scholarly journals Application Value of Rapid Predictive Model for Readmission Risk in Patients after CABG

2020 ◽  
Vol 23 (5) ◽  
pp. E668-E672
Author(s):  
Tiao Lv ◽  
Yinghong Zhang ◽  
Wen Zhang ◽  
Liu Hu ◽  
Guozhen Liu ◽  
...  
Keyword(s):  
Predictive Model ◽  
Roc Curve ◽  
Test Results ◽  
Good Discrimination ◽  
C Statistic ◽  
Lemeshow Test ◽  
Area Under Roc Curve ◽  
Cabg Patients ◽  
Readmission Risk ◽  
Heart Hospital

Objective: To explore the value of a rapid risk predictive model for the readmission of patients after CABG in China. Methods: The rapid predictive model of readmission risk was translated into Chinese, and then validated with data from 758 patients who underwent CABG in Wuhan Asian Heart Hospital from January 2018 to June 2019. The discrimination was tested by area under the ROC curve (AUC), and the calibration was tested by Hosmer-Lemeshow test. Results: The rapid risk predictive model for readmission showed good discrimination and calibration in Chinese CABG patients (The area under ROC curve c-statistic: 0.704, 95% CI: 0.614-0.794; Hosmer-Lemeshow test: P = .955). Conclusion: The rapid readmission risk predictive model can be used in Chinese CABG patients soon after admission.

scholarly journals Performa Rapid Emergency Medicine Score (REMS) dalam Memprediksi Mortalitas 30 Hari Pasien Usia Lanjut di Instalasi Gawat Darurat

2017 ◽  
Vol 4 (2) ◽  
pp. 62
Author(s):  
Aulia Rizka ◽  
Kuntjoro Harimurti ◽  
Ceva W Pitoyo ◽  
Sukamto Koesnoe
Keyword(s):  
Emergency Medicine ◽  
Elderly Patients ◽  
Roc Curve ◽  
Elderly Subjects ◽  
Calibration Plot ◽  
Mortality Incidence ◽  
Short Term Mortality ◽  
Lemeshow Test ◽  
Area Under Roc Curve ◽  
Test Discrimination

Pendahuluan. Rapid Emergency Medicine Score (REMS) merupakan suatu instrumen yang banyak digunakan untuk melakukan stratifikasi risiko pasien non-bedah di Instalasi Gawat Darurat (IGD). Namun, pasien usia lanjut yang datang ke IGD seringkali datang dengan manifestasi klinis yang atipikal, sehingga performa REMS untuk populasi khusus ini perlu diuji. Penelitian ini dilakukan untuk menilai performa REMS pada populasi pasien usia lanjut yang datang ke IGD.Metode. Dilakukan penelitian kohort prospektif berbasis penelitian prognostik pada pasien usia >60 tahun yang datang ke IGD RS dr. Cipto Mangunkusumo (RSCM), Jakarta selama September hingga Oktober 2016. Subjek diikuti selama 30 hari sejak kedatangan ke IGD. Selanjutnya dilakukan perhitungan kalibrasi (uji Hosmer Lemeshow) dan diskriminasi (perhitungan Area under ROC Curve) REMS dalam memprediksi mortalitas 30 hari pasien usia lanjut.Hasil. Terdapat 321 pasien usia lanjut masuk IGD selama periode penelitian dan 306 di antaranya memenuhi kriteria pemilihan. Dari seluruh subjek, 163 (53,2% pasien adalah laki-laki. Insiden kematian 30 hari sebanyak 22,8% (IK95% 22,3-23,3). Rerata usia 68,3 (SB 6,7) tahun. Sebanyak 83 (27%) pasien dikategorikan triage merah. Terdapat 154 (50%) pasien dengan REMS 0-7, 140 (46%) dengan REMS 8-17 dan 12(4%) with REMS lebih dari 17. Plot kalibrasi menunjukkan r=0,23 dengan hasil uji Hosmer Lemeshow buruk (p=0,00). AUC REMS untuk memprediksi mortalitas 30 hari pasien usia lanjut adalah 0,45 (95% CI 0,23-0,66).Simpulan. REMS menunjukkan performa yang buruk dalam memprediksi mortalitas 30 hari pasien usia lanjut di IGD. Kata Kunci: IGD, mortalitas, REMS, usia lanjut   Validation of Rapid Emergency Medicine Score (REMS) in Predicting 30 days Mortality in Elderly Visiting Emergency DepartmentIntroduction. Rapid Emergency Medicine Score (REMS) has been known as a useful instrument to stratify patients in emergency department (ED) based on its ability to predict short term mortality. As the clinical characteristics of elderly patients visiting ED are frequently aypical, validation of REMS in this specific population is very important. To measure predictive validity of REMS in elderly patients visiting ED Methods. Prospective cohort study in elderly visiting ED of Cipto Mangunkusumo between September to October 2016. Subjects were followed for 30 days after visiting ED. Calibration (Hosmer Lemeshow test), discrimination (Area Under ROC Curve) and REMS predictive value of 30 days mortality were measured. Result. Of 321 elderly subjects visiting ED during study period, 306 subjects were included in the study. Among them, 163 (53,2%) were men. 30 days mortality incidence was 22,8% (95% CI 22,3-23,3). Median age was 68,3 (6,7) year. As many as 83 (27%) subjects were in red triage. There were 154 (50%) patients with REMS 0-7, 140 (46%) with REMS 8-17 and 12(4%) with REMS more than 17. Calibration plot shows r=0,23 with poor calibration (p=0,00) in Hosmer Lemeshow test. AUC of REMS in predicting 30 days mortality in elderly was 0,45 (95% CI 0,23-0,66). Conclusion. REMS shows poor calibration and discrimination in eldery patients visiting ED. 

