Predicting persistent organ failure on admission in patients with acute pancreatitis: development and validation of a mobile nomogram

BackgroundEarly prediction of persistent organ failure (POF) is important for triage and timely treatment of patients with acute pancreatitis (AP).MethodsAll AP patients were consecutively admitted within 48 h of symptom onset. A nomogram was developed to predict POF on admission using data from a retrospective training cohort, validated by two prospective cohorts. The clinical utility of the nomogram was defined by concordance index (C-index), decision curve analysis (DCA), and clinical impact curve (CIC), while the performance by post-test probability.ResultsThere were 816, 398, and 880 patients in the training, internal and external validation cohorts, respectively. Six independent predictors determined by logistic regression analysis were age, respiratory rate, albumin, lactate dehydrogenase, oxygen support, and pleural effusion and were included in the nomogram (web-based calculator: https://shina.shinyapps.io/DynNomapp/). This nomogram had reasonable predictive ability (C-indexes 0.88/0.91/0.81 for each cohort) and promising clinical utility (DCA and CIC). The nomogram had a positive likelihood ratio and post-test probability of developing POF in the training, internal and external validation cohorts of 4.26/31.7%, 7.89/39.1%, and 2.75/41%, respectively, superior or equal to other prognostic scores.ConclusionsThis nomogram can predict POF of AP patients and should be considered for clinical practice and trial allocation.     

Prediction of early recurrence of hepatocellular carcinoma after liver transplantation based on computed tomography radiomics nomogram

BackgroundEarly recurrence results in poor prognosis of patients with hepatocellular carcinoma (HCC) after liver transplantation (LT). This study aimed to explore the value of computed tomography (CT)-based radiomics nomogram in predicting early recurrence of patients with HCC after LT.MethodsA cohort of 151 patients with HCC who underwent LT between December 2013 and July 2019 were retrospectively enrolled. A total of 1218 features were extracted from enhanced CT images. The least absolute shrinkage and selection operator algorithm (LASSO) logistic regression was used for dimension reduction and radiomics signature building. The clinical model was constructed after the analysis of clinical factors, and the nomogram was constructed by introducing the radiomics signature into the clinical model. The predictive performance and clinical usefulness of the three models were evaluated using receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA), respectively. Calibration curves were plotted to assess the calibration of the nomogram.ResultsThere were significant differences in radiomics signature among early recurrence patients and non-early recurrence patients in the training cohort (P < 0.001) and validation cohort (P < 0.001). The nomogram showed the best predictive performance, with the largest area under the ROC curve in the training (0.882) and validation (0.917) cohorts. Hosmer-Lemeshow testing confirmed that the nomogram showed good calibration in the training (P = 0.138) and validation (P = 0.396) cohorts. DCA showed if the threshold probability is within 0.06-1, the nomogram had better clinical usefulness than the clinical model.ConclusionsOur CT-based radiomics nomogram can preoperatively predict the risk of early recurrence in patients with HCC after LT.     

Construction and validation of a nomogram for HBV-related hepatocellular carcinoma: A large,multicenter study

Introduction and ObjectivesWe initiated this multicenter study to integrate important risk factors to create a nomogram for hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) for clinician decision-making.Patients and MethodsBetween April 2011 and March 2022, 2281 HCC patients with an HBV-related diagnosis were included. All patients were randomly divided into two groups in a ratio of 7:3 (training cohort, n = 1597; validation cohort, n = 684). The nomogram was built in the training cohort via Cox regression model and validated in the validation cohort.ResultsMultivariate Cox analyses revealed that the portal vein tumor thrombus, Child–Pugh class, tumor diameter, alanine aminotransferase level, tumor number, extrahepatic metastases, and therapy were independent predictive variables impacting overall survival. We constructed a new nomogram to predict 1-, 2-, and 3-year survival rates based on these factors. The nomogram-related receiver operating characteristics (ROC) curves indicated that the area under the curve (AUC) values were 0.809, 0.806, and 0.764 in predicting 1-, 2-, and 3-year survival rates, respectively. Furthermore, the calibration curves revealed good agreement between real measurements and nomogram predictions. The decision curve analyses (DCA) curves demonstrated excellent therapeutic application potential. In addition, stratified by risk scores, low-risk groups had longer median OS than medium–high-risk groups (p < 0.001).ConclusionsThe nomogram we constructed showed good performance in predicting the 1-year survival rate for HBV- related HCC.     

