Comparison Of Area Under The Curve Research Articles

Adding vortexing to the Maki technique provides no benefit for the diagnosis of catheter colonization or catheter-related bacteremia.

A previous study compared vortexing and Maki techniques for the diagnosis of catheter-related bloodstream infection (CRBSI), and concluded that vortexing was not superior to Maki method. To determine whether the combined use of vortexing and Maki techniques provides profitability versus the Maki technique for the diagnosis of catheter tip colonization (CTC) and CRBSI. Observational and prospective study carried out in an Intensive Care Unit. Patients with suspected catheter-related infection (CRI) and with one central venous catheter for at least 7 days were included. The area under the curve (AUC) of the Maki technique, the vortexing technique and the combination of both techniques for the diagnosis of CTC and CRBSI were compared. We included 136 episodes of suspected CRI. We found 21 cases of CTC of which 10 were also CRBSI cases. Of the 21 CTC episodes, 18 (85.7%) were diagnosed by Maki technique and vortexing technique, 3 (14.3%) only by the technique of Maki, and none only by technique of vortexing. Of the 10 CRBSI episodes, 9 (90.0%) were diagnosed by the techniques of Maki and vortexing, 1 (10.0%) was diagnosed only by the technique of Maki, and none only by the technique of vortexing. We no found differences in the comparison of AUC between the technique of Maki and the combination of Maki and vortexing techniques for the diagnosis of CTC (P = 0.99) and CRBSI (P = 0.99). The novel finding of our study was that the combined use of vortexing and Maki techniques did not provide profitability to the technique of Maki alone to CRBSI diagnosis of.

Assessment of GCS and FOUR Score as Prognostic Indicators for Hospital Stay and Morbidity in Traumatic Brain Injury Patients: An Observational Study

ABSTRACT Aim: The objective of the present research was to evaluate variations in hospital stay as well as morbidity based on the Glasgow Coma Scale (GCS) and Full Outline of Un-Responsive (FOUR) scores for patients who had traumatic brain injury (TBI). Materials and Methods: A total of 107 patients with TBI patients who attended the emergency department of MES Medical College, Perinthalmanna, were enrolled into the study. FOUR and GCS scoring systems were used to assess the patients within 24 hours of the presentation to the emergency department. Both FOUR and GCS scoring systems were assessed at the same time. The outcome was measured in terms of length of hospital stay and morbidity, which was assessed using modified Rankin score. Chi-square test was used to calculate sensitivity, specificity, positive predictive value, and negative predictive value. The area under the curve (AUC) was calculated using receiver operating characteristic curve analysis. A P value <0.05 was considered significant. Results: We found a strong positive correlation between GCS and FOUR score with a Spearman coefficient of 0.9. Comparison of AUC between GCS score and FOUR score showed a statistically significant difference (P = 0.0044), predicting that FOUR score was a better predictor of hospital stay (>15 days) than GCS score. Comparison of AUC between GCS score and FOUR score showed a significant statistical difference (P = 0.0002), showing that FOUR score was a better predictor of morbidity than GCS. Conclusion: FOUR score was a better predictor of hospital stay and morbidity as compared to GCS score.

Evaluation of the Relationship between Cognitive Impairment and Atria Score Systems in Patients with Atrial Fibrillation.

Atrial fibrillation (AF) is the main arrhythmia associated with thromboembolic complications and cognitive impairment. In this study, we aimed to evaluate the relationship between cognitive impairment and different scoring systems developed for AF to improve the medical follow-up of cognitive impairment. Between January 2019 and December 2020, 124 patients between the age of 30 and 80 years, diagnosed with AF for at least 5 years and complaining about memory impairment during cardiological follow-up, were included in the study. The patients were divided into two groups based on their cognitive status as assessed by the Mini-Mental State Examination group 1 consisted of 52 patients with cognitive impairment and group 2 comprised 72 patients without cognitive impairment. The ATRIA bleeding score had a positive moderate correlation (r = 0.454, P < 0.001), the ATRIA stroke score had a strong correlation (r = 0.738, P < 0.001), and the SAMe-TT2R2 score had a strong correlation (r = 0.688, P < 0.001) with cognitive impairment. However, CHADS2 and CHA2DS2VASc scores were not statistically correlated with cognitive impairment. According to the receiver operating characteristic (ROC) curve, the area under the curve (AUC) of the ATRIA bleeding score was 0.761 with a 95% confidence interval (CI) of 0.678-0.844 and P < 0.001; also, for the ATRIA stroke score, AUC was 0.930 with a 95% CI of 0.886-0.974 and P < 0.001. In addition, for the SAMe-TT2R2 score, AUC was 0.895 with a 95% CI of 0.838-0.952 and P < 0.001. In the pairwise comparison of AUC on ROC curves, the ATRIA stroke score and the SAMe-TT2R2 score were statistically similar (P = 0.324). ATRIA bleeding, ATRIA stroke, and SAMe-TT2R2 scores were greater than CHADS2 stroke score (P: 0.0004, P < 0.0001, and P < 0.0001, respectively), but CHA2DS2-VASc and CHADS2 stroke scores were statistically similar (P: 0.402). Both ATRIA stroke and SAMe-TT2R2 scoring systems can provide a better correlation than CHADS2 and CHA2DS2-VASc scores in patients with AF to evaluate their cognitive status. These two scores can be more useful to monitor the patients with AF for medical follow-up of cognitive status.

