Publications by authors named "Robert Chang"

184 Publications

SOCIETY FOR VASCULAR SURGERY CLINICAL PRACTICE GUIDELINES FOR MANAGEMENT OF EXTRACRANIAL CEREBROVASCULAR DISEASE.

J Vasc Surg 2021 Jun 18. Epub 2021 Jun 18.

Management of carotid bifurcation stenosis in stroke prevention has been the subject of extensive investigations, including multiple randomized controlled trials. The proper treatment of patients with carotid bifurcation disease is of major interest to vascular surgeons and other vascular specialists. In 2011, the Society for Vascular Surgery published guidelines for treatment of carotid artery disease. At the time, several randomized trials, comparing carotid endarterectomy (CEA) and carotid artery stenting (CAS), were published. Since that publication, several studies and a few systematic reviews comparing CEA and CAS have been published, and the role of medical management has been re-emphasized. The current publication updates and expands the 2011 guidelines with specific emphasis on five areas: is carotid endarterectomy recommended over maximal medical therapy in low risk patients; is carotid endarterectomy recommended over trans-femoral carotid artery stenting in low surgical risk patients with symptomatic carotid artery stenosis of >50%; timing of carotid Intervention in patients presenting with acute stroke; screening for carotid artery stenosis in asymptomatic patients; and optimal sequence for intervention in patients with combined carotid and coronary artery disease. A separate implementation document will address other important clinical issues in extracranial cerebrovascular disease. Recommendations are made using the GRADE (Grades of Recommendation Assessment, Development and Evaluation) approach, as has been done with other Society for Vascular Surgery guidelines. The committee recommends CEA as the first-line treatment for symptomatic low risk surgical patients with stenosis of 50% to 99% and asymptomatic patients with stenosis of 70% to 99%. The perioperative risk of stroke and death in asymptomatic patients must be <3% to ensure benefit for the patient. In patients with recent stable stroke (modified Rankin 0-2), carotid revascularization is considered appropriate in symptomatic patients with greater than 50% stenosis and is recommended and performed as soon as the patient is neurologically stable after 48 hours but definitely before 14 days of onset of symptoms. In the general population, screening for clinically asymptomatic carotid artery stenosis in patients without cerebrovascular symptoms or significant risk factors for carotid artery disease is not recommended. In selected asymptomatic patients who are at increased risk for carotid stenosis, we suggest screening for clinically asymptomatic carotid artery stenosis as long as the patients would potentially be fit for and willing to consider carotid intervention if significant stenosis is discovered. In patients with symptomatic carotid stenosis 50-99%, who require both CEA and CABG, we suggest CEA before or concomitant with CABG to potentially reduce the risk of stroke and stroke/death. The sequencing of the intervention depends on clinical presentation and institutional experience.
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http://dx.doi.org/10.1016/j.jvs.2021.04.073DOI Listing
June 2021

Triggered Electromyography is a Useful Intraoperative Adjunct to Predict Postoperative Neurological Deficit Following Lumbar Pedicle Screw Instrumentation.

Global Spine J 2021 May 20:21925682211018472. Epub 2021 May 20.

Department of Neurological Surgery, 6595University of Pittsburgh Medical Center, Pittsburgh, PA, USA.

Study Design: Systematic review and meta-analysis.

Objectives: Malposition of pedicle screws during instrumentation in the lumbar spine is associated with complications secondary to spinal cord or nerve root injury. Intraoperative triggered electromyographic monitoring (t-EMG) may be used during instrumentation for early detection of malposition. The association between lumbar pedicle screws stimulated at low EMG thresholds and postoperative neurological deficits, however, remains unknown. The purpose of this study is to assess whether a low threshold t-EMG response to lumbar pedicle screw stimulation can serve as a predictive tool for postoperative neurological deficit.

Methods: The present study is a meta-analysis of the literature from PubMed, Web of Science, and Embase identifying prospective/retrospective studies with outcomes of patients who underwent lumbar spinal fusion with t-EMG testing.

Results: The total study cohort consisted of 2,236 patients and the total postoperative neurological deficit rate was 3.04%. 10.78% of the patients incurred at least 1 pedicle screw that was stimulated below the respective EMG alarm threshold intraoperatively. The incidence of postoperative neurological deficits in patients with a lumbar pedicle screw stimulated below EMG alarm threshold during placement was 13.28%, while only 1.80% in the patients without. The pooled DOR was 10.14. Sensitivity was 49% while specificity was 88%.

Conclusions: Electrically activated lumbar pedicle screws resulting in low t-EMG alarm thresholds are highly specific but weakly sensitive for new postoperative neurological deficits. Patients with new postoperative neurological deficits after lumbar spine surgery were 10 times more likely to have had a lumbar pedicle screw stimulated at a low EMG threshold.
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http://dx.doi.org/10.1177/21925682211018472DOI Listing
May 2021

Diagnostic Accuracy of SSEP Changes during Lumbar Spine Surgery for Predicting Postoperative Neurological Deficit: A Systematic Review and Meta-Analysis.

Spine (Phila Pa 1976) 2021 May 6. Epub 2021 May 6.

Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA, USA Department of Orthopaedic Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA, USA Department of Neurology, University of Pittsburgh Medical Center, Pittsburgh, PA, USA Department of Neuroscience, University of Pittsburgh, Pittsburgh, PA, USA.

Study Design: This study is a meta-analysis of prospective and retrospective studies identified in PubMed, Web of Science, and Embase with outcomes of patients who received intraoperative SSEP monitoring during lumbar spine surgery.

Objective: The objective of this study is to determine the diagnostic accuracy of intraoperative lower extremity (LE) SSEP changes for predicting postoperative neurological deficit. As a secondary analysis, we evaluated three subtypes of intraoperative SSEP changes: reversible, irreversible, and total signal loss.

Summary Of Background Data: Lumbar decompression and fusion surgery can treat lumbar spinal stenosis and spondylolisthesis but carry a risk for nerve root injury. Published neurophysiological monitoring guidelines provide no conclusive evidence for the clinical utility of intraoperative somatosensory evoked potential (SSEP) monitoring during lumbar spine surgery.

Methods: A systematic review was conducted to identify studies with outcomes of patients who underwent lumbar spine surgeries with intraoperative SSEP monitoring. The sensitivity, specificity, and diagnostic odds ratio (DOR) were calculated and presented with forest plots and a summary receiver operating characteristic (ROC) curve.

Results: The study cohort consisted of 5,607 patients. All significant intraoperative SSEP changes had a sensitivity of 44% and specificity of 97% with a DOR of 22.13 (95% CI, 11.30-43.34). Reversible and irreversible SSEP changes had sensitivities of 28% and 33% and specificities of 97% and 97%, respectively. The DORs for reversible and irreversible SSEP changes were 13.93 (95% CI, 4.60-40.44) and 57.84 (95% CI, 15.95-209.84), respectively. Total loss of SSEPs had a sensitivity of 9% and specificity of 99% with a DOR of 23.91 (95% CI, 7.18-79.65).

Conclusion: SSEP changes during lumbar spine surgery are highly specific but moderately sensitive for new postoperative neurological deficits. Patients who had postoperative neurological deficit were 22 times more likely to have exhibited intraoperative SSEP changes.Level of Evidence: 2.
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http://dx.doi.org/10.1097/BRS.0000000000004099DOI Listing
May 2021

Validation of natural language processing to determine the presence and size of abdominal aortic aneurysms in a large integrated health system.

