Similar AUC Research Articles

PHARMACOKINETIC STUDY OF OLOPATADINE 10 MG EXTENDED RELEASE TABLET IN COMPARISON WITH OLOPATADINE 5 MG IMMEDIATE RELEASE TABLET IN INDIAN POPULATION

Objective: This study was designed to assess the pharmacokinetics of single dose of olopatadine hydrochloride 10 mg extended release (ER) tablet of Ranbaxy laboratories limited (two test formulations) with two doses of Allelock® 5 mg immediate release (IR) tablets of Kyowa Hakko Kogyo Co. Ltd. (reference formulation R), in healthy, adult, Indian male subjects under fed condition.
 Methods: Fifteen healthy male volunteers, 26.07±6.62 y in age and 57.17±6.68 kg in body weight, were divided into three groups and received either olopatadine hydrochloride 10 mg ER tablet or two doses of Allelock® 5 mg tablets in each period. Blood samples were taken at predetermined time points and plasma concentrations of olopatadine were monitored by liquid chromatography mass spectrometric (LCMS/MS). Pharmacokinetic (PK) parameters AUC0-t, AUC0-24, AUC0-∞, and Cmax were calculated for olopatadine using WinNonlin. A statistical analysis was performed on PK data using SAS system.
 Results: The ER formulations showed a similar AUC as compared to the IR formulation and there was no statistically significant difference in AUC of test formulation A and B and reference R. The ratios of AUC0-t, AUC0-24 and AUC0-∞ for A/R were 91.08, 94.90 and 91.32 and for B/R were 89.63, 93.95 and 89.63 respectively. The ER formulations reported a higher Cmax value as compared to IR formulation. The ratios of Cmax for A/R and B/R were 151.09 and 167.96 respectively. But these higher Cmax values did not pose any safety issue as there were no serious adverse events reported during the study.
 Conclusion: In conclusion, we can say that though the study drugs did not meet the bioequivalence criteria set by regulatory agencies, but this study gave an insight about PK properties of olopatadine extended release formulation and given an idea about effect of smoking on the PK profile of olopatadine which can be studied in future.

Neuropsychological test validation of speech markers of cognitive impairment in the Framingham Cognitive Aging Cohort.

Aim:Although clinicians primarily diagnose dementia based on a combination of metrics such as medical history and formal neuropsychological tests, recent work using linguistic analysis of narrative speech to identify dementia has shown promising results. We aim to build upon research by Thomas JA & Burkardt HA et al. (J Alzheimers Dis. 2020;76:905-22) and Alhanai et al. (arXiv:1710.07551v1. 2020) on the Framingham Heart Study (FHS) Cognitive Aging Cohort by 1) demonstrating the predictive capability of linguistic analysis in differentiating cognitively normal from cognitively impaired participants and 2) comparing the performance of the original linguistic features with the performance of expanded features.Methods:Data were derived from a subset of the FHS Cognitive Aging Cohort. We analyzed a sub-selection of 98 participants, which provided 127 unique audio files and clinical observations (n = 127, female = 47%, cognitively impaired = 43%). We built on previous work which extracted original linguistic features from transcribed audio files by extracting expanded features. We used both feature sets to train logistic regression classifiers to distinguish cognitively normal from cognitively impaired participants and compared the predictive power of the original and expanded linguistic feature sets, and participants’ Mini-Mental State Examination (MMSE) scores.Results:Based on the area under the receiver-operator characteristic curve (AUC) of the models, both the original (AUC = 0.882) and expanded (AUC = 0.883) feature sets outperformed MMSE (AUC = 0.870) in classifying cognitively impaired and cognitively normal participants. Although the original and expanded feature sets had similar AUC, the expanded feature set showed better positive and negative predictive value [expanded: positive predictive value (PPV) = 0.738, negative predictive value (NPV) = 0.889; original: PPV = 0.701, NPV = 0.869].Conclusions:Linguistic analysis has been shown to be a potentially powerful tool for clinical use in classifying cognitive impairment. This study expands the work of several others, but further studies into the plausibility of speech analysis in clinical use are vital to ensure the validity of speech analysis for clinical classification of cognitive impairment.

Pharmacokinetics and Toxicities of Oral Docetaxel Formulations Co-Administered with Ritonavir in Phase I Trials.

IntroductionDocetaxel is widely used as intravenous (IV) chemotherapy. Oral docetaxel is co-administered with the cytochrome P450 3A4 and P-glycoprotein inhibitor ritonavir to increase oral bioavailability. This research explores the relationship between the pharmacokinetics (PK) and toxicity of this novel oral chemotherapy.MethodsThe patients in two phase I trials were treated with different oral docetaxel formulations in combination with ritonavir in different dose levels, ranging from 20 to 80 mg docetaxel with 100 to 200 mg ritonavir a day. The patients were categorized based on the absence or occurrence of severe treatment-related toxicity (grade ≥3 or any grade leading to treatment alterations). The docetaxel area under the plasma concentration–time curve (AUC) and maximum plasma concentration (Cmax) were associated with toxicity.ResultsThirty-four out of 138 patients experienced severe toxicity, most frequently observed as mucositis, fatigue, diarrhea, nausea and vomiting. The severe toxicity group had a significantly higher docetaxel AUC (2231 ± 1405 vs 1011 ± 830 ng/mL*h, p<0.0001) and Cmax (218 ± 178 vs 119 ± 77 ng/mL, p<0.0001) as compared to the patients without severe toxicity. When extrapolated from IV PK data, the patients without severe toxicity had a similar cumulative docetaxel AUC as with standard 3-weekly IV docetaxel, while the Cmax was up to 10-fold lower with oral docetaxel and ritonavir.ConclusionSevere toxicity was observed in 25% of the patients treated with oral docetaxel and ritonavir. This toxicity seems related to the PK, as the docetaxel AUC0-inf and Cmax were up to twofold higher in the severe toxicity group as compared to the non-severe toxicity group. Future randomized trials will provide a further evaluation of the toxicity and efficacy of the new weekly oral docetaxel and ritonavir regimen in comparison to standard IV docetaxel.