The value of multimodal ultrasound in diagnosis of cervical lymphadenopathy: can real-time elastography help identify benign and malignant lymph nodes?

AimTo investigate the multimodal ultrasound(MMUS) features of cervical lymphadenopathy and to assess its value in the differential diagnosis of benign and malignant cervical lymph nodes.MethodsA retrospective analysis of 169 patients with cervical lymph node enlargement who attended Hangzhou Red Cross Hospital from March 2020 to October 2022. All patients underwent conventional ultrasound (CUS), contrast-enhanced ultrasound (CEUS), and real-time elastography (RTE), and were divided into training set and validation set. Univariate analysis was applied to screen out statistically significant parameters, and CUS model and MMUS model were constructed by multifactorial logistic regression analysis. The receiver operator characteristic (ROC) curve was established, and the area under the curve (AUC) was used to compare CUS model with MMUS model to assess the value of MMUS.ResultsOf the cervical 169 lymph nodes in 169 patients included in the study. The 169 enrolled patients were divided into a training set (132 patients) and a validation set (37 patients). In the training set, univariate analysis showed statistically significant differences in long diameter/short diameter(L/S), border, margin, hilus, dermal medulla boundary, blood flow type, enhancement mode, enhancement type, and RTE score (all p&amp;lt; 0.05). Multifactor logistic analysis showed that L/S, blood flow type, enhancement mode and enhancement type were correlates of malignant lymph nodes (all p&amp;lt; 0.05). The comparison of AUC demonstrated that the discriminative ability of the MMUS model was superior to using the CUS model, both in the training set(p = 0.004) and validation set (p&amp;lt;0.001).ConclusionIn this study, MMUS shows higher diagnostic efficiency than CUS. Ultrasound features such as L/S, blood flow type, mode of enhancement, type of enhancement are helpful in distinguishing benign and malignant lymphadenopathy. The addition of CEUS can greatly improve the sensitivity and specificity of ultrasonic diagnosis of malignant cervical lymph nodes. RTE score is of limited value in the diagnosis of malignant cervical lymph nodes.

Investigation of the Optimum Baseline Blood Pressure for Spinal Anesthesia to Guide Vasopressor Management for Elective Cesarean Delivery: A Case-Control Design.

Current guidelines recommend prophylactic vasopressor administration during spinal anesthesia for cesarean delivery to maintain intraoperative blood pressure above 90% of the baseline value. We sought to determine the optimum baseline mean arterial pressure (MAP) reading to guide the management of spinal hypotension. We performed a secondary analysis of data collected from normotensive patients presenting for elective cesarean delivery in a tertiary care institution from October 2018 to August 2020. We compared the magnitude of hypotension in patients who reported nausea versus those who did not, using a case-control design. Baseline MAPs at last office visit, morning of surgery, or operating room (pre-spinal) were determined. We calculated the duration and degree of hypotension using the area under the curve (AUC) when the MAP of the respective patient was below 90% of each baseline. The patients who experienced nausea (n=45) had longer and more profound periods of hypotension than those who did not develop nausea (n=240). A comparison of AUC using MAP baseline at the last office visit or on the morning of surgery showed a statistically significant between-group difference, P=0.02, and P=0.005, respectively, and no significant between-group difference when 90% of the MAP baseline in the operating room was used. Patients had the highest preoperative MAP in the operating room and the AUC was similar for those with and without nausea when the pre-spinal MAP baseline was used. Therefore, maintaining higher intraoperative blood pressure using individual pre-spinal MAP as baseline should reduce intraoperative maternal nausea.

Assessment of Predictive Value of SYNTAX-II Score for Adverse Cardiac Events and Clinical Outcomes in Patients With Acute Coronary Syndrome.

