patients with hepatic insufficiency who received RCA-CRRT.

Fate mapping RNA-sequencing reveal Malat1 regulates Sca1+ progenitor cells to vascular smooth muscle cells transition in vascular remodeling.

Regeneration of smooth muscle cells (SMCs) is vital in vascular remodeling. Sca1+ stem/progenitor cells (SPCs) can generate de novo smooth muscle cells after severe vascular injury during vessel repair and regeneration. However, the underlying mechanisms have not been conclusively determined. Here, we reported that lncRNA Metastasis-associated lung adenocarcinoma transcript 1 (Malat1) was down-regulated in various vascular diseases including arteriovenous fistula, artery injury and atherosclerosis. Using genetic lineage tracing mice and veingraft mice surgery model, we found that suppression of lncRNA Malat1 promoted Sca1+ cells to differentiate into SMCs in vivo, resulting in excess SMC accumulation in neointima and vessel stenosis. Genetic ablation of Sca1+ cells attenuated venous arterialization and impaired vascular structure normalization, and thus, resulting in less Malat1 down-regulation. Single cell sequencing further revealed a fibroblast-like phenotype of Sca1+ SPCs-derived SMCs. Protein array sequencing and in vitro assays revealed that SMC regeneration from Sca1+ SPCs was regulated by Malat1 through miR125a-5p/Stat3 signaling pathway. These findings delineate the critical role of Sca1+ SPCs in vascular remodeling and reveal that lncRNA Malat1 is a key regulator and might serve as a novel biomarker or potential therapeutic target for vascular diseases.

A severe complication of J-tip guide wire during catheterization: A case report and discussion.

J-tip guide wire entrapment within the heart is a serious and dangerous complication that is rarely mentioned. We present a case in which the J-tip guide wire was entrapped in the right atrium during tunneled cuffed venous catheterization. We were unable to remove the guide wire using previously reported methods and concluded with surgery. Owing to the special structure of the guide wire itself, a safe removal process needs to be discussed. Patient consent for publication was obtained prior to the submission of the manuscript.

Analysis of the dynamic relationship between immune profiles and the clinical features of patients with COVID-19.

BACKGROUND: The novel coronavirus disease (COVID-19) has been declared a global pandemic, with the cumulative number of confirmed cases and deaths exceeding 150 million and 3 million, respectively. Here, we examined the dynamic changes in the immune and clinical features of patients with COVID-19. METHODS: Clinical data of 98 patients with confirmed COVID-19 diagnosis were acquired from electronic medical records and curated. The data were analyzed based on the stage of the admission, deterioration, and convalescence, which included age, sex, severity, disease stages, biochemical indicators, immune cells, inflammatory cytokines, and immunoglobulins. Additionally, temporal changes in the immune response in patients undergoing continuous renal replacement therapy (CRRT) were also examined. RESULTS: Compared to mild stage patients, severe stage patients with COVID-19 exhibited a significant reduction in lymphocyte [23.10 (17.58-33.55) vs. 4.80 (2.95-6.50), P<0.001], monocyte [8.65 (7.28-10.00) vs. 3.45 (2.53-4.58), P<0.001], and NK cell levels [244.00 (150.50-335.00) vs. 59.00 (40.00-101.00), P<0.001] but showed elevated levels of neutrophils [64.90 (56.30-73.70) vs. 90.95 (87.60-93.68), P<0.001], inflammatory cytokines [Interleukin-10, 3.05 (1.37-3.86) vs. 5.94 (3.84-8.35), P=0.001; and tumor necrosis factor-α, 11.50 (6.55-26.45) vs. 12.96 (12.22-36.80), P=0.029], which improved during convalescence. Besides, the number of immune cells-T lymphocytes, B lymphocytes, helper T cells, suppressor T cells, NK cells, and monocytes, except neutrophils-slowly increased in critically ill patients receiving CRRT from 0 to 3 weeks. CONCLUSIONS: Our results indicate that the surveillance of immune cells may contribute to monitoring COVID-19 disease progression, and CRRT is a potential therapeutic strategy to regulate the immune balance in critically ill patients.

Prognostic Machine Learning Models for First-Year Mortality in Incident Hemodialysis Patients: Development and Validation Study.