Cervical-length as a screening for spontaneous preterm birth in uncomplicated twins: one vs. serial measurements

Objective While cervical length (CL) provides an effective screening tool for spontaneous preterm birth in singletons, the performance in twins is still controversial. Our aim was twofold. First, to compare the performance of a single CL measurement at mid-gestation (∼20 weeks) versus serial measurements as a predictor of spontaneous preterm birth < 34 weeks in uncomplicated twin pregnancies. Second, to describe the performance of a single CL at ∼24, ∼28 and ∼32 weeks. Material and methods cohort study of twins followed at Hospital Italiano de Buenos Aires from 2013 to 2017. Inclusion criteria were dichorionic or monochorionic diamniotic twins with CL measurement between 18 and 33 + 6 weeks with available data of the delivery. Exclusion criteria included any of the following complications: iatrogenic preterm delivery <34 weeks, cerclage, fetal growth restriction, fetal death, structural anomalies, polyhydramnios, twin–twin transfusion syndrome, selective fetal growth restriction, twin anemia–polycythemia sequence, and twin reversed arterial perfusion sequence. Spontaneous preterm birth was defined as spontaneous delivery < 34 weeks. Two different cutoffs were used to classify CL as short (positive screening) or normal (negative screening): (a) a fixed cutoff of 25 mm at any gestational age (GA). The screening was considered positive if any CL measurement was <25 mm; and (b) a GA adjusted cutoff to a 10% false positive rate (FPR). The 10% FPR for each GA was calculated and the screening was considered positive if any of the CL measurements were below this 10% FPR cutoff. We report sensitivity, specificity, positive and negative predictive value, positive and negative likelihood ratio and area under the ROC curve. Results Among 777 twins followed in our Unit, 381 met exclusion criteria and 18 were excluded due to incomplete follow-up. We included 378 patients, 284 (75%) dichorionic and 94 (25%) monochorionic. The performance of one CL at 20 weeks showed a sensitivity ≤ 20% with an area under the ROC curve of 0.58 (95% CI, 0.45–0.70), while the performance of serial measurements showed a sensitivity of 58.8% (95% CI, 40.7–75.4) with an area under the ROC curve of 0.70 (95% CI, 0.61–0.79) (p < .001). The analyses of the performance of a single CL at ∼24, ∼28 and ∼32 weeks showed similar AUC than the serial measurements and, for a FPR = 10%, the performance of one measurement at 24 and 32 weeks showed a sensitivity of 30% (95% CI, 14.7–49.4) and 31.6% (95% CI, (12.6–56.6), while the measurement at 28 weeks showed a sensitivity of 48.3% (95% CI, (29.4–67.5). Conclusion Serial measurements showed a better performance than a single one in mid-gestation. Moreover, among single measurements the CL in mid-gestation showed the poorest performance, while the 28 weeks assessment detected half of the preterm deliveries. However, all the strategies showed modest performances.

Abstract 311: Machine Learning of the Electrocardiogram to Detect Regional Structural Abnormalities of the Heart

Introduction: Regional dysfunction of cardiac myocardium can result from diverse underlying conditions and cause adverse events even in patients without clinically apparent cardiovascular disease over ejection fraction. Assessment of regional wall motion abnormalities (WMA) currently requires sophisticated imaging that is not feasible for population screening or frequent disease monitoring. Hypothesis: We hypothesized that an AI-enabled ECG model trained on a dataset of qualitative labels could identify and localize wall motion abnormalities with higher accuracy than traditional ECG analysis Methods: In a large academic center, a deep convolutional network was developed with raw 12-lead ECGs and associated reports from 82,424 transthoracic echocardiograms (N = 50,960 patients, age 64 ± 17 years, 54.5% male). 80% of the data was used in model development and the remaining 20% was used for testing. ECGs with ventricular pacing and non-finalized echocardiography reports were excluded. Pre-processing included Kors transformation and beat extraction for input size of 3x300 samples (Figure 1A) and output labels were established by NLP of semi-structured echocardiography reports. Results: ML ECG based models predicted inferior/posterior regional wall motion abnormality with C-statistic of 0.772 (Figure 1B). Physician interpretation of Q-wave ECG pattern was inferior (C-statistic of 0.505). Other segments had similar AUC (apex 0.81, anterior 0.80, lateral 0.75, septal 0.75). Patients with positive ECG screen had +LR 2.70 of having a wall motion abnormality on echocardiography and patients with WMA by echocardiography had decreased survival (LR 0.41, CI: 0.34-0.47, p&lt;0.005) mortality over follow-up of &gt;1500 days (Figure 1C). Conclusion: This study is the first to evaluate the presence and location of regional wall motion abnormalities from inexpensive and noninvasive 12-lead ECG. This approach could be applied for widespread ambulatory screening.

