scholarly journals Drain output volume after pancreaticoduodenectomy is a useful warning sign for postoperative complications

BMC Surgery ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Taro Fukui ◽  
Hiroshi Noda ◽  
Fumiaki Watanabe ◽  
Takaharu Kato ◽  
Yuhei Endo ◽  
...  
Keyword(s):  
Predictive Value ◽  
Roc Analysis ◽  
Independent Predictor ◽  
Area Under The Curve ◽  
Warning Sign ◽  
Operating Characteristics ◽  
Protein Loss ◽  
Chyle Leak ◽  
Major Complications ◽  
Output Volume

Abstract Introduction The drain output volume (DOV) after pancreaticoduodenectomy (PD) is an easily assessable indicator in clinical settings. We explored the utility of the DOV as a possible warning sign of complications after PD. Methods A total of 404 patients undergoing PD were considered for inclusion. The predictability of the DOV for overall morbidity, major complications, intraabdominal infection (IAI), clinically relevant (CR) postoperative pancreatic fistula (POPF), CR delayed gastric emptying (DGE), CR chyle leak (CL), and CR post-pancreatectomy hemorrhaging (PPH) was evaluated. Results One hundred (24.8%) patients developed major complications, and 131 (32.4%) developed IAI. Regarding CR post-pancreatectomy complications, 75 (18.6%) patients developed CR-POPF, 23 (5.7%) developed CR-DGE, 20 (5.0%) developed CR-CL, and 28 (6.9%) developed CR-PPH. The median DOV on postoperative day (POD) 1 and POD 3 was 266 and 234.5 ml, respectively. A low DOV on POD 1 was an independent predictor of CR-POPF, and a high DOV on POD 3 was an independent predictor of CR-CL. A receiver operating characteristics (ROC) analysis revealed that the DOV on POD 1 had a negative predictive value (area under the curve [AUC] 0.655, sensitivity 65.0%, specificity 65.3%, 95% confidence interval [CI]: 0.587–0.724), with a calculated optimal cut-off value of 227 ml. An ROC analysis also revealed that the DOV on POD 3 had a positive predictive value (AUC 0.753, sensitivity 70.1%, specificity 75.0%, 95% CI: 0.651–0.856), with a calculated optimal cut-off value of 332 ml. Conclusion A low DOV on POD 1 might be a postoperative warning sign for CR-POPF, similar to high drain amylase (DA) on POD 1, high DA on POD 3, and high CRP on POD 3. When the DOV on POD 1 after PD was low, surgeons should evaluate the reasons of a low DOV. A high DOV on POD 3 was a postoperative warning sign CR-CL, and might require an appropriate management of protein loss.

Tidal volumes at birth as predictor for adverse outcome in congenital diaphragmatic hernia

2019 ◽  
Vol 105 (3) ◽  
pp. 248-252 ◽  
Author(s):  
Arenda Mank ◽  
Cristina Carrasco Carrasco ◽  
Marta Thio ◽  
Jordi Clotet ◽  
Steffen C Pauws ◽  
...  
Keyword(s):  
Congenital Diaphragmatic Hernia ◽  
Diaphragmatic Hernia ◽  
Respiratory Function ◽  
Neonatal Intensive Care ◽  
Roc Analysis ◽  
Predictive Accuracy ◽  
Adverse Outcome ◽  
Independent Predictor ◽  
Area Under The Curve ◽  
Operating Characteristics