J Vasc Surg 2021 Feb 4. Epub 2021 Feb 4.

Division of Research, Kaiser Permanente Northern California, Oakland, Calif; Division of Vascular Surgery, Department of Surgery, The Permanente Medical Group, South San Francisco, Calif. Electronic address:

Objective: Previous studies of the natural history of abdominal aortic aneurysms (AAAs) have been limited by small cohort sizes or heterogeneous analyses of pooled data. By quickly and efficiently extracting imaging data from the health records, natural language processing (NLP) has the potential to substantially improve how we study and care for patients with AAAs. The aim of the present study was to test the ability of an NLP tool to accurately identify the presence or absence of AAAs and detect the maximal abdominal aortic diameter in a large dataset of imaging study reports.

Methods: Relevant imaging study reports (n = 230,660) from 2003 to 2017 were obtained for 32,778 patients followed up in a prospective aneurysm surveillance registry within a large, diverse, integrated healthcare system. A commercially available NLP algorithm was used to assess the presence of AAAs, confirm the absence of AAAs, and extract the maximal diameter of the abdominal aorta, if stated. A blinded expert manual review of 18,000 randomly selected imaging reports was used as the reference standard. The positive predictive value (PPV or precision), sensitivity (recall), and the kappa statistics were calculated.

Results: Of the randomly selected 18,000 studies that underwent expert manual review, 48.7% were positive for AAAs. In confirming the presence of an AAA, the interrater reliability of the NLP compared with the expert review showed a kappa value of 0.84 (95% confidence interval [CI], 0.83-0.85), with a PPV of 95% and sensitivity of 88.5%. The NLP algorithm showed similar results for confirming the absence of an AAA, with a kappa of 0.79 (95% CI, 0.799-0.80), PPV of 77.7%, and sensitivity of 91.9%. The kappa, PPV, and sensitivity of the NLP for correctly identifying the maximal aortic diameter was 0.88 (95% CI, 0.87-0.89), 88.8%, and 88.2% respectively.

Conclusion: The use of NLP software can accurately analyze large volumes of radiology report data to detect AAA disease and assemble a contemporary aortic diameter-based cohort of patients for longitudinal analysis to guide surveillance, medical management, and operative decision making. It can also potentially be used to identify from the electronic medical records pre- and postoperative AAA patients "lost to follow-up," leverage human resources engaged in the ongoing surveillance of patients with AAAs, and facilitate the construction and implementation of AAA screening programs.
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http://dx.doi.org/10.1016/j.jvs.2020.12.090DOI Listing
February 2021

What is the predictive value of intraoperative somatosensory evoked potential monitoring for postoperative neurological deficit in cervical spine surgery?-a meta-analysis.

Spine J 2021 04 16;21(4):555-570. Epub 2021 Jan 16.

Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA; Department of Neurology, University of Pittsburgh Medical Center, Pittsburgh, PA, USA. Electronic address:

Background Context: Cervical decompression and fusion surgery remains a mainstay of treatment for a variety of cervical pathologies. Potential intraoperative injury to the spinal cord and nerve roots poses nontrivial risk for consequent postoperative neurologic deficits. Although neuromonitoring with intraoperative somatosensory evoked potentials (SSEPs) is often used in cervical spine surgery, its therapeutic value remains controversial.

Purpose: The purpose of the present study was to evaluate whether significant SSEP changes can predict postoperative neurologic complications in cervical spine surgery. A subgroup analysis was performed to compare the predictive power of SSEP changes in both anterior and posterior approaches.

Study Design: The present study was a meta-analysis of the literature from PubMed, Web of Science, and Embase to identify prospective/retrospective studies with outcomes of patients who underwent cervical spine surgeries with intraoperative SSEP monitoring.

Patient Sample: The total cohort consisted of 7,747 patients who underwent cervical spine surgery with intraoperative SSEP monitoring.

Methods: Inclusion criteria for study selection were as follows: (1) prospective or retrospective cohort studies, (2) studies conducted in patients undergoing elective cervical spine surgery not due to aneurysm, tumor, or trauma with intraoperative SSEP monitoring, (3) studies that reported postoperative neurologic outcomes, (4) studies conducted with a sample size ≥20 patients, (5) studies with only adult patients ≥18 years of age, (6) studies published in English, (7) studies inclusive of an abstract.

Outcome Measures: The sensitivity, specificity, diagnostic odds ratio (DOR), and likelihood ratios of overall SSEP changes, reversible SSEP changes, irreversible SSEP changes, and SSEP loss for predicting postoperative neurological deficit were calculated.

Results: The total rate of postoperative neurological deficits was 2.50% (194/7,747) and the total rate of SSEP changes was 7.36% (570/7,747). The incidence of postoperative neurological deficit in patients with intraoperative SSEP changes was 16.49% (94/570) while only 1.39% (100/7,177) in patients without. All significant intraoperative SSEP changes had a sensitivity of 46.0% and specificity of 96.7% with a DOR of 27.32. Reversible and irreversible SSEP changes had sensitivities of 17.7% and 37.1% and specificities of 97.5% and 99.5%, respectively. The DORs for reversible and irreversible SSEP changes were 9.01 and 167.90, respectively. SSEP loss had a DOR of 51.39, sensitivity of 17.3% and specificity 99.6%. In anterior procedures, SSEP changes had a DOR of 9.60, sensitivity of 34.2%, and specificity of 94.7%. In posterior procedures, SSEP changes had a DOR of 13.27, sensitivity of 42.6%, and specificity of 94.0%.

Conclusions: SSEP monitoring is highly specific but weakly sensitive for postoperative neurological deficit following cervical spine surgery. The analysis found that patients with new postoperative neurological deficits were nearly 27 times more likely to have had significant intraoperative SSEP change. Loss of SSEP signals and irreversible SSEP changes seem to indicate a much higher risk of injury than reversible SSEP changes.
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http://dx.doi.org/10.1016/j.spinee.2021.01.010DOI Listing
April 2021

Smartphone-based Ophthalmic Imaging Compared With Spectral-domain Optical Coherence Tomography Assessment of Vertical Cup-to-disc Ratio Among Adults in Southwestern Uganda.

J Glaucoma 2021 Mar;30(3):e90-e98

Department of Ophthalmology, Mbarara University of Science and Technology.

Precis: Using optical coherence tomography (OCT) measurements as a reference standard for vertical cup-to-disc ratio (vCDR), a smartphone-based ophthalmic camera has a sensitivity of 67.7% and specificity of 96.7% to detect a vCDR>0.5.

Purpose: The purpose of this study was to assess the performance of a smartphone-based ophthalmic camera system using an Apple iPhone 6S and an adapter, Paxos Scope, to obtain adequate dilated fundus photos to measure clinically useful vCDR cutoffs.

Patients And Methods: Adult patients from a government tertiary level eye hospital in Southwestern Uganda were prospectively recruited from January to April 2019. All patients experienced a comprehensive eye examination, dilated posterior segment indirect ophthalmoscope imaging with the Paxos Scope, and spectral-domain OCT imaging with a Cirrus HD-OCT to measure vCDR. Patients' eyes excluded had media opacities or existing disease precluding a view of the fundus. Fundus images underwent a single masked review to assign vCDR at increments of 0.1. Descriptive statistics, parametric and χ2 tests for significance, repeated measures correlation, κ, receiver operating characteristics curve, and Bland-Altman were used to assess the data.

