Receiver Operating Characteristic AUC Research Articles

Hypersensitivity Pneumonitis Radiologic Features in Interstitial Lung Diseases

The radiologic criteria of hypersensitivity pneumonitis (HP) guidelines focus on four HP compatible features (HPCF) in high-resolution computed tomography (HRCT): ground glass opacities, mosaic attenuation, air-trapping, and centrilobular nodules. However, evidence to support these criteria are limited. Consecutive interstitial lung disease (ILD) patients who underwent HRCT between 2016 and 2021 in three medical centers were included. We assessed the prevalence of HPCF in each ILD and their association with HP diagnosis. We evaluated the impact of HPCF amount for HP diagnosis and the performance of the radiologic criteria by the ATS/JRS/ALAT and CHEST HP guidelines. 436 patients with ILD were included (mean age 66, 48% females), of them, 56 (13%) with HP. All four HPCF were more prevalent in HP than in non-HP ILD (p<0.001 for all). In multivariate analysis, air-trapping was the strongest independent predictor (AOR 4.1, 95% CI 2-8.4, p<0.001). Centrilobular nodules were present almost exclusively in HP and smoking-related ILD. The amount of HPCF in HRCT had an excellent predictive ability for HP diagnosis (receiver operating characteristic AUC 0.85, 95% CI 0.80-0.90). The radiologic criteria of both guidelines had high specificity for "typical HP" and high sensitivity for "compatible with HP", although with low positive predictive values. Our findings remained robust even when including only patients that had a diagnostic biopsy. The presence and amount of HPCF in HRCT predicted HP diagnosis in real-life settings. While current HP radiologic criteria demonstrated good diagnostic performance, our findings highlight areas for future improvement.

B-333 Optimizing AFP Cutoffs for Hepatocellular Carcinoma Screening: Insights from the National Cancer Screening Program in Korea

Abstract Background The incidence rate and mortality rate of liver cancer were 11.6 (ranked 8th among cancers) and 10.7 (4th) per 100,000 individuals respectively globally in 2020, whereas in Korea, they were higher at 29.5 (7th) and 20.6 (2nd) per 100,000 individuals. The National Cancer Screening Program (NCSP) in Korea conducts biannual concurrent liver ultrasound and serum alpha-fetoprotein (AFP) measurement for hepatocellular carcinoma (HCC) surveillance in high-risk groups, including those with chronic hepatitis B and C, and liver cirrhosis. The effectiveness of surveillance is impacted by varying AFP cutoffs; however, within the NCSP, different cutoffs are being used, and it is not clear which cutoffs are being employed. Harmonization of AFP test results by major reagent manufacturers have been achieved, enabling the adoption of a uniform threshold. This study aims to assess the variation of AFP cutoffs among institutions within the NCSP and suggest a unified and optimal AFP threshold. Methods This study examined HCC screening results from the NCSP between 2018 and 2020, investigating unit and cutoff usage for AFP test across institutions each year (number of institutions were 4452 for 2018, 4754 for 2019, and 4847 for 2020). To determine the optimal AFP cutoff for HCC screening, datasets comprised unique patient results from 2018 to 2020 (number of patients = 819,644). Receiver operating characteristic (ROC) curve analyses were conducted for determine best AFP cutoffs. Cancer diagnosis was defined by billing records indicating HCC within one year post-screening. Results More than 96% of institutions used ng/mL as a unit of AFP test. Among institutions using ng/mL, the most frequently used AFP cutoff was 7 ng/mL, with frequency percentages of 75.7%, 72.2%, and 62.2% in 2018, 2019, 2020, respectively. The percentiles (1st, 10th, 90th, 99th) of AFP cutoff usage for the years 2018, 2019, and 2020 were (7, 7, 8.8, 15), (7, 7, 8.9, 15), and (7, 7, 9, 15) respectively. The AUC of ROC was 0.824 and some cut-off points with their sensitivity and specificity values were as follows: 5 ng/mL (0.648, 0.874); 10 (0.457, 0.976); 20 (0.327, 0.993); 40 (0.246, 0.997); 100 (0.169, 0.998); 200 (0.123, 0.999); 400 (0.084, 1). Conclusions Different cutoffs observed across institutions in NCSP. Our study cautiously suggests that the optimal AFP value for screening HCC in NCSP may range from 10 to 20 ng/mL, considering sensitivity and specificity when AFP is combined with ultrasound in regions with a high prevalence of HCC. For a more suitable AFP cutoff recommendation, additional analyses based on ultrasound findings and underlying diseases should be considered.

A Longitudinal Model for a Dynamic Risk Score to Predict Delayed Cerebral Ischemia after Subarachnoid Hemorrhage.

