scholarly journals A Nomogram for Predicting Intraoperative Hemodynamic Instability in Patients With Pheochromocytoma

2022 ◽  
Vol 12 ◽  
Author(s):  
Zhiqiang Zhang ◽  
Yunlin Ye ◽  
Jiajie Yu ◽  
Shufen Liao ◽  
Weibin Pan ◽  
...  
Keyword(s):  
Characteristic Curve ◽  
Clinical Effectiveness ◽  
Hemodynamic Instability ◽  
Calibration Plot ◽  
Surgical Removal ◽  
Lemeshow Test ◽  
Life Threatening ◽  
Selection Operator ◽  
Risk Predictors ◽  
Good Agreement

PurposeSurgical removal of pheochromocytoma (PCC), including open, laparoscopic, and robot-assisted adrenalectomy, is the cornerstone of therapy, which is associated with high risk of intraoperative and postoperative life-threatening complications due to intraoperative hemodynamic instability (IHD). This study aims to develop and validate a nomogram based on clinical characteristics as well as computed tomography (CT) features for the prediction of IHD in pheochromocytoma surgery.MethodsThe data from 112 patients with pheochromocytoma were collected at a single center between January 1, 2010, and December 31, 2019. Clinical and radiological features were selected with the least absolute shrinkage and selection operator regression analysis to predict IHD then constitute a nomogram. The performance of the nomogram was assessed in terms of discrimination, calibration, and clinical utility.ResultsAge, tumor shape, Mayo Adhesive Probability score, laterality, necrosis, body mass index, and surgical technique were identified as risk predictors of the presence of IHD. The nomogram was then developed using these seven variables. The model showed good discrimination with a C-index of 0.773 (95% CI, 0.683–0.862) and an area under the receiver operating characteristic curve (AUC) of 0.739 (95% CI, 0.642–0.837). The calibration plot suggested good agreement between predicted and actual probabilities. Besides, calibration was tested with the Hosmer–Lemeshow test (P = 0.961). The decision curve showed the clinical effectiveness of the nomogram.ConclusionsOur nomogram based on clinical and CT parameters could facilitate the treatment strategy according to assessment of the risk of IHD in patients with pheochromocytoma.

Development and Validation of a Nomogram for Predicting Bladder Calculi Risk in Patients With Benign Prostatic Hyperplasia

2021 ◽  
Author(s):  
Euxu Xie ◽  
Xuelian Gu ◽  
Chen Ma ◽  
Li Guo ◽  
Man Li ◽  
...  
Keyword(s):  
Risk Factors ◽  
Benign Prostatic Hyperplasia ◽  
Characteristic Curve ◽  
Prostatic Hyperplasia ◽  
Calibration Plot ◽  
Lasso Regression ◽  
Net Benefit ◽  
Bladder Calculi ◽  
Validation Set ◽  
Selection Operator

Abstract Objective To develop and validate a nomogram for predicting bladder calculi risk in patients with benign prostatic hyperplasia (BPH).Methods A total of 368 patients who underwent transurethral resection of the prostate (TURP) and had histologically proven BPH from January 2018 to January 2021 were retrospectively collected. Eligible patients were randomly assigned to the training and validation datasets. Least absolute shrinkage and selection operator (LASSO) regression was used to select the optimal risk factors. A prediction model was established based on the selected characteristics. The performance of the nomogram was assessed by calibration plots and the area under the receiver operating characteristic curve (AUROC). Furthermore, decision curve analysis (DCA) was used to determine the net benefit rate of of the nomogram. Results Among 368 patients who met the inclusion criteria, older age, a history of diabetes and hyperuricemia, longer intravesical prostatic protrusion (IPP)and larger prostatic urethral angulation (PUA) were independent risk factors for bladder calculi in patients with BPH. These factors were used to develop a nomogram, which had a good identification ability in predicting the risk of bladder calculi in patients, with AUROCs of 0.911 (95% CI: 0.876–0.945) in the training set and 0.884 (95% CI: 0.820–0.948) in the validation set. The calibration plot showed that the model had good calibration. Moreover, DCA indicated that the model had a goodclinical benefit. Conclusion We developed and internally validated the first nomogram to date to help physicians assess the risk of bladder calculi in patients with BPH, which may help physicians improve individual interventions and make better clinical decisions.

scholarly journals A Risk Score for Fluconazole Failure among Patients with Candidemia

