Development and validation of a diagnostic prediction model for severe periventricular-intraventricular hemorrhage in newborns: insights from a retrospective analysis utilizing the MIMIC-III database

Abstract Objective: Periventricular-intraventricular hemorrhage is the most common type of intracranial bleeding in newborns, especially in the first 3 days after birth. Severe periventricular-intraventricular hemorrhage is considered a progression from mild periventricular-intraventricular hemorrhage and is often closely associated with severe neurological sequelae. However, no specific indicators are available to predict the progression from mild to severe periventricular-intraventricular in early admission. This study aims to establish an early diagnostic prediction model for severe PIVH. Method: This study was a retrospective cohort study with data collected from the MIMIC-III (v1.4) database. Laboratory and clinical data collected within the first 24 h of NICU admission have been used as variables for both univariate and multivariate logistic regression analyses to construct a nomogram-based early prediction model for severe periventricular-intraventricular hemorrhage and subsequently validated. Results: A predictive model was established and represented by a nomogram, it comprised three variables: output, lowest platelet count and use of vasoactive drugs within 24 h of NICU admission. The model's predictive performance showed by the calculated area under the curve was 0.792, indicating good discriminatory power. The calibration plot demonstrated good calibration between observed and predicted outcomes, and the Hosmer-Lemeshow test showed high consistency (p = 0.990). Internal validation showed the calculated area under a curve of 0.788. Conclusions: This severe PIVH predictive model, established by three easily obtainable indicators within the NICU, demonstrated good predictive ability. It offered a more user-friendly and convenient option for neonatologists.

A prediction model for coronary artery abnormalities in children with Kawasaki disease older than 5 years

Abstract Objective: Reliably prediction models for coronary artery abnormalities (CAA) in children aged > 5 years with Kawasaki disease (KD) are still lacking. This study aimed to develop a nomogram model for predicting CAA at 4 to 8 weeks of illness in children with KD older than 5 years. Methods: A total of 644 eligible children were randomly assigned to a training cohort (n = 450) and a validation cohort (n = 194). The least absolute shrinkage and selection operator (LASSO) analysis was used for optimal predictors selection, and multivariate logistic regression was used to develop a nomogram model based on the selected predictors. Area under the receiver operating characteristic curve (AUC), calibration curves, Hosmer-Lemeshow test, Brier score, and decision curve analysis (DCA) were used to assess model performance. Results: Neutrophil to lymphocyte ratio, intravenous immunoglobulin resistance, and maximum baseline z-score ≥ 2.5 were identified by LASSO as significant predictors. The model incorporating these variables showed good discrimination and calibration capacities in both training and validation cohorts. The AUC of the training cohort and validation cohort were 0.854 and 0.850, respectively. The DCA confirmed the clinical usefulness of the nomogram model. Conclusions: A novel nomogram model was established to accurately assess the risk of CAA at 4-8 weeks of onset among KD children older than 5 years, which may aid clinical decisionmaking.

Development and validation of a clinical prediction model for prognostic factors in patients with primary pontine hemorrhage

Abstract We aimed to develop a prognostic model for primary pontine hemorrhage (PPH) patients and validate the predictive value of the model for a good prognosis at 90 days. A total of 254 PPH patients were included for screening of the independent predictors of prognosis, and data were analyzed by univariate and multivariable logistic regression tests. The cases were then divided into training cohort (n=219) and validation cohort (n=35) based on the two centers. A nomogram was developed using independent predictors from the training cohort to predict the 90-day good outcome and was validated from the validation cohort. Glasgow Coma Scale score, normalized pixels (used to describe bleeding volume), and mechanical ventilation were significant predictors of a good outcome of PPH at 90 days in the training cohort (all P<0.05). The U test showed no statistical difference (P=0.892) between the training cohort and the validation cohort, suggesting the model fitted well. The new model showed good discrimination (area under the curve=0.833). The decision curve analysis of the nomogram of the training cohort indicated a great net benefit. The PPH nomogram comprising the Glasgow Coma Scale score, normalized pixels, and mechanical ventilation may facilitate predicting a 90-day good outcome.

Significance of radiologic extranodal extension in locoregionally advanced nasopharyngeal carcinoma with lymph node metastasis: a comprehensive nomogram