Accurate longitudinal risk prediction for DCI (delayed cerebral ischemia) occurrence after subarachnoid hemorrhage (SAH) is essential for clinicians to administer appropriate and timely diagnostics, thereby improving treatment planning and outcome. This study aimed to develop an improved longitudinal DCI prediction model and evaluate its performance in predicting DCI between day 4 and 14 after aneurysm rupture. Two DCI classification models were trained: (1) a static model based on routinely collected demographics and SAH grading scores and (2) a dynamic model based on results from laboratory and blood gas analysis anchored at the time of DCI. A combined model was derived from these two using a voting approach. Multiple classifiers, including Logistic Regression, Support Vector Machines, Random Forests, Histogram-based Gradient Boosting, and Extremely Randomized Trees, were evaluated through cross-validation using anchored data. A leave-one-out simulation was then performed on the best-performing models to evaluate their longitudinal performance using time-dependent Receiver Operating Characteristic (ROC) analysis. The training dataset included 218 patients, with 89 of them developing DCI (41%). In the anchored ROC analysis, the combined model achieved a ROC AUC of 0.73 ± 0.05 in predicting DCI onset, the static and the dynamic model achieved a ROC AUC of 0.69 ± 0.08 and 0.66 ± 0.08, respectively. In the leave-one-out simulation experiments, the dynamic and voting model showed a highly dynamic risk score (intra-patient score range was 0.25 [0.24, 0.49] and 0.17 [0.12, 0.25] for the dynamic and the voting model, respectively, for DCI occurrence over the course of disease. In the time-dependent ROC analysis, the dynamic model performed best until day 5.4, and afterwards the voting model showed the best performance. A machine learning model for longitudinal DCI risk assessment was developed comprising a static and a dynamic sub-model. The longitudinal performance evaluation highlighted substantial time dependence in model performance, underscoring the need for a longitudinal assessment of prediction models in intensive care settings. Moreover, clinicians need to be aware of these performance variations when performing a risk assessment and weight the different model outputs correspondingly.

Association of neutrophil-to-lymphocyte ratio with age and 180-day mortality after emergency surgery

BackgroundTo examine the relationship between neutrophil-to-lymphocyte ratio (NLR), age, and mortality rates after emergency surgery.MethodsIn this observational study, a total of 851 patients undergoing emergency surgery between January 2022 and January 2023 were retrospective examined. Using 30 and 180 days mortality data, NLR differences and receiver operating characteristic (ROC) curves were analyzed using a 65-year threshold. A multiple logistic regression model was constructed incorporating age and NLR. Finally, Kaplan–Meier curves were constructed for mortality.ResultsAmong 851 patients, the 30 and 180 days mortality rates were 5.2% and 10.8%, respectively. Median NLR in 30 days was 5.6 (3.1 to 9.6) in survivors and 8.7 (4.6 to 13.4) in deceased patients (p < 0.0001); in 180 days, it was 5.5 (3.1 to 9.8) and 8.8 (4.8 to 14.5), respectively (p < 0.0001). In the 30- and 180-days mortality analyses, median NLRs were 5.1 (2.9 to 8.9) and 4.9 (2.9 to 8.8) in survivors and 10.6 (6.9 to 16.6) and 9.3 (5.4 to 14.9) in deceased patients aged < 65 years, respectively. The ROC AUC in patients younger than 65 years was higher for 30 days (AUC 0.75; 95% CI 0.72 to 0.87) and 180 days (AUC 0.73; 95% CI 0.64 to 0.81). Multivariate logistic regression revealed that the NLR (odds ratio, 1.03 [95% CI 1.005 to 1.053; p = 0.0133) and age (odds ratio, 1.05 [95% CI 1.034 to 1.064; p < 0.0001) significantly contributed to the model. Survival analysis revealed differences in the 180 days mortality (p = 0.0006).ConclusionWe observed differences in preoperative NLR between patients who survived and those who died after emergency surgery. Age impacts the use of NLR as a mortality risk factor.Trial registrationNCT06549101, retrospectively registered.

Factors related to the occurrence of fetal birth defects and the construction of a Nomogram model.

To explore the influencing factors of fetal birth defects (BD) and construct a nomogram model. A total of 341 newborns admitted to Meizhou people's hospital from September 2021 to September 2023 were randomly grouped into a modeling group (239 cases) and a validation group (102 cases). The modeling group fetuses were separated into BD and non-BD groups. Multivariate logistic regression analyzed risk factors for BD; R software constructed a nomogram model; Receiver operating characteristic (ROC) curve evaluated the model's discrimination for BD. The top 5 types of BD were congenital heart disease, polydactyly/syndactyly, cleft lip/palate, ear malformation, and foot malformation, with incidence rates of 23.81%, 20.63%, 12.70%, 11.11%, and 7.94%, respectively. BD incidence was 26.36% (63/239). Significant differences between BD and non-BD groups were found in maternal age, gestational age, history of adverse pregnancy/childbirth, gestational hypertension, adverse emotions during pregnancy, and folic acid intake duration (P<0.05). Logistic regression showed maternal age (OR: 4.125), gestational age (OR: 3.066), adverse pregnancy history (OR: 10.628), gestational hypertension (OR: 5.658), adverse emotions (OR: 5.467), and folic acid intake duration (OR: 4.586) were risk factors for BD (P<0.05). The modeling group's ROC AUC was 0.938, calibration curve slope close to 1, H-L test =8.342, P=0.692; external validation AUC was 0.961, calibration slope close to 1, H-L test =7.634, P=0.635. Identified risk factors include maternal age, gestational age, adverse pregnancy history, gestational hypertension, adverse emotions, and folic acid intake duration. The nomogram model shows good discrimination and consistency for evaluating neonatal BD risk.

The ratio of bone marrow myeloid progenitor cell proportion to mature lymphocytes proportion can effectively differentiate aplastic anemia and hypoplastic myelodysplastic syndrome and evaluate the quality of bone marrow aspirates.