2017 ◽  
Vol 61 (5) ◽  
Author(s):  
Luis Ostrosky-Zeichner ◽  
Rachel Harrington ◽  
Nkechi Azie ◽  
Hongbo Yang ◽  
Nanxin Li ◽  
...  
Keyword(s):  
High Risk ◽  
Prediction Model ◽  
Positive Culture ◽  
The United States ◽  
Content Type ◽  
C Statistic ◽  
Lemeshow Test ◽  
Selection Operator ◽  
Risk Predictors ◽  
Antifungal Use

ABSTRACT This study aimed to develop a prediction model to identify patients with candidemia who were at high risk of failing fluconazole treatment. Adult patients in the United States with candidemia who received fluconazole during hospitalization were selected from the Cerner Health Facts Hospital Database (04/2004 to 03/2013). Fluconazole failure was defined as switching/adding another antifungal, positive Candida culture ≥10 days after fluconazole initiation, or death during hospitalization. Patients were randomized into modeling and validation samples. Using the modeling sample, a regression analysis of least absolute shrinkage and selection operator was used to select risk predictors of fluconazole failure (demographics, Candida species, initiation of fluconazole before positive culture and after admission, and comorbidities, procedures, and treatments during the 6 months before admission and fluconazole initiation). The prediction model was evaluated using the validation sample. We found that of 987 identified patients (average age of 61 years, 51% male, 72% Caucasian), 49% failed and 51% did not fail fluconazole treatment. Of those who failed, 70% switched or added another antifungal, 21% had a second positive Candida test, and 42% died during hospitalization. Nine risk factors were included in the prediction model: days to start fluconazole after admission, Candida glabrata or Candida krusei infection, hematological malignancy, venous thromboembolism (VTE), enteral nutrition, use of nonoperative intubation/irrigation, and other antifungal use. All but VTE were associated with a higher risk of failure. The model's c-statistic was 0.65, with a Hosmer-Lemeshow test P value of 0.23. In summary, this prediction model identified patients with a high risk of fluconazole failure, illustrating the potential value and feasibility of personalizing candidemia treatment.

scholarly journals Development of a nomogram for predicting the presence of combined pulmonary fibrosis and emphysema

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xueting Yuan ◽  
Jin Jin ◽  
Xiaomao Xu
Keyword(s):  
Risk Factors ◽  
Pulmonary Fibrosis ◽  
Early Recognition ◽  
Pulmonary Function Tests ◽  
Characteristic Curve ◽  
Calibration Plot ◽  
Multivariable Logistic Regression Analysis ◽  
Significant Difference ◽  
Lemeshow Test ◽  
Good Concordance

Abstract Background In the clinical management of patients with combined pulmonary fibrosis and emphysema (CPFE), early recognition and appropriate treatment is essential. This study was designed to develop an accurate prognostic nomogram model to predict the presence of CPFE. Methods We retrospectively enrolled 85 patients with CPFE and 128 patients with idiopathic pulmonary fibrosis (IPF) between January 2015 and January 2020. Clinical characteristics were compared between groups. A multivariable logistic regression analysis was performed to identify risk factors for CPFE. Then, and a nomogram to predict the presence of CPFE was constructed for clinical use. Concordance index (C-index), area under the receiver operating characteristic curve (AUC), and calibration plot was used to evaluate the efficiency of the nomogram. Results Compared to the IPF group, the proportion of patients with male, smoking and allergies were significantly higher in the CPFE group. In terms of pulmonary function tests, patients with CPFE had lower FEV1/FVC%, DLCO/VA% pred, and higher RV, RV%pred, VC, VC%pred, TLC%pred, VA, TLC, TLC%pred, FVC, FVC%pred and FEV1 with significant difference than the other group. Positive correlation was found between DLCO and VA%, RV%, TLC% in patients with IPF but not in patients with CPFE. By multivariate analysis, male, smoking, allergies, FEV1/FVC% and DLCO/VA%pred were identified as independent predictors of the presence of CPFE. The nomogram was then developed using these five variables. After 1000 internal validations of bootstrap resampling, the C-index of the nomogram was 0.863 (95% CI 0.795–0.931) and the AUC was 0.839 (95% CI 0.764–0.913). Moreover, the calibration plot showed good concordance of incidence of CPFE between nomogram prediction and actual observation (Hosmer–Lemeshow test: P = 0.307). Conclusions Patients of CPFE have a characteristic lung function profile including relatively preserved lung volumes and ventilating function, contrasting with a disproportionate reduction of carbon monoxide transfer. By incorporating clinical risk factors, we created a nomogram to predict the presence of CPFE, which may serve as a potential tool to guide personalized treatment.

scholarly journals Risk factors of prolonged ventilation after thymectomy in thymoma myasthenia gravis patients

