Development and validation of a prediction model for hyperuricemia risk in hypertensive patients.

OBJECTIVE: This study aimed to create a predictive model for hyperuricemia (HUA) in patients diagnosed with hypertension and evaluate its predictive accuracy. METHODS: Employing a retrospective cohort design, this study investigated HUA incidence and clinical data among 228 patients with essential hypertension selected from the Department of Cardiology at a tertiary A-level hospital in Anhui Province, China, between January 2018 and June 2021. The patients were divided randomly into a training group (168 cases) and a validation group (60 cases) at a 7:3 ratio. The training group underwent univariate and multivariate logistic regression analyses to identify risk factors for HUA. Additionally, an R software-generated nomogram model estimated HUA risk in hypertensive patients. The validation group assessed the nomogram model's discriminatory power and calibration using receiver operating characteristic curve analysis and the Hosmer-Lemeshow goodness-of-fit test. RESULTS: The study found a 29.39% prevalence of HUA among the 228 participants. Logistic regression analyses identified age, body mass index, and concomitant coronary heart disease as independent HUA risk factors (odds ratio [OR] > 1 and P < 0.05). Conversely, high-density lipoprotein cholesterol emerged as an independent protective factor against HUA in hypertensive patients (OR < 1 and P < 0.05). Using these factors, a nomogram model was constructed to assess HUA risk, with an AUC of 0.873 (95% confidence interval [CI]: 0.818-0.928) in the training group and 0.841 (95% CI: 0.735-0.946) in the validation group, indicating a strong discriminatory ability. The Hosmer-Lemeshow goodness-of-fit test showed no significant deviation between predicted and actual HUA frequency in both groups (χ2 = 5.980, 9.780, P = 0.649, 0.281), supporting the nomogram's reliability. CONCLUSION: The developed nomogram model, utilizing independent risk factors for HUA in hypertensive patients, exhibits strong discrimination and calibration. It holds promise as a valuable tool for cardiovascular professionals in clinical decision-making.

Development and validation of a nomogram model for predicting the risk of pre-hospital delay in patients with acute myocardial infarction.

BACKGROUND: Acute myocardial infarction (AMI) is a severe cardiovascular disease caused by the blockage of coronary arteries that leads to ischemic necrosis of the myocardium. Timely medical contact is critical for successful AMI treatment, and delays increase the risk of death for patients. Pre-hospital delay time (PDT) is a significant challenge for reducing treatment times, as identifying high-risk patients with AMI remains difficult. This study aims to construct a risk prediction model to identify high-risk patients and develop targeted strategies for effective and prompt care, ultimately reducing PDT and improving treatment outcomes. AIM: To construct a nomogram model for forecasting pre-hospital delay (PHD) likelihood in patients with AMI and to assess the precision of the nomogram model in predicting PHD risk. METHODS: A retrospective cohort design was employed to investigate predictive factors for PHD in patients with AMI diagnosed between January 2022 and September 2022. The study included 252 patients, with 180 randomly assigned to the development group and the remaining 72 to the validation group in a 7:3 ratio. Independent risk factors influencing PHD were identified in the development group, leading to the establishment of a nomogram model for predicting PHD in patients with AMI. The model's predictive performance was evaluated using the receiver operating characteristic curve in both the development and validation groups. RESULTS: Independent risk factors for PHD in patients with AMI included living alone, hyperlipidemia, age, diabetes mellitus, and digestive system diseases (P < 0.05). A nomogram model incorporating these five predictors accurately predicted PHD occurrence. The receiver operating characteristic curve analysis indicated area under the receiver operating characteristic curve values of 0.787 (95% confidence interval: 0.716-0.858) and 0.770 (95% confidence interval: 0.660-0.879) in the development and validation groups, respectively, demonstrating the model's good discriminatory ability. The Hosmer-Lemeshow goodness-of-fit test revealed no statistically significant disparity between the anticipated and observed incidence of PHD in both development and validation cohorts (P > 0.05), indicating satisfactory model calibration. CONCLUSION: The nomogram model, developed with independent risk factors, accurately forecasts PHD likelihood in AMI individuals, enabling efficient identification of PHD risk in these patients.

Clinical study of acupuncture combined with surface anesthesia using proparacaine in geriatric cataract phacoemulsification.