Aplastic anemia (AA) and hypoplastic myelodysplastic syndrome (MDS-h) are bone marrow failure disease and difficult to distinguish merely by morphological analysis. In this study, we investigated the value of flow cytometry (FCM) in the differential diagnosis of AA and MDS-h. We included 822 patients (626 control, 69 AA, 22 MDS-h and 105 dilution patients) from January 2017 to December 2022 for a retrospective study. Bone marrow myeloid progenitor (MP) cell and mature lymphocytes proportions were analyzed by FCM. The ratio of MP cell proportion and mature lymphocytes proportion, MPLR, was calculated. Data were compared by Kruskal-Wallis test. Differential diagnostic efficacy was evaluated by receiver operating characteristic (ROC) curve. Cutoff value was determined by the maximum Youden index. Bone marrow MP cell proportion and MPLR of MDS-h patients were higher than AA patients. Mature lymphocytes proportion of MDS-h patients was lower than AA patients. Area under ROC curve (AUC of ROC) of MP cell proportion, MPLR and mature lymphocytes proportion to distinguish AA from MDS-h were 0.992, 0.988, and 0.850, respectively. Moreover, MPLR of dilution patients was higher than AA patients but lower than MDS-h patients. The AUC of ROC curves of MPLR to distinguish MDS-h and AA from dilution were 0.854 and 0.871, respectively. Bone marrow MP cell proportion and MPLR can effectively discriminate AA from MDS-h with similar differential efficacy, which is higher than mature lymphocytes proportion. Moreover, MPLR can evaluate the quality of bone marrow aspirates, which would interfere with the differential diagnosis.

Clinicopathological features affecting the efficacy in 131I ablation therapy of papillary thyroid carcinoma with lymph node metastasis.

Lymph node metastasis is the major cause of increased recurrence and death in patients with papillary thyroid carcinoma (PTC). We evaluate the clinicopathologic factors affecting excellent response (ER) in patients with PTC with lymph node metastasis following operation and 131I ablation therapy. A total of 423 patients with PTC with lymph node metastasis who underwent thyroidectomy and postoperative 131I ablation therapy were enrolled. The relationship between clinicopathological factors affecting ER achievement was analyzed. Multivariate analysis showed that the foci diameter (≤1 cm), unifocal, combination with Hashimoto's thyroiditis (HT), lymph node metastases rate (LR) (≤40%), no postoperative lymph node metastasis, low preablative stimulated thyroglobulin (ps-Tg) level (≤3.87 ng/mL), and the time of 131I ablation therapy (one time) were positively correlated with the ER achievement [odds ratio (OR): 1.744, 3.114, 3.920, 4.018, 2.074, 9.767, and 49.491, respectively; all p < 0.05]. The receiver operating characteristic (ROC) curves showed that the cutoff values of ps-Tg and LR were 4.625 ng/mL and 50.50%, respectively. The AUC of ROC of ps-Tg and LR for predicting ER achievement was 0.821 and 0.746, respectively. The Tg and the cumulative risk of non-ER elevated with the increase of LR, especially for the high-level ps-Tg (>4.625 ng/mL) group. The foci diameter and number, combination with HT, LR, and ps-Tg level are independent factors for ER. Ps-Tg level and LR are valid predictive factors for the efficacy of 131I therapy in patients with PTC. The predictive value of the cumulative risk of non-ER can be improved by the combination of ps-Tg and LR.

Predicting an unfavorable outcome in patients with liver failure associated with obstructive jaundice syndrome: a prospective observational study

INTRODUCTION: Specialized scales developed to assess survival and mortality of patients after liver transplantation have not been validated when applied to liver failure in the setting of obstructive jaundice. OBJECTIVE: To determine the prognostic value of multiparametric scoring scales and to identify predictors of unfavorable outcome in liver failure due to obstructive jaundice. MATERIALS AND METHODS: 53 patients with confirmed liver failure due to obstructive jaundice of benign etiology who underwent biliary decompression were included in this prospective, observational, single-center study. Depending on the outcome two groups were distinguished: with favorable (n = 27, 51 %) and with unfavorable outcome (n = 26, 49 %). The following time points were defined for the dynamic evaluation of the course of the disease: day 1, day 3, day 7, and day 11 after decompression. Statistical processing of the data was performed using IBM SPSS Statistics 22 software for social science data analysis. RESULTS: The sensitivity and specificity of the studied scales in predicting liver failure due to obstructive jaundice were calculated on the basis of receiver operating characteristic (ROC) analysis. The AUROC for the SOFA was 0.862, for the MELD — 0.882, for the APACHE II — 0.864, for the Child-Turcotte-Pugh — 0.813. The sensitivity and specificity values for the SOFA were 78.9 and 77.8 %, for the MELD — 80.8 and 79.7 %, for the APACHE II — 57.7 and 81.9 %, and for the Child-Turcotte-Pugh — 75.1 and 70.9 %, respectively. Albumin was an independent predictor of unfavorable outcome (AUC ROC 0.909, p = 0.01), sensitivity 88.6 %, specificity 85.2 %. CONCLUSIONS: The scales presented in the study and the biomarker candidate “albumin” showed significant prognostic ability, but low values of sensitivity and specificity (less than 80 %) in some points of the study require the search for additional predictors of unfavorable outcome of liver failure due to obstructive jaundice.

