Multimodal video and IMU kinematic dataset on daily life activities using affordable devices.

Human activity recognition and clinical biomechanics are challenging problems in physical telerehabilitation medicine. However, most publicly available datasets on human body movements cannot be used to study both problems in an out-of-the-lab movement acquisition setting. The objective of the VIDIMU dataset is to pave the way towards affordable patient gross motor tracking solutions for daily life activities recognition and kinematic analysis. The dataset includes 13 activities registered using a commodity camera and five inertial sensors. The video recordings were acquired in 54 subjects, of which 16 also had simultaneous recordings of inertial sensors. The novelty of dataset lies in: (i) the clinical relevance of the chosen movements, (ii) the combined utilization of affordable video and custom sensors, and (iii) the implementation of state-of-the-art tools for multimodal data processing of 3D body pose tracking and motion reconstruction in a musculoskeletal model from inertial data. The validation confirms that a minimally disturbing acquisition protocol, performed according to real-life conditions can provide a comprehensive picture of human joint angles during daily life activities.

Early identification of frailty: Developing an international delphi consensus on pre-frailty.

BACKGROUND: Frailty is associated with a prodromal stage called pre-frailty, a potentially reversible and highly prevalent intermediate state before frailty becomes established. Despite being widely-used in the literature and increasingly in clinical practice, it is poorly understood. OBJECTIVE: To establish consensus on the construct and approaches to diagnose and manage pre-frailty. METHODS: We conducted a modified (electronic, two-round) Delphi consensus study. The questionnaire included statements concerning the concept, aspects and causes, types, mechanism, assessment, consequences, prevention and management of pre-frailty. Qualitative and quantitative analysis methods were employed. An agreement level of 70% was applied. RESULTS: Twenty-three experts with different backgrounds from 12 countries participated. In total, 70 statements were circulated in Round 1. Of these, 52.8% were accepted. Following comments, 51 statements were re-circulated in Round 2 and 92.1% were accepted. It was agreed that physical and non-physical factors including psychological and social capacity are involved in the development of pre-frailty, potentially adversely affecting health and health-related quality of life. Experts considered pre-frailty to be an age-associated multi-factorial, multi-dimensional, and non-linear process that does not inevitably lead to frailty. It can be reversed or attenuated by targeted interventions. Brief, feasible, and validated tools and multidimensional assessment are recommended to identify pre-frailty. CONCLUSIONS: Consensus suggests that pre-frailty lies along the frailty continuum. It is a multidimensional risk-state associated with one or more of physical impairment, cognitive decline, nutritional deficiencies and socioeconomic disadvantages, predisposing to the development of frailty. More research is needed to agree an operational definition and optimal management strategies.

Custom IMU-Based Wearable System for Robust 2.4 GHz Wireless Human Body Parts Orientation Tracking and 3D Movement Visualization on an Avatar.

Recent studies confirm the applicability of Inertial Measurement Unit (IMU)-based systems for human motion analysis. Notwithstanding, high-end IMU-based commercial solutions are yet too expensive and complex to democratize their use among a wide range of potential users. Less featured entry-level commercial solutions are being introduced in the market, trying to fill this gap, but still present some limitations that need to be overcome. At the same time, there is a growing number of scientific papers using not commercial, but custom do-it-yourself IMU-based systems in medical and sports applications. Even though these solutions can help to popularize the use of this technology, they have more limited features and the description on how to design and build them from scratch is yet too scarce in the literature. The aim of this work is two-fold: (1) Proving the feasibility of building an affordable custom solution aimed at simultaneous multiple body parts orientation tracking; while providing a detailed bottom-up description of the required hardware, tools, and mathematical operations to estimate and represent 3D movement in real-time. (2) Showing how the introduction of a custom 2.4 GHz communication protocol including a channel hopping strategy can address some of the current communication limitations of entry-level commercial solutions. The proposed system can be used for wireless real-time human body parts orientation tracking with up to 10 custom sensors, at least at 50 Hz. In addition, it provides a more reliable motion data acquisition in Bluetooth and Wi-Fi crowded environments, where the use of entry-level commercial solutions might be unfeasible. This system can be used as a groundwork for developing affordable human motion analysis solutions that do not require an accurate kinematic analysis.