BACKGROUND: During anesthesia administration for cataract surgery, low pH of proparacaine may induce pain or complications such as corneal damage and poor wound healing, with the use of additional drops intraoperatively increasing the risk of complications. Accordingly, there is a clinical need for adjuncts to local anesthesia needs to improve the efficiency of anesthesia and reduce the required amount of intraoperative proparacaine. AIM: To identify a method of anesthesia for geriatric cataract phacoemulsification that provides more efficient analgesia and improves clinical efficacy. METHODS: A total of 130 geriatric patients with cataracts who attended Hebei Eye Hospital from December 2020 to December 2022 were included in the present study. Patients were divided into the proparacaine surface anesthesia (SA) group (65 cases) and the compound acupuncture-medicine anesthesia group (CAMA group, 65 cases). Patients in the CAMA group were provided acupuncture analgesia in addition to SA. Preoperative anxiety [Self-Rating Anxiety Scale (SAS) score and state anxiety inventory (SAI) score], intraoperative stress, vital signs, analgesia, and cooperation, as well as postoperative adverse events, were compared between groups. RESULTS: More marked reductions in anxiety were observed among patients in the CAMA group, with corresponding reductions in SAS and SAI scores. During the operation, no change in the secretion of E, NE, or Cor group compared to the preoperative period was observed in the CAMA, which was markedly lower than that in the SA group. Heart rate, blood pressure, and respiratory rate were more stable intraoperatively in the CAMA group. In addition, the incidence of intraoperative pain and the number of additional doses of anesthesia required in the CAMA group were markedly lower than in the SA group. Accordingly, patients in the CAMA group were able to avoid eye movements and eyelid closing leading to greater cooperation with surgeons during surgery. Furthermore, marked reductions in intraoperative adverse effects were observed in the CAMA group, indicating greater overall safety. CONCLUSION: Proparacaine SA combined with acupuncture as an analgesic provides improved analgesia with greater safety compared to surface anesthesia with proparacaine during geriatric cataract phacoemulsification.

Prognostic significance of post-preoperative tumor markers increments in patients with non-metastatic gastric cancer.

PURPOSE: Carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA19-9) are the most common tumor markers detected before and after gastric cancer (GC) surgery. However, the impact of post-preoperative CEA/CA19-9 increments on prognosis of GC remains unclear. In addition, there is no research incorporating post-preoperative CEA/CA19-9 increments into the prognostic model. METHODS: Patients who underwent radical gastrectomy for GC at the First Affiliated Hospital of Anhui Medical University and Anhui Provincial Hospital from January 2013 to December 2017 were enrolled and divided into the discovery and validation cohort. Prognostic value of post-preoperative CEA/CA19-9 increments and preoperative CEA/CA199 levels were assessed by Kaplan-Meier log-rank analysis and compared by time-dependent receiver operating characteristic (t-ROC) curves. Multivariate Cox regression analysis was applied to establish the nomogram. The performance of the prognostic model was validated by the concordance index (C-index), calibration curve, and ROC curve analysis. RESULTS: A total of 562 GC patients were included in this study. Overall survival (OS) rates decreased with an increasing number of incremental tumor markers after surgery. The t-ROC curves implied that the prognostic ability of the number of incremental post-preoperative tumor markers was superior to that of the number of positive preoperative tumor markers. Cox regression analysis suggested that the number of incremental post-preoperative tumor markers was an independent prognostic factor. The nomogram incorporated with the post-preoperative CEA/CA19-9 increments showed reliable accuracy. CONCLUSIONS: Incremental post-preoperative CEA/CA19-9 were indicator of poor prognosis of GC. The prognostic value of post-preoperative CEA/CA19-9 increments exceed that of preoperative CEA/CA19-9 levels.

Prediction of overall survival after radical gastrectomy using nomograms created by tumor markers.

Prediction of prognosis after radical resection of gastric cancer has not been well established. Therefore, we aimed to establish a prognostic model based on a new score system of patients with gastric cancer. A total of 1235 patients who underwent curative gastrectomy at our hospital from October 2015 to April 2017 were included in this study. Univariate and multivariate analyses were used to screen for prognostic risk factors. Construction of the nomogram was based on Cox proportional hazard regression models. The construction of the new score models was analyzed by the receiver operating characteristic curve (ROC curve), calibration curve, and decision curve. Multivariate analysis showed that tumor size, T, N, carcinoembryonic antigen, CA125, and CA19-9 were independent prognostic factors. The new score model had a greater AUC (The area under the ROC curve) than other systems, and the C-index of the nomogram was highly reliable for evaluating the survival of patients with gastric cancer. Based on the tumor markers and other clinical indicators, we developed a precise model to predict the prognosis of patients with gastric cancer after radical surgery. This score system can be helpful to both surgeons and patients.