Nomogram for predicting the overall survival of the patients with oesophageal signet ring cell carcinoma

BackgroundThe purpose of this study was to explore the prognostic factors of oesophageal signet ring cell (SRC) carcinoma and to construct a nomogram for predicting the outcome of SRC carcinoma of oesophagus.MethodsA total of 968 cases of oesophageal SRC carcinoma were extracted from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2016. Cases were divided into training cohort and validation cohort. Univariate and multivariable Cox analyses was performed to select the predictors of overall survival (OS for the nomogram. The performance of nomogram was validated with Harrell’s concordance index (C-index), calibration curves and decision curve analysis (DCA).ResultsThe 1- and 5-year OS in the training cohort were 0.446 and 0.146, respectively, and the 1- and 5-year OS in the validation cohort were 0.459 and 0.138. The independent prognostic factors for establishing the nomogram were marital status, invasion of the surrounding tissue, lymph node metastasis, distant metastasis, surgery and chemotherapy. The Harrell’s c-index value of the training cohort and validation cohort were 0.723 and 0.708. In the calibration curves, the predicted survival probability and the actual survival probability have a considerable consistency. DCA indicated the favourable potential clinical utility of the nomogram.ConclusionsA nomogram to predict the OS of patients with oesophageal SRC carcinoma was established. The validation of the nomogram fully demonstrates its great performance.     

Development and validation of a nomogram for arterial stiffness

Even though as a gold standard for noninvasive measurement of arterial stiffness, carotid-femoral pulse wave velocity (cfPWV) is not widely used in primary healthcare institutions due to time-consuming and unavailable equipment. The aim of this study was to develop a convenient and low-cost nomogram model for arterial stiffness screening. A cross-sectional study was undertaken in the department of general practice, the First Affiliated Hospital of Fujian Medical University. Arterial stiffness was defined as cfPWV ≥ 10 m/s. A total of 2717 participants were recruited to construct the nomogram using the least absolute shrinkage and selection operator and logistic regressions. Receiver operating characteristic (ROC) curve, calibration curve, decision curve analysis, clinical impact curve were used to evaluate the performance of the model. The model was validated internally and externally (399 participants) by bootstrap method. Arterial stiffness was identified in 913 participants (33.60%). Age, sex, waist to hip ratio, systolic blood pressure, duration of diabetes, heart rate were selected to construct the nomogram model. Good discrimination and accuracy were exhibited with area under curve of 0.820 (95% CI 0.803–0.837) in ROC curve and mean absolute error = 0.005 in calibration curve. A positive net benefit was shown in decision curve analysis and clinical impact curve. A satisfactory agreement was displayed in internal validation and external validation. The low cost and user-friendly nomogram is suitable for arterial stiffness screening in primary healthcare institutions.     

Development and validation of nomogram to predict lymph node metastasis preoperatively in patients with pancreatic neuroendocrine tumor

BackgroundRoutine lymphadenectomy in pancreatic neuroendocrine tumors (pNETs) is debated. There lacks accurate model to predict lymph node metastasis (LNM) preoperatively in pNETs. Therefore, this study aimed at developing a nomogram in predicting LNM in pNETs preoperatively.MethodsPatients undergoing surgery from Surveillance, Epidemiology, and End Results (SEER) database (design cohort, n = 2742) and First Affiliated Hospital of Sun Yat-sen University (validation cohort, n = 136) were enrolled. Nomogram was developed based on risk factors determined by logistic regression analyses. The performance of nomogram was evaluated by area under receiver operating characteristics curve (AUC), calibration curve, and decision curve analysis.ResultsIn design cohort, 915 of 2742 patients had LNM. Tumor in the pancreatic head, T stage, and tumor size were significantly associated with LNM (all p < 0.05). Prediction of nomogram was accurate with AUC of 0.776 in design cohort and 0.622 in validation cohort. The nomogram showed good agreement between prediction and observation in the design and validation cohort. Based on nomogram-predicted risk, patients with higher risk of LNM had worse overall survival over patients with lower risk of LNM (log-rank p < 0.001).ConclusionsThe novel nomogram could accurately predict LNM in pNET preoperatively. For patients with high risk of LNM, lymphadenectomy was recommended.     