A Deep Learning Approach for Brain Tumor Classification and Segmentation Using a Multiscale Convolutional Neural Network.

In this paper, we present a fully automatic brain tumor segmentation and classification model using a Deep Convolutional Neural Network that includes a multiscale approach. One of the differences of our proposal with respect to previous works is that input images are processed in three spatial scales along different processing pathways. This mechanism is inspired in the inherent operation of the Human Visual System. The proposed neural model can analyze MRI images containing three types of tumors: meningioma, glioma, and pituitary tumor, over sagittal, coronal, and axial views and does not need preprocessing of input images to remove skull or vertebral column parts in advance. The performance of our method on a publicly available MRI image dataset of 3064 slices from 233 patients is compared with previously classical machine learning and deep learning published methods. In the comparison, our method remarkably obtained a tumor classification accuracy of 0.973, higher than the other approaches using the same database.

Comparative Analysis of Kinect-Based and Oculus-Based Gaze Region Estimation Methods in a Driving Simulator.

Driver's gaze information can be crucial in driving research because of its relation to driver attention. Particularly, the inclusion of gaze data in driving simulators broadens the scope of research studies as they can relate drivers' gaze patterns to their features and performance. In this paper, we present two gaze region estimation modules integrated in a driving simulator. One uses the 3D Kinect device and another uses the virtual reality Oculus Rift device. The modules are able to detect the region, out of seven in which the driving scene was divided, where a driver is gazing at in every route processed frame. Four methods were implemented and compared for gaze estimation, which learn the relation between gaze displacement and head movement. Two are simpler and based on points that try to capture this relation and two are based on classifiers such as MLP and SVM. Experiments were carried out with 12 users that drove on the same scenario twice, each one with a different visualization display, first with a big screen and later with Oculus Rift. On the whole, Oculus Rift outperformed Kinect as the best hardware for gaze estimation. The Oculus-based gaze region estimation method with the highest performance achieved an accuracy of 97.94%. The information provided by the Oculus Rift module enriches the driving simulator data and makes it possible a multimodal driving performance analysis apart from the immersion and realism obtained with the virtual reality experience provided by Oculus.

A Physiological Sensor-Based Android Application Synchronized with a Driving Simulator for Driver Monitoring.

In this paper, we present an Android application to control and monitor the physiological sensors from the Shimmer platform and its synchronized working with a driving simulator. The Android app can monitor drivers and their parameters can be used to analyze the relation between their physiological states and driving performance. The app can configure, select, receive, process, represent graphically, and store the signals from electrocardiogram (ECG), electromyogram (EMG) and galvanic skin response (GSR) modules and accelerometers, a magnetometer and a gyroscope. The Android app is synchronized in two steps with a driving simulator that we previously developed using the Unity game engine to analyze driving security and efficiency. The Android app was tested with different sensors working simultaneously at various sampling rates and in different Android devices. We also tested the synchronized working of the driving simulator and the Android app with 25 people and analyzed the relation between data from the ECG, EMG, GSR, and gyroscope sensors and from the simulator. Among others, some significant correlations between a gyroscope-based feature calculated by the Android app and vehicle data and particular traffic offences were found. The Android app can be applied with minor adaptations to other different users such as patients with chronic diseases or athletes.

Comparative Study of Neural Network Frameworks for the Next Generation of Adaptive Optics Systems.

