Publications by authors named "Justin Glavis-Bloom"

28 Publications

  • Page 1 of 1

A 61-year-old woman with jejunal lymphatic malformation visualized on computed tomography: a case report.

J Med Case Rep 2021 May 27;15(1):302. Epub 2021 May 27.

Department of Obstetrics and Gynecology, University of California Irvine, 333 City Boulevard West, Suite 1400, Orange, CA, 92868, USA.

Background: Jejunal lymphatic malformations are congenital lesions that are seldom diagnosed in adults and rarely seen on imaging.

Case Presentation: A 61-year-old Caucasian woman was initially diagnosed and treated for mucinous ovarian carcinoma. After an exploratory laparotomy with left salpingo-oophorectomy, a computed tomography scan of the abdomen and pelvis demonstrated suspicious fluid-containing lesions involving a segment of jejunum and adjacent mesentery. Resection of the lesion during subsequent debulking surgery revealed that the lesion seen on imaging was a jejunal lymphatic malformation and not a cancerous implant.

Conclusions: Abdominal lymphatic malformations are difficult to diagnose solely on imaging but should remain on the differential in adult cancer patients with persistent cystic abdominal lesions despite chemotherapy and must be differentiated from metastatic implants.
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http://dx.doi.org/10.1186/s13256-021-02872-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8157699PMC
May 2021

Prostate minimally invasive procedures: complications and normal vs. abnormal findings on multiparametric magnetic resonance imaging (mpMRI).

Abdom Radiol (NY) 2021 May 11. Epub 2021 May 11.

Department of Radiological Sciences, University of California, Irvine, Orange, CA, 92868-3201, USA.

Minimally invasive alternatives to traditional prostate surgery are increasingly utilized to treat benign prostatic hyperplasia and localized prostate cancer in select patients. Advantages of these treatments over prostatectomy include lower risk of complication, shorter length of hospital stay, and a more favorable safety profile. Multiparametric magnetic resonance imaging (mpMRI) has become a widely accepted imaging modality for evaluation of the prostate gland and provides both anatomical and functional information. As prostate mpMRI and minimally invasive prostate procedure volumes increase, it is important for radiologists to be familiar with normal post-procedure imaging findings and potential complications. This paper reviews the indications, procedural concepts, common post-procedure imaging findings, and potential complications of prostatic artery embolization, prostatic urethral lift, irreversible electroporation, photodynamic therapy, high-intensity focused ultrasound, focal cryotherapy, and focal laser ablation.
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http://dx.doi.org/10.1007/s00261-021-03097-6DOI Listing
May 2021

Outcomes of Artificial Intelligence Volumetric Assessment of Kidneys and Renal Tumors for Preoperative Assessment of Nephron Sparing Interventions.

J Endourol 2021 Apr 13. Epub 2021 Apr 13.

University of California Irvine School of Medicine, 12219, Radiological Sciences, Orange, California, United States.

Background Renal cell carcinoma is the most common kidney cancer and the 13th most common cause of cancer death worldwide. Partial nephrectomy and percutaneous ablation, increasingly utilized to treat small renal masses and preserve renal parenchyma, require precise preoperative imaging interpretation. We sought to develop and evaluate a convolutional neural network (CNN), a type of deep learning artificial intelligence, to act as a surgical planning aid by determining renal tumor and kidney volumes via segmentation on single-phase computed tomography (CT). Materials and Methods After institutional review board approval, the CT images of 319 patients were retrospectively analyzed. Two distinct CNNs were developed for (1) bounding cube localization of the right and left hemi-abdomen and (2) segmentation of the renal parenchyma and tumor within each bounding cube. Training was performed on a randomly selected cohort of 269 patients. CNN performance was evaluated on a separate cohort of 50 patients using Sorensen-Dice coefficients (which measures the spatial overlap between the manually segmented and neural network derived segmentations) and Pearson correlation coefficients. Experiments were run on a GPU-optimized workstation with a single NVIDIA GeForce GTX Titan X (12GB, Maxwell architecture). Results Median Dice coefficients for kidney and tumor segmentation were 0.970 and 0.816, respectively; Pearson correlation coefficients between CNN-generated and human-annotated estimates for kidney and tumor volume were 0.998 and 0.993 (p < 0.001), respectively. End-to-end trained CNNs were able to perform renal parenchyma and tumor segmentation on a new test case in an average of 5.6 seconds. Conclusions Initial experience with automated deep learning artificial intelligence demonstrates that it is capable of rapidly and accurately segmenting kidneys and renal tumors on single-phase contrast-enhanced CT scans and calculating tumor and renal volumes.
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http://dx.doi.org/10.1089/end.2020.1125DOI Listing
April 2021

Development and external validation of a prognostic tool for COVID-19 critical disease.

PLoS One 2020 9;15(12):e0242953. Epub 2020 Dec 9.

Department of Radiological Sciences, University of California, Irvine, California, United States of America.

Background: The rapid spread of coronavirus disease 2019 (COVID-19) revealed significant constraints in critical care capacity. In anticipation of subsequent waves, reliable prediction of disease severity is essential for critical care capacity management and may enable earlier targeted interventions to improve patient outcomes. The purpose of this study is to develop and externally validate a prognostic model/clinical tool for predicting COVID-19 critical disease at presentation to medical care.

Methods: This is a retrospective study of a prognostic model for the prediction of COVID-19 critical disease where critical disease was defined as ICU admission, ventilation, and/or death. The derivation cohort was used to develop a multivariable logistic regression model. Covariates included patient comorbidities, presenting vital signs, and laboratory values. Model performance was assessed on the validation cohort by concordance statistics. The model was developed with consecutive patients with COVID-19 who presented to University of California Irvine Medical Center in Orange County, California. External validation was performed with a random sample of patients with COVID-19 at Emory Healthcare in Atlanta, Georgia.