ObjectiveTo assess the predictive value of tidal volume (Vt) of spontaneous breaths at birth in infants with congenital diaphragmatic hernia (CDH).DesignProspective study.SettingTertiary neonatal intensive care unit.PatientsThirty infants with antenatally diagnosed CDH born at Hospital Sant Joan de Déu in Barcelona from September 2013 to September 2015.InterventionsSpontaneous breaths and inflations given in the first 10 min after intubation at birth were recorded using respiratory function monitor. Only expired Vt of uninterrupted spontaneous breaths was included for analysis. Receiver operating characteristics (ROC) analysis was performed and the area under the curve (AUC) was estimated to assess the predictive accuracy of Vt.Main outcome measuresMortality before hospital discharge and chronic lung disease (CLD) at day 28 of life.ResultsThere were 1.233 uninterrupted spontaneous breaths measured, and the overall mean Vt was 2.8±2.1 mL/kg. A lower Vt was found in infants who died (n=14) compared with survivors (n=16) (1.7±1.6 vs 3.7±2.1 mL/kg; p=0.008). Vt was lower in infants who died during admission or had CLD (n=20) compared with survivors without CLD (n=10) (2.0±1.7 vs 4.3±2.2 mL/kg; p=0.004). ROC analysis showed that Vt ≤2.2 mL/kg predicted mortality with 79% sensitivity and 81% specificity (AUC=0.77, p=0.013). Vt ≤3.4 mL/kg was a good predictor of death or CLD (AUC=0.80, p=0.008) with 85% sensitivity and 70% specificity.ConclusionVt of spontaneous breaths measured immediately after birth is associated with mortality and CLD. Vt seems to be a reliable predictor but is not an independent predictor after adjustment for observed/expected lung to head ratio and liver position.

scholarly journals New screening approach to detecting congenital syphilis in China: a retrospective cohort study

2020 ◽  
pp. archdischild-2020-320549
Author(s):  
Fang Hu ◽  
Shuai-Jun Guo ◽  
Jian-Jun Lu ◽  
Ning-Xuan Hua ◽  
Yan-Yan Song ◽  
...  
Keyword(s):  
Predictive Value ◽  
Congenital Syphilis ◽  
Area Under The Curve ◽  
Diagnostic Tools ◽  
Operating Characteristics ◽  
Loss To Follow Up ◽  
Sensitivity Specificity ◽  
Mother To Child ◽  
Rule Out

BackgroundDiagnosis of congenital syphilis (CS) is not straightforward and can be challenging. This study aimed to evaluate the validity of an algorithm using timing of maternal antisyphilis treatment and titres of non-treponemal antibody as predictors of CS.MethodsConfirmed CS cases and those where CS was excluded were obtained from the Guangzhou Prevention of Mother-to-Child Transmission of syphilis programme between 2011 and 2019. We calculated sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) using receiver operating characteristics (ROC) in two situations: (1) receiving antisyphilis treatment or no-treatment during pregnancy and (2) initiating treatment before 28 gestational weeks (GWs), initiating after 28 GWs or receiving no treatment for syphilis seropositive women.ResultsAmong 1558 syphilis-exposed children, 39 had confirmed CS. Area under the curve, sensitivity and specificity of maternal non-treponemal titres before treatment and treatment during pregnancy were 0.80, 76.9%, 78.7% and 0.79, 69.2%, 88.7%, respectively, for children with CS. For the algorithm, ROC results showed that PPV and NPV for predicting CS were 37.3% and 96.4% (non-treponemal titres cut-off value 1:8 and no antisyphilis treatment), 9.4% and 100% (non-treponemal titres cut-off value 1:16 and treatment after 28 GWs), 4.2% and 99.5% (non-treponemal titres cut-off value 1:32 and treatment before 28 GWs), respectively.ConclusionsAn algorithm using maternal non-treponemal titres and timing of treatment during pregnancy could be an effective strategy to diagnose or rule out CS, especially when the rate of loss to follow-up is high or there are no straightforward diagnostic tools.

First trimester prediction of maternal glycemic status

2015 ◽  
Vol 43 (3) ◽  
Author(s):  
Rinat Gabbay-Benziv ◽  
Lauren E. Doyle ◽  
Miriam Blitzer ◽  
Ahmet A. Baschat
Keyword(s):  
Risk Score ◽  
Predictive Value ◽  
Challenge Test ◽  
Area Under The Curve ◽  
First Trimester ◽  
Tolerance Test ◽  
Oral Glucose ◽  
Operating Characteristics ◽  
Maternal Characteristics ◽  
Predictive Algorithm