CTNI-09. A PHASE I HEALTHY VOLUNTEER STUDY ON THE RELATIVE BIOAVAILABILITY AND FOOD EFFECT OF CAPSULE AND GRANULE FORMULATIONS OF SELUMETINIB

Abstract Selumetinib (AZD6244, ARRY-142886) is an oral, potent and highly selective allosteric MEK 1/2 inhibitor approved by the FDA as a capsule formulation for treatment of pediatric patients ≥ 2 years old with neurofibromatosis type 1 and symptomatic, inoperable plexiform neurofibromas. A new granule formulation is being developed to support dose flexibility and for patients unable to swallow capsules. This Phase I, open-label, single-center, randomized crossover pharmacokinetics study (NCT03649165) investigated the new granule versus capsule formulation in both fasted and fed (low-fat) states. Twenty-four healthy adult male volunteers were randomized to receive single-dose selumetinib in one of four treatment sequences: 25 mg granule (fasted); 50 mg capsule (fasted); 25 mg granule (fed); and 50 mg capsule (fed). Primary endpoint: to compare pharmacokinetics of the formulations in fasted state. Secondary endpoints: pharmacokinetics of the formulations in fasted versus fed states, granule palatability, safety and tolerability. In fasted state, a slight delay in absorption of selumetinib by ~0.60 h, with geometric mean ratios (90% CI) of 0.65 (0.58, 0.74) for Cmax/dose and 0.87 (0.81, 0.92) for AUC/dose, was detected when administered as granule versus capsule. For granule in fed versus fasted states, geometric mean Cmax and AUC ratios (90% CI) were 0.61 (0.51, 0.72) and 0.97 (0.91, 1.02). For capsule in fed versus fasted states, geometric mean Cmax and AUC ratios (90% CI) were 0.40 (0.33, 0.48) and 0.62 (0.55, 0.70). Granule palatability was acceptable; volunteers indicated they would take it again. Selumetinib was well-tolerated; for both formulations, few adverse events of mild intensity were reported; dry eyes (fasted) versus dry eyes and rhinorrhea (fed) were most frequent. This was the first study to test the granule formulation in humans; results indicate the granule formulation has similar AUC to the capsule formulation and minimal food effect, supporting planned clinical trials in pediatric patients.

Comparison of Individualized Versus MAP-Bayesian Predicted AUC of Busulfan in FluBu4 Treated Patients Undergoing Allogeneic Transplant

Although myeloablative fludarabine/busulfan (FluBu4) has been widely adopted in clinical practice, considerable interpatient variability exists in systemic busulfan exposure (AUC) when using body weight or body surface area based-dosing, leading to decreased efficacy (i.e. relapse) or increased toxicity (i.e., mucositis, veno-occlusive disease). This well-defined dose-exposure-outcome relationship has led to the widespread clinical implementation of therapeutic drug monitoring (TDM). However, individualized TDM can be time and labor intensive as well as potentially biased due to the lack of incorporation of any previously established PK data (Bayesian prior). In contrast, Bayesian maximum a posteriori (MAP) PK models consider the Bayesian prior and individualized TDM to generate a revised probability distribution (Bayes conditional posterior) to more accurately and rapidly estimate the AUC with reduced bias. There are a paucity of data comparing busulfan AUCs using individualized PK versus MAP-Bayesian-based models in adults although these more sophisticated approaches may assist in optimizing dosing of busulfan in this vulnerable population. This was a retrospective, single-center study of patients who received FluBu4 with busulfan TDM between January 1999 and September 2019. 109 patients diagnosed with a hematologic malignancy who received either sequential (n=46) or concurrent (n=63) FluBu4 were analyzed. The median age was 48 (range: 18-66), and were Hispanic (n=38), White (n=46) or African-American (n=14). TDM was performed either after a test dose of 0.8 mg/kg (n=52) or after the first dose (3.2 mg/kg) of busulfan administered during the preparative regimen (n=71), with dosing was based on actual or adjusted body weight. For PK analysis, plasma busulfan concentrations were analyzed via gas chromatography with mass selective detection. Individualized PK data were generated using WinNonlin while the MAP-Bayesian approach utilized the Bayesian prior developed from McCune et al (Clin Cancer Res, 2014). An AUC of 4800 µM˖min/24 hours was targeted based on previous literature. Based on individualized PK data, total recommended busulfan doses ranged from 9.3-21.3 mg/kg (-27.1% to +66.7% compared to FDA labeled dose of 12.8 mg/kg). When first-dose busulfan PK was compared between busulfan given sequentially versus concurrently with fludarabine there was a trend towards a higher AUC with concomitant administration (4651 vs. 4988 µM˖min; p=0.13). A strong correlation between the AUC generated from both the individualized PK an MAP-Bayesian models was observed with both the test dose (R2=0.91) and first dose (R2=0.86) of busulfan. Using the MAP Bayesian model, AUC predictions were on average higher (mean AUC 5069 versus 4886 µM˖min, p&amp;lt;0.0001) compared to the patient-specific individualized PK estimates. Figure 1 shows the Bland Altman plots for comparison of the individualized AUC vs. MAP-Bayesian estimates for test dose and first dose. Our individualized busulfan PK approach generated relatively similar AUC values compared to MAP-Bayesian estimates, although the higher AUC generated via MAP-Bayesian predictions may allow for lower doses of busulfan to be administered thereby potentially reducing toxicity while maintaining efficacy. Further, use of the MAP-Bayesian method may allow for more rapid dose optimization and a decreased number of serum concentrations. Further prospective studies including more patients are warranted to confirm these findings. Figure 1 Disclosures Calip: Flatiron Health: Current Employment. Patel:Janssen: Consultancy; Amgen: Consultancy; Celgene: Consultancy.