scholarly journals Temporal Validation of a Predictive Score for Death in Children with Visceral Leishmaniasis

2021 ◽  
Vol 2021 ◽  
pp. 1-6
Author(s):  
Juliana Foinquinos ◽  
Maria do Carmo Duarte ◽  
Jose Natal Figueiroa ◽  
Jailson B. Correia ◽  
Nara Vasconcelos Cavalcanti
Keyword(s):  
Visceral Leishmaniasis ◽  
Predictive Model ◽  
Roc Curve ◽  
Validation Cohort ◽  
Hospital Setting ◽  
Predictive Score ◽  
Convenience Sample ◽  
Derivation Cohort ◽  
Temporal Validation ◽  
Lemeshow Test

Objectives. To perform a temporal validation of a predictive model for death in children with visceral leishmaniasis (VL). Methods. A temporal validation of a children-exclusive predictive model of death due to VL (Sampaio et al. 2010 model), using a retrospective cohort, hereby called validation cohort. The validation cohort convenience sample was made of 156 patients less than 15 years old hospitalized between 2008 and 2018 with VL. Patients included in the Sampaio et al. 2010 study are here denominated derivation cohort, which was composed of 546 patients hospitalized in the same hospital setting in the period from 1996 to 2006. The calibration and discriminative capacity of the model to predict death by VL in the validation cohort were then assessed through the procedure of logistic recalibration that readjusted its coefficients. The calibration of the updated model was tested using Hosmer–Lemeshow test and Spiegelhalter test. A ROC curve was built and the value of the area under this curve represented the model’s discrimination. Results. The validation cohort found a lethality of 6.4%. The Sampaio et al. 2010 model demonstrated inadequate calibration in the validation cohort (Spiegelhalter test: p = 0.007 ). It also presented unsatisfactory discriminative capacity, evaluated by the area under the ROC curve = 0.618. After the coefficient readjustment, the model showed adequate calibration (Spiegelhalter test, p = 0.988 ) and better discrimination, becoming satisfactory (AUROC = 0.762). The score developed by Sampaio et al. 2010 attributed 1 point to the variables dyspnea, associated infections, and neutrophil count <500/mm3; 2 points to jaundice and mucosal bleeding; and 3 points to platelet count <50,000/mm3. In the recalibrated model, each one of the variables had a scoring of 1 point for each. Conclusion. The temporally validated model, after coefficient readjustment, presented adequate calibration and discrimination to predict death in children hospitalized with VL.