Effects and mechanisms of trifluridine alone or in combination with cryptotanshinone in inhibiting malignant biological behavior of gastric cancer.

BACKGROUND: The incidence of gastric cancer (GC) ranks fourth among all malignant tumors worldwide, and the fatality rate ranks second among all malignant tumors. Several Chinese traditional medicines have been used in the treatment of advanced gastric cancer. This study aims to investigate the effect of combinational use of natural product cryptotanshinone (CTS) with anti-cancer drug trifluorothymidine (FTD) in GC. METHODS: Cell Counting Kit-8 assay was used to detect the inhibitory effect of the combinational or separate use of FTD and CTS on the growth of HGC-27 and AGS GC cells. The combined index of FTD and CTS was calculated using CompuSyn software. To understand the mechanism, we applied flow cytometry to study the cell cycle and cell apoptosis after treatment. We also investigated the amount of FTD incorporated into the DNA by immunofluorescence assay. The expression of relevant proteins was monitored using western blot. Furthermore, the effect of using TAS-102 in combination with CTS was studied in xenograft tumor nude mice model. RESULTS: FTD and CTS inhibited the growth of GC cells in a dose-dependent manner, respectively. They both exhibited low to sub-micromolar potency in HGC-27 and AGS cells. The combination of FTD and CTS showed synergistic anticancer effect in HGC-27 cells and AGS cells. Our mechanism studies indicate that FTD could block HGC-27 cells at G2/M phase, while CTS could block HGC-27 cells at G1/G0 phase, while FTD combined with CTS could mainly block HGC-27 cells at G2 phase. FTD in combination with CTS significantly increased the apoptosis of HGC-27 cells. We observed that CTS treatment increased the incorporation of FTD into the DNA HGC-27 cell. FTD treatment activated STAT3 phosphorylation in HGC-27 cells, while CTS treatment down-regulated the concentration of p-STAT3. Interestingly, the combination of CTS and FTD reduced STAT3 phosphorylation induced by FTD. In the in vivo experiments, we observed that the combination of TAS-102 with CTS was significantly more potent than TAS-102 on tumor growth inhibition. CONCLUSIONS: FTD combined with CTS has a synergistic anti-gastric cancer effect as shown by in vitro and in vivo experiments, and the combined treatment of FTD and CTS will be a promising treatment option for advanced gastric cancer.

Nomogram established using risk factors of early gastric cancer for predicting the lymph node metastasis.

BACKGROUND: For the prognosis of patients with early gastric cancer (EGC), lymph node metastasis (LNM) plays a crucial role. A thorough and precise evaluation of the patient for LNM is now required. AIM: To determine the factors influencing LNM and to construct a prediction model of LNM for EGC patients. METHODS: Clinical information and pathology data of 2217 EGC patients downloaded from the Surveillance, Epidemiology, and End Results database were collected and analyzed. Based on a 7:3 ratio, 1550 people were categorized into training sets and 667 people were assigned to testing sets, randomly. Based on the factors influencing LNM determined by the training sets, the nomogram was drawn and verified. RESULTS: Based on multivariate analysis, age at diagnosis, histology type, grade, T-stage, and size were risk factors of LNM for EGC. Besides, nomogram was drawn to predict the risk of LNM for EGC patients. Among the categorical variables, the effect of grade (well, moderate, and poor) was the most significant prognosis factor. For training sets and testing sets, respectively, area under the receiver-operating characteristic curve of nomograms were 0.751 [95% confidence interval (CI): 0.721-0.782] and 0.786 (95%CI: 0.742-0.830). In addition, the calibration curves showed that the prediction model of LNM had good consistency. CONCLUSION: Age at diagnosis, histology type, grade, T-stage, and tumor size were independent variables for LNM in EGC. Based on the above risk factors, prediction model may offer some guiding implications for the choice of subsequent therapeutic approaches for EGC.

Efficacy and outcome of extensive intraoperative peritoneal lavage plus surgery vs surgery alone with advanced gastric cancer patients.