Serum uric acid level is associated with glomerular ischemic lesions in patients with primary membranous nephropathy: an analytical, cross-sectional study

To investigate the relationship between serum uric acid level and glomerular ischemic lesions (GIL) in patients with primary membranous nephropathy (PMN) and identify relevant risk factors. A total of 201 patients with PMN but normal renal function confirmed by renal biopsy executed in the Liaocheng People’s Hospital, China, during January 2020-January 2023 were analyzed retrospectively. The enrolled patients were divided into a hyperuricemia group and a normal serum uric acid group (control group) according to their serum uric acid levels. Then, the participants were further divided into a non-GIL group or a GIL group based on the patient’s renal biopsy results. The two groups’ clinical and pathological data and meaningful indicators for differences were analyzed by binary logistic regression analysis. Additionally, the serum uric acid level prediction value on GIL was investigated using receiver operating characteristic (ROC) curves. Compared with the control group, the hyperuricemia group exhibited high serum uric acid, the prevalence of GIL, serum albumin, the prevalence of hypertension, and low-density lipoprotein cholesterol (LDL) levels (P < 0.05). Compared with the non-GIL group, the GIL group exhibited were older, had enhanced serum uric acid, serum albumin, and an increased prevalence of tubular atrophy/interstitial fibrosis (TA/IF), arteriolosclerosis, and low eGFR levels (P < 0.05). The binary logistic regression analysis revealed that the serum uric acid and the TA/IF are independent risk factors of GIL (P < 0.05). The AUC of ROC of GIL of PMN patients, predicted based on the serum uric acid concentration, was 0.736 (P < 0.05), wherein the threshold = 426.5 μmol/L and the Youden’s index = 0.41. Serum uric acid concentration and the TA/IF are independent risk factors of GIL in patients with PMN, and the former exhibits prediction value on GIL in patients with PMN.

Development and external validation of a novel score for predicting postoperative 30‑day mortality in tumor craniotomy patients: A cross‑sectional diagnostic study.

The identification of patients with craniotomy at high risk for postoperative 30-day mortality may contribute to achieving targeted delivery of interventions. The present study aimed to develop a personalized nomogram and scoring system for predicting the risk of postoperative 30-day mortality in such patients. In this retrospective cross-sectional study, 18,642 patients with craniotomy were stratified into a training cohort (n=7,800; year of surgery, 2012-2013) and an external validation cohort (n=10,842; year of surgery, 2014-2015). The least absolute shrinkage and selection operator (LASSO) model was used to select the most important variables among the candidate variables. Furthermore, a stepwise logistic regression model was established to screen out the risk factors based on the predictors chosen by the LASSO model. The model and a nomogram were constructed. The area under the receiver operating characteristic (ROC) curve (AUC) and calibration plot analysis were used to assess the model's discrimination ability and accuracy. The associated risk factors were categorized according to clinical cutoff points to create a scoring model for postoperative 30-day mortality. The total score was divided into four risk categories: Extremely high, high, intermediate and low risk. The postoperative 30-day mortality rates were 2.43 and 2.58% in the training and validation cohort, respectively. A simple nomogram and scoring system were developed for predicting the risk of postoperative 30-day mortality according to the white blood cell count; hematocrit and blood urea nitrogen levels; age range; functional health status; and incidence of disseminated cancer cells. The ROC AUC of the nomogram was 0.795 (95% CI: 0.764 to 0.826) in the training cohort and it was 0.738 (95% CI: 0.7091 to 0.7674) in the validation cohort. The calibration demonstrated a perfect fit between the predicted 30-day mortality risk and the observed 30-day mortality risk. Low, intermediate, high and extremely high risk statuses for 30-day mortality were associated with total scores of (-1.5 to -1), (-0.5 to 0.5), (1 to 2) and (2.5 to 9), respectively. A personalized nomogram and scoring system for predicting postoperative 30-day mortality in adult patients who underwent craniotomy were developed and validated, and individuals at high risk of 30-day mortality were able to be identified.

Validation of a Stenotrophomonas maltophilia bloodstream infection prediction score in the hematologic malignancy population

Stenotrophomonas maltophilia (SM) bloodstream infections (BSIs) contribute to significant mortality in hematologic malignancy (HM) and hematopoietic stem cell transplantation (HSCT) patients. A risk score to predict SM BSI could reduce time to appropriate antimicrobial therapy (TTAT) and improve patient outcomes. A single center cohort study of hospitalized adults with HM/HSCT was conducted. Patients had ≥ 1 blood culture with a Gram-negative (GN) organism. A StenoSCORE was calculated for each patient. The StenoSCORE2 was developed using risk factors for SM BSI identified via logistic regression. Receiver operating characteristic (ROC) curves were plotted. Sensitivity and specificity for the StenoSCORE and StenoSCORE2 were calculated. Thirty-six SM patients and 534 non-SM patients were assessed. A StenoSCORE ≥ 33 points was 80% sensitive, 68% specific, and accurately classified 69% of GN BSIs. StenoSCORE2 variables included acute leukemia, prolonged neutropenia, mucositis, ICU admission, recent meropenem and/or cefepime exposure. The StenoSCORE2 performed better than the StenoSCORE (ROC AUC 0.84 vs. 0.77). A StenoSCORE2 ≥ 4 points was 86% sensitive, 76% specific, and accurately classified 77% of GN BSIs. TTAT was significantly longer for patients with SM BSI compared with non-SM BSI (45.16 h vs. 0.57 h; p < 0.0001). In-hospital and 28-day mortality were significantly higher for patients with SM BSI compared to non-SM BSI (58.3% vs. 18.5% and 66.7% vs. 26.4%; p-value < 0.0001). The StenoSCORE and StenoSCORE2 performed well in predicting SM BSIs in patients with HM/HSCT and GN BSI. Clinical studies evaluating whether StenoSCORE and/or StenoSCORE2 implementation improves TTAT and clinical outcomes are warranted.