Results: Among 467 (consecutive) individuals, fundus photographs acquired with the Paxos Scope demonstrated a 67.7% [95% confidence interval (CI), 63.0-72.0] sensitivity and 96.7% (95% CI, 94.2-98.3) specificity to detect a vCDR>0.5, using OCT as the reference standard. A total of 138 eyes were excluded due to poor imaging acquisition, such as dense cataract, rendering 796 eyes for analysis. The vCDR from graded Paxos Scope images and OCT correlated well with repeated measures correlation of 0.82 (95% CI, 0.77-0.86, P<0.001) and agreement, dichotomized as >0.5 or ≤0.5, was 80.9% (κ=0.63±0.034, P<0.001). Among glaucoma and glaucoma suspects (85 eyes), the sensitivity and specificity dichotomized using vCDR>0.5 were 97.5% (95% CI, 91.3-99.7) and 80.0% (95% CI, 28.4-99.5), respectively. The area under the receiver operating characteristics curve was 0.92 (95% CI, 0.89-0.94) for all eyes and 0.98 (95% CI, 0.78-1.0) for glaucoma and glaucoma suspects.

Conclusions: The Paxos Scope produced images that can be reliably used to estimate vCDR, which is closely aligned with the automated algorithm from the OCT optic disc cube scan. The low-cost, ready-to-integrate adapter, and minimal training requirements make it a viable option for population-based screening in low-resource settings.
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http://dx.doi.org/10.1097/IJG.0000000000001779DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8191139PMC
March 2021

Automatic Identification of Referral-Warranted Diabetic Retinopathy Using Deep Learning on Mobile Phone Images.

Transl Vis Sci Technol 2020 12 4;9(2):60. Epub 2020 Dec 4.

Department of Ophthalmology, Byers Eye Institute at Stanford, Stanford University School of Medicine, Palo Alto, CA, USA.

Purpose: To evaluate the performance of a deep learning algorithm in the detection of referral-warranted diabetic retinopathy (RDR) on low-resolution fundus images acquired with a smartphone and indirect ophthalmoscope lens adapter.

Methods: An automated deep learning algorithm trained on 92,364 traditional fundus camera images was tested on a dataset of smartphone fundus images from 103 eyes acquired from two previously published studies. Images were extracted from live video screenshots from fundus examinations using a commercially available lens adapter and exported as a screenshot from live video clips filmed at 1080p resolution. Each image was graded twice by a board-certified ophthalmologist and compared to the output of the algorithm, which classified each image as having RDR (moderate nonproliferative DR or worse) or no RDR.

Results: In spite of the presence of multiple artifacts (lens glare, lens particulates/smudging, user hands over the objective lens) and low-resolution images achieved by users of various levels of medical training, the algorithm achieved a 0.89 (95% confidence interval [CI] 0.83-0.95) area under the curve with an 89% sensitivity (95% CI 81%-100%) and 83% specificity (95% CI 77%-89%) for detecting RDR on mobile phone acquired fundus photos.

Conclusions: The fully data-driven artificial intelligence-based grading algorithm herein can be used to screen fundus photos taken from mobile devices and identify with high reliability which cases should be referred to an ophthalmologist for further evaluation and treatment.

Translational Relevance: The implementation of this algorithm on a global basis could drastically reduce the rate of vision loss attributed to DR.
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http://dx.doi.org/10.1167/tvst.9.2.60DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7718806PMC
December 2020

Long-term stroke risk with carotid endarterectomy in patients with severe carotid stenosis.

J Vasc Surg 2021 Mar 21;73(3):983-991. Epub 2020 Jul 21.

Division of Research, Kaiser Permanente Northern California, Oakland, Calif; Department of Vascular Surgery, The Permanente Medical Group, South San Francisco, Calif. Electronic address:

Objective: Informed debate regarding the optimal use of carotid endarterectomy (CEA) for stroke risk reduction requires contemporary assessment of both long-term risk and periprocedural risk. In this study, we report long-term stroke and death risk after CEA in a large integrated health care system.

Methods: All patients with documented severe (70%-99%) stenosis from 2008 to 2012 who underwent CEA were identified and stratified by asymptomatic or symptomatic indication. Those with prior ipsilateral interventions were excluded. Patients were followed up through 2017 for the primary outcomes of any stroke/death within 30 days of intervention and long-term ipsilateral ischemic stroke; secondary outcomes were any stroke and overall survival.

Results: Overall, 1949 patients (63.2% male; mean age, 71.3 ± 8.9 years) underwent 2078 primary CEAs, 1196 (58%) for asymptomatic stenosis and 882 (42%) for symptomatic stenosis. Mean follow-up was 5.5 ± 2.7 years. Median time to surgery was 72.0 (interquartile range, 38.5-198.0) days for asymptomatic patients and 21.0 (interquartile range, 5.0-55.0) days for symptomatic patients (P < .001). Most of the patients' demographics and characteristics were similar in both groups. Controlled blood pressure rates were similar at the time of CEA. Baseline statin use was seen in 60.5% of the asymptomatic group compared with 39.9% in the symptomatic group (P < .001), and statin adherence by 80% medication possession ratio was 19.3% asymptomatic vs 12.4% symptomatic (P < .001). The crude overall 30-day any stroke/death rates were 0.9% and 1.5% for the asymptomatic group and the symptomatic group, respectively. The 5-year risk of ipsilateral stroke and a combined end point of any stroke/death by Kaplan-Meier survival analysis were 2.5% and 28.7% for the asymptomatic group and 4.0% and 31.4% for the symptomatic group, respectively. Unadjusted cumulative all-cause survival was 74.2% for the asymptomatic group and 71.8% for the symptomatic group at 5 years.

Conclusions: In a contemporary review of CEA, outcomes for either operative indication show low adverse events perioperatively and low long-term stroke risk up to 5 years. These results are well within consensus guidelines and published trial outcomes and should help inform the discussion around optimal CEA use for severe carotid stenosis.
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http://dx.doi.org/10.1016/j.jvs.2020.06.124DOI Listing
March 2021

A 3D Deep Learning System for Detecting Referable Glaucoma Using Full OCT Macular Cube Scans.

Transl Vis Sci Technol 2020 02 18;9(2):12. Epub 2020 Feb 18.

Byers Eye Institute, Stanford University, Palo Alto, CA, USA.

Purpose: The purpose of this study was to develop a 3D deep learning system from spectral domain optical coherence tomography (SD-OCT) macular cubes to differentiate between referable and nonreferable cases for glaucoma applied to real-world datasets to understand how this would affect the performance.

Methods: There were 2805 Cirrus optical coherence tomography (OCT) macula volumes (Macula protocol 512 × 128) of 1095 eyes from 586 patients at a single site that were used to train a fully 3D convolutional neural network (CNN). Referable glaucoma included true glaucoma, pre-perimetric glaucoma, and high-risk suspects, based on qualitative fundus photographs, visual fields, OCT reports, and clinical examinations, including intraocular pressure (IOP) and treatment history as the binary (two class) ground truth. The curated real-world dataset did not include eyes with retinal disease or nonglaucomatous optic neuropathies. The cubes were first homogenized using layer segmentation with the Orion Software (Voxeleron) to achieve standardization. The algorithm was tested on two separate external validation sets from different glaucoma studies, comprised of Cirrus macular cube scans of 505 and 336 eyes, respectively.