BACKGROUND: Gastric cancer (GC) is one of the most common malignant tumors. After resection, one of the major problems is its peritoneal dissemination and recurrence. Some free cancer cells may still exist after resection. In addition, the surgery itself may lead to the dissemination of tumor cells. Therefore, it is necessary to remove residual tumor cells. Recently, some researchers found that extensive intraoperative peritoneal lavage (EIPL) plus intraperitoneal chemotherapy can improve the prognosis of patients and eradicate peritoneal free cancer for GC patients. However, few studies explored the safety and long-term outcome of EIPL after curative gastrectomy. AIM: To evaluate the efficacy and long-term outcome of advanced GC patients treated with EIPL. METHODS: According to the inclusion and exclusion criteria, a total of 150 patients with advanced GC were enrolled in this study. The patients were randomly allocated to two groups. All patients received laparotomy. For the non-EIPL group, peritoneal lavage was washed using no more than 3 L of warm saline. In the EIPL group, patients received 10 L or more of saline (1 L at a time) before the closure of the abdomen. The surviving rate analysis was compared by the Kaplan-Meier method. The prognostic factors were carried out using the Cox appropriate hazard pattern. RESULTS: The basic information in the EIPL group and the non-EIPL group had no significant difference. The median follow-up time was 30 mo (range: 0-45 mo). The 1- and 3-year overall survival (OS) rates were 71.0% and 26.5%, respectively. The symptoms of ileus and abdominal abscess appeared more frequently in the non-EIPL group (P < 0.05). For the OS of patients, the EIPL, Borrmann classification, tumor size, N stage, T stage and vascular invasion were significant indicators. Then multivariate analysis revealed that EIPL, tumor size, vascular invasion, N stage and T stage were independent prognostic factors. The prognosis of the EIPL group was better than the non-EIPL group (P < 0.001). The 3-year survival rate of the EIPL group (38.4%) was higher than the non-EIPL group (21.7%). For the recurrence-free survival (RFS) of patients, the risk factor of RFS included EIPL, N stage, vascular invasion, type of surgery, tumor location, Borrmann classification, and tumor size. EIPL and tumor size were independent risk factors. The RFS curve of the EIPL group was better than the non-EIPL group (P = 0.004), and the recurrence rate of the EIPL group (24.7%) was lower than the non-EIPL group (46.4%). The overall recurrence rate and peritoneum recurrence rate in the EIPL group was lower than the non-EIPL group (P < 0.05). CONCLUSION: EIPL can reduce the possibility of perioperative complications including ileus and abdominal abscess. In addition, the overall survival curve and RFS curve were better in the EIPL group.

Development and validation of a novel nomogram for predicting overall survival in gastric cancer based on inflammatory markers.

BACKGROUND: Nearly 66% of occurrences of gastric cancer (GC), which has the second-highest death rate of all cancers, arise in developing countries. In several cancers, the predictive significance of inflammatory markers has been established. AIM: To identify clinical characteristics and develop a specific nomogram to determine overall survival for GC patients. METHODS: Nine hundred and four GC patients treated at the First Affiliated Hospital of Anhui Medical University between January 2010 and January 2013 were recruited. Prognostic risk variables were screened for Cox analysis. The C index, receiver operator characteristic (ROC) curve, and decision curve analysis were used to evaluate the nomogram. RESULTS: Tumor node metastasis stage, carcinoembryonic antigen, systemic immune-inflammation index, and age were identified as independent predictive variables by multivariate analysis. Systemic immune-inflammation index value was superior to that of other inflammatory indicators. The ROC indicated the nomogram had a higher area under the curve than other factors, and its C-index for assessing the validation and training groups of GC patients was extremely reliable. CONCLUSION: We created a novel nomogram to forecast the prognosis of GC patients following curative gastrectomy based on blood markers and other characteristics. Both surgeons and patients can benefit significantly from this new scoring system.

A predictive model of bowel resection for incarcerated inguinal hernia based on the systemic immune-inflammation index.

Background and Purpose: An inguinal hernia is a common surgical disease. Once incarcerated or strangulated, it may endanger the life of the patient. Therefore, it is essential to study the risk factors of incarcerated inguinal hernia (IIH) and strangulated inguinal hernia (SIH). One of the serious complications of IIH and SIH is intestinal necrosis, which occurs owing to blood supply disorder. The study explores the risk factors of intestinal resection and establishes a simple model to assess the incidence of intestinal resection to provide significant assistance and limited guidance for clinical work. Patients and Methods: Our research team collected and retrospectively analysed the clinical data of 338 patients with IIH who were hospitalized in the First Affiliated Hospital of Wenzhou Medical University between September 2008 and December 2016. According to the surgical plan, we divided the included cases into two groups, non-intestinal and intestinal resection groups, and the clinical case characteristics of these groups were statistically analysed. Results: Based on multivariable logistic regression analysis, we found that increased risk of bowel resection was highly correlated among the elderly (≥70 years), and for people with high temperature (≥37.3°C), high systemic immune-inflammation index(SII) values (≥1230.13), presence of bowel obstruction, and signs of peritonitis. Further, we processed the five independent risk factors using special software to obtain a simple model called a nomogram. To verify the nomogram's accuracy and predictive ability, we calculate the C-index: 0.806 and use the calibration curve to evaluate its stability and predictive performance. We constructed the ROC curve nomogram and other sub-variables, and calculated the area under the curve (AUC) corresponding to the nomogram (AUC = 0.808, 95% CI = 0.762 to 0.848), SII (AUC = 0.752, 95% CI = 0.703 to 0.797), age (AUC = 0.641, 95% CI = 0.587 to 0.692), temperature (AUC = 0.579, 95% CI = 0.524 to 0.632), bowel obstruction (AUC = 0.685, 95% CI = 0.633 to 0.734), and signs of peritonitis (AUC = 0.580, 95% CI = 0.525 to 0.633). Conclusion: It can be said that we found for the first time that clinical variables such as SII are independent risk factors for enterectomy for IIH. The nomogram based on SII and other variables can accurately and easily predict the probability of IIH requiring bowel resection.