DeepBiomarker2: Prediction of Alcohol and Substance Use Disorder Risk in Post-Traumatic Stress Disorder Patients Using Electronic Medical Records and Multiple Social Determinants of Health.

Prediction of high-risk events amongst patients with mental disorders is critical for personalized interventions. We developed DeepBiomarker2 by leveraging deep learning and natural language processing to analyze lab tests, medication use, diagnosis, social determinants of health (SDoH) parameters, and psychotherapy for outcome prediction. To increase the model's interpretability, we further refined our contribution analysis to identify key features by scaling with a factor from a reference feature. We applied DeepBiomarker2 to analyze the EMR data of 38,807 patients from the University of Pittsburgh Medical Center diagnosed with post-traumatic stress disorder (PTSD) to determine their risk of developing alcohol and substance use disorder (ASUD). DeepBiomarker2 predicted whether a PTSD patient would have a diagnosis of ASUD within the following 3 months with an average c-statistic (receiver operating characteristic AUC) of 0.93 and average F1 score, precision, and recall of 0.880, 0.895, and 0.866 in the test sets, respectively. Our study found that the medications clindamycin, enalapril, penicillin, valacyclovir, Xarelto/rivaroxaban, moxifloxacin, and atropine and the SDoH parameters access to psychotherapy, living in zip codes with a high normalized vegetative index, Gini index, and low-income segregation may have potential to reduce the risk of ASUDs in PTSD. In conclusion, the integration of SDoH information, coupled with the refined feature contribution analysis, empowers DeepBiomarker2 to accurately predict ASUD risk. Moreover, the model can further identify potential indicators of increased risk along with medications with beneficial effects.

Type-2 diabetes mellitus remission prediction models after Roux-En-Y gastric bypass and sleeve gastrectomy based on disease severity scores

AimMetabolic and bariatric surgery (MBS) is considered one of the most effective interventions for weight loss and associated type-2 diabetes mellitus (T2DM) remission. Multiple scores including the Individualized Metabolic Surgery (IMS), DiaRem, advanced DiaRem, and Robert et al. scores, have been developed predict T2DM remission after MBS. We aim to validate each of these scores in our cohort of patients undergoing MBS with long-term follow-up and assess their efficacy based on procedure type and preoperative BMI. MethodsWe conducted a multicenter cohort study including patients with T2DM undergoing either Roux-en-Y gastric bypass (RYGB) or sleeve gastrectomy (SG). Areas under the receiver operating characteristics (ROC) curve (AUC) were calculated to assess the discriminatory ability of the four models to detect T2DM remission. ResultsA total of 503 patients (67 % females, mean age 53.5 [11] years, BMI 46.2 [8.8] kg/m2) with T2DM were included. The majority (78 %) underwent RYGB, while the rest (28 %) had SG. All four scores predicted T2DM remission in our cohort with an ROC AUC of 0.79 for IMS, 0.78 for both DiaRem and advanced-DiaRem, and 0.75 for Robert et al. score. Specific subgroups for each of these scores demonstrated higher T2DM remission rates after RYGB compared to SG. ConclusionWe demonstrate the ability of the IMS, DiaRem, advanced-DiaRem and Robert et al. scores to predict T2DM remission in patients undergoing MBS. T2DM remission rates was demonstrated to decrease with more severe IMS, DiaRem and advanced-DiaRem scores and lower Robert et al. scores.

Metabolic imaging of human embryos is predictive of ploidy status but is not associated with clinical pregnancy outcomes: a pilot trial.