Results: The area under the receiver operating characteristic (AUROC) curve for the development dataset for distinguishing referable glaucoma was 0.88 for our CNN using homogenization, 0.82 without homogenization, and 0.81 for a CNN architecture from the existing literature. For the external validation datasets, which had different glaucoma definitions, the AUCs were 0.78 and 0.95, respectively. The performance of the model across myopia severity distribution has been assessed in the dataset from the United States and was found to have an AUC of 0.85, 0.92, and 0.95 in the severe, moderate, and mild myopia, respectively.

Conclusions: A 3D deep learning algorithm trained on macular OCT volumes without retinal disease to detect referable glaucoma performs better with retinal segmentation preprocessing and performs reasonably well across all levels of myopia.

Translational Relevance: Interpretation of OCT macula volumes based on normative data color distributions is highly influenced by population demographics and characteristics, such as refractive error, as well as the size of the normative database. Referable glaucoma, in this study, was chosen to include cases that should be seen by a specialist. This study is unique because it uses multimodal patient data for the glaucoma definition, and includes all severities of myopia as well as validates the algorithm with international data to understand generalizability potential.
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http://dx.doi.org/10.1167/tvst.9.2.12DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7347026PMC
February 2020

Midterm outcomes for 605 patients receiving Endologix AFX or AFX2 Endovascular AAA Systems in an integrated healthcare system.

J Vasc Surg 2021 Mar 3;73(3):856-866. Epub 2020 Jul 3.

Surgical Outcomes and Analysis, Kaiser Permanente, San Diego, Calif.

Background: Endologix issued important safety updates for the AFX Endovascular AAA System in 2016 and 2018 owing to the risk of type III endoleaks. Outcomes with these devices are limited to small case series with short-term follow-up. We describe the midterm outcomes for a large cohort of patients who received an Endologix AFX or AFX2 device.

Study Design: Data from an integrated healthcare system's implant registry, which prospectively monitors all patients after endovascular aortic repair, was used for this descriptive study. Patients undergoing endovascular aortic repair with three AFX System variations (Strata [AFX-S], Duraply [AFX-D], and AFX2 with Duraply [AFX2]) were identified (2011-2017). Crude cumulative event probabilities for endoleak (types I and III), major reintervention, conversion to open, rupture, and mortality (aneurysm related and all cause) were estimated.

Results: Among 605 patients, 375 received AFX-S, 197 received AFX-D, and 33 received AFX2. Median follow-up for the cohort was 3.9 (interquartile range, 2.5-5.1) years. The crude 2-year incidence of overall endoleak, any subsequent reintervention or conversion, and mortality was 8.8% (95% confidence interval [CI], 6.3-12.3), 12.0% (95% CI, 9.1-15.9), and 8.8% (95% CI, 6.3-12.2) for AFX-S. Respective estimates for AFX-D were 7.9% (95% CI, 4.8-13.0), 10.6% (95% CI, 6.9-16.1), and 9.7% (95% CI, 6.3-14.7); for AFX2, they were 14.1% (95% CI, 4.7-38.2), 16.2% (95% CI, 6.4-37.7), and 21.2% (95% CI, 10.7-39.4).

Conclusions: The midterm outcomes of a large U.S. patient cohort with an Endologix AFX or AFX2 System demonstrate a concerning rate of adverse postoperative events. Patients with these devices should receive close clinical surveillance to prevent device-related adverse events.
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http://dx.doi.org/10.1016/j.jvs.2020.06.048DOI Listing
March 2021

Impact of a Best Practice Advisory for Pediatric Patients With Staphylococcus aureus Bacteremia.

J Pediatric Infect Dis Soc 2021 Apr;10(3):282-288

Division of Pediatric Infectious Diseases, University of Michigan, Ann Arbor, Michigan.

Background: Infectious diseases (ID) consultation and optimal antibiotic therapy improve outcomes in Staphylococcus aureus bacteremia (SAB). Data on strategies to improve adherence to these practices in children are limited.

Methods: This was a quasi-experimental study evaluating the impact of an electronic medical record (EMR)-based best practice advisory (BPA) for SAB, recommending ID consult and optimal antibiotic therapy based on rapid mecA gene detection. Inpatients < 21 years old with SAB before (January 2015-July 2017) and after (August 2017-December 2018) BPA implementation were included. Primary outcome was receipt of ID consult. Secondary outcomes included receipt of optimal therapy, time to ID consult and optimal therapy, recurrent SAB, and 30-day all-cause mortality. ID consultation rates pre- and postimplementation were compared using interrupted time series (ITS) analysis. Hazard ratios (HRs) and 95% confidence intervals (CIs) for time to optimal therapy were calculated using Cox regression.

Results: We included 99 SAB episodes (70 preintervention, 29 postintervention). Preintervention, 48 (68.6%) patients received an ID consult compared to 27 (93.1%) postintervention, but this was not statistically significant on ITS analysis due to a preexisting trend of increasing consultation. Median hours to optimal therapy decreased from 26.1 to 5.5 (P = .03), most notably in patients with methicillin-sensitive S. aureus (MSSA) (42.2 to 10.8; P < .01). On Cox regression, BPA implementation was associated with faster time to optimal therapy (HR, 3.22 [95% CI, 1.04-10.01]).

Conclusions: Implementation of an EMR-based BPA for SAB resulted in faster time to optimal antibiotic therapy, particularly for patients with MSSA. ID consultation increased throughout the study period and was not significantly impacted by the BPA.
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http://dx.doi.org/10.1093/jpids/piaa058DOI Listing
April 2021

Towards multi-center glaucoma OCT image screening with semi-supervised joint structure and function multi-task learning.

Med Image Anal 2020 07 19;63:101695. Epub 2020 May 19.

Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong, China.

Glaucoma is the leading cause of irreversible blindness in the world. Structure and function assessments play an important role in diagnosing glaucoma. Nowadays, Optical Coherence Tomography (OCT) imaging gains increasing popularity in measuring the structural change of eyes. However, few automated methods have been developed based on OCT images to screen glaucoma. In this paper, we are the first to unify the structure analysis and function regression to distinguish glaucoma patients from normal controls effectively. Specifically, our method works in two steps: a semi-supervised learning strategy with smoothness assumption is first applied for the surrogate assignment of missing function regression labels. Subsequently, the proposed multi-task learning network is capable of exploring the structure and function relationship between the OCT image and visual field measurement simultaneously, which contributes to classification performance improvement. It is also worth noting that the proposed method is assessed by two large-scale multi-center datasets. In other words, we first build the largest glaucoma OCT image dataset (i.e., HK dataset) involving 975,400 B-scans from 4,877 volumes to develop and evaluate the proposed method, then the model without further fine-tuning is directly applied on another independent dataset (i.e., Stanford dataset) containing 246,200 B-scans from 1,231 volumes. Extensive experiments are conducted to assess the contribution of each component within our framework. The proposed method outperforms the baseline methods and two glaucoma experts by a large margin, achieving volume-level Area Under ROC Curve (AUC) of 0.977 on HK dataset and 0.933 on Stanford dataset, respectively. The experimental results indicate the great potential of the proposed approach for the automated diagnosis system.
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http://dx.doi.org/10.1016/j.media.2020.101695DOI Listing
July 2020

Comparison of 1-Year Effectiveness of Trabecular Microbypass Stent implantation (iStent) in Conjunction With Phacoemulsification Among Mild, Moderate, and Severe Primary Open-angle Glaucoma Patients.