Nomogram predicting cancer-specific survival in elderly patients with stages I–III colon cancer

Abstract

Aim: This study aims to establish and validate an effective nomogram to predict cancer-specific survival (CSS) in elderly patients with stages I–III colon cancer.

Methods: The data of elderly colon cancer patients with stages I–III were enrolled from the Surveillance, Epidemiology, and End Results database (SEER) between 2010 and 2015. The eligible patients were randomly divided into a training cohort and a validation cohort (ratio 1:1). All predictors of cancer-specific survival were determined by Cox regression. The concordance index (C-index) and calibration curves were used for validation of nomograms. Decision curve analysis (DCA) was performed to evaluate the clinical net benefit of the nomogram.

Results: Cox hazard analysis in the training cohort indicated that grade, tumor stage, node stage, colectomy, and CEA were independent predictors of CSS. Nomogram was constructed based on these predictors. The C-index of nomograms for CSS was 0.728 (95%CI: 0.7133–0.7427), and were superior to that of AJCC TNM Stage (C-index: 0.625, 95%CI: 0.6093–0.6406). The calibration curves showed satisfactory consistency between actual observation and nomogram-predicted CSS probabilities. The validation cohort demonstrated similar results. The DCA showed high net benefit of nomogram in a clinical context. The population was divided into three groups based on the scores of the nomogram, and the survival analysis showed that this prognostic stratification was statistically significant (p?<?0.01).

Conclusion: The nomograms showed significant accuracy in predicting 1-, 3-, and 5-year CSS in elderly patients with stages I–III colon cancer and may be helpful inpatient counseling clinical decision guidance.     

Development and Validation of a Prognostic Model for One-year Survival of Cirrhosis Patients with First-ever Spontaneous Bacterial Peritonitis

Background and AimsSpontaneous bacterial peritonitis (SBP) is one of the leading causes of death in patients with liver cirrhosis. We aimed to establish a prognostic model to evaluate the 1-year survival of cirrhosis patients after the first episode of SBP.MethodsA prognostic model was developed based on a retrospective derivation cohort of 309 cirrhosis patients with first-ever SBP and was validated in a separate validation cohort of 141 patients. We used Uno’s concordance, calibration curve, and decision curve (DCA) analysis to evaluate the discrimination, calibration, and clinical net benefit of the model.ResultsA total of 59 (19.1%) patients in the derivation cohort and 42 (29.8%) patients in the validation cohort died over the course of 1 year. A prognostic model in nomogram form was developed with predictors including age [hazard ratio (HR): 1.25; 95% confidence interval (CI): 0.92–1.71], total serum bilirubin (HR: 1.66; 95% CI: 1.28–2.14), serum sodium (HR: 0.94; 95% CI: 0.90–0.98), history of hypertension (HR: 2.52; 95% CI: 1.44–4.41) and hepatic encephalopathy (HR: 2.06; 95% CI: 1.13–3.73). The nomogram had a higher concordance (0.79) compared with the model end-stage liver disease (0.67) or Child-Turcotte-Pugh (0.71) score. The nomogram also showed acceptable calibration (calibration slope, 1.12; Bier score, 0.15±0.21) and optimal clinical net benefit in the validation cohort.ConclusionsThis prediction model developed based on characteristics of first-ever SBP patients may benefit the prediction of patients’ 1-year survival.     