Model established based on blood markers predicts overall survival in patients after radical resection of types II and III adenocarcinoma of the esophagogastric junction.

BACKGROUND: In recent years, the incidence of types II and III adenocarcinoma of the esophagogastric junction (AEG) has shown an obvious upward trend worldwide. The prognostic prediction after radical resection of AEG has not been well established. AIM: To establish a prognostic model for AEG (types II and III) based on routine markers. METHODS: A total of 355 patients who underwent curative AEG at The First Affiliated Hospital of Anhui Medical University from January 2014 to June 2015 were retrospectively included in this study. Univariate and multivariate analyses were performed to identify the independent risk factors. A nomogram was constructed based on Cox proportional hazards models. The new score models was analyzed by C index and calibration curves. The receiver operating characteristic (ROC) curve was used to compare the predictive accuracy of the scoring system and tumor-node-metastasis (TNM) stage. Overall survival was calculated using the Kaplan-Meier curve amongst different risk AEG patients. RESULTS: Multivariate analysis showed that TNM stage (hazard ratio [HR] = 2.286, P = 0.008), neutrophil-to-lymphocyte ratio (HR = 2.979, P = 0.001), and body mass index (HR = 0.626, P = 0.026) were independent prognostic factors. The new scoring system had a higher concordance index (0.697), and the calibration curves of the nomogram were reliable. The area under the ROC curve of the new score model (3-year: 0.725, 95% confidence interval [CI]: 0.676-0.777; 5-year: 0.758, 95%CI: 0.708-0.807) was larger than that of TNM staging (3-year: 0.630, 95%CI: 0.585-0.684; 5-year: 0.665, 95%CI: 0.616-0.715). CONCLUSION: Based on the serum markers and other clinical indicators, we have developed a precise model to predict the prognosis of patients with AEG (types II and III). The new prognostic nomogram could effectively enhance the predictive value of the TNM staging system. This scoring system can be advantageous and helpful for surgeons and patients.

A Combination Analysis of IVIM-DWI Biomarkers and T2WI-Based Texture Features for Tumor Differentiation Grade of Cervical Squamous Cell Carcinoma.

Purpose: To explore the value of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and texture analysis on T2-weighted imaging (T2WI) for evaluating pathological differentiation of cervical squamous cell carcinoma. Method: This retrospective study included a total of 138 patients with pathologically confirmed poor/moderate/well-differentiated (71/49/18) who underwent conventional MRI and IVIM-DWI scans. The values of ADC, D, D ∗ , and f and 58 T2WI-based texture features (18 histogram features, 24 gray-level co-occurrence matrix features, and 16 gray-level run length matrix features) were obtained. Multiple comparison, correlation, and regression analyses were used. Results: For IVIM-DWI, the ADC, D, D ∗ , and f were significantly different among the three groups (p < 0.05). ADC, D, and D ∗ were positively correlated with pathological differentiation (r = 0.262, 0.401, 0.401; p < 0.05), while the correlation was negative for f (r = -0.221; p < 0.05). The comparison of 52 parameters of texture analysis on T2WI reached statistically significant levels (p < 0.05). Multivariate logistic regression analysis incorporated significant IVIM-DWI, and texture features on T2WI showed good diagnostic performance both in the four differentiation groups (poorly vs. moderately, area under the curve(AUC) = 0.797; moderately vs. well, AUC = 0.954; poorly vs. moderately and well, AUC = 0.795; and well vs. moderately and poorly, AUC = 0.952). The AUCs of each parameters alone were smaller than that of each regression model (0.503∼0.684, 0.547∼0.805, 0.511∼0.712, and 0.636∼0.792, respectively; pairwise comparison of ROC curves between regression model and individual variables, p < 0.05). Conclusions: IVIM-DWI biomarkers and T2WI-based texture features had potential to evaluate the pathological differentiation of cervical squamous cell carcinoma. The combination of IVIM-DWI with texture analysis improved the predictive performance.