AbstractTo predict gestational diabetes mellitus (GDM) or normoglycemic status using first trimester maternal characteristics.We used data from a prospective cohort study. First trimester maternal characteristics were compared between women with and without GDM. Association of these variables with sugar values at glucose challenge test (GCT) and subsequent GDM was tested to identify key parameters. A predictive algorithm for GDM was developed and receiver operating characteristics (ROC) statistics was used to derive the optimal risk score. We defined normoglycemic state, when GCT and all four sugar values at oral glucose tolerance test, whenever obtained, were normal. Using same statistical approach, we developed an algorithm to predict the normoglycemic state.Maternal age, race, prior GDM, first trimester BMI, and systolic blood pressure (SBP) were all significantly associated with GDM. Age, BMI, and SBP were also associated with GCT values. The logistic regression analysis constructed equation and the calculated risk score yielded sensitivity, specificity, positive predictive value, and negative predictive value of 85%, 62%, 13.8%, and 98.3% for a cut-off value of 0.042, respectively (ROC-AUC – area under the curve 0.819, CI – confidence interval 0.769–0.868). The model constructed for normoglycemia prediction demonstrated lower performance (ROC-AUC 0.707, CI 0.668–0.746).GDM prediction can be achieved during the first trimester encounter by integration of maternal characteristics and basic measurements while normoglycemic status prediction is less effective.

238 SERUM ALBUMIN EARLY DECREASE IS AN INDEPENDENT PREDICTOR OF MAJOR COMPLICATIONS AFTER ONCOLOGICAL ESOPHAGECTOMY; RESULTS FROM A LARGE EUROPEAN SERIES

2021 ◽  
Vol 34 (Supplement_1) ◽  
Author(s):  
Ismail Labgaa ◽  
Styliani Mantziari ◽  
Michael Winiker-Seeberger ◽  
Jerôme Pasquier ◽  
Marguerite Messier ◽  
...  
Keyword(s):  
Predictive Value ◽  
Independent Predictor ◽  
Multivariable Analysis ◽  
Length Of Hospital Stay ◽  
Adverse Outcomes ◽  
Major Surgery ◽  
Roc Curve Analysis ◽  
Comprehensive Complication Index ◽  
Major Complications ◽  
Patients At Risk

Abstract   The predictive value of postoperative albuminemia decrease (ΔAlb) has been increasingly evidenced in different types of major surgery but data on esophagectomy remain scarce. This study aimed to assess the predictive value of ΔAlb for adverse short-term outcomes after oncological esophagectomy. Methods Retrospective analysis of an international multicentric cohort of patients undergoing oncological esophagectomy between 2006–2017. Patients with missing pre- and postoperative albumin values were excluded from the analysis. Primary endpoint was postoperative morbidity according to Clavien classification. Secondary endpoints were Comprehensive Complication Index (CCI) and length of hospital stay (LoS). Results A total of 1046 patients were analyzed. Major complications were reported in 363 (34.7%) patients. Albuminemia showed a rapid postoperative decrease on postoperative day 1 (POD1) (ΔAlb POD1) with a median value of 11 g/L. ROC curve analysis determined a cut-off of 11 g/L for the prediction of overall complications. Patients with ΔAlb POD1 ≥ 11 g/L showed increased overall complications (p = 0.004), major complications (p = 0.009) and CCI (p = 0.006) while LoS was comparable (p = 0.099). On multivariable analysis, ΔAlb POD1 ≥ 11 g/L was an independent predictor of overall (OR: 1.55; 95% CI 1.09–2.21; p = 0.015) and major complications (OR: 1.43; 95% CI 1.09–1.89; p = 0.009). Conclusion Oncological esophagectomy induced a rapid decrease of albuminemia. ΔAlb POD1 ≥ 11 g/L was independently associated with the occurrence of overall and major postoperative complications. ΔAlb appears as a promising biomarker to detect patients at risk of adverse outcomes after oncological esophagectomy.