Abstract Objective We aimed to assess the significance of rENE and creat a predictive tool (nomogram) for estimating Overall Survival (OS) in locoregionally advanced Nasopharyngeal Carcinoma (NPC) patients with Lymph Node Metastasis (LNM) based on their clinical characteristics and Radiologic Extranodal Extension (rENE). Methods Five hundred and sixty-nine NPC patients with LNM were randomly divided into training and validation groups. Significant factors were identified using univariate and multivariate analyses in the training cohort. Then, the nomogram based on the screening results was established to predict the Overall Survival (OS). Calibration curves and the Concordance index (C-index) gauged predictive accuracy and discrimination. Receiver Operating Characteristic (ROC) analysis assessed risk stratification, and clinical utility was measured using Decision Curve Analysis (DCA). The nomogram's performance was validated for discrimination and calibration in an independent validation cohort. Results A total of 360 (63.2%) patients were present with radiologic extranodal extension at initial diagnosis. Patients with rENE had significantly lower OS than other patients. Multivariate analysis identified the five factors, including rENE, for the nomogram model. The C-index was 0.75 (0.71-0.78) in the training cohort and 0.76 (0.69-0.83) in the validation cohort. Notably, the nomogram outperformed the 8th TNM staging system, as evident from the higher AUC values (0.77 vs. 0.60 for 2 year and 0.75 vs. 0.65 for 3 year) and well-calibrated calibration curves. Decision curve analysis indicated improved Net Benefit (NB) with the nomogram for predicting OS. The log-rank test confirmed significant survival distinctions between risk groups in both training and validation cohorts. Conclusions We demonstrated the prognostic value of rENE in nasopharyngeal carcinoma and developed a nomogram based on rENE and other factors to provide individual prediction of OS for locoregionally advanced nasopharyngeal carcinoma with lymph node metastasis. Level of evidence: III.

A predictive model of lymph node metastasis after thoracoscopic surgery for lung adenocarcinoma with a diameter≤3 cm / 中国胸心血管外科临床杂志

@#Objective    To predict the probability of lymph node metastasis after thoracoscopic surgery in patients with lung adenocarcinoma based on nomogram. Methods    We analyzed the clinical data of the patients with lung adenocarcinoma treated in the department of thoracic surgery of our hospital from June 2018 to May 2021. The patients were randomly divided into a training group and a validation group. The variables that may affect the lymph node metastasis of lung adenocarcinoma were screened out by univariate logistic regression, and then the clinical prediction model was constructed by multivariate logistic regression. The nomogram was used to show the model visually, the receiver operating characteristic (ROC) curve, calibration curve and clinical decision curve to evaluate the calibration degree and practicability of the model. Results    Finally 249 patients were collected, including 117 males aged 53.15±13.95 years and 132 females aged 47.36±13.10 years. There were 180 patients in the training group, and 69 patients in the validation group. There was a significant correlation between the 6 clinicopathological characteristics and lymph node metastasis of lung adenocarcinoma in the univariate logistic regression. The area under the ROC curve in the training group was 0.863, suggesting the ability to distinguish lymph node metastasis, which was confirmed in the validation group (area under the ROC curve was 0.847). The nomogram and clinical decision curve also performed well in the follow-up analysis, which proved its potential clinical value. Conclusion    This study provides a nomogram combined with clinicopathological characteristics, which can be used to predict the risk of lymph node metastasis in patients with lung adenocarcinoma with a diameter≤3 cm.

Establishment of a Predictive Model for Chronic Cough after Pulmonary Resection / 中国肺癌杂志

BACKGROUND@#Chronic cough after pulmonary resection is one of the most common complications, which seriously affects the quality of life of patients after surgery. Therefore, the aim of this study is to explore the risk factors of chronic cough after pulmonary resection and construct a prediction model.@*METHODS@#The clinical data and postoperative cough of 499 patients who underwent pneumonectomy or pulmonary resection in The First Affiliated Hospital of University of Science and Technology of China from January 2021 to June 2023 were retrospectively analyzed. The patients were randomly divided into training set (n=348) and validation set (n=151) according to the principle of 7:3 randomization. According to whether the patients in the training set had chronic cough after surgery, they were divided into cough group and non-cough group. The Mandarin Chinese version of Leicester cough questionnare (LCQ-MC) was used to assess the severity of cough and its impact on patients' quality of life before and after surgery. The visual analog scale (VAS) and the self-designed numerical rating scale (NRS) were used to evaluate the postoperative chronic cough. Univariate and multivariate Logistic regression analysis were used to analyze the independent risk factors and construct a model. Receiver operator characteristic (ROC) curve was used to evaluate the discrimination of the model, and calibration curve was used to evaluate the consistency of the model. The clinical application value of the model was evaluated by decision curve analysis (DCA).@*RESULTS@#Multivariate Logistic analysis screened out that preoperative forced expiratory volume in the first second/forced vital capacity (FEV1/FVC), surgical procedure, upper mediastinal lymph node dissection, subcarinal lymph node dissection, and postoperative closed thoracic drainage time were independent risk factors for postoperative chronic cough. Based on the results of multivariate analysis, a Nomogram prediction model was constructed. The area under the ROC curve was 0.954 (95%CI: 0.930-0.978), and the cut-off value corresponding to the maximum Youden index was 0.171, with a sensitivity of 94.7% and a specificity of 86.6%. With a Bootstrap sample of 1000 times, the predicted risk of chronic cough after pulmonary resection by the calibration curve was highly consistent with the actual risk. DCA showed that when the preprobability of the prediction model probability was between 0.1 and 0.9, patients showed a positive net benefit.@*CONCLUSIONS@#Chronic cough after pulmonary resection seriously affects the quality of life of patients. The visual presentation form of the Nomogram is helpful to accurately predict chronic cough after pulmonary resection and provide support for clinical decision-making.