Results: Of a total 3208 patients tested in the derivation cohort, 9% (299/3028) were positive for COVID-19. Clinical data including past medical history and presenting laboratory values were available for 29% (87/299) of patients (median age, 48 years [range, 21-88 years]; 64% [36/55] male). The most common comorbidities included obesity (37%, 31/87), hypertension (37%, 32/87), and diabetes (24%, 24/87). Critical disease was present in 24% (21/87). After backward stepwise selection, the following factors were associated with greatest increased risk of critical disease: number of comorbidities, body mass index, respiratory rate, white blood cell count, % lymphocytes, serum creatinine, lactate dehydrogenase, high sensitivity troponin I, ferritin, procalcitonin, and C-reactive protein. Of a total of 40 patients in the validation cohort (median age, 60 years [range, 27-88 years]; 55% [22/40] male), critical disease was present in 65% (26/40). Model discrimination in the validation cohort was high (concordance statistic: 0.94, 95% confidence interval 0.87-1.01). A web-based tool was developed to enable clinicians to input patient data and view likelihood of critical disease.

Conclusions And Relevance: We present a model which accurately predicted COVID-19 critical disease risk using comorbidities and presenting vital signs and laboratory values, on derivation and validation cohorts from two different institutions. If further validated on additional cohorts of patients, this model/clinical tool may provide useful prognostication of critical care needs.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0242953PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7725393PMC
December 2020

A 3D-2D Hybrid U-Net Convolutional Neural Network Approach to Prostate Organ Segmentation of Multiparametric MRI.

AJR Am J Roentgenol 2021 01 10;216(1):111-116. Epub 2020 Nov 10.

Department of Radiological Sciences, University of California, Irvine, CA.

Objective: Prostate cancer is the most commonly diagnosed cancer in men in the United States with more than 200,000 new cases in 2018. Multiparametric MRI (mpMRI) is increasingly used for prostate cancer evaluation. Prostate organ segmentation is an essential step of surgical planning for prostate fusion biopsies. Deep learning convolutional neural networks (CNNs) are the predominant method of machine learning for medical image recognition. In this study, we describe a deep learning approach, a subset of artificial intelligence, for automatic localization and segmentation of prostates from mpMRI.

Materials And Methods: This retrospective study included patients who underwent prostate MRI and ultrasound-MRI fusion transrectal biopsy between September 2014 and December 2016. Axial T2-weighted images were manually segmented by two abdominal radiologists, which served as ground truth. These manually segmented images were used for training on a customized hybrid 3D-2D U-Net CNN architecture in a fivefold cross-validation paradigm for neural network training and validation. The Dice score, a measure of overlap between manually segmented and automatically derived segmentations, and Pearson linear correlation coefficient of prostate volume were used for statistical evaluation.

Results: The CNN was trained on 299 MRI examinations (total number of MR images = 7774) of 287 patients. The customized hybrid 3D-2D U-Net had a mean Dice score of 0.898 (range, 0.890-0.908) and a Pearson correlation coefficient for prostate volume of 0.974.

Conclusion: A deep learning CNN can automatically segment the prostate organ from clinical MR images. Further studies should examine developing pattern recognition for lesion localization and quantification.
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http://dx.doi.org/10.2214/AJR.19.22168DOI Listing
January 2021

Effect of shelter-in-place on emergency department radiology volumes during the COVID-19 pandemic.

Emerg Radiol 2020 Dec 5;27(6):781-784. Epub 2020 Jun 5.

Department of Radiologic Sciences, Irvine School of Medicine, University of California, 101 The City Dr S, Orange, CA, 92868, USA.

Purpose: The coronavirus disease 2019 (COVID-19) pandemic has led to significant disruptions in the healthcare system including surges of infected patients exceeding local capacity, closures of primary care offices, and delays of non-emergent medical care. Government-initiated measures to decrease healthcare utilization (i.e., "flattening the curve") have included shelter-in-place mandates and social distancing, which have taken effect across most of the USA. We evaluate the immediate impact of the Public Health Messaging and shelter-in-place mandates on Emergency Department (ED) demand for radiology services.

Methods: We analyzed ED radiology volumes from the five University of California health systems during a 2-week time period following the shelter-in-place mandate and compared those volumes with March 2019 and early April 2019 volumes.

Results: ED radiology volumes declined from the 2019 baseline by 32 to 40% (p < 0.001) across the five health systems with a total decrease in volumes across all 5 systems by 35% (p < 0.001). Stratifying by subspecialty, the smallest declines were seen in non-trauma thoracic imaging, which decreased 18% (p value < 0.001), while all other non-trauma studies decreased by 48% (p < 0.001).

Conclusion: Total ED radiology demand may be a marker for public adherence to shelter-in-place mandates, though ED chest radiology demand may increase with an increase in COVID-19 cases.
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http://dx.doi.org/10.1007/s10140-020-01797-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7273127PMC
December 2020

Applications of Artificial Intelligence to Prostate Multiparametric MRI (mpMRI): Current and Emerging Trends.

Cancers (Basel) 2020 May 11;12(5). Epub 2020 May 11.

Department of Radiology, University of California, Irvine, Orange, CA 92868-3201, USA.