J Glaucoma 2020 07;29(7):542-549

Department of Ophthalmology, Stanford University, Palo Alto, CA.

Precis: The study compared 1-year effectiveness of single trabecular microbypass stent (iStent) implantation with phacoemulsification among glaucoma severities in primary open-angle glaucoma. The study found that mild glaucoma had greater success rate and lower number of medications compared with moderate and severe glaucoma.

Purpose: To evaluate the effectiveness of iStent implantation in combination with cataract surgery in moderate to severe glaucoma compared with mild glaucoma.

Methods: Medical charts of primary open-angle glaucoma subjects undergoing 1 iStent implantation were retrospectively reviewed. Glaucoma was classified on the basis of mean deviation (MD) of the preoperative standard automated perimetry into mild (MD>-6 dB), moderate (MD -6 to -12 dB), and severe (MD<-12 dB). Mixed effect regression models were performed to determine the effect of iStent at 1 year. The outcomes included as follows: (1) intraocular pressure (IOP) and the number of medications, (2) eyes with IOP ≤ severity-based target (18 mm Hg for mild, 15 mm Hg for moderate, 12 mm Hg for severe) (2A) without medication, and (2B) with medication reduction.

Results: In total, 104 eyes from 89 subjects were analyzed. Cataract combined with iStent surgery significantly lowered the number of medications in all groups and significantly decreased IOP in moderate and severe glaucoma (P<0.05). There was significantly higher number of medications in moderate (β: 0.58, P=0.002) and severe (β: 1.20, P<0.001) compared with mild glaucoma. Eyes with moderate glaucoma had significantly lower rate of success (criterion 2A) compared with mild glaucoma [odds ratio (OR): 0.008, P=0.047]. Eyes with moderate and severe glaucoma had significantly lower rates of success (criterion 2B) (moderate vs. mild OR: 0.002, P=0.028; severe vs. mild OR: 0.026, P=0.026).

Conclusions: Combined phacoemulsification with iStent seems to have a better IOP-lowering and medication-lowering effect in mild glaucoma cases versus those with moderate and severe glaucoma. This difference was found in real-world data over one-year follow-up period. Long-term studies with defined IOP goals and medication removal protocols are warranted.
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http://dx.doi.org/10.1097/IJG.0000000000001542DOI Listing
July 2020

Diagnostic accuracy of various EEG changes during carotid endarterectomy to detect 30-day perioperative stroke: A systematic review.

Clin Neurophysiol 2020 07 23;131(7):1508-1516. Epub 2020 Apr 23.

Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA, USA; Department of Neurology, University of Pittsburgh Medical Center, Pittsburgh, PA, USA. Electronic address:

Objectives: We assessed whether significant intraoperative electroencephalography (EEG) changes have predictive value for perioperative stroke within 30 days after carotid endarterectomy (CEA) procedures for carotid stenosis (CS) patients. We also assessed the diagnostic accuracy of various EEG changes in predicting perioperative stroke.

Methods: We searched databases for reports with outcomes of CS patients who underwent CEA with intraoperative EEG monitoring. We calculated the sensitivity, specificity, and diagnostic odds ratio (DOR) of EEG changes for predicting perioperative stroke. Sensitivity and specificity were presented with forest plots and a summary receiver operating characteristic (ROC) curve.

Results: The meta-analysis included 10,672 patients. Intraoperative EEG changes predicted 30-day stroke with a sensitivity of 46% (95% CI, 38-54%) and specificity of 86% (95% CI, 83-88%). The estimated DOR was 5.79 (95% CI, 3.86-8.69). The estimated DOR for reversible and irreversible EEG changes were 8.25 (95% CI, 3.34-20.34) and 70.84 (95% CI, 36.01-139.37), respectively.

Conclusion: Intraoperative EEG changes have high specificity but modest sensitivity for predicting perioperative stroke following CEA. Patients with irreversible EEG changes are at high risk for perioperative stroke.

Significance: Intraoperative EEG changes can help surgeons predict the risk of perioperative stroke for CS patients following CEA.
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http://dx.doi.org/10.1016/j.clinph.2020.03.037DOI Listing
July 2020

Comparison of Using One Trabecular Microbypass Stent versus Two during Cataract Surgery at Two Sites: One-Year Follow-Up.

Biomed Res Int 2020 7;2020:1920352. Epub 2020 Apr 7.

Byers Eye Institute, Stanford University School of Medicine, Palo Alto, CA, USA.

Purpose: To compare IOP and ocular hypotensive medication reduction of using one trabecular microbypass stent versus two in patients with open-angle glaucoma. . Palo Alto Veterans Affairs (VA) Hospital and the Byers Eye Institute at Stanford University, Palo Alto, California, USA.

Design: Retrospective case series.

Methods: A chart review included patients who underwent trabecular microbypass implantation with cataract surgery in 2015-2017, with at least one-year follow-up. Subjects were divided into two groups by location (always one stent at Stanford versus two stents at the VA). Primary outcome measures included IOP and medication reduction at baseline and 12-month follow-up.

Results: 132 subjects (166 eyes) were included. The preoperative IOP was 16.3 ± 3.4 mmHg on 2.6 ± 1.1 medications in the one-stent group ( = 85) and 17.5 ± 3.1 mmHg on 2.7 ± 0.6 medications in the two-stent group ( = 81). There was no significant difference between the two groups ( = 0.06). At the 12-month visit, there was a 13.37% ± 2.93 reduction in IOP in the 1-stent group ( ≤ 0.001) and 13.49% ± 2.69 in the 2-stent group ( ≤ 0.001); both were not significantly different from each other ( = 0.074). At 12 months, there was also a 14.5% reduction in medication use for the 1-stent group and 15.3% reduction in the 2-stent group, both statistically significant from baseline, ( = 0.022 and = 0.037, respectively).

Conclusions: Implantation with either one or two stents during cataract surgery in patients with glaucoma demonstrated similar IOP and med reduction in both groups between the two sites.
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http://dx.doi.org/10.1155/2020/1920352DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7166285PMC
January 2021

The Utility of Intraoperative Lateral Spread Recording in Microvascular Decompression for Hemifacial Spasm: A Systematic Review and Meta-Analysis.

Neurosurgery 2020 09;87(4):E473-E484

Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania.

Background: Microvascular decompression (MVD) is the surgical treatment of choice for hemifacial spasm (HFS). During MVD, monitoring of the abnormal lateral spread response (LSR), an evoked response to facial nerve stimulation, has been traditionally used to monitor adequacy of cranial nerve (CN) VII decompression.

Objective: To assess the utility of LSR monitoring in predicting spasm-free status after MVD postoperatively.

Methods: We searched PubMed, Web of Science, and Embase for relevant publications. We included studies reporting on intraoperative LSR monitoring during MVD for HFS and spasm-free status following the procedure. Sensitivity of LSR, specificity, diagnostic odds ratio, and positive predictive value were calculated.