Utility of the 5-Item Modified Frailty Index for Predicting Adverse Outcomes Following Elective Anterior Cervical Discectomy and Fusion

Frailty is an increasingly studied tool for preoperative risk stratification, but its prognostic value for anterior cervical discectomy and fusion (ACDF) patients is unclear. We sought to evaluate the association of the 5-item modified Frailty Index (5i-mFI) with 30-day adverse outcomes following ACDF and its predictive performance compared with other common metrics. The National Surgical Quality Improvement Program was queried from 2016-2018 for patients undergoing elective ACDF for degenerative diseases. Outcomes of interest included 30-day complications, extended length of stay (LOS), non-home discharge, and unplanned readmissions. Unadjusted/adjusted odds ratios were calculated. The discriminatory performance of the 5i-mFI compared with age, American Society of Anesthesiologists (ASA) classification, and body mass index was computed using the area under the receiver operating characteristic curve (AUC). A total of 23,754 patients were identified. On adjusted analysis, an index of 1 was significantly associated with extended LOS, non-home discharge, and unplanned readmissions (P < 0.001, P= 0.023, P= 0.003, respectively), but not complications (all P > 0.05). An index ≥2 was significantly associated with each outcome (all P < 0.001). The 5i-mFI was found to have a significantly higher AUC than body mass index for each outcome, a similar AUC compared with ASA classification and age for complications and unplanned readmissions, and a significantly lower AUC than ASA classification and age for extended LOS and non-home discharge. The 5i-mFI was found to be significantly associated with 30-day adverse outcomes following ACDF but had similar or lesser predictive performance compared with more universally available and easily implemented metrics, such as ASA classification and age.

A comparison of machine learning models for predicting rehospitalisation and death after a first hospitalisation with heart failure

Abstract Background Many machine learning models exist, including Multilayer Perceptron (MLP), Random Forest algorithm (RF), Support Vector Machine (SVM), and Gradient Boosted Machine (GBM), but their value for predicting outcome in patients with heart failure has not been compared. Aim To predict rehospitalisation (all-cause) and death (all-cause) at 1-, 3- and 12 months after discharge from a first hospitalisation for heart failure using four machine learning models. Methods The National Health Service Greater Glasgow and Clyde Health Board serves a population of ∼1.1 million. We obtained de-identified administrative data, including investigations, diagnosis and prescriptions, linked to hospital admissions and deaths for anyone with a diagnosis of vascular disease or heart failure or prescribed loop diuretics, statins or neuro-endocrine antagonists at any time between 1st January 2010 and 1st June 2018. Patients who were under 18 or had no prior hospitalisation for heart failure were excluded. Four ML algorithms using 46 variables were applied. Results Of 360,000 people who met the above criteria between 2010–2018, 6,372 had a hospitalisation for heart failure prior to 1st January 2010 and 8,304 had a first hospitalisation for heart failure thereafter. Between 2010 and 2018 there were 3,086 re-hospitalisations over 24 hours and 3,706 patients died, with 5,070 patients experiencing the composite outcome. GBM and RF consistently outperformed MLP and SVM when comparing AUC, sensitivity and specificity combined, with GBM performing best in all scenarios. Since GBM and RF are both tree-based models, and with SVM and MLP regularly reporting very poor sensitivity or specificity despite a similar AUC to the others, this suggests that SVM and MLP may be suffering from overfitting and might perform better in larger data-sets. Both GBM and RF work by ordering variables, so the final model can be used to determine the most important prediction variables. Age, number of times a blood sample was taken out of hospital, length of stay, social deprivation index and haemoglobin concentration consistently ranked amongst the most important variables. Models predicted all 1-month events better than later events. Conclusions Some, but not all, ML models applied to this data-set predicted rehospitalisation and death with great accuracy for up to 3 months after a first hospitalisation for heart failure. The models identified several important prognostic variables that are currently seldom collected in clinical research registries but perhaps should be. Funding Acknowledgement Type of funding source: Public grant(s) – National budget only. Main funding source(s): Medical Research Council

Major vault protein/lung resistance related protein: a novel biomarker for rheumatoid arthritis.

Rheumatoid arthritis (RA) can lead to joint destruction and early institution of effective treatment can preserve joint function. Biomarkers can establish early diagnosis and predict effect of treatment. Vault particles, large cytoplasmic ribonucleoprotein particles that participate in inflammation, might serve as biomarkers. The aim of this study was to assess the diagnostic and the prognostic value of major vault protein (MVP) and their antibodies in RA. Serum samples from 159 RA patients, 26 early RA (ERA) patients, 21 patients with osteoarthritis (OA) and 30 healthy individuals were tested for MVP, anti-cyclic citrullinated peptide (anti-CCP) and C-reactive protein (CRP) using enzyme-linked immunosorbent assays (ELISA). Rheumatoid factor (RF) was tested by nephelometry, and anti-MVP antibodies were detected by anti-MVP peptide ELISA using an in-house protocol. MVP levels were higher in RA and ERA, compared to OA and healthy controls (p<0.00001). A combination of MVP with RF or anti-CCP showed an improved diagnostic accuracy compared to RF or anti-CCP alone in RA and ERA. MVP exhibited similar AUC levels to anti-CCP and RF in RA whereas in ERA, MVP exhibited the same or slightly higher AUC levels, compared to anti-CCP and RF, respectively. High MVP levels were associated with lack of response to treatment. Levels of anti-MVP peptide 2 antibodies were significantly higher in RA compared to healthy controls (t= 2.73, p=0.007). MVP and autoantibodies against MVP may have the potential to serve as diagnostic and prognostic biomarkers in RA.