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Anqi Du ◽  
Xiao Li ◽  
Youzhong An ◽  
Zhancheng Gao
Keyword(s):  
Risk Factors ◽  
Myasthenia Gravis ◽  
Characteristic Curve ◽  
Operation Time ◽  
Calibration Plot ◽  
Multivariable Logistic Regression Analysis ◽  
Predictive Tool ◽  
Prolonged Ventilation ◽  
Peking University ◽  
Lemeshow Test

Abstract Background To explore the risk factors for prolonged ventilation after thymectomy in patients with thymoma associated with myasthenia gravis (TAMG). Methods We reviewed the records of 112 patients with TAMG after thymectomy between January 2010 and December 2019 in Peking University People’s Hospital. Demographic, pathological, preoperative data and the Anesthesia, surgery details were assessed with multivariable logistic regression analysis to predict the risk of prolonged ventilation after thymectomy. A nomogram to predict the probability of post-thymectomy ventilation was constructed with R software. Discrimination and calibration were employed to evaluate the performance of the nomogram. Results By multivariate analysis, male, low vital capacity (VC), Osserman classification (IIb, III, IV), total intravenous anesthesia, and long operation time were identified as the risk factors and entered into the nomogram. The nomogram showed a robust discrimination, with an area under the receiver operating characteristic curve (AUC) of 0. 835 (95% confidence interval [CI], 0.757–0.913). The calibration plot indicated that the nomogram-predicted probabilities compared very well with the actual probabilities (Hosmer–Lemeshow test: P = 0.921). Conclusion The nomogram is a valuable predictive tool for prolonged ventilation after thymectomy in patients with TAMG.

Biomarker-based score for predicting in-hospital mortality of children admitted to the intensive care unit

2021 ◽  
pp. jim-2021-001855
Author(s):  
Yin Zhang ◽  
Qingxia Shi ◽  
Guochao Zhong ◽  
Xun Lei ◽  
Jilei Lin ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Predictive Model ◽  
Characteristic Curve ◽  
Calibration Plot ◽  
P Value ◽  
Lasso Regression ◽  
Risk Of Death ◽  
Lemeshow Test

This study aims to establish a new scoring system based on biomarkers for predicting in-hospital mortality of children admitted to the pediatric intensive care unit (PICU). The biomarkers were chosen using the least absolute shrinkage and selection operator (LASSO)-logistic regression in this observational case-control study. The performance of the new predictive model was evaluated by the area under the receiver operating characteristic curve (AUC). Calibration plot was established to validate the new score accompanied by the Hosmer-Lemeshow test. There were 8818 patients included in this study. Finally, six predictors were included in the LASSO-regression model. Albumin <40 g/L, lactate dehydrogenase >452 U/L, lactate >3.2 mmol/L, urea >5.6 mmol/L, arterial PH <7.3 and glucose >6.9 mmol/L were treated as risk factors for higher mortality. The new score ranged from 1 to 6 among all the included patients. In the training set, the AUC of the probability of in-hospital mortality for the new predictive model was 0.81 (95% CI 0.79 to 0.84), which is larger than for the Pediatric Critical Illness Score (PCIS) (0.69, 95% CI 0.66 to 0.72). Similarly, in the validating set, the AUC of the probability of in-hospital mortality was larger for the new score (0.80, 95% CI 0.77 to 0.84) than for PCIS (0.67, 95% CI 0.63 to 0.72). The calibration plot and Hosmer-Lemeshow test showed excellent calibration. The calculated ORs showed a trend that higher scores indicated higher risk of death (p value for trend <0.001). In summary, this study develops and validates a totally biomarker-based new score to predict in-hospital mortality for pediatric patients admitted to PICU. More attention and more positive care and treatment should be given to children with a higher score.

scholarly journals Novel Gene Signatures Predictive of Patient Recurrence-Free Survival and Castration Resistance in Prostate Cancer

Cancers ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 917
Author(s):  
Jun A ◽  
Baotong Zhang ◽  
Zhiqian Zhang ◽  
Hailiang Hu ◽  
Jin-Tang Dong
Keyword(s):  
Prostate Cancer ◽  
Cox Regression ◽  
Characteristic Curve ◽  
Treatment Decision ◽  
Rank Aggregation ◽  
Lymph Node Status ◽  
Calibration Plot ◽  
Recurrence Free Survival ◽  
Castration Resistance ◽  
Free Survival

