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Zhang X, Mao W, Ke L, Wu T, Xu M, Tan Y, Liu Y, Liu L, Li G, Zhou J, Zhang J, Ye B, Tong Z, Guo J, Li W. Visceral adipose tissue area predicts major adverse kidney events in patients with acute necrotizing pancreatitis. Am J Med Sci 2024:S0002-9629(24)01394-6. [PMID: 39127419 DOI: 10.1016/j.amjms.2024.08.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Revised: 07/23/2024] [Accepted: 08/02/2024] [Indexed: 08/12/2024]
Abstract
BACKGROUND Given the previously reported harmful effects of abdominal fat burden on kidney function, we aim to investigate the relationship between major adverse kidney events within 30 days (MAKE30) and abdominal obesity in acute necrotizing pancreatitis (ANP) patients and explore the underlying risk factors. METHODS A retrospective cohort study of all patients admitted within 72 h after the first episode of ANP to a tertiary center between June 2015 and June 2019 was conducted. Automatic image analysis software was used to calculate the area of subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT) and skeletal muscle from computed tomography scans at the umbilical level. The potential risk factors of MAKE30 were analyzed by logistic regression. RESULTS A total of 208 eligible ANP patients were enrolled, with an incidence of 23% for MAKE30. VAT area was more closely associated with the development of MAKE30, with an area under the ROC curve of 0.69 (cutoff value 200 cm2, 63.8% sensitivity and 66.7% specificity). Multivariate logistic regression analysis demonstrated that VAT area [OR 1.01 (1.01-1.02); p < 0.001] was an independent risk factor in predicting MAKE30. Patients with a VAT area > 200 cm2 had more requirements of renal replacement therapy (32% vs. 12%, P < 0.001), and a significantly higher incidence of other poor clinical outcomes (all p < 0.05). CONCLUSION Early assessment of the VAT area may help identify ANP patients at high risk of MAKE30, suggesting that it could be a potential indicator for adverse kidney events.
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Affiliation(s)
- Xihong Zhang
- Department of Gastroenterology, The Second Hospital of Shandong University, Jinan 250012, Shandong, China; Department of Critical Care Medicine, Liaocheng People's Hospital, Liaocheng 252000, Shandong, China; Department of Critical Care Medicine, Jinling Hospital, Medical School of Nanjing University, Nanjing 210002, Jiangsu, China
| | - Wenjian Mao
- Department of Critical Care Medicine, Jinling Hospital, Nanjing Medical University, Nanjing 210002, Jiangsu, China
| | - Lu Ke
- Department of Critical Care Medicine, Jinling Hospital, Medical School of Nanjing University, Nanjing 210002, Jiangsu, China
| | - Tiejun Wu
- Department of Critical Care Medicine, Liaocheng People's Hospital, Liaocheng 252000, Shandong, China
| | - Minyi Xu
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 210002, Jiangsu, China
| | - Yunze Tan
- Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing 210002, Jiangsu, China
| | - Yu Liu
- Department of Gastroenterology, Jinling Hospital, Medical School of Nanjing University, Nanjing 210002, Jiangsu, China; Department of Pharmacology, College of Pharmacy, Naval Medical University, Shanghai 200433, China
| | - Luyu Liu
- Department of Hepatopancreatobiliary Surgery, Chengdu Fifth People's Hospital, Chengdu 611130, Sichuan, China
| | - Gang Li
- Department of Critical Care Medicine, Jinling Hospital, Medical School of Nanjing University, Nanjing 210002, Jiangsu, China
| | - Jing Zhou
- Department of Critical Care Medicine, Jinling Hospital, Medical School of Nanjing University, Nanjing 210002, Jiangsu, China
| | - Jingzhu Zhang
- Department of Critical Care Medicine, Jinling Hospital, Medical School of Nanjing University, Nanjing 210002, Jiangsu, China
| | - Bo Ye
- Department of Critical Care Medicine, Jinling Hospital, Medical School of Nanjing University, Nanjing 210002, Jiangsu, China.
| | - Zhihui Tong
- Department of Critical Care Medicine, Jinling Hospital, Medical School of Nanjing University, Nanjing 210002, Jiangsu, China.
| | - Jianqiang Guo
- Department of Gastroenterology, The Second Hospital of Shandong University, Jinan 250012, Shandong, China.