Many of the next generation of adaptive optics systems on large and extremely large telescopes require tomographic techniques in order to correct for atmospheric turbulence over a large field of view. Multi-object adaptive optics is one such technique. In this paper, different implementations of a tomographic reconstructor based on a machine learning architecture named "CARMEN" are presented. Basic concepts of adaptive optics are introduced first, with a short explanation of three different control systems used on real telescopes and the sensors utilised. The operation of the reconstructor, along with the three neural network frameworks used, and the developed CUDA code are detailed. Changes to the size of the reconstructor influence the training and execution time of the neural network. The native CUDA code turns out to be the best choice for all the systems, although some of the other frameworks offer good performance under certain circumstances.

Efficient transfer entropy analysis of non-stationary neural time series.

Information theory allows us to investigate information processing in neural systems in terms of information transfer, storage and modification. Especially the measure of information transfer, transfer entropy, has seen a dramatic surge of interest in neuroscience. Estimating transfer entropy from two processes requires the observation of multiple realizations of these processes to estimate associated probability density functions. To obtain these necessary observations, available estimators typically assume stationarity of processes to allow pooling of observations over time. This assumption however, is a major obstacle to the application of these estimators in neuroscience as observed processes are often non-stationary. As a solution, Gomez-Herrero and colleagues theoretically showed that the stationarity assumption may be avoided by estimating transfer entropy from an ensemble of realizations. Such an ensemble of realizations is often readily available in neuroscience experiments in the form of experimental trials. Thus, in this work we combine the ensemble method with a recently proposed transfer entropy estimator to make transfer entropy estimation applicable to non-stationary time series. We present an efficient implementation of the approach that is suitable for the increased computational demand of the ensemble method's practical application. In particular, we use a massively parallel implementation for a graphics processing unit to handle the computationally most heavy aspects of the ensemble method for transfer entropy estimation. We test the performance and robustness of our implementation on data from numerical simulations of stochastic processes. We also demonstrate the applicability of the ensemble method to magnetoencephalographic data. While we mainly evaluate the proposed method for neuroscience data, we expect it to be applicable in a variety of fields that are concerned with the analysis of information transfer in complex biological, social, and artificial systems.

Cross-Approximate Entropy parallel computation on GPUs for biomedical signal analysis. Application to MEG recordings.

Cross-Approximate Entropy (Cross-ApEn) is a useful measure to quantify the statistical dissimilarity of two time series. In spite of the advantage of Cross-ApEn over its one-dimensional counterpart (Approximate Entropy), only a few studies have applied it to biomedical signals, mainly due to its high computational cost. In this paper, we propose a fast GPU-based implementation of the Cross-ApEn that makes feasible its use over a large amount of multidimensional data. The scheme followed is fully scalable, thus maximizes the use of the GPU despite of the number of neural signals being processed. The approach consists in processing many trials or epochs simultaneously, with independence of its origin. In the case of MEG data, these trials can proceed from different input channels or subjects. The proposed implementation achieves an average speedup greater than 250× against a CPU parallel version running on a processor containing six cores. A dataset of 30 subjects containing 148 MEG channels (49 epochs of 1024 samples per channel) can be analyzed using our development in about 30min. The same processing takes 5 days on six cores and 15 days when running on a single core. The speedup is much larger if compared to a basic sequential Matlab(®) implementation, that would need 58 days per subject. To our knowledge, this is the first contribution of Cross-ApEn measure computation using GPUs. This study demonstrates that this hardware is, to the day, the best option for the signal processing of biomedical data with Cross-ApEn.

Meta-analysis and literature review of techniques to achieve hemostasis in endoscopic sinus surgery.