A nomogram for predicting overall survival rate in patients with brain metastatic non-small cell lung cancer

The purpose was to develop a nomogram for the prediction of the 1- and 2-year overall survival (OS) rates in patients with brain metastatic non-small cell lung cancer (BMNSCLC).Patients were collected from the Surveillance Epidemiology and End Results program (SEER) and classified into the training and validation groups. Several independent prognostic factors identified by statistical methods were incorporated to establish a predictive nomogram. The concordance index (C-index), the area under the receiver operating characteristics curve (AUC), and calibration curve were applied to estimate predictive ability of the nomogram. To compare the clinical practicability of the nomogram and TNM staging system by decision curve analysis (DCA).A total of 24,164 eligible patients were collected and assigned into the training (n = 16,916) and validation groups (n = 7248). Based on the prognostic factors, we developed a nomogram with good discriminative ability. The C-indices for training and validation group were 0.727 and 0.728. The AUCs of 1- and 2-year OS rates were both 0.8, and the calibration curves also demonstrated good performance of the nomogram. DCA illustrated that the nomogram provided clinical net benefit compared with the TNM staging system.We developed a predictive nomogram for more accurate and comprehensive prediction of OS in BMNSCLC patients, which can be a useful and convenient tool for clinicians to make proper clinical decisions, and adjust follow-up management strategies.     

An association between the sarcolemmal membrane-associated protein gene and microvascular endothelial diabetic retinopathy in patients with type 2 diabetes mellitus: A preliminary case control study

Background and aimsDiabetic retinopathy (DR) is one of the most common microvascular diabetic complications. Sarcolemmal membrane-associated protein (SLMAP) has been implicated in playing a role in microvascular endothelial dysfunction. This study aimed to assess the significance of SLMAP rs17058639C > T gene polymorphism among patients with type 2 diabetes mellitus (T2DM) and its relevance to microvascular endothelial diabetic retinopathy.MethodsWe conducted this case-control study on 100 individuals divided into 60 participants with T2DM and 40 healthy controls. Patients with T2D were stratified into two groups: 40 patients with DR and 20 patients with diabetic non-retinopathy (DNR). Patients with T2DM were compared with age- and sex-matched healthy controls. Fundus examinations were conducted to detect microvascular endothelial changes. The polymorphism of SLMAP rs17058639C > T gene was identified by real-time polymerase chain reaction (RT-PCR) TaqMan allelic discrimination.ResultsPatients with DR have significantly increased glycated hemoglobin (HbA1c) compared to patients with DNR (P < 0.001). There was no statistically significant difference found between diabetic and control groups regarding the frequency of SLMAP rs17058639C > T genotypes. The homozygous CC genotype was the most common variant among patients with DR; however, the results did not reach statistical significance.ConclusionsDiabetic retinopathy is correlated with poor glycemic control, and SLMAP rs17058639C > T polymorphism was associated with microvascular endothelial DR in patients with T2DM, although further studies with a large sample size are needed to confirm our findings.     

Develop and validate a novel online AIHI-nomogram to predict severe liver inflammation in patients with autoimmune hepatitis

Introduction and ObjectivesAssessment of liver inflammation plays a vital role in the management of patients with autoimmune hepatitis (AIH). We aimed to establish and validate a nomogram to predict severe liver inflammation in AIH patients.Patients and MethodsAIH patients who underwent liver biopsy were included and randomly divided into a training set and a validation set. Independent predictors of severe liver inflammation were selected by the least absolute shrinkage and selection operator regression from the training set and used to conduct a nomogram. Receiver characteristic curves (ROC), calibration curves, and decision curve analysis (DCA) were adopted to evaluate the performance of nomogram.ResultsOf the 213 patients, female patients accounted for 83.1% and the median age was 53.0 years. The albumin, gamma-glutamyl transpeptidase, total bilirubin, red cell distribution width, prothrombin time, and platelets were independent predictors of severe inflammation. An online AIHI-nomogram was established and was available at https://ndth-zzy.shinyapps.io/AIHI-nomogram/. The calibration curve revealed that the AIHI-nomogram had a good agreement with actual observation in the training and validation sets. The area under the ROCs of AIHI-nomogram were 0.795 in the training set and 0.759 in the validation set, showing significantly better performance than alanine aminotransferase and immunoglobulin G in the training and validation sets, as well in AIH patients with normal ALT in the training set. DCA indicated that the AIHI-nomogram was clinically useful.ConclusionsThis novel AIHI-nomogram provided an excellent prediction of severe liver inflammation in AIH patients and could be used for the better management of AIH.     

