Ophthalmology. Glaucoma最新文献

{"title":"Characterization of Temporal Delay and Modeling of Intraocular Pressure and Visual Field Progression in the African Descent and Glaucoma Evaluation Study","authors":"Anfei Li MD, PhD,&nbsp;Carlos Gustavo De Moraes MD, PhD,&nbsp;Aakriti Garg Shukla MD, MSc,&nbsp;Christopher A. Girkin MD, MSPH,&nbsp;Robert N. Weinreb MD,&nbsp;Noga Harizman MD,&nbsp;Ives Valenzuela MD,&nbsp;George A. Cioffi MD,&nbsp;Linda M. Zangwill PhD,&nbsp;Jeffrey M. Liebmann MD","doi":"10.1016/j.ogla.2026.02.007","DOIUrl":"10.1016/j.ogla.2026.02.007","url":null,"abstract":"<div><h3>Purpose</h3><div>Despite its utility, mathematical modeling of an individualized intraocular pressure (IOP) goal has been hindered by the variable temporal relationships between IOP and visual field (VF) rate of progression (ROP). In this study, we fit a regression model after accounting for the temporal delays between IOP and ROP to help predict individual IOP goals.</div></div><div><h3>Design</h3><div>This is a retrospective study analyzing the IOP–ROP temporal relationship and identifying predictive factors of IOP of stability (IOS).</div></div><div><h3>Participants</h3><div>Four hundred eight eyes from the African Descent and Glaucoma Evaluation Study with more than 14 VFs were included.</div></div><div><h3>Methods</h3><div>For each eye, a ROP time series was produced and correlated to the IOP time series with incremental temporal shifts to estimate the delay between the 2 series. Average IOP during VF progression (worse than –0.5 dB/year) and stability (better than –0.5 dB/year) were calculated accounting for the delay. Contributing factors for IOS were analyzed using multivariable analysis, and significant factors were used to fit a regression model to help predict an individualized IOP goal.</div></div><div><h3>Main Outcome Measures</h3><div>Temporal delay between IOP and ROP changes, and magnitude of error between the predicted IOS and the actual IOS.</div></div><div><h3>Results</h3><div>Delay between IOP and VF changes was found to have a median of 7 months and mode of 4 months. Multivariable analysis found that thinner central corneal thickness (CCT) (<em>P</em> &lt; 0.001) and greater mean deviation (MD) (<em>P</em> &lt; 0.001) were associated with lower required IOP to maintain VF stability. Using CCT and MD, fitted regression models were able to predict individualized IOP that maintains VF stability within ±2 to 3 mmHg.</div></div><div><h3>Conclusions</h3><div>Rate of progression changes trail IOP changes by 4-7 months, an important consideration when obtaining additional VFs to capture or rule-out progression. Accounting for this delay, we modeled individualized IOS to within 2-3 mmHg using only 2 clinical measures, CCT and MD. This simple IOP goal calculation will enable clinicians to make early treatment decisions prior to the delayed VF-based confirmation.</div></div><div><h3>Financial Disclosure(s)</h3><div>Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.</div></div>","PeriodicalId":19519,"journal":{"name":"Ophthalmology. Glaucoma","volume":"9 5","pages":"Pages 543-554"},"PeriodicalIF":3.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147367300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Detection of Structural Glaucoma Progression with Deep Learning on Serial Optic Disc Photographs","authors":"Vahid Mohammadzadeh MD,&nbsp;Tyler Davis PhD,&nbsp;Esteban Morales MS,&nbsp;Diana Salazar Vega MD,&nbsp;Daniela Khaliliyeh MD,&nbsp;Maral Namdari MD,&nbsp;Zhe Fei PhD,&nbsp;Fabien Scalzo PhD,&nbsp;Kouros Nouri-Mahdavi MD, MS,&nbsp;Joseph Caprioli MD","doi":"10.1016/j.ogla.2026.03.005","DOIUrl":"10.1016/j.ogla.2026.03.005","url":null,"abstract":"<div><h3>Purpose</h3><div>To design a supervised deep learning (DL) model to detect glaucoma progression with serial optic disc photographs (DPs).