Prognostic information is important for the management of acute coronary syndrome (ACS). Our aim was to evaluate Synergy between PCI with Taxus and Cardiac Surgery (SYNTAX) score-II (SSII) for predicting contrast induced nephropathy (CIN) and one-year major adverse cardiac events (MACE) in ACS patients. Coronary angiographic recordings of 1304 ACS patients were retrospectively examined. Predictive values of SYNTAX score (SS), SSII-percutaneous coronary intervention (SSII-PCI), SSII-coronary artery bypass graft (SSII-CABG) scores for CIN and MACE were assessed. Combination of CIN and MACE ratios constituted primary composite end-point. Patients with SSII-PCI scores >32.55 were compared with patients with lower scores. All of the three scoring systems predicted the composite primary end-point [SS: Area under the curve (AUC): .718, P < .001 (95% CI: .689-.747), SSII-PCI: AUC: .824, P < .001 (95% CI: .800-.849), SSII-CABG: AUC: .778, P < .001 (95% CI: .751-.805)]. Comparison of AUC of receiver operating characteristic curves showed that SSII-PCI score had better predictive value than that of SS and SSII-CABG scores. In multivariate analysis, the only predictor of the primary composite end-point was SSII-PCI score (odds ratio: 1.126, 95% CI: 1.107-1.146, P < .001). SSII-PCI score was a valuable tool for prediction of shock, CABG, myocardial infarction, stent thrombosis, development of CIN and one-year mortality.

Frailty and risk of adverse outcomes among community-dwelling older adults in China: a comparison of four different frailty scales.

Data on which frailty scales are most suitable for estimating risk in Chinese community populations remain limited. Herein we examined and compared four commonly used frailty scales in predicting adverse outcomes in a large population-based cohort of Chinese older adults. A total of 5402 subjects (mean age 66.3 ± 9.6 years, 46.6% male) from the WHO Study on global AGEing and adult health (SAGE) in Shanghai were studied. Frailty was measured using a 35-item frailty index (FI), the frailty phenotype (FP), FRAIL, and Tilburg Frailty Indicator (TFI). Multivariate logistic regression models were performed to evaluate the independent association between frailty and outcomes including 4-year disability, hospitalization, and 4- and 7-year all-cause mortality. The accuracy for predicting these outcomes was determined by evaluating the area under the curve (AUC). The prevalence of frailty, sensitivity, and specificity were calculated using our proposed cut-off points and other different values. Prevalence of frailty ranged from 4.2% (FRAIL) to 16.9% (FI). FI, FRAIL and TFI were comparably associated with 4-year hospitalization, and 4- and 7-year mortality (adjusted odds ratios [aORs] 1.44-1.69, 1.91-2.22 and 1.85-2.88, respectively). FRAIL conferred the greatest risk of 4-year disability, followed by FI and TFI (aOR 5.55, 3.50, and 1.91, respectively). FP only independently predicted 4- and 7-year mortality (aOR 1.57 and 2.21, respectively). AUC comparisons showed that FI, followed by TFI and FRAIL, exhibited acceptable predictive accuracy for 4-year disability, 4- and 7-year mortality (AUCs 0.76-0.78, 0.71-0.71, 0.65-0.72, respectively), whereas all scales poorly predicted 4-year hospitalization (AUCs 0.53-0.57). For each scale, while specificity estimates (85.3-97.3%) were high and similar across all outcomes, their sensitivity estimates (6.3-56.8%) were not sufficient yet. Prevalence of frailty, sensitivity, and specificity varied considerably when different cut-off points were used. Frailty defined using any of the four scales was associated with an increased risk of adverse outcomes. Although FI, FRAIL and TFI exhibited fair-to-moderate predictive accuracy and high specificity estimates, their sensitivity estimates were not sufficient yet. Overall, FI performed best in estimating risk, while TFI and FRAIL were additionally useful, the latter perhaps being more applicable to Chinese community-dwelling older adults.

The mitral to aortic/pulmonary velocity-time integral ratio is a simple, feasible and accurate discriminator for echocardiographic evaluation of severe isolated mitral regurgitation

Abstract Background Echocardiographic quantification of mitral regurgitation (MR) remains challenging, requiring dedicated image acquisition, and is limited by potential error from geometric assumptions of annular dimensions. Volume is a product of area and flow and assuming proportional mitral/aortic areas, an increased mitral-inflow volume compared to LV/RV-outflow semi-quantitatively represents greater MR regurgitant volume. Therefore, we investigated the feasibility and diagnostic performance of the mitral-aortic velocity-time integral (VTI) ratio in isolated MR. We also investigated the use of the mitral-pulmonary VTI ratio as an alternative in clinical situations where the LV outflow tract (LVOT) VTI could not be used. Methods We reviewed 166 consecutive patients (54 (33% severe MR by multi-parameter integrated expert opinion)). Pulsed-Doppler VTI at the mitral leaflet tips and the left ventricular outflow and continuous-wave Doppler of the right ventricular outflow tract were measured individually and independently by blinded readers (expert and trainee status) to derive the ratio. Receiver operator characteristic area under the curve (AUC) comparison was calculated and compared with effective regurgitant orifice area (EROA &amp;gt;40 mm), regurgitant volume (RVol &amp;gt;6 0mL), vena contracta (VC &amp;gt;0.7 cm), E-velocity &amp;gt;1.2 cm, systolic flow reversal (SFR), left atrial and ventricular dilatation. Results Increasing ratio was associated with severe MR (AUC 0.94) with optimal threshold defined at 1.3. This provided significant discrimination for severe MR (AUC 0.81) compared to EROA (0.68), VC (0.52), LV dilatation (0.69), LA dilatation (0.70), SFR (0.73), E-velocity (0.68) all p&amp;lt;0.05, with sensitivity 82% and specificity 94%. The mitral-pulmonary VTI ratio demonstrated similar discrimination (AUC 0.92) with optimal threshold defined at 1.14. Excellent inter-observer reproducibility (intra-class correlation 0.97) was seen between trainee and expert readers. There was no difference in AUC comparison by MR mechanism or patient rhythm. Conclusions The mitral-aortic or mitral-pulmonary VTI ratio is a simple, geometric-free parameter feasibly reproducible from routine echocardiographic datasets and is an excellent discriminative tool for severe MR. Readers should consider integration of this parameter in routine reporting. Funding Acknowledgement Type of funding sources: None.