A nomogram-based model to predict postoperative transient neurological dysfunctions in patients receiving acute type A aortic dissection surgery

The purposes of this study were to develop and validate a nomogram for predicting postoperative transient neurological dysfunctions (TND) in patients with acute type A aortic dissection (AAAD) who underwent modified triple-branched stent graft implantation. This retrospective study developed a nomogram-based model in a consecutive cohort of 146 patients. Patient characteristics, preoperative clinical indices, and operative data were analyzed. Univariate and multivariable analyses were applied to identify the most useful predictive variables for constructing the nomogram. Discrimination and the calibration of the model was evaluated through the receiver operating characteristic curve (ROC), the Hosmer–Lemeshow goodness-of-fit test and the decision curve analysis (DCA). At the same time, to identify and compare long-term cumulative survival rate, Kaplan-Meier survival curve was plotted. The incidence rate of postoperative TND observed in our cohort were 40.9%. Supra-aortic dissection with or without thrombosis, creatinine >115 μmol and albumin <39.7 g/L, selective antegrade cerebral perfusion (SACP) time >7 min and total operation time >303 min, were confirmed as independent predictors that enhanced the likelihood of TND. Internal validation showed good discrimination of the model with under the ROC curve (AUC) of 0.818 and good calibration (Hosmer–Lemeshow test, p > .05). DCA revealed that the nomogram was clinically useful. In the long-term survival there was no significant difference between patients with or without TND history. The results showed the predict model based on readily available predictors has sufficient validity to identify TND risk in this population, that maybe useful for clinical decision-making.     

Serum fibroblast growth factor 21 concentrations in type 2 diabetic retinopathy patients

Aims/purposeFibroblast growth factor 21 (FGF21) is a major metabolic regulator in the body that has been shown to be elevated in a number of metabolic disturbances including type 2 diabetes mellitus (T2DM) and the metabolic syndrome. However, little is known regarding the circulating levels of FGF21 in type 2 diabetic retinopathy (T2DR) and its association with the severity of the condition.MethodsIn a cross-sectional setting, 142 individuals, consisting of (1) T2DM patients without T2DR, (2) T2DM patients with T2DR, and (3) healthy control subjects were recruited for this study. Various clinical and biochemical parameters were assessed and entered for analysis.ResultsSerum FGF21 levels were significantly elevated in T2DM subjects without retinopathy (103.50 [75.75] pg/mL) compared with healthy controls (99.00 [126.75] pg/mL). Circulating FGF21 levels were comparable across different stages of T2DR (233.00 [109.00] for nonproliferative type 2 diabetic retinopathy [NPT2DR] vs. 215.00 [122.00] for proliferative type 2 diabetic retinopathy [PT2DR] groups, P = 361). FGF21, triglycerides, and duration of diabetes mellitus were significantly associated with T2DM in baseline models. However, after adjustment for potential confounders, in the final multivariate model, FGF21 emerged as the only significant factor associated with T2DM (OR = 13.772, 95% CI = 3.062–61.948, P = 001).ConclusionsSerum FGF21 concentrations are markedly elevated in patients with T2RN. The association between FGF21 and T2DR appears to be independent of the effects of potential confounding variables. These findings may suggest FGF21 as a novel surrogate diagnostic biomarker in initial stages of T2DR (particularly with FGF21 values above 135.5 pg/mL).     