Prognostic factors for disease-free survival in postoperative patients with hepatocellular carcinoma and construction of a nomogram model.

BACKGROUND: Hepatocellular carcinoma (HCC) is the most common type of liver cancer and has a high risk of invasion and metastasis along with a poor prognosis. AIM: To investigate the independent predictive markers for disease-free survival (DFS) in patients with HCC and establish a trustworthy nomogram. METHODS: In this study, 445 patients who were hospitalized in The First Affiliated Hospital of Anhui Medical College between December 2009 and December 2014 were retrospectively examined. The survival curve was plotted using the Kaplan-Meier method and survival was determined using the log-rank test. To identify the prognostic variables, multivariate Cox regression analyses were carried out. To predict the DFS in patients with HCC, a nomogram was created. C-indices and receiver operator characteristic curves were used to evaluate the nomogram's performance. Decision curve analysis (DCA) was used to evaluate the clinical application value of the nomogram. RESULTS: Longer DFS was observed in patients with the following characteristics: elderly, I-II stage, and no history of hepatitis B. The calibration curve showed that this nomogram was reliable and had a higher area under the curve value than the tumor node metastasis (TNM) stage. Moreover, the DCA curve revealed that the nomogram had good clinical applicability in predicting 3- and 5-year DFS in HCC patients after surgery. CONCLUSION: Age, TNM stage, and history of hepatitis B infection were independent factors for DFS in HCC patients, and a novel nomogram for DFS of HCC patients was created and validated.

Establishment and evaluation of a nomogram prediction model for recurrence risk of atrial fibrillation patients after radiofrequency ablation.

OBJECTIVE: To explore the risk factors for recurrence of atrial fibrillation (AF) in patients after radiofrequency ablation and construction of a targeted nomogram prediction model. METHODS: A prospective cohort study design was used to select 312 patients who were separated into two groups; a recurrence group (n = 79) and a non-recurrence group (n = 233) with or without AF, who underwent radiofrequency ablation for the first time between January 2017 and December 2017, with a completed a 12-month follow-up after surgery. The recurrence of AF within 12 months after follow-up was recorded. The nomogram prediction model was established. The original data were resampled using the Bootstrap method. The recurrence risk after resampling was predicted using a nomogram model. The calibration curve and ROC curve of the nomogram model were established. The predicted calibration degree and discrimination degree of the nomogram model were evaluated with the Hosmer-Lemeshow deviation test and area under the curve. RESULTS: The 12-month follow-up showed that a total of 79 patients (25.32%) had recurrence of AF. The type of AF, sex, gender, disease course, left atrial anteroposterior diameter, left atrial volume, and cardiac function classification were independent risk factors for the recurrence of AF (P < 0.05). After the nomogram prediction model passed the Bootstrap self-sampling 1000 times, Hosmer-Lemeshow deviation test: χ2 = 8.070, P = 0.427; the area under ROC curve was 0.852 (95% CI: 0.806-0.898), the sensitivity was 78.48%, and the specificity was 81.12%, suggesting that the nomogram model has better predictive calibration and discrimination. CONCLUSION: The recurrence rate in patients with AF after radiofrequency ablation is high. The nomogram model based on the risk factors of AF recurrence has high prediction accuracy and can be used to predict the recurrence risk of AF in patients after radiofrequency ablation.

Nomogram Model for Predicting the Risk of Multidrug-Resistant Bacteria Infection in Diabetic Foot Patients.

OBJECTIVE: This study established an individualized nomogram for predicting the risk of multidrug-resistant bacterial (MDRB) infection in patients with the diabetic foot (DF), and providing a reference for clinical prevention and treatment. METHODS: A total of 199 DF patients admitted to the hospital from July 2015 to December 2018 were included in this study. The pathogenic bacteria at the site of infection were detected and the factors affecting the occurrence of MDRB infection in DF patients summarized. The R software was used to draw the nomogram, and the Bootstrap Method used to internally verify the model. The calibration curve and the Harrell's Concordance Index (C-index) were used to evaluate the predictive effect of the nomogram model. RESULTS: Logistic regression analysis showed that age, course of diabetes, previous use of antibacterial drugs, types of antibacterial drugs, and osteoporosis were risk factors for multidrug-resistant infections in DF (P<0.05). The area under the receiver operating characteristic curve (AUC, Area Under Curve) of the nomogram model after internal verification was 0.773 (95% CI: 0.704-0.830). The mean absolute error between the predicted probability of infection in the nomogram and the actual occurrence of MDRB was 0.032, indicating that the nomogram model had good forecasting efficiency and stability. CONCLUSION: The risk factors for multidrug-resistant infections in DF are age, course of diabetes, previous use of antibacterial drugs, types of antibacterial drugs used, and osteoporosis. The nomogram model drawn on these risk factors has good predictive accuracy and can assist medical staff in formulating targeted infection prevention strategies for patients.