Classification of bladder cancer based on immune cell infiltration and construction of a risk prediction model for prognosis / 浙江大学学报·医学版

OBJECTIVES@#To classify bladder cancer based on immune cell infiltration score and to construct a risk assessment model for prognosis of patients.@*METHODS@#The transcriptome data and data of breast cancer patients were obtained from the TCGA database. The single sample gene set enrichment analysis was used to calculate the infiltration scores of 16 immune cells. The classification of breast cancer patients was realized by unsupervised clustering, and the sensitivity of patients with different types to immunotherapy and chemotherapy was analyzed. The key modules significantly related to the infiltration of key immune cells were identified by weighted correlation network analysis (WGCNA), and the key genes in the modules were extracted. A risk scoring model and a nomogram for risk assessment of prognosis for bladder cancer patients were constructed and verified.@*RESULTS@#The immune cell infiltration scores of normal tissues and tumor tissues were calculated, and B cells, mast cells, neutrophils, T helper cells and tumor infiltrating lymphocytes were determined to be the key immune cells of bladder cancer. Breast cancer patients were clustered into two groups (Cluster 1 and Custer 2) based on immune cell infiltration scores. Compared with patients with Cluster 1, patients with Cluster 2 were more likely to benefit from immunotherapy (P<0.05), and patients with Cluster 2 were more sensitive to Enbeaten, Docetaxel, Cyclopamine, and Akadixin (P<0.05). WGCNA screened out 35 genes related to key immune cells, and 4 genes (GPR171, HOXB3, HOXB5 and HOXB6) related to the prognosis of bladder cancer were further screened by LASSO Cox regression. The areas under the ROC curve (AUC) of the bladder cancer prognosis risk scoring model based on these 4 genes to predict the 1-, 3- and 5-year survival of patients were 0.735, 0.765 and 0.799, respectively. The nomogram constructed by combining risk score and clinical parameters has high accuracy in predicting the 1-, 3-, and 5-year overall survival of bladder cancer patients.@*CONCLUSIONS@#According to the immune cell infiltration score, bladder cancer patients can be classified. And the bladder cancer prognosis risk scoring model and nomogram based on key immune cell-related genes have high accuracy in predicting the prognosis of bladder cancer patients.

Risk factors for ketoacidosis in children/adolescents with type 1 diabetes mellitus and establishment of a predictive model / 中国当代儿科杂志

OBJECTIVES@#To investigate the risk factors for diabetic ketoacidosis (DKA) in children/adolescents with type 1 diabetes mellitus (T1DM) and to establish a model for predicting the risk of DKA.@*METHODS@#A retrospective analysis was performed on 217 children/adolescents with T1DM who were admitted to General Hospital of Ningxia Medical University from January 2018 to December 2021. Among the 217 children/adolescents,169 cases with DKA were included as the DKA group and 48 cases without DKA were included as the non-DKA group. The risk factors for DKA in the children/adolescents with T1DM were analyzed, and a nomogram model was established for predicting the risk of DKA in children/adolescents with T1DM.@*RESULTS@#For the 217 children/adolescents with T1DM, the incidence rate of DKA was 77.9% (169/217). The multivariate logistic regression analysis showed that high levels of random blood glucose, hemoglobin A1c (HbA1c), blood ketone body, and triglyceride on admission were closely associated with the development of DKA in the children/adolescents with T1DM (OR=1.156, 3.2031015, 20.131, and 9.519 respectively; P<0.05). The nomogram prediction model had a C-statistic of 0.95, with a mean absolute error of 0.004 between the risk of DKA predicted by the nomogram model and the actual risk of DKA, indicating that the model had a good overall prediction ability.@*CONCLUSIONS@#High levels of random blood glucose, HbA1c, blood ketone body, and triglyceride on admission are closely associated with the development of DKA in children/adolescents with T1DM, and targeted intervention measures should be developed to reduce the risk of DKA.

Construction of a individualized model for predicting the risk of recurrence in patients with retinal vein occlusion induced macular edema / 国际眼科杂志(Guoji Yanke Zazhi)