</div></div><div><h3>Design</h3><div>A retrospective longitudinal cohort study.</div></div><div><h3>Participants</h3><div>One thousand five hundred ten eyes (916 patients) with ≥2 years of follow-up and 2 pairs of DPs per eye were included.</div></div><div><h3>Methods</h3><div>Longitudinal series of DPs were labeled as having evidence of progression or stable by 2 ophthalmologists, and discrepancies were adjudicated by 2 glaucoma specialists. An automated cropping was applied centered on the optic disc to reduce less relevant information. The dataset was split into training and testing/validation sets with an 80/10/10 ratio. A twin convolutional neural network was designed to assess baseline and final DPs to detect glaucoma progression.</div></div><div><h3>Main Outcome Measures</h3><div>Area under receiver operating characteristic curves (AUCs) for detection of glaucoma progression; sensitivity and specificity for automated classification compared to clinical classification as ground truth.</div></div><div><h3>Results</h3><div>Baseline visual field mean deviation (±standard deviation) was –4.0 (±5.6) dB. Twenty-two percent of eyes deteriorated based on the clinical review of DPs. The final DL model’s AUC (95% confidence interval) for detection of glaucoma progression was 0.821 (0.764–0.887) with an overall accuracy for classification of 72% (66%–88%) with a sensitivity and specificity of 87% (60%–95%) and 68% (61%–93%), respectively.</div></div><div><h3>Conclusions</h3><div>Our twin convolutional neural network model is able to detect glaucoma progression with clinically relevant accuracy. Deep learning is promising as an adjunctive method for clinical decision-making for detection of structural glaucoma progression.</div></div><div><h3>Financial Disclosure(s)</h3><div>Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.</div></div>","PeriodicalId":19519,"journal":{"name":"Ophthalmology. Glaucoma","volume":"9 5","pages":"Pages 565-574"},"PeriodicalIF":3.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147488648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Seasonal Pattern of Glaucoma Emergencies in New England","authors":"In Young Chung MBBS, MPH,&nbsp;Anthony Marte MD,&nbsp;Kyoung Min Lee MD, PhD,&nbsp;Eric S. Wang BA,&nbsp;Paul Parker MD,&nbsp;Grayson W. Armstrong MD, MPH,&nbsp;Mengyu Wang PhD,&nbsp;Tobias Elze PhD,&nbsp;Lucy Q. Shen MD","doi":"10.1016/j.ogla.2026.04.010","DOIUrl":"10.1016/j.ogla.2026.04.010","url":null,"abstract":"","PeriodicalId":19519,"journal":{"name":"Ophthalmology. Glaucoma","volume":"9 5","pages":"Pages 610-612"},"PeriodicalIF":3.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147935598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Paradoxical Deep Anterior Chamber during Inflammatory Hypotony","authors":"Reika Shu MD,&nbsp;Kyoko Ohno-Matsui MD, PhD,&nbsp;Koju Kamoi MD, PhD","doi":"10.1016/j.ogla.2026.06.008","DOIUrl":"10.1016/j.ogla.2026.06.008","url":null,"abstract":"","PeriodicalId":19519,"journal":{"name":"Ophthalmology. Glaucoma","volume":"9 5","pages":"Page e21"},"PeriodicalIF":3.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148551565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Re: Hamilton et al: Clinical outcomes of Hydrus microstent implantation for open-angle glaucoma (Ophthalmol Glaucoma. 2026;9:48–61)","authors":"Colin I. Clement FRANZCO, PhD,&nbsp;Tina Wong FRCOphth, PhD","doi":"10.1016/j.ogla.2026.06.006","DOIUrl":"10.1016/j.ogla.2026.06.006","url":null,"abstract":"","PeriodicalId":19519,"journal":{"name":"Ophthalmology. Glaucoma","volume":"9 5","pages":"Pages e15-e16"},"PeriodicalIF":3.