Prognostic value of AIMS65 score in cirrhotic patients with variceal bleeding

MedPharmRes ◽  
2021 ◽  
Vol 6 (1) ◽  
pp. 22-26
Author(s):  
Trong Nguyen Dang Huynh
Keyword(s):  
Variceal Bleeding ◽  
Predictive Value ◽  
Prognostic Value ◽  
Area Under The Curve ◽  
Scoring Systems ◽  
Meld Score ◽  
Operating Characteristics ◽  
Increased Risk ◽  
Cirrhotic Patients ◽  
Ctp Score

Background: In cirrhotic patients, variceal bleeding remains a major cause of death. After a variceal bleeding episode, mortality and rebleeding rates spike for the first 6 weeks before levelling off. We aimed to evaluate the performance of AIMS65 score in comparison with Child-Turcotte-Pugh (CTP) score and model for end-stage liver disease (MELD) score in predicting 6-week mortality and rebleeding in cirrhotic patients with variceal bleeding. Method: Data were collected prospectively from patients with cirrhosis and variceal bleeding at Gastroenterology and Hepatology Department of Cho Ray hospital from September 2016 to April 2017. The primary endpoint was 6-week mortality and rebleeding. The prognostic value of AIMS65, CTP, and MELD scoring systems for 6-week mortality and rebleeding was compared by receiver operating characteristics curves (ROC) and the area under the curve (AUC). Results: Among 80 patients, 15% rebled and 25% died during 6-week follow-up. AUCROC of AIMS65, CTP, and MELD scores in predicting 6-week rebleeding were 0.68, 0.54, and 0.48, respectively. AUCROC of AIMS65, CTP, and MELD scores in predicting 6-week mortality were 0.80, 0.74, and 0.64, respectively. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of AIMS65 score at the cutoff point of 2 were 95%, 55%, 41.3%, and 97%, respectively. Conclusion: AIMS65 score is a simple yet applicable tool for risk stratification in cirrhotic patients with variceal bleeding. We recommend using AIMS65 score with a cut-off point of 2 to identify patients at increased risk for 6-week mortality after variceal bleeding.

scholarly journals The role of red cell distribution width in the differential diagnosis of iron deficiency anemia and non-transfusion dependent thalassemia patients

2018 ◽  
Vol 10 (3) ◽  
Author(s):  
Pokpong Piriyakhuntorn ◽  
Adisak Tantiworawit ◽  
Thanawat Rattanathammethee ◽  
Chatree Chai-Adisaksopha ◽  
Ekarat Rattarittamrong ◽  
...  
Keyword(s):  
Diagnostic Accuracy ◽  
Predictive Value ◽  
Area Under The Curve ◽  
Microcytic Anemia ◽  
Deficiency Anemia ◽  
Operating Characteristics ◽  
Training Set ◽  
Distribution Width ◽  
Validation Set ◽  
Sensitivity Specificity

This study aims to find the cut-off value and diagnostic accuracy of the use of RDW as initial investigation in enabling the differentiation between IDA and NTDT patients. Patients with microcytic anemia were enrolled in the training set and used to plot a receiving operating characteristics (ROC) curve to obtain the cut-off value of RDW. A second set of patients were included in the validation set and used to analyze the diagnostic accuracy. We recruited 94 IDA and 64 NTDT patients into the training set. The area under the curve of the ROC in the training set was 0.803. The best cut-off value of RDW in the diagnosis of NTDT was 21.0% with a sensitivity and specificity of 81.3% and 55.3% respectively. In the validation set, there were 34 IDA and 58 NTDT patients using the cut-off value of >21.0% to validate. The sensitivity, specificity, positive predictive value and negative predictive value were 84.5%, 70.6%, 83.1% and 72.7% respectively. We can therefore conclude that RDW >21.0% is useful in differentiating between IDA and NTDT patients with high diagnostic accuracy

scholarly journals Fukuda Stepping Test: Sensitivity and Specificity

2009 ◽  
Vol 20 (05) ◽  
pp. 311-314 ◽  
Author(s):  
Julie A. Honaker ◽  
Thomas E. Boismier ◽  
Nathan P. Shepard ◽  
Neil T. Shepard
Keyword(s):  
Sensitivity And Specificity ◽  
Roc Analysis ◽  
Screening Tool ◽  
Area Under The Curve ◽  
Future Research ◽  
Operating Characteristics ◽  
Caloric Irrigation ◽  
Test Sensitivity ◽  
Unilateral Weakness ◽  
Vestibular Asymmetry