Results: From 148 studies, 26 studies with 7479 patients were ultimately included in this meta-analysis. The final intraoperative LSR status predicted the clinical outcome of MVD with the following specificities and sensitivities: 89% (0.83- 0.93) and 40% (0.30- 0.51) at discharge, 90% (0.84-0.94) and 41% (0.29-0.53) at 3 mo, 89% (0.83-0.93) and 40% (0.30-0.51) at 1 yr. When LSR persisted after MVD, the probability (95% CI) for HFS persistence was 47.8% (0.33-0.63) at discharge, 40.8% (0.23-0.61) at 3 mo, and 24.4% (0.13-0.41) at 1 yr. However, when LSR resolved, the probability for HFS persistence was 7.3% at discharge, 4.2% at 3 mo, and 4.0% at 1 yr.

Conclusion: Intraoperative LSR monitoring has high specificity but modest sensitivity in predicting the spasm-free status following MVD. Persistence of LSR carries high risk for immediate and long-term facial spasm persistence. Therefore, adequacy of decompression should be thoroughly investigated before closing in cases where intraoperative LSR persists.
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http://dx.doi.org/10.1093/neuros/nyaa069DOI Listing
September 2020

3D Bioprinted GelMA Based Models for the Study of Trophoblast Cell Invasion.

Sci Rep 2019 12 11;9(1):18854. Epub 2019 Dec 11.

Stevens Institute of Technology, Department of Mechanical Engineering, Hoboken, NJ, 07030, USA.

Bioprinting is an emerging and promising technique for fabricating 3D cell-laden constructs for various biomedical applications. In this paper, we employed 3D bioprinted GelMA-based models to investigate the trophoblast cell invasion phenomenon, enabling studies of key placental functions. Initially, a set of optimized material and process parameters including GelMA concentration, UV crosslinking time and printing configuration were identified by systematic, parametric study. Following this, a multiple-ring model (2D multi-ring model) was tested with the HTR-8/SVneo trophoblast cell line to measure cell movement under the influence of EGF (chemoattractant) gradients. In the multi-ring model, the cell front used as a cell invasion indicator moves at a rate of 85 ± 33 µm/day with an EGF gradient of 16 µM. However, the rate was dramatically reduced to 13 ± 5 µm/day, when the multi-ring model was covered with a GelMA layer to constrain cells within the 3D environment (3D multi-ring model). Due to the geometric and the functional limitations of multi-ring model, a multi-strip model (2D multi-strip model) was developed to investigate cell movement in the presence and absence of the EGF chemoattractant. The results show that in the absence of an overlying cell-free layer of GelMA, movement of the cell front shows no significant differences between control and EGF-stimulated rates, due to the combination of migration and proliferation at high cell density (6 × 10 cells/ml) near the GelMA surface. When the model was covered by a layer of GelMA (3D multi-strip model) and migration was excluded, EGF-stimulated cells showed an invasion rate of 21 ± 3 µm/day compared to the rate for unstimulated cells, of 5 ± 4 µm/day. The novel features described in this report advance the use of the 3D bioprinted placental model as a practical tool for not only measurement of trophoblast invasion but also the interaction of invading cells with other tissue elements.
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http://dx.doi.org/10.1038/s41598-019-55052-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6906490PMC
December 2019

A Branching Algorithm.

J Hosp Med 2019 11 23;14(11):707-711. Epub 2019 Oct 23.

Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan.

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http://dx.doi.org/10.12788/jhm.3315DOI Listing
November 2019

Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs.

JAMA Ophthalmol 2019 12;137(12):1353-1360

Beijing Institute of Ophthalmology, Beijing Tongren Hospital, Capital Medical University, Beijing, China.

Importance: A deep learning system (DLS) that could automatically detect glaucomatous optic neuropathy (GON) with high sensitivity and specificity could expedite screening for GON.

Objective: To establish a DLS for detection of GON using retinal fundus images and glaucoma diagnosis with convoluted neural networks (GD-CNN) that has the ability to be generalized across populations.

Design, Setting, And Participants: In this cross-sectional study, a DLS for the classification of GON was developed for automated classification of GON using retinal fundus images obtained from the Chinese Glaucoma Study Alliance, the Handan Eye Study, and online databases. The researchers selected 241 032 images were selected as the training data set. The images were entered into the databases on June 9, 2009, obtained on July 11, 2018, and analyses were performed on December 15, 2018. The generalization of the DLS was tested in several validation data sets, which allowed assessment of the DLS in a clinical setting without exclusions, testing against variable image quality based on fundus photographs obtained from websites, evaluation in a population-based study that reflects a natural distribution of patients with glaucoma within the cohort and an additive data set that has a diverse ethnic distribution. An online learning system was established to transfer the trained and validated DLS to generalize the results with fundus images from new sources. To better understand the DLS decision-making process, a prediction visualization test was performed that identified regions of the fundus images utilized by the DLS for diagnosis.

Exposures: Use of a deep learning system.

Main Outcomes And Measures: Area under the receiver operating characteristics curve (AUC), sensitivity and specificity for DLS with reference to professional graders.

Results: From a total of 274 413 fundus images initially obtained from CGSA, 269 601 images passed initial image quality review and were graded for GON. A total of 241 032 images (definite GON 29 865 [12.4%], probable GON 11 046 [4.6%], unlikely GON 200 121 [83%]) from 68 013 patients were selected using random sampling to train the GD-CNN model. Validation and evaluation of the GD-CNN model was assessed using the remaining 28 569 images from CGSA. The AUC of the GD-CNN model in primary local validation data sets was 0.996 (95% CI, 0.995-0.998), with sensitivity of 96.2% and specificity of 97.7%. The most common reason for both false-negative and false-positive grading by GD-CNN (51 of 119 [46.3%] and 191 of 588 [32.3%]) and manual grading (50 of 113 [44.2%] and 183 of 538 [34.0%]) was pathologic or high myopia.

Conclusions And Relevance: Application of GD-CNN to fundus images from different settings and varying image quality demonstrated a high sensitivity, specificity, and generalizability for detecting GON. These findings suggest that automated DLS could enhance current screening programs in a cost-effective and time-efficient manner.
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http://dx.doi.org/10.1001/jamaophthalmol.2019.3501DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6743057PMC
December 2019

Long-term freedom from aneurysm-related mortality remains favorable after endovascular abdominal aortic aneurysm repair in a 15-year multicenter registry.

J Vasc Surg 2020 03 5;71(3):790-798. Epub 2019 Sep 5.

Department of Vascular Surgery, Permanente Medical Group, South San Francisco, Calif. Electronic address:

Objective: Endovascular aneurysm repair (EVAR) has become the preferred approach to abdominal aortic aneurysm (AAA) because of lower early morbidity and mortality than open repair. However, the ability of EVAR to prevent long-term aneurysm-related mortality (ARM) has been questioned in light of recent trial data. We have updated our long-term EVAR experience in a large multicenter registry to further examine this issue.

Methods: Between 2000 and 2010, 1736 patients with AAA underwent EVAR in a large integrated regional healthcare system. We extended follow-up in this previously reported cohort through 2015 and identified predictors associated with ARM and need for major reintervention. The primary outcome was ARM. Secondary outcomes were all-cause mortality, delayed aneurysm rupture, major adverse event, major reintervention, sac growth of more than 5 mm, and type I or III endoleak. End points were analyzed for the whole cohort and compared for patients who underwent EVAR during the earlier (2000-2005) and latter (2006-2010) halves of the enrollment period to assess for changes in outcomes over time of repair.