Regional Cerebral Small Vessel Disease (rCSVD) Score: A clinical MRI grading system validated in a stroke cohort

BackgroundCurrent methods for quantitative assessment of cerebral small vessel disease (CSVD) ignore critical aspects of the disease, namely lesion type and regionality. We developed and tested a new scoring system for CSVD, “regional Cerebral Small Vessel Disease” (rCSVD) based on regional assessment of magnetic resonance imaging (MRI) features. Methods141 patients were retrospectively included with a derivation cohort of 46 consecutive brain MRI exams and a validation cohort of 95 patients with known cerebrovascular disease. We compared the predictive value of rCSVD against existing scoring methods. We determined the predictive value of rCSVD score for all-cause mortality and recurrent strokes. Results46 (44 male) veteran patients (age: 66–93 years), were included for derivation of the rCSVD score. A non-overlapping validation cohort consisted of 95 patients (89 male; age: 34–91 years) with known cerebrovascular disease were enrolled. Based on ROC analysis with comparison of AUC (Area Under the Curve), “rCSVD” score performed better compared to “total SVD score” and Fazekas score for predicting all-cause mortality (0.75 vs 0.68 vs 0.69; p = 0.046). “rCSVD” and total SVD scores were predictive of recurrent strokes in our validation cohort (p-values 0.004 and 0.001). At a median of 5.1 years (range 2–17 years) follow-up, Kaplan-Meier survival analysis demonstrated an rCSVD score of 2 to be a significant predictor of all-cause-mortality. Conclusion“rCSVD” score can be derived from routine brain MRI, has value in risk stratification of patients at risk of CSVD, and has potential in clinical trials once fully validated in a larger patient cohort.

Best indices of dual Scheimpflug/Placido tomographer for keratoconus detection.

To evaluate the accuracy of different corneal parameters in detecting keratoconus using a dual Scheimpflug/Placido system (Sirius, CSO, Italy). Sixty-eight eyes of 68 keratoconus patients and 77 eyes of 77 normal subjects were prospectively assessed in a diagnostic test study. The mean differences of the corneal parameters were compared using the independent t-test. The accuracy of curvature, elevation, pachymetry, and aberrometry indices, aqueous depth, and corneal volume in 10mm was evaluated using the area under the curve (AUC), and the DeLong method was used for the comparison of AUCs. Multiple tests in a parallel manner and multiple logistic regression analysis were applied to determine the best predictor indices. All indices except aqueous depth and corneal volume were significantly different between the two groups (P < 0.001). Back keratoconus vertex (KVb) and front Baiocchi-Calossi-Versaci index (BCVf) had the highest sensitivity (for both 98.53%) followed by front symmetry index (SIf) (96.12%) and thinnest point of the cornea (88.24%) in elevation, aberrometry, curvature, and pachymetry parameters, respectively. The highest diagnostic ability was observed in KVb (AUC 0.993) and BCVf index (AUC 0.992) (DeLong > 0.05). Multiple test analysis showed a combination of indices with the highest accuracy that was similar to the performance of each one individually, and keratoconus was diagnosed correctly in 98.5% of the cases (R2 = 93%). The parameters extracted from Sirius can differentiate keratoconus from normal corneas with high accuracy without the need for complex computational algorithms. Elevation-based and combined aberrometry indices had the highest diagnostic power.