302 Biomarker Profiling for Obstructive Coronary Artery Disease: A PROMISE Substudy

Coronary artery disease (CAD) is a prevalent condition, frequently diagnosed by imaging studies. Laboratory-based adjuncts would be useful but currently play a limited role in diagnosis. We hypothesized that a multimarker blood-based panel could exclude obstructive CAD such that further noninvasive imaging would not be required. We used banked samples from the randomized PROMISE trial. Patients were symptomatic outpatients without diagnosed CAD referred for noninvasive cardiovascular testing for suspected CAD who were randomized to either coronary computed tomography (CT) or functional testing (exercise ECG or stress echocardiogram or SPECT imaging). Traditional clinical CAD risk factor information was collected including age, sex, race, and a history of hypertension, diabetes, dyslipidemia smoking, or family history of CAD. Baseline blood samples were collected, banked, and tested for a panel of 13 cardiovascular risk biomarkers (high sensitivity troponin I (hsTn), Cystatin C, Galectin-3, NT-pro-BNP, Creatinine, Homocysteine, Beta2, Lipoprotein A, Glucose, Insulin, ALT, Free T3, and Uric Acid) using least absolute shrinkage and selection operator (LASSO) regression analysis with 10-fold nested cross validation to estimate prediction performance. Our endpoint was obstructive CAD as defined by >70% stenosis on coronary CT. CT scans were read at a core lab for study purposes. We compared models using only clinical variables to those using all biomarker variables, hsTn alone, or either of these plus clinical variables. The PROMISE biomarker repository included 1,716 patients who were randomized to and received an evaluable coronary CT, with mean age 60.2 years, 52.5 % female and 87.3% white. On average, patients had 2.4 clinical risk factors for CAD and a ASCVD score of 14. A total of 102 patients had obstructive CAD; these patients were mostly male (71.6%) and smokers (65.7%). A predictive model using only clinical variables had similar negative predictive value (NPV), AUC, and Youden index (sensitivity + specificity -1) compared to a biomarker + clinical model. Similar results were found for hsTn in combination with clinical variables (Table 1). A biomarker-only model and hsTn alone had lower AUC and Youden index, with the former superior to the latter. In this population of symptomatic outpatients being evaluated for suspected CAD, clinical variables had only modest overall accuracy but good negative predictive value. A biomarker panel of 13 different analytes also had modest overall accuracy but was inferior to clinical factors alone, or hsTN alone. Combining the biomarkers with clinical data did not provide significant incremental accuracy to exclude CAD.Table 1Model Performance Summary for Obstructive CAD.ModelAUC (95% CI)NPV %, (95% CI)PPV %, (95% CI)YoudenSensitivity %, (95% CI)Specificity %, (95% CI)Clinical0.681 (0.630, 0.732)88.2% (85.6, 89.3%)11.1% (10.1, 16.3%)0.33866.0% (55.8, 75.2%)67.8% (65.5, 70.0%)Biomarkers0.604 (0.547, 0.662)85.7% (82.6, 87.0%)7.2% (6.6, 11.2%)0.17570.8% (60.7, 79.7%)46.7% (44.2, 49.1%)Clinical + Biomarkers0.691 (0.64, 0.743)89.2% (86.6, 90.2%)10.2% (9.3, 15.8%)0.34771.7% (61.4, 80.6%)63.0% (60.6, 65.4%)Hs Troponin I alone0.651 (0.598, 0.703)85.0% (81.9, 86.5%)8.8% (8.0, 12.9%)0.23762.7% (52.6, 72.1%)61.0% (58.7, 63.4%)Clinical + Hs Troponin I0.695 (0.642, 0.747)(85.2, 89.0%)88.0%10.7% (9.8, 16.2%)0.35871.4% (61.4, 80.1%)64.4% (62.0, 66.7%) Open table in a new tab

Preparation, optimization and preliminary pharmacokinetic study of curcumin encapsulated turmeric oil microemulsion in zebra fish

The present investigation aimed to develop curcumin loaded turmeric oil microemulsion for brain targeting. An effort has been made to investigate the role of functional components in developing brain targeted formulation which could enhance the bioavailability and uptake of drug in the brain upon oral administration. Preliminary studies like solubility study, emulsification study and construction of the pseudo ternary phase diagram were performed for screening components. The formulation was optimized by using extreme vertices mixture design. The optimized formulation was characterized for appearance, stability to centrifugation, dilution potential, globule size, zeta potential and drug content. Furthermore, ex-vivo permeation in chicken gut sac non everted technique and pharmacokinetic study in adult zebra fishes were carried out. The optimized formulation was found to clear, yellow-colored with the absence of phase separation and precipitation denoted the stability of formulation to centrifugation and dilution. The mean globule size, polydispersity index, zeta potential and drug content was observed as 29.13± 0.12 nm, 0.23 ± 0.01,-12.33 ± 1.37 mV and 99.10±3.91 %, respectively. Ex vivo permeation study revealed 2.41 fold enhancement in the steady-state flux when compared to curcumin solution. Furthermore, optimized formulation showed shorter Tmax (5 min) and higher AUC(0-∞) (7.93 μg/brain*min) compared to the curcumin solution which showed similar Tmax and AUC(0-∞) of 2.78 μg/brain*min after oral administration to zebra fishes revealing 3.97 fold enhancement. The results revealed enhanced ex vivo oral absorption and enhanced in vivo brain pharmacokinetics of curcumin via functional microemulsion in the zebra fish model.

Pharmacodynamic Evaluation of MRX-8, a Novel Polymyxin, in the Neutropenic Mouse Thigh and Lung Infection Models against Gram-Negative Pathogens.