A Simple Model Established by Blood Markers Predicting Overall Survival After Radical Resection of Pancreatic Ductal Adenocarcinoma.

Background: The prognostic prediction after radical resection of pancreatic ductal adenocarcinoma (PDAC) has not been well-established. We aimed to establish a prognostic model for PDAC based on a new score system, which included a clinical routine serum marker. Methods: A total of 438 patients who underwent curative PDAC at the First Affiliated Hospital of Anhui Medical University from January 2007 to January 2014 were included in this study. Univariate and multivariate analyses were used to screen for prognostic risk factors. We constructed the nomogram based on Cox proportional hazard regression models. The construction of the new score models was analyzed by the receiver operator characteristic curve (ROC curve), which were compared with other clinical indexes. Results: Multivariate analysis showed that TNM stage, CA199, CEA, globulin, neutrophil-to-lymphocyte ratio (NLR), and lymphocyte-to-monocyte ratio (LMR) were independent prognostic factors. The new score system had a higher AUC value than other risk factors, and the C-index of the nomogram was highly consistent for evaluating survival of PDAC patients in the validation groups and training group, and the external population also verified the nomogram. Conclusions: For the patients with PDAC after radical surgery, we developed a precise model to predict the prognosis based on the serum markers and other clinical indicators. For surgeons and patients, this score system can be an effective help.

Nomogram Model for Predicting Risk of Postoperative Delirium After Deep Brain Stimulation Surgery in Patients Older Than 50 Years with Parkinson Disease.

OBJECTIVE: To explore the influencing factors of postoperative delirium (POD) after deep brain electric stimulation (DBS) in patients older than 50 years with Parkinson disease (PD) and to construct a nomogram model to predict the risk of POD. METHODS: A retrospective cohort study was conducted of 229 patients older than 50 years with PD hospitalized from January 2015 to August 2019. All patients received DBS during hospitalization. The incidence of POD of patients and clinical data such as gender, age, educational level, and duration of disease were collected, the influencing factors of POD of patients with PD were analyzed, and a nomogram model for predicting the risk of POD was established. RESULTS: POD occurred in 47 of 229 patients with PD, with an incidence rate of 20.52%. Gender, age, Parkinson's Disease Sleep Scale score, preoperative cerebral ischemia, preoperative pulmonary inflammation, and preoperative length of stay are the influencing factors of POD in patients older than 50 years with PD (P < 0.05). After deviation correction, the area under the receiver operating characteristic curve of the nomogram model for predicting POD risk is 0.755, the sensitivity is 74.47%, and the specificity is 73.08%. The mean absolute error between the prediction of POD risk by the nomogram model and actual delirium risk is 0.024, suggesting that the nomogram model has good prediction efficiency. CONCLUSIONS: Based on the influencing factors of delirium after DBS for patients older than 50 years with PD, the nomogram model for predicting the risk of POD has been established in this study. The prediction efficiency is good, which can provide a reference for early clinical identification of high-risk patients and formulate interventional countermeasures as soon as possible.

Metallic Nanofilm Enhanced Fluorescence Cell Imaging: A Study of Distance-Dependent Intensity and Lifetime by Optical Sectioning Microscopy.

Simple, stable, easily-fabricated smooth metallic nanofilm can improve the imaging intensity and imaging contrast. However, its application in micrometer-scale cells has not been popularized due to the lack of full understanding of their related fluorescence properties. In this study, fluorescence enhancement of cell imaging on smooth Au nanofilm was investigated over a micrometer-scale range via employment of the optical sectioning method available with a laser scanning confocal fluorescence microscope. The fluorescence enhancement reduced with the distance away from the surface of metallic nanofilm, and this distance dependence was determined by the factors of numerical aperture, dye-substrate distance, and emission wavelength. In addition, distance-dependent fluorescence lifetime images of cells were also measured to study the interaction between fluorophores and metallic film. The enhancement effect of Au nanofilm on fluorescence cell imaging can be induced not only by the standing wave formed by the reflected light and exciting light but also by the interaction between fluorophore and surface plasmons on the metallic nanofilm. Our study on smooth metallic nanofilm should pave the way for utilizing its uniform fluorescence enhancement characteristic for biological imaging.