Abstract 8 Health-Related Quality of Life (HRQL) Following Transplantation with Omidubicel Versus Umbilical Cord Blood (UCB) in Patients with Hematologic Malignancies: Results from a Phase III Randomized, Multicenter Study

IntroductionOmidubicel, an advanced cell therapy used for allogeneic hematopoietic stem cell transplant has demonstrated faster hematopoietic recovery, shorter hospitalization, and lower rates of bacterial, viral, and invasive fungal infections compared with umbilical cord blood (UCB) in a phase III randomized trial (NCT02730299;Blood 2021;138:1429).ObjectiveThe objective was to compare changes in health-related quality of life (HRQL) between treatment groups in the phase III trial.MethodsPatients who received protocol-defined treatment and provided HRQL evaluations at baseline and ≥1 follow-up visit were analyzed. Outcomes included Functional Assessment of Cancer Therapy General (FACT-G) domain scores for physical, social/family, functional and emotional well-being, and EQ-5D-3L index scores, at days 42, 100, 180, and 365 post-transplant. HRQL changes from baseline were compared using mixed effect models with repeated measures, adjusting for age, sex, race, region, primary diagnosis, HCT comorbidity index, and baseline HRQL score. Average HRQL over time was compared using the area under the curve (AUC) of mean HRQL trajectories in each treatment group.ResultsSeventy-five patients (omidubiceln = 37, UCB n = 38) provided HRQL data for inclusion and were representative of the full randomized population (N = 125) at baseline. Median age was 38 years, and 41% were female. During the first year post-transplant, patients receiving omidubicel had numerically superior average FACT-G domain and EQ-5D-3L index scores compared with UCB, with mean differences across time points ranging from 1.4 to 3.1 for physical well-being, 0 to 1.3 for social/family well-being, 0.5 to 1.4 for emotional well-being, 1.6 to 3.2 for functional well-being, and 0.03 to 0.09 for the EQ-5D-3L index score. Minimal clinically important differences (MCIDs) were exceeded at ≥1 time point for mean physical and functional well-being (MCIDs = 2 units) and for the EQ-5D-3L (MCID = 0.07 units). Initial mean declines in HRQL occurred for all measures at day 42 and were consistently numerically smaller in the omidubicel group than in the UCB group. Averaging across the first year post-transplant, patients receiving omidubicel had significantly improved HRQL for physical and functional well-being domains (P < .05 for comparison of AUCs).DiscussionAlong with faster time to engraftment, lower infection risk, and shorter hospitalization, omidubicel was associated with meaningfully greater preservation or improvement of important HRQL domains compared with UCB.

5-mFI is more accurate than ASA score in predicting postoperative mortality in rectal cancer: A case series of 109 patients

IntroductionThe aim of this study was to compare the accuracy of 5-mFI (modified frailty index) to ASA score (American Society of Anesthesiologists score) in predicting postoperative mortality in patients with rectal cancer. Materials and methodsThe ability of each parameter to predict postoperative mortality was attested in 2 ways: Area under the curve (AUC) was determined using ROC curves analysis. A comparison of AUC was performed using Delong test and Henley-McNeil test.-Multivariate analysis to determine the weight of each variable in predicting postoperative mortality. ResultsThe records of 109 patients undergoing surgical resection, for curative intent, for rectal cancer, were analyzed. Nine patients died during the 30-day postoperative period (8.25%). The optimum cutoff for 5-mFI to predict mortality using the ROC analysis was 1.5. The AUC at the cut-off point was 0.93. The optimum cutoff for ASA score to predict mortality was 1.5 and the AUC at the cut-off point was 0.81. The AUC of 5-mFI was significantly higher than the AUC of ASA score (p < 0.0001 using Delong test and p = 0.0024 using Hanley and McNeil test).On univariate analysis, predictive factors of mortality were: age (p = 0.002), ASA score≥2 (p = 0.0001) and 5-mFI≥2 (p = 0.0001). On multivariate analysis, 5-mFI≥2 was the only factor significantly associated with increased odds of postoperative mortality (OR = 1.73; 95% CI 1.05–2.01). Conclusion5-mFI was more accurate than ASA score in predicting postoperative mortality in patients with rectal cancer.

A Novel Non-invasive Index of Cardiopulmonary Reserve for the Prediction of Failure of Weaning From Mechanical Ventilation.

Purpose: To develop an easy-to-implement prediction index of weaning failure for ICU patients.Materials and methods: We developed a prediction index modifying respiratory exchange ratio (RER), Mod-RER, a parameter measured during the cardiopulmonary exercise test (CPET) based on respiratory quotient. The Mod-RER index is the ratio of partial pressure of CO2 in central venous blood over the difference of partial pressure of O2 in arterial and central venous blood (Mod-RER=PcvCO2/PaO2-PcvO2, where PcvCO2 = partial pressure of CO2 in central venous blood, PaO2 = partial pressure of O2 in arterial blood, and PcvO2 = partial pressure of O2 in central venous blood). We prospectively tested its predictive value, compared to other indices of weaning outcome, in an observational study of difficult-to-wean ICU patients.Results:Mod-RER index increased significantly only in failed trials and receiver operating characteristic (ROC) analysis for prediction of outcome based on Mod-RER index change had an area under the curve (AUC) 0.80 (p<0.001). Mod-RER change exhibited the highest sensitivity (84.6%) and specificity (78.1%) among the tested indices, with the optimal cut-off of 19.3%. Comparison of AUCs did not reach statistical significance (p=0.106).Conclusions: We conclude that Mod-RER index is an accurate, easy-to-use prediction tool of weaning failure, useful in decision making of timely extubation of ICU patients, especially in the demanding era of the coronavirus disease 2019 (COVID-19) pandemic.