BACKGROUND: Functional endoscopic sinus surgery (FESS) has been used as the standard of treatment for sinonasal disease in which medical therapy fails to ameliorate the disease. Intraoperative hemostasis is a crucial factor in FESS. Currently, ideal techniques for creating intraoperative hemostasis have yet to be clarified and standardized. We sought to better understand what variables can affect intraoperative blood loss and therefore improve surgical field outcomes. METHODS: A literature search was conducted using PubMed, OVID, MD Consult, and Micromedex with keywords including: FESS, intraoperative blood loss, hemorrhage, and vasoconstriction. The articles were then evaluated with regard to blood loss, surgical grade, and operative time. Eleven articles were cross-referenced to determine the most statistically significant techniques in 3 main categories: general anesthetics, preoperative steroids, and use of epinephrine. RESULTS: Analysis of the articles indicate that total intravenous anesthesia (TIVA) is statistically more beneficial than balanced anesthesia (BA), providing an average difference in blood loss of 75.3057 mL; the use of preoperative steroids is statistically more beneficial than placebo, with an improved difference in blood loss of 28 mL; and a trend toward hemostasis with the use of local anesthetics at a concentration of 1:200,000. CONCLUSION: Meta-analysis of 1148 patients concludes that hemostasis during FESS is best conducted using TIVA, preoperative steroids, and topical local anesthetic at a 1:200,000 concentration.

Comparison of response times of a mobile-web EHRs system using PHP and JSP languages.

Performance evaluation is highly important in the Electronic Health Records (EHRs) system implementation. Response time's measurement can be considered as one manner to make that evaluation. In the e-health field, after the creation of EHRs available through different platforms such as Web and/or mobile, a performance evaluation is necessary. The operation of the system in the right way is essential. In this paper, a comparison of the response times for the MEHRmobile system is presented. The first version uses PHP language with a MySQL database and the second one employs JSP with an eXist database. Both versions have got the same functionalities. In addition to the technological aspects, a significant difference is the way the information is stored. The main goal of this paper is choosing the version which offers better response times. We have created a new benchmark to calculate the response times. Better results have been obtained for the PHP version. Nowadays, this version is being used for specialists from Fundación Intras, Spain.

A content analysis of chronic diseases social groups on Facebook and Twitter.

Research on the use of social networks for health-related purposes is limited. This study aims to characterize the purpose and use of Facebook and Twitter groups concerning colorectal cancer, breast cancer, and diabetes. We searched in Facebook ( www.facebook.com ) and Twitter ( www.twitter.com ) using the terms "colorectal cancer," "breast cancer," and "diabetes." Each important group has been analyzed by extracting its network name, number of members, interests, and Web site URL. We found 216 breast cancer groups, 171 colorectal cancer groups, and 527 diabetes groups on Facebook and Twitter. The largest percentage of the colorectal cancer groups (25.58%) addresses prevention, similarly to breast cancer, whereas diabetes groups are mainly focused on research issues (25.09%). There are more social groups about breast cancer and diabetes on Facebook (around 82%) than on Twitter (around 18%). Regarding colorectal cancer, the difference is less: Facebook had 62.23%, and Twitter 31.76%. Social networks are a useful tool for supporting patients suffering from these three diseases. Regarding the use of these social networks for disease support purposes, Facebook shows a higher usage rate than Twitter, perhaps because Twitter is newer than Facebook, and its use is not so generalized.

Synchrony analysis of spontaneous MEG activity in Alzheimer's disease patients.

The aim of this study was to analyze the magnetoencephalography (MEG) background activity in Alzheimer's disease (AD) patients using cross-approximate entropy (Cross-ApEn). Cross-ApEn is a nonlinear measure of asynchrony between time series. Five minutes of recording were acquired with a 148-channel whole-head magnetometer in 12 AD patients and 12 age-matched control subjects. We found significantly higher synchrony between MEG signals from AD patients compared with control subjects. Additionally, we evaluated the ability of Cross-ApEn to discriminate these two groups using receiver operating characteristic (ROC) curves with a leave-one-out cross-validation procedure. We obtained an accuracy of 70.83% (66.67% sensitivity, 75% specificity) and a value of area under the ROC curve of 0.83. These results provide evidence of disconnection problems in AD. Our findings show the usefulness of Cross-ApEn to detect the brain dysfunction in AD.