Molecular signatures predictive of recurrence-free survival (RFS) and castration resistance are critical for treatment decision-making in prostate cancer (PCa), but the robustness of current signatures is limited. Here, we applied the Robust Rank Aggregation (RRA) method to PCa transcriptome profiles and identified 287 genes differentially expressed between localized castration-resistant PCa (CRPC) and hormone-sensitive PCa (HSPC). Least absolute shrinkage and selection operator (LASSO) and stepwise Cox regression analyses of the 287 genes developed a 6-gene signature predictive of RFS in PCa. This signature included NPEPL1, VWF, LMO7, ALDH2, NUAK1, and TPT1, and was named CRPC-derived prognosis signature (CRPCPS). Interestingly, three of these 6 genes constituted another signature capable of distinguishing CRPC from HSPC. The CRPCPS predicted RFS in 5/9 cohorts in the multivariate analysis and remained valid in patients stratified by tumor stage, Gleason score, and lymph node status. The signature also predicted overall survival and metastasis-free survival. The signature’s robustness was demonstrated by the C-index (0.55–0.74) and the calibration plot in all nine cohorts and the 3-, 5-, and 8-year area under the receiver operating characteristic curve (0.67–0.77) in three cohorts. The nomogram analyses demonstrated CRPCPS’ clinical applicability. The CRPCPS thus appears useful for RFS prediction in PCa.

scholarly journals Prognostic nomogram for the severity of acute organophosphate insecticide self-poisoning: a retrospective observational cohort study

BMJ Open ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. e042765
Author(s):  
Ning Dong ◽  
Shaokun Wang ◽  
Xingliang Li ◽  
Wei Li ◽  
Nan Gao ◽  
...  
Keyword(s):  
New York ◽  
Characteristic Curve ◽  
Oral Intake ◽  
Heart Association ◽  
Northern China ◽  
Primary Outcome Measure ◽  
Plasma Cholinesterase ◽  
Hospital Death ◽  
Calibration Plot ◽  
Organophosphate Insecticide

ObjectiveTo develop a convenient nomogram for the bedside evaluation of patients with acute organophosphorus poisoning (AOPP).DesignThis was a retrospective study.SettingTwo independent hospitals in northern China, the First Hospital of Jilin University and the Lequn Hospital of the First Hospital of Jilin University.ParticipantsA total of 1657 consecutive patients admitted for the deliberate oral intake of AOPP within 24 hours from exposure and aged >18 years were enrolled between 1 January 2013 and 31 December 2018. The exclusion criteria were: normal range of plasma cholinesterase, exposure to any other type of poisonous drug(s), severe chronic comorbidities including symptomatic heart failure (New York Heart Association III or IV) or any other kidney, liver and pulmonary diseases. Eight hundred and thirty-four patients were included.Primary outcome measureThe existence of severely poisoned cases, defined as patients with any of the following complications: cardiac arrest, respiratory failure requiring ventilator support, hypotension or in-hospital death.Results440 patients from one hospital were included in the study to develop a nomogram of severe AOPP, whereas 394 patients from the other hospital were used for the validation. Associated risk factors were identified by multivariate logistic regression. The nomogram was validated by the area under the receiver operating characteristic curve (AUC). A nomogram was developed with age, white cells, albumin, cholinesterase, blood pH and lactic acid levels. The AUC was 0.875 (95% CI 0.837 to 0.913) and 0.855 (95% CI 0.81 to 0.9) in the derivation and validation cohorts, respectively. The calibration plot for the probability of severe AOPP showed an optimal agreement between the prediction by nomogram and actual observation in both derivation and validation cohorts.ConclusionA convenient severity evaluation nomogram for patients with AOPP was developed, which could be used by physicians in making clinical decisions and predicting patients’ prognosis.

scholarly journals Individualized Prediction of Survival Benefits of Pancreatectomy Plus Chemotherapy in Patients With Simultaneous Metastatic Pancreatic Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Duorui Nie ◽  
Guihua Lai ◽  
Guilin An ◽  
Zhuojun Wu ◽  
Shujun Lei ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Tumor Size ◽  
Proportional Hazards ◽  
Survival Curve ◽  
Characteristic Curve ◽  
Cox Proportional Hazards ◽  
Metastatic Pancreatic Cancer ◽  
Calibration Plot ◽  
Term Survival ◽  
Good Ability