MRX-8 is a novel polymyxin analogue in development for the treatment of infections caused by Gram-negative pathogens, including those resistant to other antibiotic classes. In the present study, we examined the pharmacodynamic activity of MRX-8 against a variety of common Gram-negative pathogens in the neutropenic mouse thigh and lung models. Additionally, we examined polymyxin B (PMB) as a comparator. Plasma pharmacokinetics of MRX-8 and PMB were linear over a broad dosing range of 0.156 to 10 mg/kg of body weight and had similar AUC0-∞ (area under the drug concentration-time curve from 0 h to infinity) exposures of MRX-8, 0.22 to 12.64 mg · h/liter, and PMB, 0.12 to 13.22 mg · h/liter. Dose fractionation was performed for MRX-8 using a single Escherichia coli isolate, and the results demonstrated that both Cmax (maximum concentration of drug in serum)/MIC and AUC/MIC ratios were strongly associated with efficacy. In the thigh model, dose-ranging studies included strains of E. coli (n = 3), Pseudomonas aeruginosa (n = 2), Klebsiella pneumoniae (n = 3), and Acinetobacter baumannii (n = 1). Both MRX-8 and PMB exhibited increased effects with increasing doses. MRX-8 and PMB free AUC/MIC exposures for net stasis were similar for E. coli and K. pneumoniae at 20 to 30. Notably, for P. aeruginosa and A. baumannii, the free AUC/MIC ratio for stasis was numerically much smaller for MRX-8 at 6 to 8 than for PMB at 16 to 37. In the lung model, MRX-8 was also more effective than PMB when dosed to achieve similar free-drug AUC exposures over the study period. MRX-8 is a promising novel polymyxin analogue with in vivo activity against many different clinically relevant species in both the mouse thigh and lung models.

Identifying Cardiac Amyloid in Aortic Stenosis: ECV Quantification by CT in TAVR Patients

ObjectivesThe purpose of this study was to validate computed tomography measured ECV (ECVCT) as part of routine evaluation for the detection of cardiac amyloid in patients with aortic stenosis (AS)-amyloid. BackgroundAS-amyloid affects 1 in 7 elderly patients referred for transcatheter aortic valve replacement (TAVR). Bone scintigraphy with exclusion of a plasma cell dyscrasia can diagnose transthyretin-related cardiac amyloid noninvasively, for which novel treatments are emerging. Amyloid interstitial expansion increases the myocardial extracellular volume (ECV). MethodsPatients with severe AS underwent bone scintigraphy (Perugini grade 0, negative; Perugini grades 1 to 3, increasingly positive) and routine TAVR evaluation CT imaging with ECVCT using 3- and 5-min post-contrast acquisitions. Twenty non-AS control patients also had ECVCT performed using the 5-min post-contrast acquisition. ResultsA total of 109 patients (43% male; mean age 86 ± 5 years) with severe AS and 20 control subjects were recruited. Sixteen (15%) had AS-amyloid on bone scintigraphy (grade 1, n = 5; grade 2, n = 11). ECVCT was 32 ± 3%, 34 ± 4%, and 43 ± 6% in Perugini grades 0, 1, and 2, respectively (p < 0.001 for trend) with control subjects lower than lone AS (28 ± 2%; p < 0.001). ECVCT accuracy for AS-amyloid detection versus lone AS was 0.87 (0.95 for 99mTc-3,3-diphosphono-1,2-propanodicarboxylic acid Perugini grade 2 only), outperforming conventional electrocardiogram and echocardiography parameters. One composite parameter, the voltage/mass ratio, had utility (similar AUC of 0.87 for any cardiac amyloid detection), although in one-third of patients, this could not be calculated due to bundle branch block or ventricular paced rhythm. ConclusionsECVCT during routine CT TAVR evaluation can reliably detect AS-amyloid, and the measured ECVCT tracks the degree of infiltration. Another measure of interstitial expansion, the voltage/mass ratio, also performed well.

Derivation and validation of a prognostic score for neonatal mortality in Ethiopia: a case-control study

BackgroundEarly warning scores for neonatal mortality have not been designed for low income countries. We developed and validated a score to predict mortality upon admission to a NICU in Ethiopia.MethodsWe conducted a retrospective case-control study at the University of Gondar Hospital, Gondar, Ethiopia. Neonates hospitalized in the NICU between January 1, 2016 to June 31, 2017. Cases were neonates who died and controls were neonates who survived.ResultsUnivariate logistic regression identified variables associated with mortality. The final model was developed with stepwise logistic regression. We created the Neonatal Mortality Score, which ranged from 0 to 52, from the model’s coefficients. Bootstrap analysis internally validated the model. The discrimination and calibration were calculated. In the derivation dataset, there were 207 cases and 605 controls. Variables associated with mortality were admission level of consciousness, admission respiratory distress, gestational age, and birthweight. The AUC for neonatal mortality using these variables in aggregate was 0.88 (95% CI 0.85–0.91). The model achieved excellent discrimination (bias-corrected AUC) under internal validation. Using a cut-off of 12, the sensitivity and specificity of the Neonatal Mortality Score was 81 and 80%, respectively. The AUC for the Neonatal Mortality Score was 0.88 (95% CI 0.85–0.91), with similar bias-corrected AUC. In the validation dataset, there were 124 cases and 122 controls, the final model and the Neonatal Mortality Score had similar discrimination and calibration.ConclusionsWe developed, internally validated, and externally validated a score that predicts neonatal mortality upon NICU admission with excellent discrimination and calibration.