Prostate carcinoma is one of the most prevalent cancers worldwide. Multiparametric magnetic resonance imaging (mpMRI) is a non-invasive tool that can improve prostate lesion detection, classification, and volume quantification. Machine learning (ML), a branch of artificial intelligence, can rapidly and accurately analyze mpMRI images. ML could provide better standardization and consistency in identifying prostate lesions and enhance prostate carcinoma management. This review summarizes ML applications to prostate mpMRI and focuses on prostate organ segmentation, lesion detection and segmentation, and lesion characterization. A literature search was conducted to find studies that have applied ML methods to prostate mpMRI. To date, prostate organ segmentation and volume approximation have been well executed using various ML techniques. Prostate lesion detection and segmentation are much more challenging tasks for ML and were attempted in several studies. They largely remain unsolved problems due to data scarcity and the limitations of current ML algorithms. By contrast, prostate lesion characterization has been successfully completed in several studies because of better data availability. Overall, ML is well situated to become a tool that enhances radiologists' accuracy and speed.
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http://dx.doi.org/10.3390/cancers12051204DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7281682PMC
May 2020

Ensuring Appropriateness of Pediatric Second Opinion Consultations.

Curr Probl Diagn Radiol 2020 Mar - Apr;49(2):82-84. Epub 2019 May 10.

Department of Radiology, Children's Hospital Los Angeles, Los Angeles, CA. Electronic address:

Purpose: We sought to evaluate discrepancy rates between outside interpretations, radiology trainee preliminary reports, and subspecialist attending final interpretations for pediatric second opinion consultations on plain film and computed tomography imaging and to evaluate the impact of a process improvement for second opinion consultations.

Methods: Of a total of 572 requests for second opinion consultations during 1-year preintervention period, we utilized RADPEER to score concurrence of 158 requests which occurred overnight and included outside radiologist interpretations and resident preliminary reports. In consultation with clinician committees, we developed new guidelines for requesting second opinion consultations. We evaluated the impact on the number of consultations for the 1-year period following implementation of this process improvement.

Results: There was concurrence between the outside interpretation and pediatric subspecialist second opinion in 146 of 158 cases (92%). There was concurrence between the radiology resident and pediatric subspecialist second opinion in 145 of 158 cases (92%). During the 1-year period following our process improvement implementation, the total number of second opinion consultations decreased to 185 (from 572, a decrease of 68%) and the number of overnight requests for resident preliminary reports decreased to 11 (from 158, a decrease of 93%).

Conclusions: There was a high degree of concurrence between interpretations provided by outside radiologists, overnight radiology residents, and attending pediatric radiologists at our institution. Analyzing institutional-specific discrepancy rates is a valuable first step in partnering with clinicians to develop appropriate guidelines for second opinion consultations.
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http://dx.doi.org/10.1067/j.cpradiol.2019.05.009DOI Listing
November 2020

Multiple renal capillary hemangiomas in a patient with end-stage renal disease.

Radiol Case Rep 2019 Jun 3;14(6):750-754. Epub 2019 Apr 3.

Department of Radiological Sciences, University of California Irvine, Orange, CA, USA.

Renal capillary hemangiomas are rare and benign vascular tumors which are typically incidentally discovered on imaging. Surgical excision is often performed, as imaging appearance is similar to malignant lesions. Renal hemangiomas are typically solitary and unilateral. We present a rare case of multiple renal capillary hemangiomas in a patient with end-stage renal disease. Two hemangiomas were detected on imaging and 2 smaller hemangiomas were detected upon pathological evaluation, suggesting there may be a wider prevalence of smaller, radiographically-occult renal hemangiomas.
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http://dx.doi.org/10.1016/j.radcr.2019.03.027DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6449744PMC
June 2019

Congenital neuroglial choristoma of the foot.

Radiol Case Rep 2019 Jun 2;14(6):718-722. Epub 2019 Apr 2.

Department of Diagnostic Imaging, Children's Hospital of Orange County, Orange, CA, USA.

Neuroglial choristomas are rare malformations of heterotopic neural tissue that have been previously reported predominantly in the head and neck. Competing theories of embryogenesis propose their origin as encephaloceles that have undergone resorption of their cranial connection or displaced neuroectodermal cells which have undergone ectopic proliferation. Most cases occur in midline or para-midline structures. There have been no prior published cases of a neuroglial choristoma in the extremities. We present a case of a 13-month-old otherwise healthy child who presented to our institution with a slowly growing foot mass who was found to have a neuroglial choristoma. This case suggests an early embryological migration defect as the etiology and offers a unique differential consideration for a benign extremity mass.
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http://dx.doi.org/10.1016/j.radcr.2019.03.025DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6447744PMC
June 2019

Developing a Technologist-Focused Quality Improvement Program.

J Am Coll Radiol 2017 12 24;14(12):1598-1602. Epub 2017 May 24.

Children's Hospital Los Angeles, Los Angeles, California. Electronic address:

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http://dx.doi.org/10.1016/j.jacr.2017.04.011DOI Listing
December 2017

Characteristics and Outcomes of Pediatric Patients With Ebola Virus Disease Admitted to Treatment Units in Liberia and Sierra Leone: A Retrospective Cohort Study.

Clin Infect Dis 2017 Feb 25;64(3):243-249. Epub 2016 Oct 25.

Warren Alpert Medical School, and

Background: The clinical and virologic characteristics of Ebola virus disease (EVD) in children have not been thoroughly documented.

Methods: Consecutive children aged <18 years with real-time polymerase chain reaction (RT-PCR)-confirmed EVD were enrolled retrospectively in 5 Ebola treatment units in Liberia and Sierra Leone in 2014/2015. Data collection and medical management were based on standardized International Medical Corps protocols. We performed descriptive statistics, multivariate logistic regression, and Kaplan-Meier survival analyses.