AIM: To analyze the recurrence factors of patients with retinal vein occlusion(RVO)induced macular edema(ME)and construct a nomogram model.METHODS: Retrospective study. A total of 306 patients with RVO induced ME admitted to our hospital from January 2019 to June 2022 were included as study objects, and they were divided into modeling group with 214 cases(214 eyes)and 92 cases(92 eyes)in the verification group by 7:3. All patients were followed up for 1 a after receiving anti-vascular endothelial growth factor(VEGF)treatment, and patients in the modeling group were separated into a recurrence group(n=66)and a non recurrence group(n=148)based on whether they had recurrence. Clinical data were collected and multivariate Logistic regression was applied to analyze and determine the factors affecting recurrence in patients with RVO induced ME; R3.6.3 software was applied to construct a nomogram model for predicting the recurrence risk of patients with RVO induced ME; ROC curve and calibration curve were applied to evaluate the discrimination and consistency of nomogram model in predicting the recurrence risk of patients with RVO induced ME.RESULTS: There were statistically significant differences in central retinal thickness(CRT), course of disease, hyperreflective foci(HF), disorder of retinal inner layer structure, and injection frequency between the non recurrence group and the recurrence group before treatment(all P&#x0026;#x003C;0.05). The multivariate Logistic regression analysis showed that pre-treatment CRT(OR=1.011), course of disease(OR=1.104), HF(OR=5.074), retinal inner layer structural disorder(OR=4.640), and injection frequency(OR=4.036)were influencing factors for recurrence in patients with RVO induced ME(all P&#x0026;#x003C;0.01). The area under the ROC curve of the modeling group was 0.924(95%CI: 0.882-0.966), the slope of the calibration curve was close to 1, and the results of the Hosmer-Lemeshow goodness of fit test showed that χ2=11.817, P=0.160; the area under the ROC curve of the verification group was 0.939(95%CI: 0.892-0.985), the slope of the calibration curve was close to 1, and the results of the Hosmer-Lemeshow goodness of fit test showed χ2=6.082, P=0.638.CONCLUSION: Pre-treatment CRT, course of disease, HF, disorder of retinal inner layer structure, and injection frequency are independent risk factors for recurrence in patients with RVO induced ME. The nomogram model constructed based on this has a high discrimination and consistency in predicting the recurrence risk of patients with RVO induced ME.

Construction and validation of a prediction model for public acceptance of kidney xenotransplantation in China / 器官移植

Objective To explore the public attitude towards kidney xenotransplantation in China by constructing and validating the prediction model based on xenotransplantation questionnaire. Methods A convenient sampling survey was conducted among the public in China with the platform of Wenjuanxing to analyze public acceptance of kidney xenotransplantation and influencing factors. Using random distribution method, all included questionnaires (n=2 280) were divided into the training and validation sets according to a ratio of 7:3. A prediction model was constructed and validated. Results A total of 2 280 questionnaires were included. The public acceptance rate of xenotransplantation was 71.3%. Multivariate analysis showed that gender, marital status, resident area, medical insurance coverage, religious belief, vegetarianism, awareness of kidney xenotransplantation and whether on the waiting list for kidney transplantation were the independent influencing factors for public acceptance of kidney xenotransplantation (all P<0.05). The area under the curve (AUC) of receiver operating characteristic (ROC) of the prediction model in the training set was 0.773, and 0.785 in the validation set. The calibration curves in the training and validation sets indicated that the prediction models yielded good prediction value. Decision curve analysis (DCA) suggested that the prediction efficiency of the model was high. Conclusions In China, public acceptance of kidney xenotransplantation is relatively high, whereas it remains to be significantly enhanced. The prediction model based on questionnaire survey has favorable prediction efficiency, which provides reference for subsequent research.

Establishment and validation of nomogram prediction model of cefoperazone/sulbactam-induced thrombocytopenia / 中国药房

OBJECTIVE To explore the predictive factors of cefoperazone/sulbactam-induced thrombocytopenia in adult inpatients， and to establish and validate the nomogram prediction model. METHODS Data of adult inpatients treated with cefoperazone/sulbactam in Xi’an Central Hospital from Jun. 30th， 2021 to Jun. 30th， 2023 were retrospectively collected. The training set and internal validation set were randomly constructed in a 7∶3 ratio. Singler factor and multifactor Logistic regression analysis were used to screen the independent predictors of cefoperazone/sulbactam-induced thrombocytopenia. The nomogram was drawn by using “RMS” of R 4.0.3 software， and the predictive performance of the model was evaluated by the receiver operating characteristic curve and C-index curve. Hosmer-Lemeshow goodness-of-fit test was used to evaluate the calibration degree of the model. Using the same standard， the clinical data of hospitalized patients receiving cefoperazone/sulbactam in Xi’an First Hospital in the same period were collected for external validation of the nomogram prediction model. RESULTS A total of 1 045 patients in Xi’an Central Hospital were included in this study， among which 67 patients suffered from cefoperazone/sulbactam-induced thrombocytopenia， with an incidence of 6.41%. After the false positive patients were excluded， 473 patients were included finally， including 331 in the training set and 142 in theinternal validation set. Multifactor Logistic regression analysis showed that age [OR＝1.043， 95%CI （1.017， 1.070）]， estimated glomerular filtration rate （eGFR） [OR＝0.988，95%CI（0.977， 0.998）]， baseline platelet （PLT） [OR＝0.989， 95%CI（0.982， 0.996）]， nutritional risk [OR＝3.863， 95%CI（1.884， 7.921）] and cumulative defined daily doses （DDDs） [OR＝1.082， 95%CI（1.020， 1.147）] were independent predictors for cefoperazone/sulbactam-induced thrombocytopenia （P＜0.05）. The C-index values of the training set and the internal validation set were 0.824 [95%CI （0.759， 0.890）] and 0.828 [95%CI （0.749， 0.933）]， respectively. The results of the Hosmer-Lemeshow test showed that χ 2 values were 0.441 （P＝0.802） and 1.804 （P＝0.406）. In the external validation set， the C-index value was 0.808 [95%CI （0.672， 0.945）]， the χ 2 value of the Hosmer-Lemeshow test was 0.899 （P＝0.638）. CONCLUSIONS The independent predictors of cefoperazone/sulbactam-induced thrombocytopenia include age， baseline PLT， eGFR， nutritional risk and cumulative DDDs. The model has good predictive efficacy and extrapolation ability， which can help clinic identify the potential risk of cefoperazone/sulbactam-induced thrombocytopenia quickly and accurately.