SAT-432 Pharmacokinetics (PK) and Exposure-Response Relationship of Teprotumumab, an Insulin-Like Growth Factor-1 Receptor (IGF-1R) Blocking Antibody, in Active Thyroid Eye Disease (TED)

Introduction: Teprotumumab treatment resulted in statistically and clinically meaningful improvements across multiple facets of active TED and was generally well-tolerated in Phase 2 and 3 trials.1,2 An initial intravenous infusion of 10 mg/kg followed by 20 mg/kg every 3 weeks was selected based on in vitro activity and clinical PK profile, to maintain pharmacologically active exposures and >90% saturation of IGF-1R over dosing intervals and to achieve efficacy at a well-tolerated dose for this vision-threatening disease. Methods: Population PK analysis were performed on data from a Phase 1 oncology study (n=60)3 and Phase 2 and 3 trials in active TED (N=83)2,3 and covariate effect on PK was assessed. Exposure-response relationship was evaluated in TED studies for key efficacy endpoints (proptosis response rate, % patients with a clinical activity score value of 0 or 1, and diplopia responder rate) and selected safety variables (hyperglycemia and muscle spasms). Results: Teprotumumab PK was linear in TED patients and consistent with other immunoglobulin G1 monoclonal antibodies (IgG1 mAbs), with low systemic clearance (0.334 L/day), low volume of distribution (3.9 L for central compartment and 4.2 L for peripheral compartment), and long elimination half-life (19.9 days). 4,5 Model-predicted mean (± standard deviation) steady-state area under the concentration curve (AUCss), peak (Cmax,ss), and trough (Cmin,ss) concentrations in TED patients were 131 (± 30.9) mg∙hr/mL, 643 (± 130) µg/mL and 157 (± 50.6) µg/mL, respectively, suggesting low inter-subject variability.Population PK analysis indicated no significant impact of baseline age, gender, race, weight, smoking status, renal impairment (mild/moderate), and hepatic function (total bilirubin, aspartate and alanine aminotransferases) on teprotumumab PK. Female patients had 15% higher Cmax,ss but similar AUC compared to male patients, which is not considered clinically relevant.Exposure-response analysis from the TED dose regimen indicated no meaningful correlations between exposures (AUCss, Cmax,ss and Cmin,ss) and key efficacy endpoints or selected safety variables, supporting the demonstrated, favorable benefit-risk profile of the TED dose regimen.2 Conclusion: Teprotumumab PK was characterized in TED patients by long elimination half-life, low systemic clearance and low volume of distribution, consistent with other IgG1 mAbs. There was no meaningful exposure-response relationship at the selected TED dose regimen for both efficacy and safety endpoints, supporting the teprotumumab dose regimen used in TED patients. Reference: (1) Smith TJ, et al. N Engl J Med 2017;376:1748-1761. (2) Douglas RS, et al. AACE 2019 late-breaking abstract. (3) ClinicalTrials.gov: NCT00400361. (4) Dirks NL et al. Clin Pharmacokinet. 2010;49(10):633-59. (5) Ryman JT et al. CPT Pharmacometrics Syst Pharmacol. 2017;6(9):576-88.

Speckle tracking deformation imaging to detect regional fibrosis in hypertrophic cardiomyopathy: a comparison between 2D and 3D echo modalities.

We aimed at directly comparing three-dimensional (3D) and two-dimensional (2D) deformation parameters in hypertrophic hearts and depict which may best reflect underlying fibrosis in hypertrophic cardiomyopathy (HCM), defined by late gadolinium enhancement (LGE) in cardiac magnetic resonance (CMR). We included 40 HCM [54.1 ± 14.3 years, 82.5% male, maximum wall thickness (MWT) 19.3 ± 4.8 mm] and 15 hypertensive (HTN) patients showing myocardial hypertrophy (58.1 ± 15.6 years, 80% male, MWT 12.8 ± 1.4 mm) who have consecutively undergone 2D-, 3D-speckle tracking echocardiography and LGE CMR. Deformation parameters (2D and 3D) presented overall poor to moderate correlations, with 3D_longitudinal strain (LS) and 3D_circumferential strain (CS) values being constantly higher compared to 2D derivatives. By regression analysis, hypertrophy substrate (HCM vs. hypertension) and hypertrophy magnitude were the parameters to influence 2D-3D LS and CS strain correlations (R2 = 0.66, P < 0.001 and R2 = 0.5, P = 0.001 accordingly). Among segmental deformation indices, 2D_LS showed the best area under the curve [AUC = 0.78, 95% confidence intervals (CI) (0.75-0.81), P < 0.0005] to detect fibrosis, with 3D deformation parameters showing similar AUC (0.65) and 3D_LS presenting the highest specificity [93.1%, 95% CI (90.6-95.1)]. In hypertrophic hearts, 2D and 3D deformation parameters are not interchangeable, showing modest correlations. Thickness, substrate, and tracking algorithm calculating assumptions seem to induce this variability. Nevertheless, among HCM patients 2D_peak segmental longitudinal strain remains the best strain parameter for tissue characterization and fibrosis detection.

Dosage scaling of alcohol in binge exposure models in mice: An empirical assessment of the relationship between dose, alcohol exposure, and peak blood concentrations in humans and mice.

Binge drinking is a remarkably prevalent behavior. In 2015, 27% of U.S. residents 18 years old or older reported at least one episode of binge drinking in the previous month. Rodent models for binge drinking are widely used to study the mechanisms by which alcohol causes a variety of adverse health effects in humans. Concerns have been raised that many binge-drinking studies in rodents involve alcohol doses that would be unrealistically high in humans. Allometric dosage scaling can be used to estimate the dose of a drug or chemical in mice that would be necessary to achieve similar biological effects at a realistic dose in humans. However, it has become apparent that no single allometric conversion factor is applicable for all drugs and chemicals, so it is necessary to evaluate each compound empirically. In the present study, we compared the area under the blood alcohol concentration vs. time curve (AUC) and the peak blood alcohol concentration following oral alcohol administration at various doses in mice and humans, using data from previously published studies. The results demonstrated that the oral dose of alcohol must be larger in mice (on a g of alcohol to kg of body weight basis) than in humans to achieve similar alcohol AUC values or to achieve similar peak concentrations in the blood. The dose required in mice was about 2-fold greater than the dose required in humans to achieve similar alcohol AUC and peak concentrations. The results shown here were substantially different from the average 5-12-fold difference between mice and humans calculated in previous studies using agents other than alcohol. Results shown here demonstrate that an empirical approach using data from several independent experiments provides information needed to determine the alcohol dose in mice that produces a similar level of exposure (AUC and peak concentration) as in humans. The results indicate that a single alcohol dose in the range of 5-6g/kg, a range often used in mouse models for binge drinking, is not excessive when modeling human binge drinking. Results presented here illustrate that in mice both alcohol AUC and peak alcohol concentration correlate well with an important biological effect - activation of the hypothalamic-pituitary-adrenal axis - as indicated by increased corticosterone AUC values.