Results: Of 122 children enrolled, the median age was 7 years and one-third were aged <5 years. The female-to-male ratio was 1.3. The most common clinical features at triage and during hospitalization were fever, weakness, anorexia, and diarrhea, although 21% of patients were initially afebrile and 6 patients remained afebrile. Bleeding was rare at presentation (5%) and manifested subsequently in fewer than 50%. The overall case fatality rate was 57%. Factors associated with death in bivariate analyses were age <5 years, bleeding at any time during hospitalization, and high viral load. After adjustment with logistic regression modeling, the odds of death were 14.8-fold higher if patients were aged <5 years, 5-fold higher if the patient had any evidence of bleeding, and 5.2-fold higher if EVD RT-PCR cycle threshold value was ≤20. Plasmodium parasitemia had no impact on EVD outcomes.

Conclusions: Age <5 years, bleeding, and high viral loads were poor prognostic indicators of children with EVD. Research to understand mechanisms of these risk factors and the impact of dehydration and electrolyte imbalance will improve health outcomes.
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http://dx.doi.org/10.1093/cid/ciw725DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5241778PMC
February 2017

Regional Anesthesia for Painful Injuries after Disasters (RAPID): study protocol for a randomized controlled trial.

Trials 2016 11 14;17(1):542. Epub 2016 Nov 14.

Epicentre, Paris, France.

Background: Lower extremity trauma during earthquakes accounts for the largest burden of disaster-related injuries. Insufficient pain management is common in resource-limited disaster settings, and regional anesthesia (RA) may reduce pain in injured patients beyond current standards of care. To date, no controlled trials have been conducted to evaluate the use of RA for pain management in a disaster setting.

Methods/design: The Regional Anesthesia for Painful Injuries after Disasters (RAPID) study aims to evaluate whether regional anesthesia (RA), either with or without ultrasound (US) guidance, can reduce pain from earthquake-related lower limb injuries in a disaster setting. The proposed study is a blinded, randomized controlled equivalence trial among earthquake victims with serious lower extremity injuries in a resource-limited setting. After obtaining informed consent, study participants will be randomized in a 1:1:1 allocation to either: standard care (parenteral morphine at 0.1 mg/kg); standard care plus a landmark-guided fascia iliaca compartment block (FICB); or standard care plus an US-guided femoral nerve block. General practice humanitarian response providers who have undergone a focused training in RA will perform nerve blocks with 20 ml 0.5 % levobupivacaine. US sham activities will be used in the standard care and FICB arms and a normal saline injection will be given to the control group to blind both participants and nonresearch team providers. The primary outcome measure will be the summed pain intensity difference calculated using a standard 11-point Numerical Rating Scale reported by patients over 24 h of follow-up. Secondary outcome measures will include overall analgesic requirements, adverse events, and participant satisfaction.

Discussion: Given the high burden of lower extremity injuries in the aftermath of earthquakes and the currently limited treatment options, research into adjuvant interventions for pain management of these injuries is necessary. While anecdotal reports on the use of RA for patients injured during earthquakes exist, no controlled studies have been undertaken. If demonstrated to be effective in a disaster setting, RA has the potential to significantly assist in reducing both acute suffering and long-term complications for survivors of earthquake trauma.

Trial Registration: ClinicalTrials.gov ( NCT02698228 ), registered on 16 February 2016.
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http://dx.doi.org/10.1186/s13063-016-1671-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5109730PMC
November 2016

External validation of the DHAKA score and comparison with the current IMCI algorithm for the assessment of dehydration in children with diarrhoea: a prospective cohort study.

Lancet Glob Health 2016 10 23;4(10):e744-51. Epub 2016 Aug 23.

International Centre for Diarrhoeal Disease Research, Bangladesh, Dhaka, Bangladesh.

Background: Dehydration due to diarrhoea is a leading cause of child death worldwide, yet no clinical tools for assessing dehydration have been validated in resource-limited settings. The Dehydration: Assessing Kids Accurately (DHAKA) score was derived for assessing dehydration in children with diarrhoea in a low-income country setting. In this study, we aimed to externally validate the DHAKA score in a new population of children and compare its accuracy and reliability to the current Integrated Management of Childhood Illness (IMCI) algorithm.

Methods: DHAKA was a prospective cohort study done in children younger than 60 months presenting to the International Centre for Diarrhoeal Disease Research, Bangladesh, with acute diarrhoea (defined by WHO as three or more loose stools per day for less than 14 days). Local nurses assessed children and classified their dehydration status using both the DHAKA score and the IMCI algorithm. Serial weights were obtained and dehydration status was established by percentage weight change with rehydration. We did regression analyses to validate the DHAKA score and compared the accuracy and reliability of the DHAKA score and IMCI algorithm with receiver operator characteristic (ROC) curves and the weighted κ statistic. This study was registered with ClinicalTrials.gov, number NCT02007733.

Findings: Between March 22, 2015, and May 15, 2015, 496 patients were included in our primary analyses. On the basis of our criterion standard, 242 (49%) of 496 children had no dehydration, 184 (37%) of 496 had some dehydration, and 70 (14%) of 496 had severe dehydration. In multivariable regression analyses, each 1-point increase in the DHAKA score predicted an increase of 0·6% in the percentage dehydration of the child and increased the odds of both some and severe dehydration by a factor of 1·4. Both the accuracy and reliability of the DHAKA score were significantly greater than those of the IMCI algorithm.

Interpretation: The DHAKA score is the first clinical tool for assessing dehydration in children with acute diarrhoea to be externally validated in a low-income country. Further validation studies in a diverse range of settings and paediatric populations are warranted.