Nomogram including serum ferritin to predict the occurrence of diabetic retinopathy / 国际眼科杂志(Guoji Yanke Zazhi)

AIM:To establish a nomogram model to predict the effect of serum ferritin on diabetic retinopathy and evaluate the model.METHODS:A total of 21 variables, including ferritin, were screened by univariate and multivariate regression analysis to determine the risk factors of diabetic retinopathy. A nomogram prediction model was established for evaluation and calibration.RESULTS:Ferritin, duration of diabetes, hemoglobin, urine microalbumin, regularity of medication and body mass index were included in the nomogram model. The consistency index of the prediction model with serum ferritin was 0.813(95%CI: 0.748-0.879). The calibration curves of internal and external verification showed good performance, and the probability of the threshold suggested by the decision curve was in the range 10% to 90%. The model had a high net profit value.CONCLUSIONS:Serum ferritin is an important risk factor for diabetic retinopathy. A new nomogram model, which includes body mass index, duration of diabetes, ferritin, hemoglobin, urine microalbumin and regularity of medication, has a high predictive accuracy and could provide early prediction for clinicians.

Construction of a column-line graph for predicting the probability of survival in early-stage elderly HER2-positive breast cancer based on the SEER database / 中国临床药理学与治疗学

AIM: To construct column-line plots to predict survival in elderly patients with early-stage HER2-positive breast cancer using the Surveillance, Epidemiology and End Results (SEER) database. METHODS: 5 220 (based on the era of single-targeted therapy) and 1 176 (based on the era of dual-targeted therapy) patients screened in the SEER database were randomized into a training group and an internal validation group. COX proportional risk regression was used to screen survival-related predictors and build a column-line graphical model, and the accuracy and utility of the model were tested using the consistency index (C-index), calibration curves, and time-dependent ROC curves. Patients receiving chemotherapy and non-chemotherapy were statistically paired using two-group propensity score matching, and subgroup analyses were performed on the screened variables. RESULTS: The single-targeted therapy era line graph was constructed from seven variables: age, marital status, T-stage, N-stage, surgery, chemotherapy, and radiotherapy. The dual-targeted therapy era line graph was constructed from five variables: age, AJCC staging, surgery, chemotherapy, and radiotherapy. The results of the subgroup analysis showed that older HER2-positive breast cancer patients who received chemotherapy had better OS. CONCLUSION: Based on the SEER database, an accurate column-line graph predicting survival in elderly patients with early-stage HER2-positive breast cancer was established and validated. This study suggests that chemotherapy increases survival benefit in elderly patients.

Comprehensive analysis of clinicopathologic and sonographic features in thyroid cancer with skip lymph node metastasis: establish and assessment of a prediction nomogram

Abstract Lateral Lymph Node Metastasis (LLNM) is common in Papillary Thyroid Carcinoma (PTC) and is associated with a poor prognosis. LLNM without central lymph node metastasis as skip metastasis is not common. We aimed to investigate clinicopathologic and sonographic risk factors for skip metastasis in PTC patients, and to establish a nomogram for predicting the possibility of skip metastasis in order to determine the therapeutic strategy. We retrospectively reviewed the data of 1037 PTC patients who underwent surgery from 2016 to 2020 at a single institution. Univariate and multivariate analyses were used to identify the clinicopathologic and preoperative sonographic risk factors of skip metastasis. A nomogram including the risk factors for predicting skip metastasis was further developed and validated. The incidence of skip metastasis was 10.7%. The univariate and multivariate analyses suggested that gender (p = 0.001), tumor location (p = 0.000), extrathyroidal extension (p = 0.000), and calcification (p = 0.000) were independent risk factors. For papillary thyroid microcarcinoma, tumor location (p = 0.000) and calcification (p = 0.001) were independent risk factors. A nomogram according to the clinicopathologic and sonographic predictors was developed. The receiver operating characteristic curve indicated that AUC was 0.824 and had an excellent consistency. The calibration plot analysis showed a good performance and clinical utility of the model. Decision curve analysis revealed it was clinically useful. A nomogram for predicting the probability of skip metastasis was developed, which exhibited a favorable predictive value and consistency. For the female PTC patient, tumor located at the upper pole is more likely to have skip metastasis. Surgeons and sonographers should pay close attention to the patients who have the risk factors. Evidence level: This article's evidence level is 3. Level 3 evidence is derived from nonrandomized, controlled clinical trials. In this study, patients who receive an intervention are compared to a control group. Authors may detect a statistically significant and clinically relevant outcome.