Does fluorescence lifetime imaging microscopy (FLIM)-based metabolic imaging assessment of human blastocysts prior to frozen transfer correlate with pregnancy outcomes? FLIM failed to distinguish consistent patterns in mitochondrial metabolism between blastocysts leading to pregnancy compared to those that did not. FLIM measurements provide quantitative information on NAD(P)H and flavin adenine dinucleotide (FAD+) concentrations. The metabolism of embryos has long been linked to their viability, suggesting the potential utility of metabolic measurements to aid in selection. This was a pilot trial enrolling 121 IVF couples who consented to have their frozen blastocyst measured using non-invasive metabolic imaging. After being warmed, 105 couples' good-quality blastocysts underwent a 6-min scan in a controlled temperature and gas environment. FLIM-assessed blastocysts were then transferred without any intervention in management. Eight metabolic parameters were obtained from each blastocyst (4 for NAD(P)H and 4 for FAD): short and long fluorescence lifetime, fluorescence intensity, and fraction of the molecule engaged with enzyme. The redox ratio (intensity of NAD(P)H)/(intensity of FAD) was also calculated. FLIM data were combined with known metadata and analyzed to quantify the ability of metabolic imaging to differentiate embryos that resulted in pregnancy from embryos that did not. De-identified discarded aneuploid human embryos (n = 158) were also measured to quantify correlations with ploidy status and other factors. Statistical comparisons were performed using logistic regression and receiver operating characteristic (ROC) curves with 5-fold cross-validation averaged over 100 repeats with random sampling. AUC values were used to quantify the ability to distinguish between classes. No metabolic imaging parameters showed significant differences between good-quality blastocysts resulting in pregnancy versus those that did not. A logistic regression using metabolic data and metadata produced an ROC AUC of 0.58. In contrast, robust AUCs were obtained when classifying other factors such as comparison of Day 5 (n = 64) versus Day 6 (n = 41) blastocysts (AUC = 0.78), inner cell mass versus trophectoderm (n = 105: AUC = 0.88) and aneuploid (n = 158) versus euploid and positive pregnancy embryos (n = 108) (AUC = 0.82). The study protocol did not select which embryo to transfer and the cohort of 105 included blastocysts were all high quality. The study was also limited in number of participants and study sites. Increased power and performing the trial in more sites may have provided a stronger conclusion regarding the merits of the use of FLIM clinically. FLIM failed to distinguish consistent patterns in mitochondrial metabolism between good-quality blastocysts leading to pregnancy compared to those that did not. Blastocyst ploidy status was, however, highly distinguishable. In addition, embryo regions and embryo day were consistently revealed by FLIM. While metabolic imaging detects mitochondrial metabolic features in human blastocysts, this pilot trial indicates it does not have the potential to serve as an effective embryo viability detection tool. This may be because mitochondrial metabolism plays an alternative role post-implantation. This study was sponsored by Optiva Fertility, Inc. Boston IVF contributed to the clinical site and services. Becker Hickl, GmbH, provided the FLIM system on loan. T.S. was the founder and held stock in Optiva Fertility, Inc., and D.S. and E.S. had options with Optiva Fertility, Inc., during this study. The study was approved by WCG Connexus IRB (Study Number 1298156).

Comparative study of two models predicting the risk of deep vein thrombosis progression in spinal trauma patients after operation

ObjectivePatients with preoperative deep vein thrombosis (DVT) exhibit a notable incidence of postoperative deep vein thrombosis progression (DVTp), which bears a potential for silent, severe consequences. Consequently, the development of a predictive model for the risk of postoperative DVTp among spinal trauma patients is important. MethodsData of 161 spinal traumatic patients with preoperative DVT, who underwent spine surgery after admission, were collected from our hospital between January 2016 and December 2022. The least absolute shrinkage and selection operator (LASSO) combined with multivariable logistic regression analysis was applied to select variables for the development of the predictive logistic regression models. One logistic regression model was formulated simply with the Caprini risk score (Model A), while the other model incorporated not only the previously screened variables but also the age variable (Model B). The model’s capability was evaluated using sensitivity, specificity, positive predictive value, negative predictive value, accuracy, F1 score, and receiver operating characteristic (ROC) curve. Nomograms simplified and visually presented Model B for the clinicians and patients to understand the predictive model. The decision curve was used to analyze the clinical value of Model B. ResultsA total of 161 DVT patients were enrolled in this study. Postoperative DVTp occurred in 48 spinal trauma patients, accounting for 29.81% of the total patient enrolled. Model A inadequately predicted postoperative DVTp in spinal trauma patients, with ROC AUC values of 0.595 for the training dataset and 0.593 for the test dataset. Through the application of LASSO regression and multivariable logistic regression, a screening process was conducted for seven risk factors: D-dimer, blood platelet, hyperlipidemia, blood group, preoperative anticoagulant, spinal cord injury, lower extremity varicosities. Model B demonstrated superior and consistent predictive performance, with ROC AUC values of 0.809 for the training dataset and 0.773 for the test dataset. According to the calibration curves and decision curve analysis, Model B could accurately predict the probability of postoperative DVTp after spine surgery. The nomograms enhanced the interpretability of Model B in charts and graphs. ConclusionsIn summary, we established a logistic regression model for the accurate predicting of postoperative deep vein thrombosis progression in spinal trauma patients, utilizing D-dimer, blood platelet, hyperlipidemia, blood group, preoperative anticoagulant, spinal cord injury, lower extremity varicosities, and age as predictive factors. The proposed model outperformed a logistic regression model based simply on CRS. The proposed model has the potential to aid frontline clinicians and patients in identifying and intervening in postoperative DVTp among traumatic patients undergoing spinal surgery.

631. Using a commercially available assay that measures cytomegalovirus (CMV)-specific CD4+ and CD8+ T-cell immunity to predict protection against CMV: Results from a prospective, blinded clinical trial