A novel use of a landmark to avoid injury of the anterior ethmoidal artery during endoscopic sinus surgery.

BACKGROUND: The aim of this study was to describe and correlate radiographically the anterior ethmoidal artery (AEA) to useful endoscopic surgical landmarks, such as the nasal beak (NB), nasal crest (NC), and axilla of the middle turbinate, because these are commonly encountered during endoscopic sinus surgery and skull base surgery. METHODS: A retrospective review and software analysis was performed by three independent observers. Measurements of distance and angulation from the AEA to the NC, NB, and axilla of the middle turbinate were performed. A total of 138 unique computed tomography (CT) scans performed at a university tertiary care center were evaluated. RESULTS: The average age of the patients whose scans were analyzed was 50.5 (range, 17-90 years) years of age. The gender distribution was 61 male and 89 female patients. After comparing the measurements to the three landmarks noted, it was determined that the NB had the most interpatient concordance and the least interobserver variability. The average distance between the NB and the AEA as it penetrates the lamina papyracea is 2.34 cm (variance, 0.07) at an angle of 45.21° from the Frankfurt horizontal line. CONCLUSION: The real advantage of this novel use of the NB as a landmark to identify the AEA is that it is easy to use, unobtrusive, and is not time-consuming. This relationship between the NB and the AEA is consistent across genders and ethnicities and is more valuable than others presented previously, which may be more variable.

Proteomic signatures of epidermal growth factor receptor and survival signal pathways correspond to gefitinib sensitivity in head and neck cancer.

PURPOSE: Gefitinib targeting of the epidermal growth factor receptor (EGFR) has shown limited activity in clinical trials of head and neck squamous cell carcinoma (HNSCC). To investigate the underlying molecular mechanism, the proteomic signatures and responses of EGFR and downstream signals have been studied in a panel of HNSCC cell lines and tumor specimens pre- and post-gefitinib treatment. EXPERIMENTAL DESIGN: The IC(50) of gefitinib for HNSCC cell lines were determined using 3-(4,5-dmethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide proliferation assay. The effects of gefitinib on activation of EGFR and downstream signaling molecules were determined by Western blot, ELISA, and reverse-phase protein microarray (RPMA). The biomarkers involved in the signaling pathways were examined in HNSCC tumor specimens from patients in a phase I gefitinib trial. RESULTS: In vitro, gefitinib inhibited cell proliferation with differing IC(50), and suppressed activation of EGFR and downstream signaling molecules protein kinase B (AKT), extracellular signal-regulated kinase 1/2, signal transducer and activator of transcription 3 (STAT3), and nuclear factor kappaB. The drug sensitivity was statistically correlated with activation of phosphorylated AKT (p-AKT) and phosphorylated STAT3 (p-STAT3) detected by ELISA, and consistent with results measured by RPMA. In patient samples, a broad suppression of activation of EGFR and downstream signaling molecules was observed in a molecular responder patient, in contrast to a lack of inhibition or increased activation of biomarkers in different pathways in nonresponder patients. CONCLUSIONS: Gefitinib sensitivity is correlated with p-AKT and p-STAT3 activation in HNSCC cell lines and tumor specimens. p-AKT and p-STAT3 could serve as potentially useful biomarkers and drug targets for further development of novel therapeutic agents for HNSCC.

Deficient TP53 expression, function, and cisplatin sensitivity are restored by quinacrine in head and neck cancer.