5877Comorbidity assessment for mortality risk stratification in elderly patients with acute coronary syndrome

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
M Soler Costa ◽  
J Nunez ◽  
V Ruiz ◽  
C Bonanad ◽  
F Formiga ◽  
...  
Keyword(s):  
Acute Coronary Syndrome ◽  
Risk Stratification ◽  
Elderly Patients ◽  
Predictive Model ◽  
Cardiac Disease ◽  
Reference Category ◽  
Coronary Syndrome ◽  
Medical Disorders ◽  
C Statistic ◽  
Lemeshow Test

Abstract Background The Charlson's is the most used comorbidity index. It comprises 19 comorbidities, some of which are infrequent in elderly patients with acute coronary syndrome (ACS), while some others are manifestations of cardiac disease rather than comorbidities. Purpose Our goal was to simplify comorbidity assessment in elderly non-ST-segment elevation ACS patients. Methods The study group consisted of 1 training (n=920, 76±7 years) and 1 testing (n=532; 84±4 years) cohorts. The end-point was all-cause mortality at 1-year follow-up. Comorbidities were assessed selecting those medical disorders other than cardiac disease that were independently associated with mortality by multivariable analysis. Results A total of 130 (14%) patients died in the training cohort. Six comorbidities were predictive: renal failure, anemia, diabetes, peripheral artery disease, cerebrovascular disease and chronic lung disease. The increase in the number of comorbidities yielded a gradient of risk on top of well-known clinical predictors: ≥3 comorbidities (27% mortality, HR=1.90, 95% CI 1.20–3.03, p=0.006); 2 comorbidities (16% mortality, HR=1.29, 95% CI 0.81–2.04, p=0.30); and 0–1 comorbidities (7.6% mortality, reference category). The discrimination accuracy (C-statistic= 0.80) and calibration (Hosmer-Lemeshow test, p=0.20) of the predictive model using the 6 comorbidities was comparable to the predictive model using the Charlson index (C-statistic=0.80; Hosmer-Lemeshow test, p=0.70). Similar results were reproduced in the testing cohort (≥3 comorbidities: 24% mortality, HR=2.37, 95% CI 1.25–4.49, p=0.008; 2 comorbidities: 14% mortality, HR=1.59, 95% CI 0.82–3.07, p=0.20; 0–1 comorbidities: 7.5% reference category). Kaplan-Meyer curves for mortality Conclusion A simplified comorbidity assessment comprising 6 comorbidities provides useful risk stratification in elderly patients with ACS Acknowledgement/Funding This work was supported by grants from Spain's Ministry of Economy and Competitiveness through the Carlos III Health Institute

MRI features of responsible contacts in vascular compressive trigeminal neuralgia and prediction modeling

2021 ◽  
pp. 028418512098397
Author(s):  
Yufei Zhao ◽  
Jianhua Chen ◽  
Rifeng Jiang ◽  
Xue Xu ◽  
Lin Lin ◽  
...  
Keyword(s):  
Trigeminal Neuralgia ◽  
Predictive Model ◽  
Trigeminal Nerve ◽  
Roc Curve ◽  
Neurovascular Compression ◽  
Diagnostic Efficiency ◽  
Mri Features ◽  
Vascular Origin ◽  
Magnetic Resonance Imaging Mri ◽  
Mri Characteristics