| | - Weiqin Li
- Department of Critical Care Medicine, Jinling Hospital, Medical School of Nanjing University, Nanjing 210002, Jiangsu, China
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Maeda A, Inokuchi R, Bellomo R, Doi K. Heterogeneity in the definition of major adverse kidney events: a scoping review. Intensive Care Med 2024; 50:1049-1063. [PMID: 38801518 PMCID: PMC11245451 DOI: 10.1007/s00134-024-07480-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Accepted: 05/03/2024] [Indexed: 05/29/2024]
Abstract
Acute kidney injury (AKI) is associated with persistent renal dysfunction, the receipt of dialysis, dialysis dependence, and mortality. Accordingly, the concept of major adverse kidney events (MAKE) has been adopted as an endpoint for assessing the impact of AKI. However, applied criteria or observation periods for operationalizing MAKE appear to vary across studies. To evaluate this heterogeneity for MAKE evaluation, we performed a systematic scoping review of studies that employed MAKE as an AKI endpoint. Four major academic databases were searched, and we identified 122 studies with increasing numbers over time. We found marked heterogeneity in applied criteria and observation periods for MAKE across these studies, with some even lacking a description of criteria. Moreover, 13 different observation periods were employed, with 30 days and 90 days as the most common. Persistent renal dysfunction was evaluated by estimated glomerular filtration rate (34%) or serum creatinine concentration (48%); however, 37 different definitions for this component were employed in terms of parameters, cut-off criteria, and assessment periods. The definition for the dialysis component also showed significant heterogeneity regarding assessment periods and duration of dialysis requirement (chronic vs temporary). Finally, MAKE rates could vary by 7% [interquartile range: 1.7-16.7%] with different observation periods or by 36.4% with different dialysis component definitions. Our findings revealed marked heterogeneity in MAKE definitions, particularly regarding component assessment and observation periods. Dedicated discussion is needed to establish uniform and acceptable standards to operationalize MAKE in terms of selection and applied criteria of components, observation period, and reporting criteria for future trials on AKI and related conditions.
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Affiliation(s)
- Akinori Maeda
- Department of Intensive Care, Austin Hospital, Melbourne, VIC, Australia
- Department of Emergency and Critical Care Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan
| | - Ryota Inokuchi
- Department of Emergency and Critical Care Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan
- Department of Clinical Engineering, The University of Tokyo Hospital, Tokyo, Japan
| | - Rinaldo Bellomo
- Department of Intensive Care, Austin Hospital, Melbourne, VIC, Australia
- Data Analytics Research and Evaluation Centre, The University of Melbourne and Austin Hospital, Melbourne, VIC, Australia
- Department of Critical Care, The University of Melbourne, Melbourne, VIC, Australia
- Australian and New Zealand Intensive Care Research Centre, Monash University, Melbourne, VIC, Australia
- Department of Intensive Care, The Royal Melbourne Hospital, Melbourne, Australia
| | - Kent Doi
- Department of Emergency and Critical Care Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan.
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Yu X, Xin Q, Hao Y, Zhang J, Ma T. An early warning model for predicting major adverse kidney events within 30 days in sepsis patients. Front Med (Lausanne) 2024; 10:1327036. [PMID: 38469459 PMCID: PMC10925638 DOI: 10.3389/fmed.2023.1327036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Accepted: 12/18/2023] [Indexed: 03/13/2024] Open
Abstract