Association between high-density lipoprotein cholesterol to apolipoprotein A ratio and diabetic retinopathy: A cross-sectional study

AimsOur study is aimed to investigate the relationship between high-density lipoprotein cholesterol to apolipoprotein A ratio (HDL-C/ApoA) and diabetic retinopathy (DR) in subjects with type 2 diabetes mellitus (T2DM).MethodsWe retrospect the consecutive medical files of 1058 subjects with T2DM and recorded their clinical information and laboratory findings. Subjects with T2DM were divided into DR group (n = 522) and non-DR group (n = 536). We compared the lipids values of the two groups. Meanwhile we also observed the prevalence of DR at different HDL-C/ApoA levels. Binary logistic regression was used to correct confounding factors. Smooth curve fitting model and subgroup analysis were used to determine the correlation, non-linear relationship and threshold effect between HDL/ApoA and DR.ResultsHDL-C/ApoA value of DR group was significantly higher than non-DR group (0.88 ± 0.17 vs 0.84 ± 0.13, P < 0.05). The prevalence of DR significantly increased as HDL-C/ApoA level increased. There was association between HDL/ApoA levels and DR in the adjusted models (OR 1.55, 95%CI 0.60 to 4.02). After full adjustments for other relevant clinical covariates, patients with HDL/ApoA values in quartile 3 (Q3) had 1.50 times (95 % CI 1.00 to 2.17) and in Q4 had 2.39 times (95%CI 1.65 to 3.47) as high as the risk of DR compared with patients in Q1. HDL/ApoA showed a non-linear relationship with DR, with an inflection point value of 0.759. When HDL/ApoA>0.759, HDL/ApoA was significantly positively associated with DR (HR = 26.508, 95 % CI 7.623–92.174; P < 0.0001). Compared to patients with age < 60, HDL/ApoA was obviously associated with DR when age ≥ 60 (OR = 38.05, 95 % CI 8.06–179.69; P < 0.001).ConclusionsHDL-C/ApoA was found to be associated with the incidence of DR in patients with T2DM. After adjusting potential related factors HDL-C/ApoA OR value was 1.55 (95%CI 0.60 to 4.02). A non-linear association between HDL/ApoA and DR was observed in T2DM. Subgroup analysis showed that age could alter the relationship between HDL/ApoA and DR.     

A novel seven-gene risk profile in BALF to identify high-risk patients with idiopathic pulmonary fibrosis

BackgroundIdiopathic pulmonary fibrosis (IPF) is a fatal heterogeneous disease with a varied clinical course that is difficult to predict. Accurate predictive models are urgently needed to identify individuals with poor survival for the optimal timing of referral for transplantation and provide some clues for mechanistic research on disease progression.MethodsWe obtained the gene expression profiles of bronchoalveolar lavage fluid (BALF) from the Gene Expression Omnibus. Individuals from the {"type":"entrez-geo","attrs":{"text":"GPL14550","term_id":"14550"}}GPL14550 platform were assigned to the derivation cohort (n=112) and individuals from the {"type":"entrez-geo","attrs":{"text":"GPL17077","term_id":"17077"}}GPL17077 platform to the validation cohort (n=64). Univariate Cox and least absolute shrinkage and selection operator (LASSO) regression analyses were applied to select candidate genes for overall survival. A nomogram model was constructed based on Cox hazard regression analysis. The model was assessed by C-statistic, calibration curve, and decision curve analysis (DCA) and was externally validated.ResultsA nomogram model comprising seven genes was constructed. Excellent discrimination and calibration were observed in the derivation (C-index 0.815) and validation (C-index 0.812) cohorts. The AUCs for predicting 1-, 2- and 3-year survival were 0.857, 0.918, 0.930 in the derivation cohort and 0.850, 0.880, 0.925 in the validation cohort, respectively. DCA confirmed the clinical applicability of the model. A risk score based on the model was an independent prognostic predictor and could divide patients into high- and low-risk groups. The Kaplan-Meier analysis displayed that high-risk patients exhibited significantly poorer survival compared with low-risk patients. Gene Set Enrichment Analysis (GSEA) showed that high-risk patients were primarily enriched in inflammatory hallmarks, and single sample GSEA (ssGSEA) indicated that the high-risk group is closely correlated with the immune process. These lead to increased insight into mechanisms associated with IPF progression that inflammation mediated by immune response might be involved in the disease progression.ConclusionsThe novel BALF seven-gene model performed well in risk stratification and individualized survival prediction for patients with IPF, facilitating personalized management of IPF patients. It deepened the understanding of the role of inflammation in IPF progression, which needs to be further studied.     