Funding: National Institutes of Health Fogarty International Center.
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http://dx.doi.org/10.1016/S2214-109X(16)30150-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5066390PMC
October 2016

Surveillance of Travel-Related Mosquito-borne Illness in Rhode Island.

R I Med J (2013) 2016 Jul 1;99(7):22-3. Epub 2016 Jul 1.

Associate Professor of Medicine, Warren Alpert Medical School of Brown University.

Malaria and Dengue are some of the common infections occurring in persons traveling to countries endemic for these infections. Chinkungunya virus infection is another illness that can occur in people who have travelled to areas endemic for chikungunya virus infection. Herein we report cases of malaria, dengue, and chikungunya in Newport Hospital, The Miriam Hospital and Rhode Island Hospital between January 1, 2010 and December 31, 2014. [Full article available at http://rimed.org/rimedicaljournal-2016-07.asp, free with no login].
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July 2016

Accuracy of Inferior Vena Cava Ultrasound for Predicting Dehydration in Children with Acute Diarrhea in Resource-Limited Settings.

PLoS One 2016 14;11(1):e0146859. Epub 2016 Jan 14.

Department of Emergency Medicine, The Warren Alpert Medical School of Brown University, Providence, Rhode Island, United States of America.

Introduction: Although dehydration from diarrhea is a leading cause of morbidity and mortality in children under five, existing methods of assessing dehydration status in children have limited accuracy.

Objective: To assess the accuracy of point-of-care ultrasound measurement of the aorta-to-IVC ratio as a predictor of dehydration in children.

Methods: A prospective cohort study of children under five years with acute diarrhea was conducted in the rehydration unit of the International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b). Ultrasound measurements of aorta-to-IVC ratio and dehydrated weight were obtained on patient arrival. Percent weight change was monitored during rehydration to classify children as having "some dehydration" with weight change 3-9% or "severe dehydration" with weight change > 9%. Logistic regression analysis and Receiver-Operator Characteristic (ROC) curves were used to evaluate the accuracy of aorta-to-IVC ratio as a predictor of dehydration severity.

Results: 850 children were enrolled, of which 771 were included in the final analysis. Aorta to IVC ratio was a significant predictor of the percent dehydration in children with acute diarrhea, with each 1-point increase in the aorta to IVC ratio predicting a 1.1% increase in the percent dehydration of the child. However, the area under the ROC curve (0.60), sensitivity (67%), and specificity (49%), for predicting severe dehydration were all poor.

Conclusions: Point-of-care ultrasound of the aorta-to-IVC ratio was statistically associated with volume status, but was not accurate enough to be used as an independent screening tool for dehydration in children under five years presenting with acute diarrhea in a resource-limited setting.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0146859PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4713074PMC
July 2016

Candida and cardiovascular implantable electronic devices: a case of lead and native aortic valve endocarditis and literature review.

Mycoses 2015 Nov 25;58(11):637-41. Epub 2015 Sep 25.

Division of Infectious Diseases, Warren Alpert Medical School of Brown University, Providence, RI, USA.

Use of cardiovascular implantable electronic devices (CIED), including permanent pacemakers (PPM) and implantable cardioverter defibrillators (ICD), has increased dramatically over the past two decades. Most CIED infections are caused by staphylococci. Fungal causes are rare and their prognosis is poor. To our knowledge, there has not been a previously reported case of multifocal Candida endocarditis involving both a native left-sided heart valve and a CIED lead. Here, we report the case of a 70-year-old patient who presented with nausea, vomiting, and generalised fatigue, and was found to have Candida glabrata endocarditis involving both a native aortic valve and right atrial ICD lead. We review the literature and summarise four additional cases of CIED-associated Candida endocarditis published from 2009 to 2014, updating a previously published review of cases prior to 2009. We additionally review treatment guidelines and discuss management of CIED-associated Candida endocarditis.
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http://dx.doi.org/10.1111/myc.12391DOI Listing
November 2015

Empirically Derived Dehydration Scoring and Decision Tree Models for Children With Diarrhea: Assessment and Internal Validation in a Prospective Cohort Study in Dhaka, Bangladesh.

Glob Health Sci Pract 2015 Aug 18;3(3):405-18. Epub 2015 Aug 18.

International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh.

Introduction: Diarrhea remains one of the most common and most deadly conditions affecting children worldwide. Accurately assessing dehydration status is critical to determining treatment course, yet no clinical diagnostic models for dehydration have been empirically derived and validated for use in resource-limited settings.

Methods: In the Dehydration: Assessing Kids Accurately (DHAKA) prospective cohort study, a random sample of children under 5 with acute diarrhea was enrolled between February and June 2014 in Bangladesh. Local nurses assessed children for clinical signs of dehydration on arrival, and then serial weights were obtained as subjects were rehydrated. For each child, the percent weight change with rehydration was used to classify subjects with severe dehydration (>9% weight change), some dehydration (3-9%), or no dehydration (<3%). Clinical variables were then entered into logistic regression and recursive partitioning models to develop the DHAKA Dehydration Score and DHAKA Dehydration Tree, respectively. Models were assessed for their accuracy using the area under their receiver operating characteristic curve (AUC) and for their reliability through repeat clinical exams. Bootstrapping was used to internally validate the models.