Model to Predict Overall Survival in Patients With Hepatocellular Carcinoma After Curative Hepatectomy.

BACKGROUND: The prognosis of patients with hepatocellular carcinoma (HCC) remains difficult to accurately predict. The purpose of this study was to establish a prognostic model for HCC based on a novel scoring system. METHODS: Five hundred and sixty patients who underwent a curative hepatectomy for treatment of HCC at our hospital between January 2007 and January 2014 were included in this study. Univariate and multivariate analyses were used to screen for prognostic risk factors. The nomogram construction was based on Cox proportional hazard regression models, and the development of the new scoring model was analyzed using receiver operating characteristic (ROC) curve analysis and then compared with other clinical indexes. The novel scoring system was then validated with an external dataset from a different medical institution. RESULTS: Multivariate analysis showed that tumor size, portal vein tumor thrombus (PVTT), invasion of adjacent tissues, microvascular invasion, and levels of fibrinogen and total bilirubin were independent prognostic factors. The new scoring model had higher area under the curve (AUC) values compared to other systems, and the C-index of the nomogram was highly consistent for evaluating the survival of HCC patients in the validation and training datasets, as well as the external validation dataset. CONCLUSIONS: Based on serum markers and other clinical indicators, a precise model to predict the prognosis of patients with HCC was developed. This novel scoring system can be an effective tool for both surgeons and patients.

Granulocyte colony-stimulating factor and stromal cell-derived factor-1 combination therapy: A more effective treatment for cerebral ischemic stroke.

BACKGROUND: Drugs that promote angiogenesis include statins, recombinant human granulocyte colony-stimulating factor, and stromal cell-derived factor-1. Low doses of atorvastatin could significantly increase the vascular expressions of endothelial growth factor, and the number of peripheral blood endothelial progenitor cells (EPCs), thus improving angiogenesis and local blood flow. G-CSF is an EPC-mobilization agent used in ischemia studies for targeting angiogenesis after cerebral ischemia via EPCs. In previous clinical trials, consistent conclusions have not been reached about the effectiveness of G-CSF on ischemic stroke. Therefore, the therapeutic effect of G-CSF and its combination with other medicines need further experimental verification. It is known that atorvastatin, rhG-CSF, and SDF-1 are considered the most promising neuroprotective candidates, but a comprehensive comparison of their effects is lacking. AIMS: To compare the effects of atorvastatin, stromal cell-derived factor-1, and recombinant human granulocyte colony-stimulating factor on ischemic stroke. METHODS: Adult male Sprague-Dawley rats were randomly allocated to three groups: normal, sham-operated, and middle cerebral artery occlusion operated. Middle cerebral artery occlusion operated rats were further allocated into saline, atorvastatin, recombinant human granulocyte colony-stimulating factor, and recombinant human granulocyte colony-stimulating factor + stromal cell-derived factor-1 groups. Neurological function evaluation, cerebral infarction and the blood-brain barrier integrity analysis, identification of angiogenic factors, assessment of angiogenesis, expression of growth-associated protein-43, neuroglobin, glial cell-derived neurotrophic factor, and cleaved caspase 3, were performed. RESULTS: Compared with atorvastatin or recombinant human granulocyte colony-stimulating factor alone, recombinant human granulocyte colony-stimulating factor + stromal cell-derived factor-1 treatment improved neurological performance, reduced cerebral infarction and blood-brain barrier disruption after stroke, and increased the content of stromal cell-derived factor-1, vascular endothelial growth factor, monocyte chemotactic protein 1, and basic fibroblast growth factor in peripheral blood. In addition, recombinant human granulocyte colony-stimulating factor + stromal cell-derived factor-1 promoted greater angiogenesis than atorvastatin or recombinant human granulocyte colony-stimulating factor alone and increased the expression of growth-associated protein-43, neuroglobin, and glial cell-derived neurotrophic factor, while decreasing the levels of cleaved caspase 3 in the brain after ischemic stroke. CONCLUSIONS: Combination therapy with recombinant human granulocyte colony-stimulating factor and stromal cell-derived factor-1 is more effective than atorvastatin or recombinant human granulocyte colony-stimulating factor alone in protecting against stroke-induced damage and could be an optimal therapeutic strategy for stroke.