Dynamic nomogram for persistent organ failure in acute biliary pancreatitis: Development and validation in a retrospective study

BackgroundPersistent organ failure (POF) increases the risk of death in patients with acute biliary pancreatitis (ABP). Currently, there is no early risk assessment tool for POF in patients with ABP.AimsTo establish and validate a dynamic nomogram for predicting the risk of POF in ABP.MethodsThis was a retrospective study of 792 patients with ABP, with 595 cases in the development group and 197 cases in the validation group. Least absolute shrinkage and selection operator regression screened the predictors of POF, and logistic regression established the model (P < 0.05). A dynamic nomogram showed the model. We evaluated the model's discrimination, calibration, and clinical effectiveness; used the bootstrap method for internal validation; and conducted external validation in the validation group.ResultsNeutrophils, haematocrit, serum calcium, and blood urea nitrogen were predictors of POF in ABP. In the development group and validation group, the areas under the receiver operating characteristic curves (AUROCs) were 0.875 and 0.854, respectively, and the Hosmer-Lemeshow test (P > 0.05) and calibration curve showed good consistency between the actual and prediction probability. Decision curve analysis showed that the dynamic nomogram has excellent clinical value.ConclusionThis dynamic nomogram helps with the early identification and screening of high-risk patients with POF in ABP.     

Role of cystatin C in the detection of sight-threatening diabetic retinopathy in Asian Indians with type 2 diabetes

AimTo study the association between cystatin C and sight-threatening diabetic retinopathy (STDR) in Asian Indians with type 2 diabetes (T2DM).MethodsIn a cross-sectional study carried out at two tertiary centres in India in 2022, individuals with T2DM underwent clinical and ophthalmic assessments and estimation of serum cystatin C. Grading of DR was done by retina specialists. STDR was defined by the presence of severe non-proliferative DR (NPDR), proliferative DR (PDR) and/or diabetic macular edema. Receiver operating characteristic (ROC) curves were used to identify cystatin C cut-off value for detecting STDR.ResultsAmong 420 individuals with T2DM (mean age 56 ± 9 years; mean duration of diabetes 14.5 ± 7.9 years), 121 (24.1 %) had No-DR, 119 (28.3 %) had No-STDR and 200 (49.6 %) had STDR. Mean cystatin C level was significantly higher in individuals with STDR compared to those with no-STDR and No-DR (1.34 vs 1.06 vs 0.93 mg/L, p < 0.001). Cystatin C cut-off value ≥1.11 mg/L had a C statistic of 0.944 (95 % CI: 0.909–0.968, p < 0.001), 96.8 % sensitivity and 78.2 % specificity for detection of STDR.ConclusionElevated serum cystatin C was strongly associated with STDR and could possibly be used as a biomarker for screening for sight-threatening diabetic retinopathy.     

Serum uric acid concentration is associated with worsening in severity of diabetic retinopathy among type 2 diabetic patients in Taiwan—A 3-year prospective study