Results: A total of 850 children were enrolled, with 771 included in the final analysis. Of the 771 children included in the analysis, 11% were classified with severe dehydration, 45% with some dehydration, and 44% with no dehydration. Both the DHAKA Dehydration Score and DHAKA Dehydration Tree had significant AUCs of 0.79 (95% CI = 0.74, 0.84) and 0.76 (95% CI = 0.71, 0.80), respectively, for the diagnosis of severe dehydration. Additionally, the DHAKA Dehydration Score and DHAKA Dehydration Tree had significant positive likelihood ratios of 2.0 (95% CI = 1.8, 2.3) and 2.5 (95% CI = 2.1, 2.8), respectively, and significant negative likelihood ratios of 0.23 (95% CI = 0.13, 0.40) and 0.28 (95% CI = 0.18, 0.44), respectively, for the diagnosis of severe dehydration. Both models demonstrated 90% agreement between independent raters and good reproducibility using bootstrapping.

Conclusion: This study is the first to empirically derive and internally validate accurate and reliable clinical diagnostic models for dehydration in a resource-limited setting. After external validation, frontline providers may use these new tools to better manage acute diarrhea in children.
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http://dx.doi.org/10.9745/GHSP-D-15-00097DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4570015PMC
August 2015

Midupper Arm Circumference Outperforms Weight-Based Measures of Nutritional Status in Children with Diarrhea.

J Nutr 2015 Jul 13;145(7):1582-7. Epub 2015 May 13.

The Warren Alpert Medical School, Brown University, Providence, RI;

Background: Undernutrition contributes to 45% of all deaths in children <5 y of age worldwide, with a large proportion of those deaths caused by diarrhea. However, no validated tools exist for assessing undernutrition in children with diarrhea and possible dehydration.

Objective: This study assessed the validity of different measures of undernutrition in children with diarrhea.

Methods: A prospective cohort study was conducted at an urban hospital in Bangladesh. Children <60 mo of age presenting to the hospital rehydration unit with acute diarrhea were eligible for enrollment. Study staff randomly selected 1196 children for screening, of which 1025 were eligible, 850 were enrolled, and 721 had complete data for analysis. Anthropometric measurements, including weight-for-age z score (WAZ), weight-for-length z score (WLZ), midupper arm circumference (MUAC), and midupper arm circumference z score (MUACZ), were calculated pre- and posthydration in all patients. Measurements were evaluated for their ability to correctly identify undernutrition in children with varying degrees of dehydration.

Results: Of the 721 patients with full data for analysis, the median percent dehydration was 4%. Of the 4 measures evaluated, MUAC and MUACZ demonstrated 92-94% agreement pre- and posthydration compared with 69-76% for WAZ and WLZ. Although each 1% change in hydration status was found to change weight-for-age by 0.0895 z scores and weight-for-length by 0.1304 z scores, MUAC and MUACZ were not significantly affected by dehydration status. Weight-based measures misclassified 12% of children with severe underweight and 14% with severe acute malnutrition (SAM) compared with only 1-2% for MUAC and MUACZ.

Conclusions: MUAC and MUACZ were the most accurate predictors of undernutrition in children with diarrhea. WAZ and WLZ were significantly affected by dehydration status, leading to the misdiagnosis of many patients on arrival with severe underweight and SAM. This trial was registered at clinicaltrials.gov as NCT02007733.
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http://dx.doi.org/10.3945/jn.114.209718DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4478950PMC
July 2015

Derivation and Internal Validation of the Ebola Prediction Score for Risk Stratification of Patients With Suspected Ebola Virus Disease.

Ann Emerg Med 2015 Sep 3;66(3):285-293.e1. Epub 2015 Apr 3.

College of Allied Health Sciences, Cuttington University, Suakoko, Liberia.

Study Objective: The current outbreak of Ebola virus disease in West Africa is the largest on record and has overwhelmed the capacity of local health systems and the international community to provide sufficient isolation and treatment of all suspected cases. The goal of this study is to develop a clinical prediction model that can help clinicians risk-stratify patients with suspected Ebola virus disease in the context of such an epidemic.

Methods: A retrospective analysis was performed of patient data collected during routine clinical care at the Bong County Ebola Treatment Unit in Liberia during its first 16 weeks of operation. The predictive power of 14 clinical and epidemiologic variables was measured against the primary outcome of laboratory-confirmed Ebola virus disease, using logistic regression to develop a final prediction model. Bootstrap sampling was used to assess the internal validity of the model and estimate its performance in a simulated validation cohort.

Results: Ebola virus disease testing results were available for 382 (97%) of 395 patients admitted to the Ebola treatment unit during the study period. A total of 160 patients (42%) tested positive for Ebola virus disease. Logistic regression analysis identified 6 variables independently predictive of laboratory-confirmed Ebola virus disease, including sick contact, diarrhea, loss of appetite, muscle pains, difficulty swallowing, and absence of abdominal pain. The Ebola Prediction Score, constructed with these 6 variables, had an area under the receiver operator characteristic curve of 0.75 (95% confidence interval 0.70 to 0.80) for the prediction of laboratory-confirmed Ebola virus disease. Patients with higher Ebola Prediction Scores had higher likelihoods of laboratory-confirmed Ebola virus disease.

Conclusion: The Ebola Prediction Score can be used by clinicians as an adjunct to current Ebola virus disease case definitions to risk-stratify patients with suspected Ebola virus disease. Clinicians can use this new tool for the purpose of cohorting patients within the suspected-disease ward of an Ebola treatment unit or community-based isolation center to prevent nosocomial infection or as a triage tool when patient numbers overwhelm available capacity. Given the inherent limitations of clinical prediction models, however, a low-cost, point-of-care test that can rapidly and definitively exclude Ebola virus disease in patients should be a research priority.
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http://dx.doi.org/10.1016/j.annemergmed.2015.03.011DOI Listing
September 2015

Nationwide implementation of integrated community case management of childhood illness in Rwanda.