BACKGROUND: The first-year survival rate among patients undergoing hemodialysis remains poor. Current mortality risk scores for patients undergoing hemodialysis employ regression techniques and have limited applicability and robustness. OBJECTIVE: We aimed to develop a machine learning model utilizing clinical factors to predict first-year mortality in patients undergoing hemodialysis that could assist physicians in classifying high-risk patients. METHODS: Training and testing cohorts consisted of 5351 patients from a single center and 5828 patients from 97 renal centers undergoing hemodialysis (incident only). The outcome was all-cause mortality during the first year of dialysis. Extreme gradient boosting was used for algorithm training and validation. Two models were established based on the data obtained at dialysis initiation (model 1) and data 0-3 months after dialysis initiation (model 2), and 10-fold cross-validation was applied to each model. The area under the curve (AUC), sensitivity (recall), specificity, precision, balanced accuracy, and F1 score were used to assess the predictive ability of the models. RESULTS: In the training and testing cohorts, 585 (10.93%) and 764 (13.11%) patients, respectively, died during the first-year follow-up. Of 42 candidate features, the 15 most important features were selected. The performance of model 1 (AUC 0.83, 95% CI 0.78-0.84) was similar to that of model 2 (AUC 0.85, 95% CI 0.81-0.86). CONCLUSIONS: We developed and validated 2 machine learning models to predict first-year mortality in patients undergoing hemodialysis. Both models could be used to stratify high-risk patients at the early stages of dialysis.

Long-term renal and overall survival of critically ill patients with acute renal injury who received continuous renal replacement therapy.

BACKGROUND: Acute kidney injury (AKI) is associated with the increased short-term mortality of critically ill patients on continuous renal replacement therapy (CRRT). The aim of this research was to evaluate the association of kidney function at discharge with the long-term renal and overall survival of critically ill patients with AKI who were on CRRT in an intensive care unit (ICU). METHODS: We retrospectively collected data for critically ill patients with AKI who were admitted to ICU on CRRT at a tertiary metropolitan hospital in China between 2008 and 2013. The patients were followed up to their death or to 30 September 2016 by telephone. RESULTS: A total of 403 patients were enrolled in this study. The 1-, 3- and 5-year patient survival rates were 64.3 ± 2.4, 55.8 ± 2.5 and 46.3 ± 2.7%, respectively. In multivariate analysis, age, sepsis, decreased renal perfusion (including volume contraction, congestive heart failure, hypotension and cardiac arrest), preexisting kidney disease, Apache II score, Saps II score, vasopressors and eGFR <45 mL/min/1.73 m2 at discharge were independent factors for worse long-term patient survival. And age, preexisting kidney disease, Apache II score, mechanical ventilation (MV) and eGFR <45 mL/min/1.73 m2 at discharge were also associated with worse renal survival. CONCLUSIONS: This study showed that impaired kidney function at discharge was shown to be an important risk factor affecting the long-term renal survival rates of critically ill patients with AKI. An eGFR <45 mL/min/1.73 m2 was an independent risk factor for decreased overall survival and renal survival.

Knockdown of tumor protein D52-like 2 induces cell growth inhibition and apoptosis in oral squamous cell carcinoma.

Tumor protein D52-like 2 (TPD52L2) and its family members form homo- and hetero-meric complexes essential for cell proliferation in multiple human cancers. TPD52L2 is involved in cell migration and attachment in oral squamous cell carcinoma (OSCC). To confirm the role of TPD52L2 in OSCC, we employed the lentivirus-delivered small interfering RNA (siRNA) technique to knock down TPD52L2 expression in two OSCC cell lines, CAL27, and KB. Knockdown of TPD52L2 by RNA interference markedly suppressed cell proliferation and colony formation. Cell cycle analysis showed that depletion of TPD52L2 led to CAL27 cells arrest in the S phase. We found an excessive accumulation of cells in the sub-G1 phase, which can represent apoptotic cells. TPD52L2 silencing also induced the cleavage of PARP. These results suggest that TPD52L2 is involved in OSCC cell growth and serves as a potential therapeutic target in human OSCC.

[Effects of hemoperfusion on the patients with acute toxication of 2, 4-dinitrophenol].

OBJECTIVE: To explore the management strategies of acute toxication of 2, 4-dinitrophenol by hemoperfusion. METHODS: A total of 14 patients with acute toxication of 2, 4-dinitrophenol were admitted on September 14, 2009. And they were divided into severe and mild groups according to the severity of clinical manifestation. All patients in both groups received 2-hour blood perfusion within 2 hour post-admission. Their clinical manifestations, laboratory parameters and 2, 4-dinitrophenol levels were carefully observed before and after each perfusion. And oxygenation, intravenous use of furosemide, corticosteroids and symptomatic therapies were simultaneously given to improve general conditions. RESULTS: In serious group, the levels of before and after the first perfusion were 28.21(15.56-45.23) and 16.11(10.10-27.52) mg/L (P < 0.05), respectively. In both groups, all levels of 2, 4-dinitrophenol were significantly reduced before and after each perfusion (all P < 0.05). The patients in severe group would get relieved after 3 vs 2 perfusions in mild group. In severe group, there was a remarked decrease in neutrophil and platelet count after perfusion than those in mild group. The liver enzymes and blood lipids in both groups after therapy significantly elevated than those before therapy (all P < 0.05). CONCLUSION: Crucial for managing acute toxication of 2, 4-dinitrophenol, early hemoperfusion reduces mortality.