AimsTo explore the role of serum uric acid (SUA) concentration in diabetic retinopathy (DR) for patients with type 2 diabetes mellitus (T2DM).MethodsA 3-year prospective study in 749 patients with T2DM and without proliferative diabetic retinopathy (PDR) was conducted at a medical center. Baseline SUA concentration and parameters of glycemic control, blood pressure, kidney disease, and lipid profiles were analyzed to determine their contribution to DR.ResultsFundus examination showed that 184 patients (24.6%) had non-proliferative retinopathy and 565 (75.4%) without DR at baseline. After 3 years, increase in the severity of DR was recognized in 103 patients (13.8%), including 81 patients with newly developed DR. Patients with increase in severity of DR positively associated with duration of DM (11.9 vs. 9.4 years, p = 0.001), HbA1c (7.6 vs. 7.2%, p = 0.001), albuminuria (45.5 vs. 31.0%, p = 0.006), and SUA (6.47 vs. 5.87 mg/dl, p < 0.001) than did those without change in DR stage. Cox regression showed that patients with SUA in the 3rd (5.9–6.9 mg/dl) and 4th (≥7.0 mg/dl) quartiles had hazard ratios for DR worsening of 2.57 and 3.66 (95% C.I. 1.30–5.08 and 1.92–7.00) when compared with patients with SUA in the 1st quartile (<4.9 mg/dl).ConclusionsSUA concentration is associated with the increase in severity of DR over a 3-year period in patients with T2DM. Further study is required to define the exact role of SUA in DR.     

Development of a nomogram to estimate the risk of community-acquired pneumonia in adults with acute asthma exacerbations

Objective

The aim of this study is to investigate the clinical characteristics of acute asthma exacerbations (AEs) with community-acquired pneumonia (CAP) in adults and establish a CAP prediction model for hospitalized patients with AEs.

Methods

We retrospectively collected clinical data from 308 patients admitted to Beijing Luhe Hospital, Capital Medical University, for AEs from December 2017 to August 2021. The patients were divided into CAP and non-CAP groups based on whether they had CAP. We used the Lasso regression technique and multivariate logistic regression analysis to select optimal predictors. We then developed a predictive nomogram based on the optimal predictors. The bootstrap method was used for internal validation. We used the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis (DCA) to assess the nomogram's discrimination, accuracy, and clinical practicability.

Results

The prevalence of CAP was 21% (65/308) among 308 patients hospitalized for AEs. Independent predictors of CAP in patients hospitalized with an AE (P < 0.05) were C-reactive protein > 10 mg/L, fibrinogen > 4 g/L, leukocytes > 10 × 10⁹/L, fever, use of systemic corticosteroids before admission, and early-onset asthma. The AUC of the nomogram was 0.813 (95% CI: 0.753–0.872). The concordance index of internal validation was 0.794. The calibration curve was satisfactorily consistent with the diagonal line. The DCA indicated that the nomogram provided a higher clinical net benefit when the threshold probability of patients was 3% to 89%.

Conclusions

The nomogram performed well in predicting the risk of CAP in hospitalized patients with AEs, thereby providing rapid guidance for clinical decision-making.     

Defining and predicting early recurrence after liver resection of hepatocellular carcinoma: a multi-institutional study

BackgroundA clear definition of “early recurrence” after hepatocellular carcinoma (HCC) resection is still lacking. This study aimed to determine the optimal cutoff between early and late HCC recurrence, and develop nomograms for pre- and postoperative prediction of early recurrence.MethodsPatients undergoing HCC resection were identified from a multi-institutional Chinese database. Minimum P-value approach was adopted to calculate optimal cut-off to define early recurrence. Pre- and postoperative risk factors for early recurrence were identified and further used for nomogram construction. The results were externally validated by a Western cohort.ResultsAmong 1501 patients identified, 539 (35.9%) were recurrence-free. The optimal length to distinguish between early (n = 340, 35.3%) and late recurrence (n = 622, 64.7%) was 8 months. Multivariable logistic regression analyses identified 5 preoperative and 8 postoperative factors for early recurrence, which were further incorporated into preoperative and postoperative nomograms (C-index: 0.785 and 0.834). The calibration plots for the probability of early recurrence fitted well. The nomogram performance was maintained using the validation dataset (C-index: 0.777 for preoperative prediction and 0.842 for postoperative prediction).ConclusionsAn interval of 8 months was the optimal threshold for defining early HCC recurrence. The two web-based nomograms have been published to allow accurate pre- and postoperative prediction of early recurrence. These may offer useful guidance for individual treatment or follow up for patients with resectable HCC.