Background In sepsis patients, kidney damage is among the most dangerous complications, with a high mortality rate. In addition, major adverse kidney events within 30 days (MAKE30) served as a comprehensive and unbiased clinical outcome measure for sepsis patients due to the recent shift toward targeting patient-centered renal outcomes in clinical research. However, the underlying predictive model for the prediction of MAKE30 in sepsis patients has not been reported in any study. Methods A cohort of 2,849 sepsis patients from the Medical Information Mart for Intensive Care (MIMIC)-IV database was selected and subsequently allocated into a training set (n = 2,137, 75%) and a validation set (n = 712, 25%) through randomization. In addition, 142 sepsis patients from the Xi'An No. 3 Hospital as an external validation group. Univariate and multivariate logistic regression analyses were conducted to ascertain the independent predictors of MAKE30. Subsequently, a nomogram was developed utilizing these predictors, with an area under curve (AUC) above 0.6. The performance of nomogram was assessed through calibration curve, receiver operating characteristics (ROC) curve, and decision curve analysis (DCA). The secondary outcome was 30-day mortality, persistent renal dysfunction (PRD), and new renal replacement therapy (RRT). MAKE30 were a composite of death, PRD, new RRT. Results The construction of the nomogram was based on several independent predictors (AUC above 0.6), including age, respiratory rate (RR), PaO2, lactate, and blood urea nitrogen (BUN). The predictive model demonstrated satisfactory discrimination for MAKE30, with an AUC of 0.740, 0.753, and 0.821 in the training, internal validation, and external validation cohorts, respectively. Furthermore, the simple prediction model exhibited superior predictive value compared to the SOFA model in both the training (AUC = 0.710) and validation (AUC = 0.692) cohorts. The nomogram demonstrated satisfactory calibration and clinical utility as evidenced by the calibration curve and DCA. Additionally, the predictive model exhibited excellent accuracy in forecasting 30-day mortality (AUC = 0.737), PRD (AUC = 0.639), and new RRT (AUC = 0.846) within the training dataset. Additionally, the model displayed predictive power for 30-day mortality (AUC = 0.765), PRD (AUC = 0.667), and new RRT (AUC = 0.783) in the validation set. Conclusion The proposed nomogram holds the potential to estimate the risk of MAKE30 promptly and efficiently in sepsis patients within the initial 24 h of admission, thereby equipping healthcare professionals with valuable insights to facilitate personalized interventions.
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Affiliation(s)
- Xiaoyuan Yu
- Department of Hematology, The Affiliated Hospital of Northwest University, Xi’an No. 3 Hospital, Shaanxi, Xi’an, China
| | - Qi Xin
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Yun Hao
- Department of Nephrology, Yuequn Yuan District, The First Hospital of Jilin University, Changchun, Jilin, China
| | - Jin Zhang
- Department of Hematology, The Affiliated Hospital of Northwest University, Xi’an No. 3 Hospital, Shaanxi, Xi’an, China
| | - Tiantian Ma
- Department of Hematology, The Affiliated Hospital of Northwest University, Xi’an No. 3 Hospital, Shaanxi, Xi’an, China
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Deng Y, Jiang T, Li J, Yu P, Mei Y, Li M, Qi X, Liu F. Serum iron fluctuations link ferroptosis process with mortality and prognosis of acute pancreatitis. iScience 2023; 26:107774. [PMID: 37727733 PMCID: PMC10505981 DOI: 10.1016/j.isci.2023.107774] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 04/14/2023] [Accepted: 08/26/2023] [Indexed: 09/21/2023] Open
Abstract
Recently, the existence of ferroptosis has been confirmed in chronic pancreatitis. However, its role in acute pancreatitis (AP) process, especially in critical status, has not yet been mentioned. To verify this hypothesis, we included 873 AP patients (training set) and 1,188 NAFLD patients (internal validation set) selected from MIMIC-III (Medical Information Mark for Intensive Care) database and 218 AP patients (external validation set) in Linshui County People's Hospital ICU data. We analyzed the correlation between mortality and ferroptosis associating factors (such as serum iron, ALP, lactate, etc.) in them through regression analysis. In addition, to test the significance of these factors, the nomogram, AUC, and DCA analysis were applied. The results showed that serum iron, IBC, ALP, and lactate (p < 0.05) were independent factors for the mortality and prognosis of these patients. These correlations suggest ferroptosis and follow-up cell programmed death may own an important clinical interference significance among this population.