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148594626","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Family Screening in Glaucoma","authors":"Annamalai Odayappan DO, DNB,&nbsp;Joshua R. Ehrlich MD, MPH,&nbsp;Tos T.J.M. Berendschot PhD,&nbsp;Ahmed Owda MD, MPH,&nbsp;Swetha Sampangi Rama Iyer DO, DNB,&nbsp;Michelle J. Sun MD, MPH,&nbsp;Mani Iswarya MSc,&nbsp;Radhakrishnan Mala MSc,&nbsp;Kavitha Srinivasan MS,&nbsp;Carroll A.B. Webers MD, PhD,&nbsp;Rengaraj Venkatesh DO, DNB","doi":"10.1016/j.ogla.2026.03.003","DOIUrl":"10.1016/j.ogla.2026.03.003","url":null,"abstract":"<div><h3>Topic</h3><div>To assess the prevalence of glaucoma among relatives of known patients with glaucoma, describe the response rate of relatives in different glaucoma family screening programs, and summarize the barriers to family members' participation in these screening programs.</div></div><div><h3>Clinical Relevance</h3><div>Population-based screening for glaucoma is a challenge since the prevalence in the general population is low. The presence of a positive family history is a known risk factor for glaucoma, but implementing family screening programs has not become standard practice yet. Further, the literature regarding the ideal strategy for implementing targeted glaucoma family screening programs is unclear.</div></div><div><h3>Methods</h3><div>Databases including MEDLINE, Embase, Scopus, Web of Science, Cochrane Library, Google Scholar, Joanna Briggs Institute database, and Epistemonikos were searched for relevant literature. We included studies describing probands with primary open-angle glaucoma, primary angle-closure disease, specifically primary angle-closure glaucoma and primary angle closure, pseudoexfoliation glaucoma, and pigmentary glaucoma. The concept of interest was the response rates of family members to the screening programs and the proportion of people with undetected glaucoma identified by these programs. We updated our search in February 2025.</div></div><div><h3>Results</h3><div>Forty-two studies were included in the data synthesis. The median prevalence of glaucoma among relatives was 11.25% (interquartile range [IQR]: 8.1%–17.6%), and the median prevalence of glaucoma suspects was 19.45% (IQR: 8.4%–28.7%). Further, the median prevalence of glaucoma among offspring, parents, and siblings of probands across studies was 3.4% (IQR: 1.1%–8.8%), 31.6% (IQR: 20.9%–69.0%), and 16.2% (IQR: 10.4%–33.3%), respectively. The response rate of relatives to a screening program is highly variable. Direct contact with relatives, either via letters (median: 74.6%, IQR: 39%-82.4%) or telephone (median: 48%, IQR: 38.9%–69.8%), yielded better response in contrast to indirect communication through probands as in oral counseling of probands or issuing leaflets or cards to be given to their relatives (median: 12.9%, IQR: 8.6%–30.2%).</div></div><div><h3>Conclusion</h3><div>Over 30% of relatives of known patients with primary glaucoma either have glaucoma or are diagnosed as suspects. Response rate to screening programs is low. These programs should focus on directly engaging with the relatives. More evidence is required to identify the ideal age at which glaucoma screening needs to commence.</div></div><div><h3>Financial Disclosure(s)</h3><div>Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.</div></div>","PeriodicalId":19519,"journal":{"name":"Ophthalmology. Glaucoma","volume":"9 5","pages":"Pages 584-594"},"PeriodicalIF":3.