Technical and imaging factors influencing performance of deep learning systems for diabetic retinopathy

Deep learning (DL) has been shown to be effective in developing diabetic retinopathy (DR) algorithms, possibly tackling financial and manpower challenges hindering implementation of DR screening. However, our systematic review of the literature reveals few studies studied the impact of different factors on these DL algorithms, that are important for clinical deployment in real-world settings. Using 455,491 retinal images, we evaluated two technical and three image-related factors in detection of referable DR. For technical factors, the performances of four DL models (VGGNet, ResNet, DenseNet, Ensemble) and two computational frameworks (Caffe, TensorFlow) were evaluated while for image-related factors, we evaluated image compression levels (reducing image size, 350, 300, 250, 200, 150 KB), number of fields (7-field, 2-field, 1-field) and media clarity (pseudophakic vs phakic). In detection of referable DR, four DL models showed comparable diagnostic performance (AUC 0.936-0.944). To develop the VGGNet model, two computational frameworks had similar AUC (0.936). The DL performance dropped when image size decreased below 250 KB (AUC 0.936, 0.900, p < 0.001). The DL performance performed better when there were increased number of fields (dataset 1: 2-field vs 1-field—AUC 0.936 vs 0.908, p < 0.001; dataset 2: 7-field vs 2-field vs 1-field, AUC 0.949 vs 0.911 vs 0.895). DL performed better in the pseudophakic than phakic eyes (AUC 0.918 vs 0.833, p < 0.001). Various image-related factors play more significant roles than technical factors in determining the diagnostic performance, suggesting the importance of having robust training and testing datasets for DL training and deployment in the real-world settings.

560 The inclusion of pulmonary arterial pressure misclassifies diastolic function using the current EACVI guidelines in pre-capillary pulmonary hypertension

Abstract Background Pulmonary hypertension (PH) can be pre-capillary or post-capillary (PVH) etiology based on left-sided filling pressures and pulmonary vascular resistance. The 2016 EACVI/ASE Recommendations for the Evaluation of Left Ventricular Diastolic Function (LVDF) provides flow-diagrams to categorize patients. Parameters used include left atrial volume, Doppler-derived transmitral and mitral annular velocities, and systolic PA pressure (sPAP). There are no dedicated criteria to assess the diastolic function in pulmonary arterial hypertension (PAH). Additionally, diseases such as scleroderma can result in both PAH and PVH, thus including sPAP may alter LVDF diagnostic reliability in this population. Purpose Because elevated PAP is fundamental to PAH, we hypothesized that the EACVI/ASE diastolic function algorithm has a lower predictive value in correctly classifying diastolic function in scleroderma. Methodology We performed a single-center retrospective analysis of scleroderma patients who underwent complete echocardiography and comprehensive right and left heart catheterization for PH evaluation. PH categorization was defined using the 6th World Symposium hemodynamic definitions (PAH as mPAP ≥20 mmHg, PCWP ≤15 mmHg, PVR ≥ 3 WU). Diastolic function categorization used 2016 EACVI/ASE recommendations. Index catheterization and echocardiogram closest to cardiac catheterization were analyzed. Results 260 patients underwent evaluation and 63 were diagnosed with PH. PAH was diagnosed in 35 (age 64 ±10, mPAP 55± 18 mmHg, LVEF 60 ± 6%) and PVH in 28 (age 65 ± 10, mPAP 34 ± 14 mmHg, LVEF 63 ± 6%). Of the PAH patients, 20 had normal LVEDP (≤ 12 mmHg) and 15 increased LVEDP. In the PAH normal LVEDP patients, the EACVI algorithm classified diastolic function as normal in 25%, grade 2 in 5%, Grade 3 in 5%, and "indeterminate" in 65%. In the PAH group with increased LVEDP (&amp;gt; 12 mmHg), 27% were incorrectly identified as normal, 7% as grade 2 dysfunction, and 66% as indeterminate. The diastolic function algorithm has a sensitivity of 27% and specificity of 75% to diagnose a LVEDP ≤ 12 mmHg, with an AUC of 0.508 (p = 0.91). With exclusion of sPAP from the algorithm, indeterminate cases in both PAH groups were reclassified as normal, resulting in improved sensitivity (93%) but poorer specificity (10%), and a similar AUC (0.517, p = 0.72). In PVH patients, the algorithm performed better with a sensitivity of 63% and specificity of 83% to predict LVEDP &amp;gt; 12 mmHg with AUC 0.773, p = 0.017. Conclusion In scleroderma patients with PAH, the EACVI diastolic algorithm performs poorly and is confounded by including PAP as a parameter. The sensitivity of the algorithm is improved by the exclusion of sPAP although with reduced specificity. It remains inadequate to reliably diagnose normal LVEDP. While useful in other populations, algorithm modifications including exclusion of PAP, must be employed in suspected scleroderma PAH.