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Affiliation(s)
- Yueling Deng
- Health Management Center, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Tao Jiang
- Health Management Center, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Jinhao Li
- Department of Hepatobiliary Surgery, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Pingping Yu
- Health Management Center, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Ying Mei
- Health Management Center, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Maojun Li
- Linshui County People Hospital, Guangan, Sichuan, China
| | - Xiaoya Qi
- Health Management Center, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Fuyao Liu
- Department of Hepatobiliary Surgery, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Department of GI Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
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Xin Q, Xie T, Chen R, Wang H, Zhang X, Wang S, Liu C, Zhang J. Construction and validation of an early warning model for predicting the acute kidney injury in elderly patients with sepsis. Aging Clin Exp Res 2022; 34:2993-3004. [PMID: 36053443 DOI: 10.1007/s40520-022-02236-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 08/18/2022] [Indexed: 11/28/2022]
Abstract
BACKGROUND Sepsis-induced acute kidney injury (S-AKI) is a significant complication and is associated with an increased risk of mortality, especially in elderly patients with sepsis. However, there are no reliable and robust predictive models to identify high-risk patients likely to develop S-AKI. We aimed to develop a nomogram to predict S-AKI in elderly sepsis patients and help physicians make personalized management within 24 h of admission. METHODS A total of 849 elderly sepsis patients from the First Affiliated Hospital of Xi'an Jiaotong University were identified and randomly divided into a training set (75%, n = 637) and a validation set (25%, n = 212). Univariate and multivariate logistic regression analyses were performed to identify the independent predictors of S-AKI. The corresponding nomogram was constructed based on those predictors. The calibration curve, receiver operating characteristics (ROC)curve, and decision curve analysis were performed to evaluate the nomogram. The secondary outcome was 30-day mortality and major adverse kidney events within 30 days (MAKE30). MAKE30 were a composite of death, new renal replacement therapy (RRT), or persistent renal dysfunction (PRD). RESULTS The independent predictors for nomogram construction were mean arterial pressure (MAP), serum procalcitonin (PCT), and platelet (PLT), prothrombin time activity (PTA), albumin globulin ratio (AGR), and creatinine (Cr). The predictive model had satisfactory discrimination with an area under the curve (AUC) of 0.852-0.858 in the training and validation cohorts, respectively. The nomogram showed good calibration and clinical application according to the calibration curve and decision curve analysis. Furthermore, the prediction model had perfect predictive power for predicting 30-day mortality (AUC = 0.813) and MAKE30 (AUC = 0.823) in elderly sepsis patients. CONCLUSION The proposed nomogram can quickly and effectively predict S-AKI risk in elderly sepsis patients within 24 h after admission, providing information for clinicians to make personalized interventions.
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Affiliation(s)
- Qi Xin
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China
| | - Tonghui Xie
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China
| | - Rui Chen
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China
| | - Hai Wang
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China
| | - Xing Zhang
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China
| | - Shufeng Wang
- Department of General Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Xi'an, 710061, China.
| | - Chang Liu
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China. .,Department of SICU, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China.
| | - Jingyao Zhang
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China. .,Department of SICU, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China.
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Xin Q, Xie T, Chen R, Zhang X, Tong Y, Wang H, Wang S, Liu C, Zhang J. A Predictive Model Based on Inflammatory and Coagulation Indicators for Sepsis-Induced Acute Kidney Injury. J Inflamm Res 2022; 15:4561-4571. [PMID: 35979508 PMCID: PMC9377403 DOI: 10.2147/jir.s372246] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Accepted: 07/30/2022] [Indexed: 11/23/2022] Open
Abstract
Background Sepsis-induced acute kidney injury (S-AKI) is associated with systemic inflammatory responses and coagulation system dysfunction, and it is associated with an increased risk of mortality. However, there was no study to explore the predictive value of inflammatory and coagulation indicators for S-AKI. Methods In this retrospective study, 1051 sepsis patients were identified and divided into a training cohort (75%, n = 787) and a validation cohort (25%, n = 264) in chronological order according to the date they were admitted. Univariate analyses and multivariate logistic regression analyses were performed to identify the independent predictors of S-AKI. The logistic regression analyses (enter methods) were used to conducted the prediction models. The ROC curves were used to determine the predictive value of the constructed models on S-AKI. To test whether the increase in the AUC is significant, we used a two-sided test for ROC curves available online (http://vassarstats.net/roc_comp.html). The secondary outcome was different AKI stages and major adverse kidney events within 30 days (MAKE30). Stage 3B of S-AKI was defined as both meeting the stage 3 criteria [increase of Cr level by > 300% (≥ 4.0 mg/dL with an acute increase of ≥ 0.5 mg/dL) and/or UO < 0.3 mL/kg/h for > 24 h or anuria for > 12 h and/or acute kidney replacement therapy] and having cystatin C positive. MAKE30 were a composite of death, new renal replacement therapy (RRT), or persistent renal dysfunction (PRD). Results We discovered that cardiovascular disease, white blood cell (WBC), mean arterial pressure (MAP), platelet (PLT), serum procalcitonin (PCT), prothrombin time activity (PTA), and thrombin time (TT) were independent predictors for S-AKI. The predictive value (AUC = 0.855) of the simplest model 3 (constructed with PLT, PCT, and PTA), with a sensitivity of 77.6% and a specificity of 82.4%, had a similar predictive value comparing with the model 1 (AUC = 0.872) and the model 2 (AUC = 0.864) in the training cohort (P > 0.05). Compared with the model 1 (AUC = 0.888) and the model 2 (AUC = 0.887), the model 3 (AUC = 0.887) had a similar predictive value in the validation cohort. Moreover, model 3 had the best predictive power for predicting S-AKI in the stage 3 (AUC = 0.777), especially in stage 3B (AUC = 0.771). Finally, the model 3 (AUC = 0.843) had perfect predictive power for predicting MAKE30 in sepsis patients. Conclusion Within 24 hours after admission, the simplest model 3 (constructed with PLT, PCT, and PTA) might be a robust predictor of the S-AKI in sepsis patients, providing information for timely and efficient intervention.