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13248150/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147482323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Bumpy Iris","authors":"Saloni M. Joshi DNB,&nbsp;Pawan V. Garde MS","doi":"10.1016/j.ogla.2026.06.002","DOIUrl":"10.1016/j.ogla.2026.06.002","url":null,"abstract":"","PeriodicalId":19519,"journal":{"name":"Ophthalmology. Glaucoma","volume":"9 5","pages":"Page e19"},"PeriodicalIF":3.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148407025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Topographic Agreement of Retinal Nerve Fiber and Ganglion Cell Loss Improves Incipient Glaucoma Detection","authors":"Adam Z. Xu,&nbsp;Giacinto Triolo MD,&nbsp;Maria J. Chaves-Samaniego MD,&nbsp;Maximilian G. Konarzewski BS,&nbsp;Steven J. Gedde MD,&nbsp;Jean Claude Mwanza MD, PhD,&nbsp;Donald L. Budenz MD, MPH,&nbsp;Felipe A. Medeiros MD,&nbsp;Luis E. Vazquez MD, PhD","doi":"10.1016/j.ogla.2026.03.004","DOIUrl":"10.1016/j.ogla.2026.03.004","url":null,"abstract":"<div><h3>Purpose</h3><div>To evaluate combinations of geographically corresponding retinal nerve fiber layer (RNFL) parameters and ganglion cell-inner plexiform layer (GCIPL) parameters for detection of incipient glaucoma (IG).</div></div><div><h3>Design</h3><div>A cross-sectional study.</div></div><div><h3>Subjects</h3><div>The early glaucoma (EG) exploratory cohort consisted of 156 diseased subjects and 199 age-matched controls. The IG validation cohort consisted of 75 diseased subjects and 247 age-matched controls. Only 1 eye from each subject was used.</div></div><div><h3>Methods</h3><div>Retinal nerve fiber layer and GCIPL scans were obtained with Cirrus HD-OCT. Linear regression was used to determine the degree of correlation between corresponding RNFL and GCIPL sector thinning in EG. Logistic regression models of parameter combinations were fit on the EG cohort, then used to generate receiver operating characteristic (ROC) curves. Fitted models were validated on the IG dataset. Diagnostic power was assessed by calculating area under the ROC curve (AUC).</div></div><div><h3>Main Outcome Measures</h3><div>Area under the ROC curve (AUC)</div></div><div><h3>Results</h3><div>In EG patients, inferotemporal GCIPL loss is moderately correlated to inferior RNFL loss (<em>R</em>^<em>2</em> = 0.38), and supertemporal GCIPL loss is moderately correlated to superior RNFL loss (<em>R</em>^<em>2</em> = 0.32). A logistic regression model of all these parameters combined improved significantly when these correlations were accounted for with interaction terms (ΔAIC = –17.4, ΔBIC = –9.7). The combined model performed strongly in diagnosing both EG (AUC = 0.969) and IG (AUC = 0.903) and outperformed all of the individual parameters in both EG and IG (unpaired bootstrapped AUC comparisons, <em>P</em> &lt; 0.0001 for all).</div></div><div><h3>Conclusions</h3><div>Combining corresponding sectors of the GCIPL and RNFL, and factoring in their correlation, produces a model with strong diagnostic accuracy both in EG and IG. Attention to corresponding GCIPL and RNFL thickness loss in these sectors can help clinicians detect IG.</div></div><div><h3>Financial Disclosure(s)</h3><div>Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.</div></div>","PeriodicalId":19519,"journal":{"name":"Ophthalmology. Glaucoma","volume":"9 5","pages":"Pages 555-564"},"PeriodicalIF":3.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147482329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Focal Epithelial Bullae at the Air–Cornea Interface After Glaucoma Surgery","authors":"Shubham Manchanda MS,&nbsp;Anchal Thakur MS,&nbsp;Sushmita Kaushik MS","doi":"10.1016/j.ogla.2026.06.001","DOIUrl":"10.1016/j.ogla.2026.06.001","url":null,"abstract":"","PeriodicalId":19519,"journal":{"name":"Ophthalmology. Glaucoma","volume":"9 5","pages":"Page e18"},"PeriodicalIF":3.