Impact of crossplay between ocular aberrations and depth of focus in topo-guided laser-assisted in situ keratomileusis outcomes

Purpose: To develop a nomogram in cases with mismatch between subjective and Topolyzer cylinder, and based on the magnitude of the mismatch, customize a treatment plan to attain good visual outcomes post?laser?assisted in situ keratomileusis (LASIK) surgery. Methods: The patients were evaluated preoperatively using corneal tomography with Pentacam. Five optimal corneal topography scans were obtained from the Topolyzer Vario were used for planning the LASIK treatment. For the nomogram purpose, the patients were divided into three categories based on the difference between the subjective cylinder and Topolyzer (corneal) cylinder. The first group (group 1) consisted of eyes of patients, where the difference was less than or equal to 0.4 D. The second group (group 2) consisted of eyes, where the difference was more than 0.4 D and the subjective cylinder was lesser than the Topolyzer cylinder. The third group (group 3) included eyes where the difference was more than 0.4 D but the subjective cylinder was greater than the Topolyzer cylinder. LASIK was performed with the WaveLight FS 200 femtosecond laser and WaveLight EX500 excimer laser. Assessment of astigmatism correction for the three groups was done using Aplins vector analysis. For comparison of proportions, Chi?square test was used. A P value less than 0.05 was considered statistically significant. Results: The UDVA was statistically significantly different when compared between groups 1 and 2 (P = 0.02). However, the corrected distance visual acuity (CDVA) was similar among all the three groups (P = 0.1). Group 3 showed an increase of residual cylinder by ?0.25 D, which was significant at intermediate and near reading distances (P < 0.05). Group 3 showed significantly higher target?induced astigmatism (TIA) compared to groups 1 and 2 (P = 0.01). The mean surgically induced astigmatism (SIA) was the least in group 2, which was statistically significant (P < 0.01). Conclusion: The outcomes for distance vision using our nomogram postoperatively were excellent, but further refinement for improving the near vision outcomes is required

Establishment of risk stratification model for developing cirrhosis in patients with HBeAg-negative chronic hepatitis B virus infection / 中华检验医学杂志

Objective:To explore the independent predictive factors of cirrhosis in patients with hepatitis B e antigen (HBeAg)-negative chronic hepatitis B virus (HBV) infection, and establish a nomogram model based on clinical laboratory data and analyze the predictive value of this model.Methods:The laboratory data of 596 patients with HBeAg-negative chronic HBV infection and 677 patients with hepatitis B cirrhosis, who were hospitalized in the First Hospital of China Medical University from 2011 to 2021, were retrospectively analyzed. Patients were randomly divided into training group ( n=892) and validation group ( n=381) at the ratio of 7∶3. The independent predictive factors of cirrhosis were analyzed by univariate logistic regression, multiple collinearity test and multivariate logistic regression. The nomogram model was established and the prediction value of this model was evaluated. Results:According to multivariate logistic regression analysis, hepatitis B core antibody ( OR=1.492, 95% CI 1.316-1.706), glutamine transpeptidase ( OR=1.015, 95% CI 1.010-1.022), platelet ( OR=0.986, 95% CI 0.982-0.988) and albumin ( OR=0.853, 95% CI 0.824-0.882) were independent predictors of cirrhosis ( P<0.05), and the nomogram was established based on the four indicators. Receiver operating characteristic curves showed that area under the curve of the nomogram was 0.933 (95% CI 0.916-0.950), and that of the validation group was 0.931 (95% CI 0.905-0.956). The calibration curves indicated the nomogram model was highly consistent with the actual outcome. Decision curves and clinical impact curves confirmed that the model had high net benefit and good clinical application performance. Conclusions:Hepatitis B core antibody, glutamine transpeptidase, platelet and albumin are independent predictors of cirrhosis among patients with HBeAg-negative chronic HBV infection. The newly developed nomogram model based on these factors could be used to predict cirrhosis risk in these patients.