Background: A vestibulospinal test known as the Fukuda stepping test (FST) has been suggested to be a measure of asymmetrical labyrinthine function. However, an extensive review of the performance of this test to identify a peripheral vestibular lesion has not been reported. Purpose: The purpose of this study was to evaluate the sensitivity and specificity of the standard FST and a head shaking variation for identification of a peripheral vestibular system lesion. Research Design: In this retrospective review, we compared performance on the FST with and without a head shaking component to electronystagmography (ENG) caloric irrigation unilateral weakness results. Study Sample: We studied these factors in 736 chronic dizzy patients. Results: Receiving operating characteristics (ROC) analysis and area under the curve (AUC) indicated no significant benefit to performance from the head shaking variation compared to the standard FST in identifying labyrinthine weakness as classified by caloric unilateral weakness results. Conclusions: These findings suggest that the FST with and without head shake component is not a reliable screening tool for peripheral vestibular asymmetry in chronic dizzy patients; however, future research may hold promise for the FST as a tool for patients with acute unilateral disorders.

PREDICTING SOFTWARE CHANGE IN AN OPEN SOURCE SOFTWARE USING MACHINE LEARNING ALGORITHMS

2013 ◽  
Vol 20 (06) ◽  
pp. 1350025
Author(s):  
RUCHIKA MALHOTRA ◽  
ANKITA JAIN BANSAL
Keyword(s):  
Machine Learning ◽  
Open Source ◽  
Open Source Software ◽  
Roc Analysis ◽  
Area Under The Curve ◽  
Machine Learning Algorithms ◽  
Operating Characteristics ◽  
Preventive Actions ◽  
Change Proneness ◽  
The Relationship

Due to various reasons such as ever increasing demands of the customer or change in the environment or detection of a bug, changes are incorporated in a software. This results in multiple versions or evolving nature of a software. Identification of parts of a software that are more prone to changes than others is one of the important activities. Identifying change prone classes will help developers to take focused and timely preventive actions on the classes of the software with similar characteristics in the future releases. In this paper, we have studied the relationship between various object oriented (OO) metrics and change proneness. We collected a set of OO metrics and change data of each class that appeared in two versions of an open source dataset, 'Java TreeView', i.e., version 1.1.6 and version 1.0.3. Besides this, we have also predicted various models that can be used to identify change prone classes, using machine learning and statistical techniques and then compared their performance. The results are analyzed using Area Under the Curve (AUC) obtained from Receiver Operating Characteristics (ROC) analysis. The results show that the models predicted using both machine learning and statistical methods demonstrate good performance in terms of predicting change prone classes. Based on the results, it is reasonable to claim that quality models have a significant relevance with OO metrics and hence can be used by researchers for early prediction of change prone classes.

scholarly journals Single Brain Metastasis vs Glioblastoma Multiforme: A Voi-Based Multiparametric Analysys for Differential Diagnosis

2021 ◽  
Author(s):  
Andrea Romano ◽  
Giulia Moltoni ◽  
Alessia Guarnera ◽  
Luca Pasquini ◽  
Alberto Di Napoli ◽  
...  
Keyword(s):  
Differential Diagnosis ◽  
Roc Analysis ◽  
Area Under The Curve ◽  
Solid Component ◽  
Signal Recovery ◽  
Operating Characteristics ◽  
Cerebral Lesions ◽  
Perilesional Edema ◽  
Volume Of Interest ◽  
The Mean