Background Multiple neurovascular contacts in patients with vascular compressive trigeminal neuralgia often challenge the diagnosis of responsible contacts. Purpose To analyze the magnetic resonance imaging (MRI) features of responsible contacts and establish a predictive model to accurately pinpoint the responsible contacts. Material and Methods Sixty-seven patients with unilateral trigeminal neuralgia were enrolled. A total of 153 definite contacts (45 responsible, 108 non-responsible) were analyzed for their MRI characteristics, including neurovascular compression (NVC) grading, distance from pons to contact (Dpons-contact), vascular origin of compressing vessels, diameter of vessel (Dvessel) and trigeminal nerve (Dtrigeminal nerve) at contact. The MRI characteristics of the responsible and non-responsible contacts were compared, and their diagnostic efficiencies were further evaluated using a receiver operating characteristic (ROC) curve. The significant MRI features were incorporated into the logistics regression analysis to build a predictive model for responsible contacts. Results Compared with non-responsible contacts, NVC grading and arterial compression ratio (84.44%) were significantly higher, Dpons-contact was significantly lower at responsible contacts ( P < 0.001, 0.002, and 0.033, respectively). NVC grading had a highest diagnostic area under the ROC curve (AUC) of 0.742, with a sensitivity of 64.44% and specificity of 75.00%. The logistic regression model showed a higher diagnostic efficiency, with an AUC of 0.808, sensitivity of 88.89%, and specificity of 62.04%. Conclusion Contact degree and position are important MRI features in identifying the responsible contacts of the trigeminal neuralgia. The logistic predictive model based on Dpons-contact, NVC grading, and vascular origin can qualitatively improve the prediction of responsible contacts for radiologists.

scholarly journals 651 Longitudinal, unobtrusive, and ecologically valid sleep metric estimation from a smart bed to predict the pathology of COVID-19

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A255-A255
Author(s):  
Dmytro Guzenko ◽  
Gary Garcia ◽  
Farzad Siyahjani ◽  
Kevin Monette ◽  
Susan DeFranco ◽  
...  
Keyword(s):  
Heart Rate ◽  
Sleep Quality ◽  
Predictive Model ◽  
Sleep Duration ◽  
Wearable Sensors ◽  
Test Results ◽  
Cloud Data ◽  
Cardiorespiratory Function ◽  
Group Data ◽  
Rich Information

Abstract Introduction Pathophysiologic responses to viral respiratory challenges such as SARS-CoV-2 may affect sleep duration, quality and concomitant cardiorespiratory function. Unobtrusive and ecologically valid methods to monitor longitudinal sleep metrics may therefore have practical value for surveillance and monitoring of infectious illnesses. We leveraged sleep metrics from Sleep Number 360 smart bed users to build a COVID-19 predictive model. Methods An IRB approved survey was presented to opting-in users from August to November 2020. COVID-19 test results were reported by 2003/6878 respondents (116 positive; 1887 negative). From the positive group, data from 82 responders (44.7±11.3 yrs.) who reported the date of symptom onset were used. From the negative group, data from 1519 responders (48.4±12.9 yrs.) who reported testing dates were used. Sleep duration, sleep quality, restful sleep duration, time to fall asleep, respiration rate, heart rate, and motion level were obtained from ballistocardiography signals stored in the cloud. Data from January to October 2020 were considered. The predictive model consists of two levels: 1) the daily probability of staying healthy calculated by logistic regression and 2) a continuous density Hidden Markov Model to refine the daily prediction considering the past decision history. Results With respect to their baseline, significant increases in sleep duration, average breathing rate, average heart rate and decrease in sleep quality were associated with symptom exacerbation in COVID-19 positive respondents. In COVID-19 negative respondents, no significant sleep or cardiorespiratory metrics were observed. Evaluation of the predictive model resulted in cross-validated area under the receiving-operator curve (AUC) estimate of 0.84±0.09 which is similar to values reported for wearable-sensors. Considering additional days to confirm prediction improved the AUC estimate to 0.93±0.05. Conclusion The results obtained on the smart bed user population suggest that unobtrusive sleep metrics may offer rich information to predict and track the development of symptoms in individuals infected with COVID-19. Support (if any):

NELA.03Laparoscopy in Emergency Surgery is Associated with Lower Risk-Adjusted Mortality