Glob Health Sci Pract 2014 Aug 5;2(3):328-41. Epub 2014 Aug 5.

Rwanda Ministry of Health , Kigali , Rwanda ; Harvard Medical School, Department of Global Health and Social Medicine , Boston, MA , USA ; Dartmouth College, Geisel School of Medicine , Hanover, NH , USA.

Background: Between 2008 and 2011, Rwanda introduced integrated community case management (iCCM) of childhood illness nationwide. Community health workers in each of Rwanda's nearly 15,000 villages were trained in iCCM and equipped for empirical diagnosis and treatment of pneumonia, diarrhea, and malaria; for malnutrition surveillance; and for comprehensive reporting and referral services.

Methods: We used data from the Rwanda health management information system (HMIS) to calculate monthly all-cause under-5 mortality rates, health facility use rates, and community-based treatment rates for childhood illness in each district. We then compared a 3-month baseline period prior to iCCM implementation with a seasonally matched comparison period 1 year after iCCM implementation. Finally, we compared the actual changes in all-cause child mortality and health facility use over this time period with the changes that would have been expected based on baseline trends in Rwanda.

Results: The number of children receiving community-based treatment for diarrhea and pneumonia increased significantly in the 1-year period after iCCM implementation, from 0.83 cases/1,000 child-months to 3.80 cases/1,000 child-months (P = .01) and 0.25 cases/1,000 child-months to 5.28 cases/1,000 child-months (P<.001), respectively. On average, total under-5 mortality rates declined significantly by 38% (P<.001), and health facility use declined significantly by 15% (P = .006). These decreases were significantly greater than would have been expected based on baseline trends.

Conclusions: This is the first study to demonstrate decreases in both child mortality and health facility use after implementing iCCM of childhood illness at a national level. While our study design does not allow for direct attribution of these changes to implementation of iCCM, these results are in line with those of prior studies conducted at the sub-national level in other low-income countries.
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http://dx.doi.org/10.9745/GHSP-D-14-00080DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4168626PMC
August 2014

Prediction of severe disease in children with diarrhea in a resource-limited setting.

PLoS One 2013 3;8(12):e82386. Epub 2013 Dec 3.

Division of Global Health Equity, Brigham and Women's Hospital, Boston, Massachusetts, United States of America ; Research Department, Partners in Health/Inshuti Mu Buzima, Rwinkwavu, Eastern Province, Rwanda.

Objective: To investigate the accuracy of three clinical scales for predicting severe disease (severe dehydration or death) in children with diarrhea in a resource-limited setting.

Methods: Participants included 178 children admitted to three Rwandan hospitals with diarrhea. A local physician or nurse assessed each child on arrival using the World Health Organization (WHO) severe dehydration scale and the Centers for Disease Control (CDC) scale. Children were weighed on arrival and daily until they achieved a stable weight, with a 10% increase between admission weight and stable weight considered severe dehydration. The Clinical Dehydration Scale was then constructed post-hoc using the data collected for the other two scales. Receiver Operator Characteristic (ROC) curves were constructed for each scale compared to the composite outcome of severe dehydration or death.

Results: The WHO severe dehydration scale, CDC scale, and Clinical Dehydration Scale had areas under the ROC curves (AUCs) of 0.72 (95% CI 0.60, 0.85), 0.73 (95% CI 0.62, 0.84), and 0.80 (95% CI 0.71, 0.89), respectively, in the full cohort. Only the Clinical Dehydration Scale was a significant predictor of severe disease when used in infants, with an AUC of 0.77 (95% CI 0.61, 0.93), and when used by nurses, with an AUC of 0.78 (95% CI 0.63, 0.93).

Conclusions: While all three scales were moderate predictors of severe disease in children with diarrhea, scale accuracy varied based on provider training and age of the child. Future research should focus on developing or validating clinical tools that can be used accurately by nurses and other less-skilled providers to assess all children with diarrhea in resource-limited settings.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0082386PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3857792PMC
October 2014

Fusarium infection: report of 26 cases and review of 97 cases from the literature.

Medicine (Baltimore) 2013 Nov;92(6):305-316

From the Division of Infectious Diseases (MM, TA, AD, TKK, HAC, JG-B, JJC, EM), Harvard Medical School, Massachusetts General Hospital, Boston, Massachusetts; and Division of Infectious Diseases (TA, JJC, EM), Warren Alpert Medical School of Brown University, Rhode Island Hospital, Providence, Rhode Island.

Fusarium species is a ubiquitous fungus that causes opportunistic infections. We present 26 cases of invasive fusariosis categorized according to the European Organization for Research and Treatment of Cancer/Mycoses Study Group (EORTC/MSG) criteria of fungal infections. All cases (20 proven and 6 probable) were treated from January 2000 until January 2010. We also review 97 cases reported since 2000. The most important risk factors for invasive fusariosis in our patients were compromised immune system, specifically lung transplantation (n = 6) and hematologic malignancies (n = 5), and burns (n = 7 patients with skin fusariosis), while the most commonly infected site was the skin in 11 of 26 patients. The mortality rates among our patients with disseminated, skin, and pulmonary fusariosis were 50%, 40%, and 37.5%, respectively. Fusarium solani was the most frequent species, isolated from 49% of literature cases. Blood cultures were positive in 82% of both current study and literature patients with disseminated fusariosis, while the remaining 16% had 2 noncontiguous sites of infection but negative blood cultures. Surgical removal of focal lesions was effective in both current study and literature cases. Skin lesions in immunocompromised patients should raise the suspicion for skin or disseminated fusariosis. The combination of medical monotherapy with voriconazole or amphotericin B and surgery in such cases is highly suggested.
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http://dx.doi.org/10.1097/MD.0000000000000008DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4553992PMC
November 2013

C. elegans for anti-infective discovery.

Curr Opin Pharmacol 2013 Oct 29;13(5):769-74. Epub 2013 Aug 29.