Machine learning-derived prediction of in-hospital mortality in patients with severe acute respiratory infection: analysis of claims data from the German-wide Helios hospital network

BackgroundSevere acute respiratory infections (SARI) are the most common infectious causes of death. Previous work regarding mortality prediction models for SARI using machine learning (ML) algorithms that can be useful for both individual risk stratification and quality of care assessment is scarce. We aimed to develop reliable models for mortality prediction in SARI patients utilizing ML algorithms and compare its performances with a classic regression analysis approach.MethodsAdministrative data (dataset randomly split 75%/25% for model training/testing) from years 2016–2019 of 86 German Helios hospitals was retrospectively analyzed. Inpatient SARI cases were defined by ICD-codes J09-J22. Three ML algorithms were evaluated and its performance compared to generalized linear models (GLM) by computing receiver operating characteristic area under the curve (AUC) and area under the precision-recall curve (AUPRC).ResultsThe dataset contained 241,988 inpatient SARI cases (75 years or older: 49%; male 56.2%). In-hospital mortality was 11.6%. AUC and AUPRC in the testing dataset were 0.83 and 0.372 for GLM, 0.831 and 0.384 for random forest (RF), 0.834 and 0.382 for single layer neural network (NNET) and 0.834 and 0.389 for extreme gradient boosting (XGBoost). Statistical comparison of ROC AUCs revealed a better performance of NNET and XGBoost as compared to GLM.ConclusionML algorithms for predicting in-hospital mortality were trained and tested on a large real-world administrative dataset of SARI patients and showed good discriminatory performances. Broad application of our models in clinical routine practice can contribute to patients’ risk assessment and quality management.

Radiomic Analysis of Positron-Emission Tomography and Computed Tomography Images to Differentiate between Multiple Myeloma and Skeletal Metastases.

Multiple myeloma and extensive lytic skeletal metastases may appear similar on positron-emission tomography and computed tomography (PET-CT) in the absence of an obvious primary site or occult malignancy. Radiomic analysis extracts a large number of quantitative features from medical images with the potential to uncover disease characteristics below the human visual threshold. This study aimed to evaluate the diagnostic capability of PET and CT radiomic features to differentiate skeletal metastases from multiple myeloma. Forty patients (20 histopathologically proven cases of multiple myeloma and 20 cases of a variety of bone metastases) underwent staging 18F-fluorodeoxyglucose PET-CT at our institute. A total of 138 PET and 138 CT radiomic features were extracted by manual semi-automatic segmentation and standardized. The original dataset was subject separately to receiver operating curve analysis and correlation matrix filtering. The former showed 16 CT and 19 PET parameters to be significantly related to the outcome at 5%, whereas the latter resulted in 16 CT and 14 PET features. Feature selection was done with 7 evaluators with stratified 10-fold cross-validation. The selected features of each evaluator were subject to 14 machine-learning algorithms. In view of small sample size, two approaches for model performance were adopted: The first using 10-fold stratified cross-validation and the second using independent random training and test samples (26:14). In both approaches, the highest area under the curve (AUC) values were selected for 5 CT and 5 PET features. These 10 features were combined and the same process was repeated. The quality of the performance of the models was assessed by MSE, RMSE, kappa statistic, AUC, area under the precision-recall curve, F-measure, and Matthews correlation coefficient. In the first approach, the highest AUC = 0.945 was seen with 5 CT parameters. In the second approach, the highest AUC = 0.9538 was seen with 4 CT and one PET parameter. CT neighborhood gray-level different matrix coarseness and CT gray-level run-length matrix LGRE were common parameters in both approaches. Comparison of AUC of the above models showed no significant difference (P = 0.9845). Feature selection by principal components analysis and feature classification by the multilayer perceptron machine-learning model using independent training and test samples yielded the overall highest AUC. Machine-learning models using CT parameters were found to differentiate bone metastases from multiple myeloma better than models using PET parameters. Combined models using PET and CECT data showed better overall performance than models using only either PET or CECT data. Machine-learning models using independent training and test sets were performed on par with those using 10-fold stratified cross-validation with the former incorporating slightly more PET features. Certain first- and second-order CT and PET texture features contributed in differentiating these two conditions. Our findings suggested that, in general, metastases were finer in CT and PET texture and myelomas were more compact.