2021 ◽  
Vol 108 (Supplement_7) ◽  
Author(s):  
Alexander Darbyshire ◽  
Ina Kostakis ◽  
Phil Pucher ◽  
David Prytherch ◽  
Simon Toh ◽  
...  
Keyword(s):  
Lower Risk ◽  
Operative Approach ◽  
National Database ◽  
Model Discrimination ◽  
Intestinal Surgery ◽  
Risk Models ◽  
Good Discrimination ◽  
Total Cohort ◽  
C Statistic ◽  
Expected Mortality

Abstract Aims To compare risk-adjusted outcomes after emergency intestinal surgery by operative approach. Methods Data from December 2013-November 2018 was retrieved from the NELA national database. Complete data on 102,154 patients with P-POSSUM was available, and 47,667 had NELA score. AUROC curves were calculated to assess model discrimination (c-statistic), and calibration plots to visualise agreement between predicted and observed mortality.  Standardised Mortality Ratio's (SMR) were calculated for the total cohort and by operative approach. Operative approach was divided into: laparotomy, completed laparoscopically, converted to open and lap assisted. Results Both P-POSSUM and NELA score displayed good discrimination for total cohort and by operative approach (P-POSSUM c-statistic=0.801-0.815; NELA score c-statistic=0.851-0.880).  Calibration plots demonstrated that P-POSSUM was highly accurate up to 20% mortality, after which it substantially over-predicted mortality.  NELA score was highly accurate up to 25% mortality after which it slightly under-predicted. Overall SMR of observed vs expected deaths was 0.77 using P-POSSUM, 0.8 for laparotomy and 0.46 for laparoscopy.  Restricting cases to &lt; 10% predicted mortality (n = 65,000), overall SMR improved (0.9) and was considerably lower for cases completed laparoscopically (0.41) compared to open (0.97).  Using NELA scores of &lt; 10% predicted mortality (n = 27,000) had similar overall SMR (0.96), with cases completed laparoscopically displaying much lower SMR (0.61) compared to laparotomy (1.0). Conclusions SMR's calculated using P-POSSUM and NELA score have demonstrated that laparoscopy has significantly lower observed vs expected mortality rate compared to laparotomy. This raises the question of why laparoscopy is associated with reduced mortality and should operative approach be included in risk models?

scholarly journals Parsing Expression Grammars and Their Induction Algorithm

2020 ◽  
Vol 10 (23) ◽  
pp. 8747
Author(s):  
Wojciech Wieczorek ◽  
Olgierd Unold ◽  
Łukasz Strąk
Keyword(s):  
Genetic Programming ◽  
Roc Curve ◽  
Classification Performance ◽  
Grammatical Inference ◽  
Inference Algorithm ◽  
Finite Sample ◽  
Induction Method ◽  
Grammar Learning ◽  
Area Under Roc Curve ◽  
Inference Methods

Grammatical inference (GI), i.e., the task of finding a rule that lies behind given words, can be used in the analyses of amyloidogenic sequence fragments, which are essential in studies of neurodegenerative diseases. In this paper, we developed a new method that generates non-circular parsing expression grammars (PEGs) and compares it with other GI algorithms on the sequences from a real dataset. The main contribution of this paper is a genetic programming-based algorithm for the induction of parsing expression grammars from a finite sample. The induction method has been tested on a real bioinformatics dataset and its classification performance has been compared to the achievements of existing grammatical inference methods. The evaluation of the generated PEG on an amyloidogenic dataset revealed its accuracy when predicting amyloid segments. We show that the new grammatical inference algorithm achieves the best ACC (Accuracy), AUC (Area under ROC curve), and MCC (Mathew’s correlation coefficient) scores in comparison to five other automata or grammar learning methods.

scholarly journals Clinical Characteristics, Risk Factors and Predictive Value of COVID-19 Pneumonia: A Retrospective Study of 173 Patients in Wuhan, China

2020 ◽  
Author(s):  
Yang Zhang ◽  
Jun Xue ◽  
Mi Yan ◽  
Jing Chen ◽  
Hai Liu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Predictive Model ◽  
Disease Severity ◽  
Roc Curve ◽  
Predictive Value ◽  
Older Patients ◽  
Clinical Characteristics ◽  
Lactic Dehydrogenase ◽  
Older Age ◽  
Hospital Outcome