Results: The overall follow-up rate was 96.3%, and median follow-up was 5.5 years (interquartile range, 2.8-7.7 years). During the study period, 958 patients died, of whom 63 experienced ARM (6.6%). Overall crude rate of freedom from ARM was 96.4%. Delayed aneurysm rupture was seen in 1.3% (n = 23), with a median time to event of 4.1 years (interquartile range, 1.7-7.2 years). Major adverse events occurred in 12.4% of patients, and major reintervention was performed in 10.3%. Overall freedom from major adverse event or major reintervention was seen in 84.0%. Significant predictors of ARM included female sex, age 80 to 89 years, urgent EVAR, and any major reintervention. The unadjusted cumulative probability of all-cause survival was significantly higher in the late group than the early group at 5 years (66.8% vs 59.8%; P = .01, log-rank test); however, freedom from ARM at 5 years was not significantly different (96.5% and 97.1%, respectively; P = .67, log-rank test).

Conclusions: Our results demonstrate favorable long-term freedom from major adverse event or major reintervention after EVAR and extremely low rates of ARM and delayed rupture. Our findings support EVAR as a safe, long-term solution for managing patients with AAA and provide insight into clinical parameters that can be used to stratify patients' post-EVAR surveillance and need for reintervention.
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http://dx.doi.org/10.1016/j.jvs.2019.05.043DOI Listing
March 2020

Understanding Patient Attitudes Toward Multifocal Intraocular Lenses in Online Medical Forums Through Sentiment Analysis.

Stud Health Technol Inform 2019 Aug;264:1378-1382

Byers Eye Institute, Stanford University, Palo Alto CA, USA.

Multifocal intraocular lens implants (IOLs) are a premium option for cataract surgery which patients may purchase to achieve improved spectacle-independence for near vision but may have trade-offs with visual quality. We demonstrate the use of sentiment analysis to evaluate multifocal lenses discussed on MedHelp, a leading online health forum. A search for "multifocal IOL" was performed on MedHelp.org on November 1, 2016, yielding relevant patient posts. Sentiment analysis was performed using IBM's Watson, which extracted 30,066 unique keywords and their associated sentiment scores from 7495 posts written by 1474 unique patient users. Keywords associated with monovision, monofocal, and toric lenses had positive mean sentiment, significantly higher than for keywords associated with multifocals, which had negative mean sentiment (p < 0.001, ANOVA). Many keywords represented complaints and were associated with negative sentiment, including glare, halo, and ghosting. Sentiment analysis can provide insights into patient perspectives towards multifocal lenses by interpreting online patient posts.
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http://dx.doi.org/10.3233/SHTI190453DOI Listing
August 2019

Detection of glaucomatous optic neuropathy with spectral-domain optical coherence tomography: a retrospective training and validation deep-learning analysis.

Lancet Digit Health 2019 08 9;1(4):e172-e182. Epub 2019 Aug 9.

Department of Ophthalmology and Visual Sciences, Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Hong Kong Eye Hospital, Hong Kong Special Administrative Region, China; Prince of Wales Hospital, Hong Kong Special Administrative Region, China.

Background: Spectral-domain optical coherence tomography (SDOCT) can be used to detect glaucomatous optic neuropathy, but human expertise in interpretation of SDOCT is limited. We aimed to develop and validate a three-dimensional (3D) deep-learning system using SDOCT volumes to detect glaucomatous optic neuropathy.

Methods: We retrospectively collected a dataset including 4877 SDOCT volumes of optic disc cube for training (60%), testing (20%), and primary validation (20%) from electronic medical and research records at the Chinese University of Hong Kong Eye Centre (Hong Kong, China) and the Hong Kong Eye Hospital (Hong Kong, China). Residual network was used to build the 3D deep-learning system. Three independent datasets (two from Hong Kong and one from Stanford, CA, USA), including 546, 267, and 1231 SDOCT volumes, respectively, were used for external validation of the deep-learning system. Volumes were labelled as having or not having glaucomatous optic neuropathy according to the criteria of retinal nerve fibre layer thinning on reliable SDOCT images with position-correlated visual field defect. Heatmaps were generated for qualitative assessments.

Findings: 6921 SDOCT volumes from 1 384 200 two-dimensional cross-sectional scans were studied. The 3D deep-learning system had an area under the receiver operation characteristics curve (AUROC) of 0·969 (95% CI 0·960-0·976), sensitivity of 89% (95% CI 83-93), specificity of 96% (92-99), and accuracy of 91% (89-93) in the primary validation, outperforming a two-dimensional deep-learning system that was trained on en face fundus images (AUROC 0·921 [0·905-0·937]; p<0·0001). The 3D deep-learning system performed similarly in the external validation datasets, with AUROCs of 0·893-0·897, sensitivities of 78-90%, specificities of 79-86%, and accuracies of 80-86%. The heatmaps of glaucomatous optic neuropathy showed that the learned features by the 3D deep-learning system used for detection of glaucomatous optic neuropathy were similar to those used by clinicians.

Interpretation: The proposed 3D deep-learning system performed well in detection of glaucomatous optic neuropathy in both primary and external validations. Further prospective studies are needed to estimate the incremental cost-effectiveness of incorporation of an artificial intelligence-based model for glaucoma screening.

Funding: Hong Kong Research Grants Council.
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http://dx.doi.org/10.1016/S2589-7500(19)30085-8DOI Listing
August 2019

Dry eye and sleep quality: a large community-based study in Hangzhou.

Sleep 2019 10;42(11)

Eye Center, The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.

Study Objectives: To investigate the relationship between dry eye and sleep quality in a large community-based Chinese population.

Methods: A total of 3,070 participants aged 18-80 were recruited from a community-based study in Hangzhou, China during 2016-2017. Sleep quality was evaluated using the Chinese version of the Pittsburgh Sleep Quality Index (CPSQI), and dry eye was evaluated using the Ocular Surface Disease Index (OSDI) questionnaire. Multivariable linear regression and logistic regression models were used to investigate the associations, adjusting for age, smoking, drinking, season, and other potential confounders.

Results: Overall, CPSQI score and sleep dysfunction were significantly associated with mild, moderate, and severe dry eye (ORs for CPSQI score: 1.07, 1.13, 1.14, all p < 0.001; for sleep dysfunction: 1.31, 1.73, 1.66, all p < 0.05). Furthermore, worse OSDI score was presented in participants with worse CPSQI score or sleep dysfunction (CPSQI score > 7) (β: 0.13, 0.54; all p < 0.001). In addition, six of the seven components of CPSQI showed significant associations with dry eye (all p < 0.001), except for the component of sleep medication use. Moreover, we observed significant associations of dry eye in all three subscales of OSDI with CPSQI score and sleep dysfunction.

Conclusion: Our large, community-based study showed a strong association between poor sleep quality and an increased severity of dry eye, suggesting that preventing either one of the discomforts might alleviate the other.
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http://dx.doi.org/10.1093/sleep/zsz160DOI Listing
October 2019

A Counterintuitive Tool for Connected Care.

Ann Intern Med 2019 08 16;171(4):283-284. Epub 2019 Jul 16.

University of Michigan Health System, Ann Arbor, Michigan (Z.C., R.C., V.C.).