Division of Infectious Diseases, Warren Alpert Medical School of Brown University, United States.

Widespread use of antimicrobial agents has led to the emergence of multidrug resistant pathogens, which are becoming increasingly common in clinical practice. This underscores the need to discover novel anti-infective compounds. The soil-living nematode Caenorhabditis elegans has proved to be an excellent model host in the search for such compounds. Indeed, this alternative host is successfully being used to identify traditional microbicidal agents, including antihelminthic compounds, as well as novel agents that attenuate microbial virulence or enhance the host's immune response. Thanks to numerous advantageous features, including its amenability to high-throughput automated screens that allow for the detection of bioactive products among thousands of tested substances, the C. elegans model is now in the spotlight of scientific attention.
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http://dx.doi.org/10.1016/j.coph.2013.08.002DOI Listing
October 2013

Invertebrate models of fungal infection.

Biochim Biophys Acta 2013 Sep 19;1832(9):1378-83. Epub 2013 Mar 19.

Department of Medicine, Warren Alpert Medical School of Brown University, Providence, RI 02903, USA.

The morbidity, mortality and economic burden associated with fungal infections, together with the emergence of fungal strains resistant to current antimicrobial agents, necessitate broadening our understanding of fungal pathogenesis and discovering new agents to treat these infections. Using invertebrate hosts, especially the nematode Caenorhabditis elegans and the model insects Drosophila melanogaster and Galleria mellonella, could help achieve these goals. The evolutionary conservation of several aspects of the innate immune response between invertebrates and mammals makes the use of these simple hosts an effective and fast screening method for identifying fungal virulence factors and testing potential antifungal compounds. The purpose of this review is to compare several model hosts that have been used in experimental mycology to-date and to describe their different characteristics and contribution to the study of fungal virulence and the detection of compounds with antifungal properties. This article is part of a Special Issue entitled: Animal Models of Disease.
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http://dx.doi.org/10.1016/j.bbadis.2013.03.008DOI Listing
September 2013

Mouse models for the study of fungal pneumonia: a collection of detailed experimental protocols for the study of Coccidioides, Cryptococcus, Fusarium, Histoplasma and combined infection due to Aspergillus-Rhizopus.

Virulence 2012 May 1;3(3):329-38. Epub 2012 May 1.

Division of Infectious Diseases, Harvard Medical School and Massachusetts General Hospital Boston, MA, USA.

Mouse models have facilitated the study of fungal pneumonia. In this report, we present the working protocols of groups that are working on the following pathogens: Aspergillus, Coccidioides, Cryptococcus, Fusarium, Histoplasma and Rhizopus. We describe the experimental procedures and the detailed methods that have been followed in the experienced laboratories to study pulmonary fungal infection; we also discuss the anticipated results and technical notes, and provide the practical advices that will help the users of these models.
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http://dx.doi.org/10.4161/viru.20142DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3442846PMC
May 2012

Of model hosts and man: using Caenorhabditis elegans, Drosophila melanogaster and Galleria mellonella as model hosts for infectious disease research.

Adv Exp Med Biol 2012 ;710:11-7

Division of Infectious Diseases, Massachusetts General Hospital, Boston, MA 02114, USA.

The use of invertebrate model hosts has increased in popularity due to numerous advantages of invertebrates over mammalian models, including ethical, logistical and budgetary features. This review provides an introduction to three model hosts, the nematode Caenorhabditis elegans, the fruit fly Drosophila melanogaster and the larvae of Galleria mellonella, the greater wax moth. It highlights principal experimental advantages of each model, for C. elegans the ability to run high-throughput assays, for D. melanogaster the evolutionarily conserved innate immune response, and for G. mellonella the ability to conduct experiments at 37°C and easily inoculate a precise quantity of pathogen. It additionally discusses recent research that has been conducted with each host to identify pathogen virulence factors, study the immune response, and evaluate potential antimicrobial compounds, focusing principally on fungal pathogens.
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http://dx.doi.org/10.1007/978-1-4419-5638-5_2DOI Listing
February 2012

Using C. elegans for antimicrobial drug discovery.

Expert Opin Drug Discov 2011 Jun;6(6):645-652

Division of Infectious Diseases, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA.

INTRODUCTION: The number of microorganism strains with resistance to known antimicrobials is increasing. Therefore, there is a high demand for new, non-toxic and efficient antimicrobial agents. Research with the microscopic nematode Caenorhabditis elegans can address this high demand for the discovery of new antimicrobial compounds. In particular, C. elegans can be used as a model host for in vivo drug discovery through high-throughput screens of chemical libraries. AREAS COVERED: This review introduces the use of substitute model hosts and especially C. elegans in the study of microbial pathogenesis. The authors also highlight recently published literature on the role of C. elegans in drug discovery and outline its use as a promising host with unique advantages in the discovery of new antimicrobial drugs. EXPERT OPINION: C. elegans can be used, as a model host, to research many diseases, including fungal infections and Alzheimer's disease. In addition, high-throughput techniques, for screening chemical libraries, can also be facilitated. Nevertheless, C. elegans and mammals have significant differences that both limit the use of the nematode in research and the degree by which results can be interpreted. That being said, the use of C. elegans in drug discovery still holds promise and the field continues to grow, with attempts to improve the methodology already underway.
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http://dx.doi.org/10.1517/17460441.2011.573781DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3115622PMC
June 2011