BackgroundMetastatic pancreatic cancer (mPC) is a highly lethal malignancy with poorer survival. However, chemotherapy alone was unable to maintain long‐term survival. This study aimed to evaluate the individualized survival benefits of pancreatectomy plus chemotherapy (PCT) for mPC.MethodsA total of 4546 patients with mPC from 2004 to 2015 were retrieved from the Surveillance, Epidemiology, and End Results database. The survival curve was calculated using the Kaplan-Meier method and differences in survival curves were tested using log-rank tests. Cox proportional hazards regression analyses were performed to evaluate the prognostic value of involved variables. A new nomogram was constructed to predict overall survival based on independent prognosis factors. The performance of the nomogram was measured by concordance index, calibration plot, and area under the receiver operating characteristic curve.ResultsCompared to pancreatectomy or chemotherapy alone, PCT can significantly improve the prognosis of patients with mPC. In addition, patients with well/moderately differentiated tumors, age ≤66 years, tumor size ≤42 mm, or female patients were more likely to benefit from PCT. Multivariate analysis showed that age at diagnosis, sex, marital status, grade, tumor size, and treatment were independent prognostic factors. The established nomogram has a good ability to distinguish and calibrating.ConclusionPCT can prolong survival in some patients with mPC. Our nomogram can individualize predict OS of pancreatectomy combined with chemotherapy in patients with concurrent mPC.

scholarly journals Risk Score for Predicting Dysphagia in Patients After Neurosurgery: A Prospective Observational Trial

2021 ◽  
Vol 12 ◽  
Author(s):  
Li Zeng ◽  
Yu Song ◽  
Yan Dong ◽  
Qian Wu ◽  
Lu Zhang ◽  
...  
Keyword(s):  
Tracheal Intubation ◽  
Characteristic Curve ◽  
Feeding Tube ◽  
Apache Ii ◽  
Selection Strategy ◽  
Nasogastric Feeding ◽  
Nasogastric Feeding Tube ◽  
Multicenter Prospective Observational Study ◽  
Validation Set ◽  
Risk Predictors

Background: Acquired dysphagia is common in patients with tracheal intubation and neurological disease, leading to increased mortality. This study aimed to ascertain the risk factors and develop a prediction model for acquired dysphagia in patients after neurosurgery.Methods: A multicenter prospective observational study was performed on 293 patients who underwent neurosurgery. A standardized swallowing assessment was performed bedside within 24 h of extubation, and logistic regression analysis with a best subset selection strategy was performed to select predictors. A nomogram model was then established and verified.Results: The incidence of acquired dysphagia in our study was 23.2% (68/293). Among the variables, days of neurointensive care unit (NICU) stay [odds ratio (OR), 1.433; 95% confidence interval (CI), 1.141–1.882; P = 0.005], tracheal intubation duration (OR, 1.021; CI, 1.001–1.062; P = 0.175), use of a nasogastric feeding tube (OR, 9.131; CI, 1.364–62.289; P = 0.021), and Acute Physiology and Chronic Health Evaluation (APACHE)-II C score (OR, 1.709; CI, 1.421–2.148; P &lt; 0.001) were selected as risk predictors for dysphagia and included in the nomogram model. The area under the receiver operating characteristic curve was 0.980 (CI, 0.965–0.996) in the training set and 0.971 (0.937–1) in the validation set, with Brier scores of 0.045 and 0.056, respectively.Conclusion: Patients who stay longer in the NICU, have a longer duration of tracheal intubation, require a nasogastric feeding tube, and have higher APACHE-II C scores after neurosurgery are likely to develop dysphagia. This developed model is a convenient and efficient tool for predicting the development of dysphagia.

scholarly journals Brain Catastrophe presented with endocrine disruption

2020 ◽  
Vol 8 (5) ◽  
pp. 104-110
Author(s):  
Saadi JS AlJadir
Keyword(s):  
Dynamic Testing ◽  
Hemodynamic Instability ◽  
Major Surgery ◽  
Initial Manifestation ◽  
Altered Level ◽  
Identifiable Risk Factor ◽  
Conflicting Evidence ◽  
Level Of Consciousness ◽  
Threatening Condition ◽  
Life Threatening

Pituitary Apoplexy (PA) is an acute critical endocrine condition that is infrequently encountered in daily medical practice. Its life-threatening condition that mandates prompt diagnosis and urgent treatment and may be neurosurgical intervention. Majority of cases are attributed to ischemic infarction or hemorrhage of the pituitary gland usually in the vicinity of pituitary adenoma, and in most cases could be the initial manifestation of these tumors! In reviewing the literatures there is conflicting evidence of which are the predominant, non-functional, or functional adenomas, some reports were showed that prolactin-secreting are at highest risk. There are recognizable risk factors that might precipitate this endocrine emergency like hypertension, medications, major surgery, head injury, radiation, or dynamic testing, but in majority of cases at presentation no identifiable risk factor could be detected. The typical clinical scenario includes persistent worsening headache, vomiting, and altered level of consciousness, visual defect or loss with extreme hormonal derangements which are shown by hemodynamic instability, adrenal crises with variable hormonal deficiencies.

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