Abstract Background: COVID-19 is a globally emerging infectious disease. As the global epidemic continues to spread, the risk of COVID-19 transmission and diffusion in the world will also remain. Currently, several studies describing its clinical characteristics have focused on the initial outbreak, but rarely to the later stage. Here we described clinical characteristics, risk factors for disease severity and in-hospital outcome in patients with COVID-19 pneumonia from Wuhan. Methods: Patients with COVID-19 pneumonia admitted to Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology from February 13 to March 8, 2020, were retrospectively enrolled. Multivariable logistic regression analysis was used to identify risk factors for disease severity and in-hospital outcome and establish predictive models. Receiver operating characteristic (ROC) curve was used to assess the predictive value of above models.Results: 106 (61.3%) of the patients were female. The mean age of study populations was 62.0 years, of whom 73 (42.2%) had underlying comorbidities mainly including hypertension (24.9%). The most common symptoms on admission were fever (67.6%) and cough (60.1%), digestive symptoms (22.0%) was also very common. Older age (OR: 3.420; 95%Cl: 1.415-8.266; P=0.006), diarrhea (OR: 0.143; 95%Cl: 0.033-0.611; P=0.009) and lymphopenia (OR: 4.769; 95%Cl: 2.019-11.266; P=0.000) were associated with severe illness on admission; the area under the ROC curve (AUC) of predictive model were 0.860 (95%CI: 0.802-0.918; P=0.000). Older age (OR: 0.309; 95%Cl: 0.142-0.674; P=0.003), leucopenia (OR: 0.165; 95%Cl: 0.034-0.793; P=0.025), increased lactic dehydrogenase (OR: 0.257; 95%Cl: 0.100-0.659; P=0.005) and interleukins-6 levels (OR: 0.294; 95%Cl: 0.099-0.872; P=0.027) were associated with poor in-hospital outcome; AUC of predictive model were 0.752 (95%CI: 0.681-0.824; P=0.000).Conclusion: Older patients with diarrhea and lymphopenia need early identification and timely intervention to prevent the progression to severe COVID-19 pneumonia. However, older patients with leucopenia, increased lactic dehydrogenase and interleukins-6 levels are at a high risk for poor in-hospital outcome.Trial registration: ChiCTR2000029549

scholarly journals Neonatal Sepsis-Early detection comparing Procalcitonin and CRP as Markers and Newer Tools

2016 ◽  
Vol 5 (1) ◽  
pp. 1048
Author(s):  
Altaf Ahmad Bhat ◽  
Anjum Shamim ◽  
Sabeeha Gul ◽  
Rukaya Akther ◽  
Iqra Bhat
Keyword(s):  
Early Detection ◽  
Roc Curve ◽  
Neonatal Sepsis ◽  
Individual Performance ◽  
Hematological Parameter ◽  
Total Leukocyte Count ◽  
P Value ◽  
Predictive Values ◽  
Maternal Risk ◽  
Area Under Roc Curve

<strong>Background:</strong>Neonatal sepsis continues to be a major cause of morbidity and mortality in India, but is treatable if diagnosis is made in time.<p><strong>Objectives:</strong> The present study was undertaken to evaluate and highlight the importance of procalcitonin v\s CRP in early detection of neonatal sepsis.</p><p><strong>Materials and Methods:</strong> The prospective study enrolled 150 neonates who had maternal risk factors and clinically suspected of infection (study group). Abnormal total leukocyte count, abnormal total polymorphonuclear neutrophils (PMN) count, elevated immature PMN count, elevated immature: Total (I:T) PMN ratio, platelet count ≤150,000/mm3, and pronounced degenerative or toxic changes in PMN were noted by the pathologist who were blind for the clinical status of the baby in NICU. Blood culture was taken as a gold standard for septicemia. The perinatal history, clinical profile and laboratory data were recorded and correlated in each case. Each hematological parameter was assessed for its individual performance and also with the culture-proven sepsis. Sensitivity, specificity, positive and negative predictive values (NPVs) were calculated for each parameter and for different gestational ages. P value was also calculated for different parameters.</p><p><strong>Results:</strong> Among 150 babies evaluated for sepsis in NICU over a period of one year, Procalcitonin is observed as better early marker of neonatal sepsis over and CRP:- Procalcitonin in comparison with CRP: - Sensitivity was 97% Specificity was 59% PPV was 70% and NPV was 99.9%. With area under ROC curve being 0.915(p-value of 0.02) CRP in comparison with Procalcitonin: - Sensitivity was 75% Specificity was 75% PPV was 86% and NPV was 99%. With area under ROC curve being 0.769 (p- value 0.61).</p><p><strong>Conclusion:</strong> The sensitivities of the screening test namely C-reactive protein and Procalcitonin were found to be satisfactory in identifying neonatal sepsis. Comparing to Other test procalcitonin appears to be simple and feasible diagnostic tool although costly.</p>