PURPOSE: To determine the nature and potential pharmacologic reversibility of deficient TP53 expression and function in head and neck squamous cell carcinomas (HNSCC) with wild-type TP53, previously associated with decreased sensitivity to cisplatin therapy. EXPERIMENTAL DESIGN: TP53 genotype, mRNA and protein expression, TP53-induced p21 expression, and TP53 DNA-binding and reporter gene function were determined in a panel of nine previously characterized HNSCC cell lines from the University of Michigan squamous cell carcinoma (UM-SCC) series. The genotoxic drug doxorubicin and the anti-inflammatory and antimalarial drug quinacrine, previously identified as inducers of TP53, were used to examine the nature and potential reversibility of deficient TP53 expression and function. The specific role of inducible TP53 on function and cellular proliferation was confirmed using selective TP53 inhibitor pifithrin-alpha or short hairpin RNA knockdown. The capability of quinacrine to sensitize HNSCC to the cytotoxic effects of cisplatin was assessed. RESULTS: UM-SCC cell lines with wild-type TP53 genotype underexpressed TP53 mRNA and protein when compared with normal human keratinocytes or UM-SCC with mutant TP53. Although doxorubicin failed to induce TP53 expression or functional activity, quinacrine induced TP53 mRNA and protein expression, increased TP53 reporter activity and p21 protein expression, and induced growth inhibition in these wild-type TP53 cell lines. Quinacrine-induced TP53 reporter activity and growth suppression were attenuated by pifithrin-alpha and TP53 short hairpin RNA knockdown. Furthermore, quinacrine sensitized UM-SCC to cisplatin in vitro. CONCLUSIONS: Deficient TP53 mRNA and protein expression underlies decreased function in a subset of HNSCC with wild-type TP53 and can be restored together with cisplatin sensitization by quinacrine.

Soluble CD44 is a potential marker for the early detection of head and neck cancer.

INTRODUCTION: Head and neck squamous cell carcinoma (HNSCC) is a devastating and deadly disease, largely because it is diagnosed in late stage. Cure rates, currently at 50%, could increase to >80% with early detection. In this study, we evaluate soluble CD44 (solCD44) as an early detection tool for HNSCC by determining whether it reliably distinguishes HNSCC from benign disease of the upper aerodigestive tract. METHODS: We carried out the solCD44 ELISA on oral rinses from 102 patients with HNSCC and 69 control patients with benign diseases of upper aerodigestive tract to determine the sensitivity and specificity of the test for differentiating HNSCC from benign disease. Furthermore, we did a pilot study using methylation-specific PCR primers on oral rinses from 11 HNSCC patients with low solCD44 levels and 10 benign disease controls. RESULTS: Mean salivary solCD44 levels were 24.4 +/- 32.0 ng/mL for HNSCC patients (range, 0.99-201 ng/mL) and 9.9 +/- 16.1 ng/mL (range, 0.73-124 ng/mL) for the patients with benign disease (P < 0.0001). Depending on cutoff point and HNSCC site, sensitivity ranged from 62% to 70% and specificity ranged from 75% to 88%. Nine of 11 HNSCC and 0 of 10 controls with low solCD44 levels showed hypermethylation of the CD44 promoter. CONCLUSIONS: SolCD44 is elevated in the majority of HNSCC and distinguishes cancer from benign disease with high specificity. Whereas the solCD44 test lacks sensitivity by itself, methylation status of the CD44 gene seems to complement the solCD44 test. Our pilot data indicate that, together, these markers will detect HNSCC with very high sensitivity and specificity.

The benign lymphoepithelial cyst and a classification system for lymphocytic parotid gland enlargement in the pediatric HIV population.