Abstract Background Cytomegalovirus (CMV) infection is associated with significant morbidity and mortality among kidney transplant recipients (KTR). Given toxicities and costs of antivirals, there is growing interest in assays that measure CMV-specific T-cell immunity (TCI), which may predict protection against clinical infection. The Viracor® CMV TCI Panel (TCIP) uses flow cytometry and intracellular cytokine staining to measure %CMV-specific CD4+ and CD8+ T-cells; it is the only commercially available TCI assay in the US. In this investigator-initiated study, we evaluated the performance of the TCIP in predicting clinically significant CMV events. To our knowledge, this is the first prospective blinded clinical study of the TCIP. Methods We enrolled consecutive donor (D) or recipient (R) CMV seropositive KTR, who had TCIP testing monthly until either discontinuation of valganciclovir prophylaxis or the primary outcome. We also enrolled KTR with low-level untreated DNAemia, or after completion of valganciclovir treatment, to evaluate assay predictive values for progression or relapse of CMV infection, respectively. The primary outcome was CMV DNAemia (tested at the discretion of the treating provider for symptoms or laboratory findings), prompting treatment initiation. Secondary outcomes were any DNAemia and DNAemia &amp;gt;1000 IU/mL. Treating providers were unaware of TCIP results. Results We included 46 KTR. Median age was 50.5 (range 18-74) years. 73.6% identified as men, 10.8% Black, 8.7% Hispanic; 41.3% had CMV D+/R- status. KTR with CMV events had significantly lower %CMV-specific CD8+ T-cells (Fig. 1A, p=0.024), and the CMV protection ROC AUC was significant (Fig. 1B: AUC 0.78, 95%CI 0.55-0.99, p=0.026). The positive predictive values of both CD4+ and CD8+ T-cell positivity &amp;gt;0.2% for CMV protection were 96.3% (95%CI 81-99.9%) for the primary outcome, 92.6% (95%CI 75.7-99.1%) for any DNAemia, and 100% (one-sided 95%CI 87.2%) for DNAemia &amp;gt;1000 IU/mL.Figure 1.A. Comparison of CMV-specific %CD8+ T-cells between patients with or without (protected) CMV events. B Receiver Operating Characteristic (ROC) curve for CMV protection. Conclusion The TCIP exhibited good performance in predicting protection from CMV events and could be a useful adjunct tool in clinical decision-making, regarding initiation or extension of CMV prophylaxis or treatment, as well as adjustments in immunosuppression. Disclosures Panos Arvanitis, MS, NIH: Grant/Research Support|NIH: Brown University Summer Assistantship program and from the Brown Emerging Infectious Disease Scholars (EIDS) (5R25AI140490) Dimitrios Farmakiotis, M.D., Astellas: Grant/Research Support|Merck: Grant/Research Support|Viracor: Advisor/Consultant|Viracor: Grant/Research Support

Nomogram Based on Dual-Layer Spectral Detector CTA Parameter for the Prediction of Infarct Core in Patients with Acute Ischemic Stroke.

(1) Background: Acute ischemic stroke (AIS) is time-sensitive. The accurate identification of the infarct core and penumbra areas in AIS patients is an important basis for formulating treatment plans, and is the key to dual-layer spectral detector computed tomography angiography (DLCTA), a safer and more accurate diagnostic method for AIS that will replace computed tomography perfusion (CTP) in the future. Thus, this study aimed to investigate the value of DLCTA in differentiating infarct core from penumbra in patients with AIS to establish a nomogram combined with spectral computed tomography (CT) parameters for predicting the infarct core and performing multi-angle evaluation. (2) Methods: Data for 102 patients with AIS were retrospectively collected. All patients underwent DLCTA and CTP. The patients were divided into the non-infarct core group and the infarct core group, using CTP as the reference. Multivariate logistic regression analysis was used to screen predictors related to the infarct core and establish a nomogram model. The receiver operating characteristic (ROC) curve, the calibration curve, and decision curve analysis (DCA) were used to evaluate the predictive efficacy, accuracy, and clinical practicability of the model, respectively. (3) Results: Multivariate logistic analysis identified three independent predictors: iodine density (OR: 0.022, 95% CI: 0.003-0.170, p < 0.001), hypertension (OR: 7.179, 95% CI: 1.766-29.186, p = 0.006), and triglycerides (OR: 0.255, 95% CI: 0.109-0.594, p = 0.002). The AUC-ROC of the nomogram was 0.913. Calibration was good. Decision curve analysis was clinically useful. (4) Conclusions: The spectral CT parameters, specifically iodine density values, effectively differentiate between the infarct core and penumbra areas in patients with AIS. The nomogram, based on iodine density values, showed strong predictive power, discrimination, and clinical utility to accurately predict infarct core in AIS patients.

Accuracy of the GRACE Score for mortality prediction in myocardial infarction with nonobstructive coronary arteries (MINOCA)

Abstract Introduction Myocardial infarction with nonobstructive coronary arteries (MINOCA) patients account for 3.5 to 15% of all myocardial infarctions. The GRACE risk score is a well-validated tool for estimating short- and long-term risk in acute coronary syndrome, but the accuracy of the risk score for prognostic stratification in patients with MINOCA remains uncertain. Purpose We aimed to investigate whether the GRACE risk score can predict mortality in a real-world cohort of patients presenting with MINOCA. Methods We retrospectively analyzed patients admitted with MINOCA in a single center. Patients who were diagnosed with myocarditis and Takotsubo syndrome were excluded from the analysis. The GRACE risk score on admission was calculated. Patients were divided into a low-intermediate risk group (≤ 140 points, 71.5%) and a high-risk group (&amp;gt;140 points, 28.5%) according to their GRACE risk scores. Receiver operating characteristic (ROC) analysis was used to quantify the accuracy of the GRACE risk score to estimate both in-hospital and one-year mortality in MINOCA patients. Results Of a total of 3721 myocardial infarction patients, MINOCA was identified in 11.6% (n=430). 313 patients had complete data for the calculation of the GRACE on admission and were included in the analysis. Mean age was 65±12 years, and 49% (n=154) of patients were male. Mean GRACE score was 125±31 points. Patients in the high-risk group were older (74±9 vs. 61±11 years, p&amp;lt;0.001), had a higher incidence of in-hospital mortality (0.4% vs. 5.6%, p=0.008), and had a higher rate of one-year mortality (2.7% vs. 19.5%, p&amp;lt;0.001), compared with the low-intermediate risk group. There were no differences regarding sex and cardiovascular risk factors between the groups. In-hospital mortality was 1.9% and one-year mortality was 7.3%. ROC curve analysis showed that the GRACE risk score has a high value in predicting in-hospital mortality (AUC ROC 0.892; 95% CI 0.798–0.986; p=0.001), and one-year mortality (AUC ROC 0.826; 95% CI 0.739–0.0.914; p&amp;lt;0.001) in MINOCA patients. (Figure 1). The overall c-statistics were similar compared with estimates obtained from patients with myocardial infarction and significant coronary artery disease: in-hospital mortality (AUC ROC 0.0.849; 95% CI, 0.807–0.891; p&amp;lt;0.001); and one-year mortality (AUC ROC 0.776; 95% CI, 0.747–0.806; p&amp;lt;0.001). Conclusions In conclusion, the GRACE risk score provides potentially valuable prognostic information on in-hospital and one-year mortality when applied to MINOCA patients.Figure 1