scholarly journals The value of corticotropin-releasing hormone (CRH) test for differential diagnosis of Cushing’s syndrome

2007 ◽  
Vol 135 (1-2) ◽  
pp. 31-37 ◽  
Author(s):  
Zorana Penezic ◽  
Milos Zarkovic ◽  
Svetlana Vujovic ◽  
Miomira Ivovic ◽  
Biljana Beleslin ◽  
...  
Keyword(s):  
Differential Diagnosis ◽  
Roc Curve ◽  
Acth Secretion ◽  
Ectopic Acth ◽  
Ectopic Acth Secretion ◽  
Test Sensitivity ◽  
Basal Cortisol ◽  
Area Under Roc Curve ◽  
Curve Method ◽  
Acth Secreting

Introduction: Diagnosis and differential diagnosis of Cushing?s syndrome (CS) remain considerable challenge in endocrinology. For more than 20 years, CRH has been widely used as differential diagnostic test. Following the CRH administration, the majority of patients with ACTH secreting pituitary adenoma show a significant rise of plasma cortisol and ACTH, whereas those with ectopic ACTH secretion characteristically do not. Objective The aim of our study was to assess the value of CRF test for differential diagnosis of CS using the ROC (receiver operating characteristic) curve method. Method A total of 30 patients with CS verified by pathological examination and postoperative testing were evaluated. CRH test was performed within diagnostic procedures. ACTH secreting pituitary adenoma was found in 18, ectopic ACTH secretion in 3 and cortisol secreting adrenal adenoma in 9 of all patients with CS. Cortisol and ACTH were determined -15, 0, 15, 30, 45, 60, 90 and 120 min. after i.v. administration of 100?g of ovine CRH. Cortisol and ACTH were determined by commercial RIA. Statistical data processing was done by ROC curve analysis. Due to small number, the patients with ectopic ACTH secretion were excluded from test evaluation by ROC curve method. Results In evaluated subgroups, basal cortisol was (1147.3?464.3 vs. 1589.8?296.3 vs. 839.2?405.6 nmol/L); maximal stimulated cortisol (1680.3?735.5 vs. 1749.0?386.6 vs. 906.1?335.0 nmol/L); and maximal increase as a percent of basal cortisol (49.1?36.9 vs. 9.0?7.6 vs. 16.7?37.3 %). Consequently, basal ACTH was (100.9 ?85.0 vs. 138.0?123.7 vs. 4.8?4.3 pg/mL) and maximal stimulated ACTH (203.8 ?160.1 vs. 288.0?189.5 vs. 7.4?9.2 pg/mL). For cortisol, determination area under ROC curve was 0.815?0.083 (CI 95% 0.652-0.978). For cortisol increase cut-off level of 20%, test sensitivity was 83%, with specificity of 78%. For ACTH, determination area under ROC curve was 0.637?0.142 (CI 95% 0.359-0.916). For ACTH increase cut-off level of 30%, test sensitivity was 70%, with specificity of 57%. Conclusion Determination of cortisol and ACTH levels in CRH test remains reliable tool in differential diagnosis of Cushing?s syndrome.

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