Abstract PURPOSEThe authors purpose was to evaluate ADC and rCBV values in the enhanced lesion, in the peritumoral area and in distal oedema using a Volume of Interest (VOI) based method and to analysed hemodynamic curves obtained from DSC perfusion MRI, in order to create a valid multiparametric MRI model for the differential diagnosis between Glioblastoma and solitary Brain Metastasis.MATERIALS AND METHODSForty-one patients (twenty glioblastomas and twenty-one single brain metastases) were retrospectively evaluated. MRI images were acquired before surgery, radiotherapy and chemotherapy. MRIs were analysed with Olea Sphere® 3.0 (Olea Medical, La Ciotat, France), in particular with diffusion, perfusion and volume of interest segmentation plug-ins. FLAIR, 3D T1 MP-RAGE images after gadolinium, ADC and rCBV maps for each patient were co-registered by the OleaSphere software; this was followed by visual inspection to ensure adequate alignment. Volumes of interest (VOIs) of the lesions were drawn on enhanced 3D T1 MP-RAGE avoiding cyst or necrotic degeneration, and then projected on ADC and rCBV co-registered maps. Another 2 VOIs were drawn in the region of hyperintense cerebral oedema, surrounding the lesion (GB or BM) visible on FLAIR images. The first VOI was drawn into perilesional oedema within 5mm around the enhancing tumor. The second VOI was drawn into residual oedema. Both VOIs were projected on ADC and rCBV maps. Perfusion curves were obtained for each lesion and the value of signal recovery (SR) was reported. A Two sample T-Test was obtained to compare all parameters of GB and BM groups. Receiver operating characteristics (ROC) analysis was performed to determine the optimal parameter in distinguishing GB from BM. RESULTSComparing all parameters evaluated for patients with GB and BM, the cerebral lesions were distinguishable with the mean ADC VOI- values of solid component, the PSR values and the mean and max rCBV values in the perilesional edema within 5mm around the enhancing tumor. According to ROC analysis, the area under the curve was 88%, 78% and 74% respectively for mean ADC VOI-values of the solid component, the mean and max rCBV values in the perilesional edema and the PSR. The cumulative ROC curve of these parameters reached an area under the curve of 95% .Using perilesional max rCBV>1,37, PSR>75% and mean lesional ADC<1x10-3 mm2 s-1 GB could be differentiated from solitary BM with sensitivity and specificity of 95% and 86%. CONCLUSIONWe can conclude that lower values of ADC in the enhancing tumor volume and a higher percentage of signal recovery in perfusion curves, associated with higher values of rCBV in the peritumoral edema closed to the lesion, are strongly indicative of GB than solitary BM.

Development of a Bayesian Belief Network Model for Personalized Prognostic Risk Assessment in Colon Carcinomatosis

2011 ◽  
Vol 77 (2) ◽  
pp. 221-230 ◽  
Author(s):  
Alexander Stojadinovic ◽  
Aviram Nissan ◽  
John Eberhardt ◽  
Terence C. Chua ◽  
Joerg O.W. Pelz ◽  
...  
Keyword(s):  
Decision Support ◽  
Predictive Model ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Performance Status ◽  
Area Under The Curve ◽  
Decision Support Tools ◽  
Operating Characteristics ◽  
Peritoneal Cancer ◽  
Support Tools

Multimodality therapy in selected patients with peritoneal carcinomatosis is gaining acceptance. Treatment-directing decision support tools are needed to individualize care and select patients best suited for cytoreductive surgery ± hyperthermic intraperitoneal chemotherapy (CRS ± HIPEC). The purpose of this study is to develop a predictive model that could support surgical decisions in patients with colon carcinomatosis. Fifty-three patients were enrolled in a prospective study collecting 31 clinical-pathological, treatment-related, and outcome data. The population was characterized by disease presentation, performance status, extent of peritoneal cancer (Peritoneal Cancer Index, PCI), primary tumor histology, and nodal staging. These preoperative parameters were analyzed using step-wise machine-learned Bayesian Belief Networks (BBN) to develop a predictive model for overall survival (OS) in patients considered for CRS ± HIPEC. Area-under-the-curve from receiver-operating-characteristics curves of OS predictions was calculated to determine the model's positive and negative predictive value. Model structure defined three predictors of OS: severity of symptoms (performance status), PCI, and ability to undergo CRS ± HIPEC. Patients with PCI < 10, resectable disease, and excellent performance status who underwent CRS ± HIPEC had 89 per cent probability of survival compared with 4 per cent for those with poor performance status, PCI > 20, who were not considered surgical candidates. Cross validation of the BBN model robustly classified OS (area-under-the-curve = 0.71). The model's positive predictive value and negative predictive value are 63.3 per cent and 68.3 per cent, respectively. This exploratory study supports the utility of Bayesian classification for developing decision support tools, which assess case-specific relative risk for a given patient for oncological outcomes based on clinically relevant classifiers of survival. Further prospective studies to validate the BBN model-derived prognostic assessment tool are warranted.

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