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http://dx.doi.org/10.7326/M19-0589DOI Listing
August 2019

Development and validation of a deep-learning algorithm for the detection of neovascular age-related macular degeneration from colour fundus photographs.

Clin Exp Ophthalmol 2019 Nov 25;47(8):1009-1018. Epub 2019 Jul 25.

Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, University of Melbourne, Melbourne, Victoria, Australia.

Importance: Detection of early onset neovascular age-related macular degeneration (AMD) is critical to protecting vision.

Background: To describe the development and validation of a deep-learning algorithm (DLA) for the detection of neovascular age-related macular degeneration.

Design: Development and validation of a DLA using retrospective datasets.

Participants: We developed and trained the DLA using 56 113 retinal images and an additional 86 162 images from an independent dataset to externally validate the DLA. All images were non-stereoscopic and retrospectively collected.

Methods: The internal validation dataset was derived from real-world clinical settings in China. Gold standard grading was assigned when consensus was reached by three individual ophthalmologists. The DLA classified 31 247 images as gradable and 24 866 as ungradable (poor quality or poor field definition). These ungradable images were used to create a classification model for image quality. Efficiency and diagnostic accuracy were tested using 86 162 images derived from the Melbourne Collaborative Cohort Study. Neovascular AMD and/or ungradable outcome in one or both eyes was considered referable.

Main Outcome Measures: Area under the receiver operating characteristic curve (AUC), sensitivity and specificity.

Results: In the internal validation dataset, the AUC, sensitivity and specificity of the DLA for neovascular AMD was 0.995, 96.7%, 96.4%, respectively. Testing against the independent external dataset achieved an AUC, sensitivity and specificity of 0.967, 100% and 93.4%, respectively. More than 60% of false positive cases displayed other macular pathologies. Amongst the false negative cases (internal validation dataset only), over half (57.2%) proved to be undetected detachment of the neurosensory retina or RPE layer.

Conclusions And Relevance: This DLA shows robust performance for the detection of neovascular AMD amongst retinal images from a multi-ethnic sample and under different imaging protocols. Further research is warranted to investigate where this technology could be best utilized within screening and research settings.
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http://dx.doi.org/10.1111/ceo.13575DOI Listing
November 2019

Machine learning metrology of cell confinement in melt electrowritten three-dimensional biomaterial substrates.

Microsyst Nanoeng 2019 25;5:15. Epub 2019 Mar 25.

4Mechanical Engineering Department, Stevens Institute of Technology, Hoboken, NJ USA.

Tuning cell shape by altering the biophysical properties of biomaterial substrates on which cells operate would provide a potential shape-driven pathway to control cell phenotype. However, there is an unexplored dimensional scale window of three-dimensional (3D) substrates with precisely tunable porous microarchitectures and geometrical feature sizes at the cell's operating length scales (10-100 μm). This paper demonstrates the fabrication of such high-fidelity fibrous substrates using a melt electrowriting (MEW) technique. This advanced manufacturing approach is biologically qualified with a metrology framework that models and classifies cell confinement states under various substrate dimensionalities and architectures. Using fibroblasts as a model cell system, the mechanosensing response of adherent cells is investigated as a function of variable substrate dimensionality (2D vs. 3D) and porous microarchitecture (randomly oriented, "non-woven" vs. precision-stacked, "woven"). Single-cell confinement states are modeled using confocal fluorescence microscopy in conjunction with an automated single-cell bioimage data analysis workflow that extracts quantitative metrics of the whole cell and sub-cellular focal adhesion protein features measured. The extracted multidimensional dataset is employed to train a machine learning algorithm to classify cell shape phenotypes. The results show that cells assume distinct confinement states that are enforced by the prescribed substrate dimensionalities and porous microarchitectures with the woven MEW substrates promoting the highest cell shape homogeneity compared to non-woven fibrous substrates. The technology platform established here constitutes a significant step towards the development of integrated additive manufacturing-metrology platforms for a wide range of applications including fundamental mechanobiology studies and 3D bioprinting of tissue constructs to yield specific biological designs qualified at the single-cell level.
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http://dx.doi.org/10.1038/s41378-019-0055-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6431680PMC
March 2019

CsSnI-Encapsulated Multidye-Sensitized All-Solid-State Solar Cells.

ACS Appl Mater Interfaces 2019 Jun 7;11(24):21424-21434. Epub 2019 Jun 7.

Department of Chemistry, Research Center for Sustainable Energy and Nanotechnology (RCSEN), and Innovation and Development Center of Sustainable Agriculture (IDCSA) , National Chung Hsing University , Taichung 402 , Taiwan.

The design of a dye-sensitized solar cell (DSSC) based on the simultaneous incorporation of multiple dyes is examined. By investigating the use of the porphyrin-based YD2-o-C8 and YDD6, and the organic chromophore TTAR, which can act as complementary absorbers, we are able to enhance the capture of incoming light across the solar spectrum. This is demonstrated first by using a conventional DSSC architecture with a liquid electrolyte and performed a power conversion efficiency (PCE) of 11.2%, representing an improvement over cells based on each of the independent dyes. Next, we used CsSnI as an encapsulating layer over the sensitizing molecules to reduce charge leakage across the dye layers and also added to the absorption of longer wavelengths up to one micron. Finally, we fabricated a cell utilizing a CsSnI/succinonitrile solid hole-transport electrolyte and achieved a PCE of ∼8.5%. It is expected that the all solid-state design will go a long way toward improving long-term device stability.
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http://dx.doi.org/10.1021/acsami.8b19778DOI Listing
June 2019

Characteristics of cataract surgery patients influencing patient satisfaction scores.

J Cataract Refract Surg 2019 04 27;45(4):437-442. Epub 2019 Feb 27.

Byers Eye Institute, Stanford University School of Medicine, Palo Alto, California, USA. Electronic address:

Purpose: To determine factors that influence patient satisfaction scores in individuals who have recently had cataract surgery.

Setting: Byers Eye Institute, Palo Alto, California, USA.

Design: Prospective case series.

Methods: Selected questions from the Press Ganey survey and the National Eye Institute Visual Function Questionnaire-25 were administered to each patient immediately after completion of a clinic visit. The correlation between patient-specific variables and the answer to the survey question "likelihood of recommending our practice to others," a surrogate for overall patient satisfaction, was assessed using the Student t test. A logistical regression model was used to adjust for potentially confounding variables.

Results: One hundred forty-three patients were recruited from 4 providers; 57 (39.8%) were men, and the mean age was 70.0 years ± 11.6 (SD). The main outcome was the proportion of scores less than 5, or "very good," for the likelihood of recommending the practice to others. There was a statistically significant association between a non-5 patient satisfaction score and self-reported ethnicity of Asian or Pacific Islander compared with other ethnicities (odds ratio [OR], 2.3; 95% confidence interval [CI], 1.0-5.1; P = .049); other possible correlates were not statistically significant. The relationship persisted after adjustment for potential confounding variables (OR, 2.6; 95% CI, 1.1-6.3; P = .027).

Conclusion: In postoperative cataract patients, Asian or Pacific Islander ethnicity, a factor out of the control of the provider and clinic staff, was associated with a lower overall Press Ganey patient satisfaction score compared with patients of all other ethnicities.
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http://dx.doi.org/10.1016/j.jcrs.2018.11.031DOI Listing
April 2019