Establishment and validation of nomogram model for intraocular hypertension after femtosecond laser in situ keratomileusis for high myopia / 中华眼底病杂志

Objective:To investigate the risk factors of high intraocular pressure (IOP) after femtosecond laser in situ keratomileusis (FS-LASIK) in patients with high myopia, and construct and verify nomogram model.Methods:A retrospective clinical study. From January 2019 to January 2021, 327 patients (654 eyes) with high myopia treated with FS-LASIK in the Department of Ophthalmology of the 910th Hospital of the People's Liberation Army Coalition Security Force were included in the study. The patients were categorized into high IOP group and non-high IOP group according to whether high IOP occurred after surgery, which were 60 cases and 120 eyes (18.35%, 60/327) and 267 cases and 534 eyes (81.65%, 267/327), respectively. The clinical data of patients in the two groups were analyzed and observed, and the indicators with differences were subjected to one-way and multifactorial logistic regression analyses, and the results of the regression analyses were visualized to obtain the column line graphs using R3.5.3 software, and the accuracy of the column line graphs was verified by the consistency index (C-index), the calibration curves, and the subject's work characteristic curves (ROC curves).Results:Comparison of the number of cases of affected corneal thickness ( χ2=7.424), corneal curvature ( χ2=9.849), glucocorticoid treatment ( χ2=7.222), intraoperative IOP fluctuation ( χ2=11.475), corneal hysteresis ( χ2=6.368), and the incidence of intraoperative complications ( χ2=6.673) in the hypertensive IOP group and the nonvisualized IOP group were statistically significant ( P<0.05). Binary logistic regression analysis showed that corneal thickness >450 μm, corneal curvature≤38 D, glucocorticoid treatment, intraoperative IOP fluctuation, corneal hysteresis ≤8.0 mm Hg (1 mm Hg=0.133 kPa), and intraoperative complications were the risk factors for the occurrence of high IOP after FS-LASIK surgery in patients with high myopia ( P<0.05). The C-index of the column-line graph prediction model based on this was 0.722 (95% confidence interval 0.684-0.760), the calibration curve and the ideal curve were basically the same, and the area under the ROC curve was 0.709. Conclusions:Corneal thickness> 450 μm, keratometric curvature ≤38 D, glucocorticoid treatment, intraoperative fluctuation of intraocular pressure, and corneal hysteresis ≤8.0 mm Hg are the risk factors for the development of hyperopic IOP in highly risk factors for the development of high IOP after FS-LASIK surgery in myopic patients. The column-line diagram model constructed on the basis of the risk factors hava good accuracy.

Analysis of risk factors for retinal detachment in myopic patients and construction of Nomogram prediction model / 中华眼底病杂志

Objective:To analyze the risk factors associated with retinal detachment in patients with myopia, and to establish and validate the predictive column-line diagram model.Methods:A cross-sectional clinical study. From January 2020 to November 2021, 90 patients with myopia combined with retinal detachment who were diagnosed by ophthalmologic examination in the People's Hospital of Ningxia Hui Autonomous Region were included in the study (observation group). Ninety myopic patients with age- and gender-matched myopia who underwent ophthalmologic examination for myopia during the same period were selected as the control group. The clinical data of the two groups were analyzed, and the indicators with differences were subjected to univariate and multivariate logistic regression analyses. The results of the regression analyses were visualized by using R software to obtain the column charts, and the accuracy of the column charts was verified by the ROC curves of the subjects' work characteristics; the clinical efficacy of the column chart model was verified by the internal data.Results:Compared with the control group, patients in the observation group were older, had higher myopic refraction, had more visual fatigue, ocular trauma, and cataracts, had lower choroidal and retinal thickness, and had more history of ophthalmic surgery, and the differences were statistically significant ( P<0.05). The area under the ROC curve (AUC) for age, myopic refraction, retinal thickness, and choroidal thickness were 0.612, 0.613, 0.720, and 0.704, respectively; the optimal cutoff values were 43 years old, -3.5 D, 225 μm, and 144 μm. the ROC values were 0.612, 0.613, 0.720, and 0.704 for age (>43 years old), myopic refraction (>-3.5 D), visual fatigue (yes), ocular trauma (yes), cataracts (yes), retinal thickness (≤225 μm), and choroidal thickness (≤144 μm) were the risk factors affecting the development of retinal detachment in myopic patients ( P<0.05). The consistency index of the column chart model for predicting the risk of retinal detachment in patients with myopia was 0.731 (95% confidence interval 0.665-0.824); the risk threshold for predicting the development of retinal detachment in patients was >0.07. Conclusions:Age >43 years, myopic refraction >-3.5 D, presence of visual fatigue, ocular trauma, cataract, retinal thickness ≤225 μm, choroidal thickness ≤144 μm are the risk factors affecting the development of retinal detachment in myopic patients. The column-line diagram model constructed on the basis of the risk factors has good accuracy.