OBJECTIVES/HYPOTHESIS: The objectives of this study are to present a series of parotid gland benign lymphoepithelial cysts (BLEC) in HIV-positive children and to propose a three-tiered classification system for HIV-associated lymphocytic parotid gland enlargement. STUDY DESIGN: The authors conducted a retrospective case series and literature review. METHODS: The authors conducted a retrospective chart review of four pediatric patients with HIV-associated parotid gland BLEC who presented to a tertiary care university medical center. RESULTS: Four pediatric HIV-positive patients (four girls; age range, 7-17 years [mean age, 12.8 years]) were diagnosed with parotid gland BLEC. Two patients presented with acute parotitis and the others presented with asymptomatic enlargement of the parotid glands. Three patients had bilateral parotid gland BLEC. The other patient demonstrated persistent generalized lymphadenopathy (PGL) of the intraparotid and cervical lymph nodes and early BLEC limited to the left parotid gland. One patient also displayed parotid gland microcalcifications and cystic changes in the adenoids, neither of which have been described previously in the setting of HIV-associated BLEC. Computed tomography was performed on all patients, and one patient underwent fine needle aspiration to confirm the diagnosis. All patients opted for observation and antiretroviral medication therapy as long-term treatment. Based on these findings and a review of the literature, we propose a three-tiered classification system for lymphocytic parotid gland enlargement in the HIV population: 1) PGL, 2) benign lymphoepithelial lesions (BLEL), and 3) BLEC. CONCLUSIONS: This series equals the largest pediatric series of HIV-associated parotid gland BLEC in the English literature. One patient in our series also demonstrated PGL; there were no cases of BLEL. A classification system based on morphology is proposed to help resolve the confusion in terminology used to describe this entity. Most pediatric HIV-infected patients with parotid gland BLEC can be treated with observation and antiretroviral medication therapy. For others, who are symptomatic or more concerned about their cosmetic appearance, sclerotherapy may offer a reasonable option. Radiation therapy and surgery should be reserved for select cases.

Management of pediatric airway granular cell tumor: role of laryngotracheal reconstruction.

OBJECTIVE: To discuss the role of laryngotracheal reconstruction (LTR) in granular cell tumor (GCT) and to highlight the importance and seriousness of GCT in pediatric airway cases. METHODS: A historical literature review was performed and a GCT case from the University of Miami Pediatric Otolaryngology Clinic is presented to highlight the role of LTR in the treatment of GCT. RESULTS: A case of a GCT of the laryngotracheal airway is reported and the management is discussed. Histological discussion and a review of the literature are included regarding GCT. This case is the third reported in the English literature of two synchronous GCT lesions of the upper airway repaired with a laryngotracheal reconstruction. CONCLUSIONS: In the authors' experience once conservative management consisting of endoscopic debulking has failed the treatment of choice for GCTs of the pediatric airway that are unresectable is a single stage laryngotracheal reconstruction with negative frozen section pathology to assure total wide local excision.

Early injection of high-dose recombinant factor VIIa decreases blood loss and prolongs time from injury to death in experimental liver injury.

BACKGROUND: Recombinant factor VIIa (rFVIIa) is used for treatment of bleeding episodes in hemophilia patients who develop inhibitors to factors VIII and IX. We tested the hypothesis that administration of rFVIIa early after injury would decrease bleeding and prolong the time from injury to death after experimental hepatic trauma. METHODS: Anesthetized swine were cannulated for blood sampling and hemodynamic monitoring. Avulsion of the left median lobe of the liver induced uncontrolled hemorrhage. After a 10% reduction in mean arterial pressure, animals (n = 8 per group) were blindly randomized to receive intravenous rFVIIa 180 microg/kg, rFVIIa 720 microg/kg, or placebo. Pathologic examination of brain, lung, kidney, heart, and small bowel was performed to assess intravascular thrombosis. RESULTS Mortality during the first hour was 50% (four of eight) in controls versus 0% with rFVIIa 720 microg/kg (p = 0.02, chi2). Blood loss was decreased in the rFVIIa 720 microg/kg group versus the placebo group (13.2 +/- 5.5 mL/kg vs. 21.9 +/- 7.7 mL/kg;p = 0.0223). Time from injury to death was significantly prolonged in the rFVIIa 720 microg/kg group compared with placebo (116 minutes vs. 8.5 +/- 3.5 minutes; p= 0.02). No macro- or microthrombi in vital organs were identified on pathologic examination. CONCLUSION: Intravenous administration of high-dose rFVIIa early after induction of hemorrhage decreased bleeding and prolonged survival. No evidence of thrombosis in vital organs was observed.