Comparison of base excess, lactate and pH predicting 72-h mortality of multiple trauma

ObjectiveTo compare the predictive values of base excess (BE), lactate and pH of admission arterial blood gas for 72-h mortality in patients with multiple trauma.MethodsThis was a secondary analysis based on a publicly shared trauma dataset from the Dryad database, which provided the clinical data of 3669 multiple trauma patients with ISS > = 16. The records of BE, lactate, pH and 72-h prognosis data without missing values were selected from this dataset and 2441 individuals were enrolled in the study. Logistic regression model was performed to calculate the odds ratios (ORs) of variables. Area under the curve (AUC) of receiver operating curve (ROC) was utilized to evaluate the predictive value of predictors for 72 h in-hospital mortality. Pairwise comparison of AUCs was performed using the Delong’s test.ResultsThe statistically significant correlations were observed between BE and lactate (r = − 0.5861, p < 0.05), lactate and pH (r = − 0.5039, p < 0.05), and BE and pH (r = − 0.7433, p < 0.05). The adjusted ORs of BE, lactate and pH for 72-h mortality with the adjustment for factors including gender, age, ISS category were 0.872 (95%CI: 0.854–0.890), 1.353 (95%CI: 1.296–1.413) and 0.007 (95%CI: 0.003–0.016), respectively. The AUCs of BE, lactate and pH were 0.693 (95%CI: 0.675–0.712), 0.715 (95%CI: 0.697–0.733), 0.670 (95%CI: 0.651–0.689), respectively.ConclusionsThere are significant correlations between BE, lactate and pH of the admission blood gas, all of them are independent predictors of 72-h mortality for multiple trauma. Lactate may have the best predictive value, followed by BE, and finally pH.

Efficacy of high-resolution, 3-D diffusion-weighted imaging in the detection of breast cancer compared to dynamic contrast-enhanced magnetic resonance imaging.

PurposeTo evaluate the utility of high-resolution, 3-D diffusion-weighted imaging (DWI) in the detection of breast cancer and to compare the sensitivity, specificity, and area under the curves of DWI and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).Material and methodProspective IEC approved study included 131 breast lesions detected on mammography and breast ultrasound. Cases underwent MRI on a 3 Tesla scanner using a dedicated breast coil. T2WI, STIR, T1WI, and dynamic post contrast MR. DWI MRI with b value of 50, 800, and 1500 s/mm2. Post-processing data with apparent diffusion coefficient (ADC) calculations and kinetic curves were obtained. Characteristics for lesions were analysed as per ACR BI-RADS descriptors. Final histopathological diagnosis was considered as the standard of reference. c2 test, t-test, receiver operating characteristic (ROC) curve analysis, pairwise comparison of ROC curves, sensitivity, specificity, diagnostic accuracy, and area under the curve (AUC) were calculated.ResultsSixty-six (50.38%) malignant and 65 (59.62%) benign lesions were included in the study. The mean ADC of malignant lesions was 0.870 × 10–3 mm2/s and 1.637 × 10–3 mm2/s (p < 0.0001) for benign lesions. Sensitivity and specificity for DWI were 95.45% and 90.76%, respectively, and for DCE-MRI they were 96.97% and 87.69%, respectively. Positive predictive value (PPV) and negative predictive value (NPV) were obtained at 91.30% and 95.16%, respectively, in DWI while in DCE-MRI they were 88.88% and 96.61%, respectively. The AUC for ADC was 0.979. In ROC comparison of AUC for DWI 0.931 and for DCE-MRI 0.923, the difference between the areas was 0.00781 (p = 0.782).ConclusionsHigh-resolution DWI is a non-contrast MRI technique, which improves the lesion detection with diagnostic performance comparable to DCE-MRI and has potential as an adjunct with screening mammography.

Assessment of population-based input functions for Patlak imaging of whole body dynamic 18F-FDG PET

BackgroundArterial blood sampling is the gold standard method to obtain the arterial input function (AIF) for quantification of whole body (WB) dynamic 18F-FDG PET imaging. However, this procedure is invasive and not typically available in clinical environments. As an alternative, we compared AIFs to population-based input functions (PBIFs) using two normalization methods: area under the curve (AUC) and extrapolated initial plasma concentration (CP*(0)). To scale the PBIFs, we tested two methods: (1) the AUC of the image-derived input function (IDIF) and (2) the estimated CP*(0). The aim of this study was to validate IDIF and PBIF for FDG oncological WB PET studies by comparing to the gold standard arterial blood sampling.MethodsThe Feng 18F-FDG plasma concentration model was applied to estimate AIF parameters (n = 23). AIF normalization used either AUC(0–60 min) or CP*(0), estimated from an exponential fit. CP*(0) is also described as the ratio of the injected dose (ID) to initial distribution volume (iDV). iDV was modeled using the subject height and weight, with coefficients that were estimated in 23 subjects. In 12 oncological patients, we computed IDIF (from the aorta) and PBIFs with scaling by the AUC of the IDIF from 4 time windows (15–45, 30–60, 45–75, 60–90 min) (PBIFAUC) and estimated CP*(0) (PBIFiDV). The IDIF and PBIFs were compared with the gold standard AIF, using AUC values and Patlak Ki values.ResultsThe IDIF underestimated the AIF at early times and overestimated it at later times. Thus, based on the AUC and Ki comparison, 30–60 min was the most accurate time window for PBIFAUC; later time windows for scaling underestimated Ki (− 6 ± 8 to − 13 ± 9%). Correlations of AUC between AIF and IDIF, PBIFAUC(30–60), and PBIFiDV were 0.91, 0.94, and 0.90, respectively. The bias of Ki was − 9 ± 10%, − 1 ± 8%, and 3 ± 9%, respectively.ConclusionsBoth PBIF scaling methods provided good mean performance with moderate variation. Improved performance can be obtained by refining IDIF methods and by evaluating PBIFs with test-retest data.