Establishment and validation of nomogram model for visual prognosis of macular edema secondary to retinal branch vein occlusion treated with ranibizumab / 中华眼底病杂志

Objective:To explore the influencing factors of visual prognosis of macular edema secondary to branch retinal vein occlusion (BRVO-ME) after treatment with ranibizumab, and construct and verify the nomogram model.Methods:A retrospective study. A total of 130 patients with BRVO-ME diagnosed by ophthalmology examination in the Department of Ophthalmology, Liuzhou Red Cross Hospital from January 2019 to December 2021 were selected in this study. All patients received intravitreal injection of ranibizumab. According to the random number table method, the patients were divided into the training set and the test set with a ratio of 3:1, which were 98 patients (98 eyes) and 32 patients (32 eyes), respectively. According to the difference of logarithm of the minimum angle of resolution (logMAR) best corrected visual acuity (BCVA) at 6 months after treatment and logMAR BCVA before treatment, 98 patients (98 eyes) in the training set were divided into good prognosis group (difference ≤-0.3) and poor prognosis group (difference >-0.3), which were 58 patients (58 eyes) and 40 patients (40 eyes), respectively. The clinical data of patients in the two groups were analyzed, univariate and multivariate logistic regression analysis were carried out for the different indicators, and the visualization regression analysis results were obtained by using R software. The consistency index (C-index), convolutional neural network (CNN), calibration curve and receiver operating characteristic (ROC) curve were used to verify the accuracy of the nomogram model.Results:Univariate analysis showed that age, disease course, outer membrane (ELM) integrity, elliptical zone (EZ) integrity, BCVA, center macular thickness (CMT), outer hyperreflective retinal foci (HRF), inner retina HRF, and the blood flow density of retinal deep capillary plexus (DCP) were risk factors affecting the visual prognosis after treatment with ranibizumab in BRVO-ME patients ( P<0.05). Multivariate logistic regression analysis showed that course of disease, ELM integrity, BCVA and outer HRF were independent risk factors for visual prognosis after ranibizumab treatment for BRVO-ME patients ( P<0.05). The ROC area under the curve of the training set and the test set were 0.846[95% confidence interval ( CI) 0.789-0.887) and 0.852 (95% CI 0.794 -0.873)], respectively; C-index were 0.836 (95% CI 0.793-0.865) and 0.845 (95% CI 0.780-0.872), respectively. CNN showed that the error rate gradually stabilized after 300 cycles, with good model accuracy and strong prediction ability. Conclusions:Course of disease, ELM integrity, BCVA and outer HRF were independent risk factors of visual prognosis after ranibizumab treatment in BRVO-ME patients. The nomogram model based on risk factors has good differentiation and accuracy.

Study on predicting the risk of retinal vein occlusion based on nomogram model and systemic risk factors / 中华眼底病杂志

Objective:To establish and preliminarily validate a nomogram model for predicting the risk of retinal vein occlusion (RVO).Methods:A retrospective clinical study. A total of 162 patients with RVO (RVO group) diagnosed by ophthalmology examination in The Second Affiliated Hospital of Xi'an Jiaotong University from January 2017 to April 2022 and 162 patients with age-related cataract (nRVO group) were selected as the modeling set. A total of 45 patients with branch RVO, 45 patients with central RVO and 45 patients with age-related cataract admitted to Xi'an Fourth Hospital from January 2022 to February 2023 were used as the validation set. There was no significant difference in gender composition ratio ( χ2=2.433) and age ( Z=1.006) between RVO group and nRVO group ( P=0.120, 0.320). Age, gender, blood routine (white blood cell count, hemoglobin concentration, platelet count, neutrophil count, monocyte count, lymphocyte count, erythrocyte volume, mean platelet volume, platelet volume distribution width), and four items of thrombin (prothrombin time, activated partial thrombin time, fibrinogen, and thrombin time) were collected in detail ), uric acid, blood lipids (total cholesterol, triglyceride, high-density lipoprotein, low-density lipoprotein, lipoprotein a), hypertension, diabetes mellitus, coronary heart disease, and cerebral infarction. Neutrophil/lymphocyte ratio and platelet/lymphocyte ratio were calculated. The single logistic regression was used to analyze the clinical parameters of the two groups of patients in the modeling set, and the stepwise regression method was used to screen the variables, and the column graph for predicting the risk of RVO was constructed. The Bootstrap method was used to repeated sample 1 000 times for internal and external verification. The H-L goodness-of-fit test and receiver operating characteristic (ROC) curve were used to evaluate the calibration and discrimination of the nomogram model. Results:After univariate logistic regression and stepwise regression analysis, high density lipoprotein, neutrophil count and hypertension were included in the final prediction model to construct the nomogram. The χ2 values of the H-L goodness-of-fit test of the modeling set and the validation set were 0.711 and 4.230, respectively, and the P values were 0.701 and 0.121, respectively, indicating that the nomogram model had good prediction accuracy. The area under the ROC curve of the nomogram model for predicting the occurrence of post-stroke depression in the modeling set and the verification set was 0.741 [95% confidence interval ( CI) 0.688-0.795] and 0.741 (95% CI 0.646-0.836), suggesting that the nomogram model had a good discrimination. Conclusions:Low high density lipoprotein level, high neutrophil count and hypertension are independent risk factors for RVO. The nomogram model established based on the above risk factors can effectively assess and quantify the risk of post-stroke depression in patients with cerebral infarction.