Stress-only dynamic computed tomography perfusion protocol (CTP) alone without computed tomography coronary angiography (CCTA) has limited specificity to diagnose ischemia: A retrospective two-center study

PurposeTo investigate diagnostic performance of stress-only dynamic myocardial computed tomography perfusion (CTP) without computed tomography coronary angiography (CCTA) to diagnose ischemia with invasive fractional flow reserve (FFR) as a reference standard. Method135 datasets (68 positive for ischemia with invasive FFR < 0.8) acquired with a 256-slice CT system (Revolution, GE Healthcare, Chicago, IL, USA) were retrieved, postprocessed with a deep learning-based algorithm (Advanced intelligent Clear-IQ Engine (AiCE), Canon Medical Systems, Otawara, Japan) (FC03/cardiac kernel, 8 mm slice thickness), analyzed using a dedicated workstation (Vitrea research 7.11.0. Vital Images, Minnetonka, MN, USA), and loaded into a clinical workstation (CardIQ, GE Healthcare, Chicago, IL, USA) for review. Ten observers with various experience from two research sites evaluated the post-processed images, perfusion slices and maps to indicate presence vs absence of perfusion defect and its probability (five-point Likert scale). Binary decisions and probability scores were used to calculate sensitivity and specificity for each reader, and to create receiver operating characteristics (ROC) curves, respectively. Furthermore, the correlation coefficient (ICC) was computed. ROC AUC of a purely quantitative analysis was obtained thanks to a color-coded map with a fixed scale superimposed on myocardial walls displaying myocardial blood flow (MBF) values. ResultsThe overall case-based sensitivity and specificity for the detection of perfusion deficit were 0.79 and 0.30, respectively. No significant differences were detected in the AUC across readers (p value = 0.66). The AUC values were 0.50, 0.58, 0.63, 0.59, 0.45, 0.60, 0.56, 0.61, 0.52, 0.61. Absolute reader agreement ICC was 0.60 (good agreement) for an average case. ConclusionDynamic CTP alone has good sensitivity, but low specificity when analyzed without CCTA. These findings reinforce the need to guide the interpretation functional test with the knowledge of coronary artery anatomy.

UTILITY OF STREM-1 BIOMARKER AND HCP GENE FOR IDENTIFICATION OF ACINETOBACTER BAUMANNII COLONIZATION AND INFECTION IN LUNG.

Objective: Respiratory infections or colonization of Acinetobacter baumannii (Ab) are common in clinical practice but are treated differently. Early identification of Ab infection and colonization reduces the risk of antibiotic mismatch but objective laboratory indicators to distinguish between bacterial infections and colonization are lacking. To distinguish infection and colonization of Ab, we tested the role of two biomarkers, triggering receptor expressed on myeloid cells-1 (TREM-1) and hemolysin coregulated protein. Methods: A total of 96 inpatients with Ab were divided into infection and colonization groups. Blood samples were collected on days 1, 2, 3, 5, 8, and 10 and daily maximum body temperature was recorded. Polymerase Chain Reaction and Reverse Transcription Polymerase Chain Reaction were used to detect the presence and expression levels of the hcp gene in Ab clinical isolates. Results : sTREM-1 and procalcitonin (PCT) levels on days 1 to 10 and neutrophil classification (N%) on days 1 to 3 were different ( P < 0.05) in the infection group and colonization group. Receiver operating characteristic (ROC) curves showed significant differences in N% and sTREM-1 on days 2 and 3 ( P < 0.01). sTREM-1 had the highest AUC ROC on days 1, 2, and 3 of all the markers. On day 1, the ROC curve of "WBC&N%&PCT&sTREM-1" was statistically different from individual indices (white blood cell count, N%, and PCT; P < 0.05) and was equal to the ROC curve of sTREM-1 ( P > 0.05). Thirty five of 96 patients were classified as infection group and 61 as colonization group with hcp gene detection rates of 71.43% (25/35) and 31.15% (19/61), respectively. No differences in hcp gene presence and transcript levels were found between two groups ( P > 0.05). Conclusions: Dynamic monitoring of sTREM-1 and PCT is valuable in identifying Ab infection and colonization. sTREM-1 can be improved by combination with multiple biomarkers in the early stage for identification of infection and colonization. The hcp gene was more likely to be present in the infection cohort.