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148354776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of an Intraluminal Suture on Outflow Resistance in an in Vitro Styrene-Block-Isobutylene-Block-Styrene Microshunt Partial Occlusion Model","authors":"William J. Herspiegel BSc,&nbsp;James J. Armstrong MD, PhD,&nbsp;Anastasiya Vinokurtseva MD,&nbsp;Taylor Lukasik MD,&nbsp;Cindy M.L. Hutnik MD, PhD,&nbsp;Iqbal Ike K. Ahmed MD,&nbsp;David B. Yan MD","doi":"10.1016/j.ogla.2026.03.007","DOIUrl":"10.1016/j.ogla.2026.03.007","url":null,"abstract":"<div><h3>Purpose</h3><div>Measure outflow resistance of the styrene-block-isobutylene-block-styrene (SIBS) microshunt when sutures of differing lengths, sizes, and materials partially occlude the lumen.</div></div><div><h3>Design</h3><div>In vitro experiment</div></div><div><h3>Methods</h3><div>The SIBS microshunt proximal end was connected to a gravity perfusion system. The distal tip was submerged within a fluid-filled covered collection-beaker. Microshunt flow was quantified through collection-beaker mass changes. Each 5-minute trial was replicated 4 times per condition. Various sutures were inserted into the distal end of the microshunt’s lumen, and outflow resistance was measured in partly occluded states (4-mm or 8-mm suture length inserted, 9-0 or 10-0 suture diameters, Vicryl or nylon suture). The 4-mm 10-0 nylon condition was repeated with sutures from different lots to investigate the effects of suture manufacturing variability.</div></div><div><h3>Main Outcome Measure</h3><div>Outflow resistance.</div></div><div><h3>Results</h3><div>Resistance of nonoccluded SIBS microshunts (<em>n</em> = 5) was 1.74 ± 0.06 mmHg/μl/minute, matching the theoretical 1.76 mmHg/μl/minute from the Hagen–Poiseuille formula. Partial occlusion with a 4-mm 10-0 suture increased resistance to 3.42 ± 0.13 mmHg/μl/minute for nylon and 3.55 ± 0.13 for Vicryl. Partial occlusion with an 8-mm 10-0 suture increased resistance to 4.66 ± 0.21 for nylon and 5.08 ± 0.23 for Vicryl. Partial occlusion with a 4-mm 9-0 suture increased resistance to 5.11 ± 0.28 for nylon and 5.00 ± 0.27 for Vicryl. Partial occlusion with an 8-mm 9-0 suture increased resistance to 7.24 ± 0.37 for nylon and 7.87 ± 0.55 for Vicryl. Resistance differed significantly between nonoccluded versus all partially occluded states (<em>P</em> &lt; 0.0001), 4- versus 8-mm partially occlusion lengths (<em>P</em> &lt; 0.0001), 10-0 versus 9-0 suture diameters (<em>P</em> &lt; 0.0001), and 4-mm 10-0 nylon sutures from different lots (<em>P</em> &lt; 0.0001). No difference was observed between suture materials (<em>P</em> &gt; 0.05) or different microshunts (<em>P</em> &gt; 0.05).</div></div><div><h3>Conclusions</h3><div>Nonoccluded microshunt resistance measured by the perfusion model matched theoretical values. Partial occlusion with either suture material caused substantial resistance increases, depending on suture diameter and length, compared with nonoccluded microshunts. If desired, partial occlusion with 4-mm 9-0 nylon or 8-mm 10-0 nylon suture is recommended, producing resistance consistently above the hypotony threshold while maintaining optimal therapeutic efficacy.</div></div><div><h3>Financial Disclosure(s)</h3><div>Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.</div></div>","PeriodicalId":19519,"journal":{"name":"Ophthalmology. Glaucoma","volume":"9 5","pages":"Pages 595-603"},"PeriodicalIF":3.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147596573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}