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Affiliation(s)
- Qi Xin
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, People's Republic of China
| | - Tonghui Xie
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, People's Republic of China
| | - Rui Chen
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, People's Republic of China
| | - Xing Zhang
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, People's Republic of China
| | - Yingmu Tong
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, People's Republic of China
| | - Hai Wang
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, People's Republic of China
| | - Shufeng Wang
- Department of General Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, People's Republic of China
| | - Chang Liu
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, People's Republic of China.,Department of SICU, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, People's Republic of China
| | - Jingyao Zhang
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, People's Republic of China.,Department of SICU, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, People's Republic of China
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Xin Q, Xie T, Chen R, Wang H, Zhang X, Wang S, Liu C, Zhang J. Predictive nomogram model for major adverse kidney events within 30 days in sepsis patients with type 2 diabetes mellitus. Front Endocrinol (Lausanne) 2022; 13:1024500. [PMID: 36589822 PMCID: PMC9800518 DOI: 10.3389/fendo.2022.1024500] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Accepted: 12/06/2022] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND In sepsis patients, Type 2 Diabetes Mellitus (T2DM) was associated with an increased risk of kidney injury. Furthermore, kidney damage is among the dangerous complications, with a high mortality rate in sepsis patients. However, the underlying predictive model on the prediction of major adverse kidney events within 30 days (MAKE30) in sepsis patients with T2DM has not been reported by any study. METHODS A total of 406 sepsis patients with T2DM were retrospectively enrolled and divided into a non-MAKE30 group (261 cases) and a MAKE30 group (145 cases). In sepsis patients with T2DM, univariate and multivariate logistic regression analyses were conducted to identify independent predictors of MAKE30. Based on the findings of multivariate logistic regression analysis, the corresponding nomogram was constructed. The nomogram was evaluated using the calibration curve, Receiver Operating Characteristic (ROC) curve, and decision curve analysis. A composite of death, new Renal Replacement Therapy (RRT), or Persistent Renal Dysfunction (PRD) comprised MAKE30. Finally, subgroup analyses of the nomogram for 30-day mortality, new RRT, and PRD were performed. RESULTS In sepsis patients with T2DM, Mean Arterial Pressure (MAP), Platelet (PLT), cystatin C, High-Density Lipoprotein (HDL), and apolipoprotein E (apoE) were independent predictors for MAKE30. According to the ROC curve, calibration curve, and decision curve analysis, the nomogram model based on those predictors had satisfactory discrimination (AUC = 0.916), good calibration, and clinical application. Additionally, in sepsis patients with T2DM, the nomogram model exhibited a high ability to predict the occurrence of 30-day mortality (AUC = 0.822), new RRT (AUC = 0.874), and PRD (AUC = 0.801). CONCLUSION The nomogram model, which is available within 24 hours after admission, had a robust and accurate assessment for the MAKE30 occurrence, and it provided information to better manage sepsis patients with T2DM.
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Affiliation(s)
- Qi Xin
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Tonghui Xie
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Rui Chen
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Hai Wang
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Xing Zhang
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Shufeng Wang
- Department of General Surgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China
- *Correspondence: Shufeng Wang, ; Chang Liu, ; Jingyao Zhang,
| | - Chang Liu
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China
- Department of Surgical Intensive Care Unit, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China
- *Correspondence: Shufeng Wang, ; Chang Liu, ; Jingyao Zhang,
| | - Jingyao Zhang
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China
- Department of Surgical Intensive Care Unit, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China
- *Correspondence: Shufeng Wang, ; Chang Liu, ; Jingyao Zhang,
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