The validity of salivary gland scintigraphy in Sjögren's syndrome diagnosis: comparison of visual and excretion fraction analyses.

The diagnostic validity of salivary gland scintigraphy in Sjögren's syndrome (SS) has not been conclusively defined. Whether a quantitative (excretion fraction) interpretation of scintigraphy is superior to a qualitative one (visual analysis) remains a matter of debate. We sought to determine whether the diagnostic discrimination of excretion fraction is higher compared to that obtained by visual analysis. Diagnostic test validity study that encompassed 137 suspected SS subjects who underwent scintigraphy for diagnostic purposes. Patients were diagnosed as SS and non-SS according to the rheumatologist's clinical judgment, and by using the American-European Consensus Group (AECG) and American College of Rheumatology (ACR) classification criteria. Visual analysis (normal vs. abnormal and Schall's classification grade) and excretion fraction scores were calculated. The diagnostic discrimination of these methods was compared through the area under the curve (AUC) analysis. Scintigraphy associations with SS clinical and laboratory features were assessed through multivariable regression analysis. Schall's classification AUC reached statistical significance in its diagnostic discrimination for SS clinical judgment (0.704 [95%CI 0.597-0.811]) and AECG criteria (0.764 [95%CI 0.641-0.886]). Similarly, submandibular excretion fraction was associated with SS diagnosis based on ACR (0.737 [95%CI 0.546-0.931]) and AECG criteria (0.715 [95%CI 0.597-0.833]). However, AUC comparisons between qualitative and quantitative methods did not yield statistically significant values. Both interpretation modalities were associated with SS serological features. Moreover, excretion fraction was also associated with salivary gland biopsy. SS diagnostic discrimination of excretion fraction is not superior to that obtained by qualitative visual analysis. Both qualitative and quantitative scintigraphy methods are associated with SS clinical and laboratory characteristics.

Development and validation of a LC-MS/MS assay for quantifying the uptake of docosahexaenoic acid-d5 into mouse microglia

Docosahexaenoic acid (DHA) is a polyunsaturated fatty acid with the capacity to reduce the proinflammatory response of activated microglia that occurs during neuroinflammation. The uptake of DHA into microglia is essential for it to exert its neuroprotective effects. However, quantifying the uptake of DHA into microglia is complicated by the presence of endogenous DHA interfering with any quantification technique. A sensitive liquid chromatography-tandem mass spectrometry (LC–MS/MS) assay was therefore developed and validated in order to assess the microglial uptake of docosahexaenoic acid-d5 (DHA-d5) as a surrogate for DHA. Using a mobile phase consisting of 90 % (v/v) acetonitrile and 10 % (v/v) water containing 2 mM ammonium acetate, a flow rate of 0.3 mL/min, and MS/MS detection in the negative ionization mode, DHA-d5 was detected at m/z transitions of 332.1/228.3/234.2, with good linearity between chromatographic area under the curve (AUC) and DHA-d5 mass (R2 = 0.999) over the range of 0.0063−0.1 ng. The precision and accuracy values for the quality control samples (0.0063, 0.025, and 0.1 ng) were less than 9.3 % and 96.6–109.8 %, respectively, and a comparison of DHA-d5 AUC when prepared in PBS or in microglial cell lysate demonstrated no significant difference between quantification of these quality control samples. Utilizing this quantification approach (with preparation of DHA-d5 calibration standards in PBS), the uptake of DHA-d5 into BV-2 microglial cells over a 15 min period was assessed, following the spiking of DHA-d5 at 50 ng/mL. Following protein normalization using a BCA protein assay, a rapid and linear uptake of DHA-d5 into BV-2 cells was observed in the first 2 min, after which a plateau in uptake was observed, in line with that reported for DHA uptake in other cell types. This novel LC–MS/MS technique can now be exploited to unravel the processes involved in microglial uptake of DHA, insights that may be used to maximize the anti-inflammatory effects of DHA in neuroinflammation.