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To evaluate the relationship between plasma biomarkers of systemic inflammation and incident age-related macular degeneration (AMD) in persons with the AIDS.Case-control study.Participants with incident intermediate-stage AMD (N = 26) in the Longitudinal Study of the Ocular Complications of AIDS (LSOCA) and controls (N = 60) without AMD. Cryopreserved baseline plasma specimens were assayed for biomarkers of inflammation, including high-sensitivity C-reactive protein (CRP), interleukin (IL)-6, interferon-γ inducible protein (IP)-10, soluble CD14 (sCD14), soluble CD163 (sCD163), and intestinal fatty acid-binding protein (I-FABP).After adjustment for age, sex, and race/ethnicity, baseline mean ± standard deviation (SD) log10(mg/ml) plasma levels of CRP (0.52 ± 0.60 vs. 0.20 ± 0.43; P = 0.01) and mean ± SD log10(pg/ml) plasma levels of sCD14 (6.31 ± 0.11 vs. 6.23 ± 0.14; P = 0.008) were significantly higher among cases (incident AMD) than among controls (no AMD). There was a suggestion that mean ± SD baseline log10(pg/ml) plasma IL-6 levels (0.24 ± 0.33 vs. 0.11 ± 0.29; P = 0.10) might be higher among cases than controls. In a separate analysis of 548 participants in LSOCA, elevated baseline levels of plasma inflammatory biomarkers were associated with a greater risk of mortality but not with an increased risk of incident cataract.These data suggest that systemic inflammatory biomarkers are associated with incident AMD but not incident cataract in persons with AIDS, and that systemic inflammation may play a role in the pathogenesis of AMD.

Purpose To determine classification criteria for Fuchs uveitis syndrome. Design Machine learning of cases with Fuchs uveitis syndrome and 8 other anterior uveitides. Methods Cases of anterior uveitides were collected in an informatics-designed preliminary database, and a final database was constructed of cases achieving supermajority agreement on the diagnosis, using formal consensus techniques. Cases were split into a training set and a validation set. Machine learning using multinomial logistic regression was used on the training set to determine a parsimonious set of criteria that minimized the misclassification rate among the anterior uveitides. The resulting criteria were evaluated on the validation set. Results One thousand eighty-three cases of anterior uveitides, including 146 cases of Fuchs uveitis syndrome, were evaluated by machine learning. The overall accuracy for anterior uveitides was 97.5% in the training set and 96.7% in the validation set (95% confidence interval 92.4, 98.6). Key criteria for Fuchs uveitis syndrome included unilateral anterior uveitis with or without vitritis and either: 1) heterochromia or 2) unilateral diffuse iris atrophy and stellate keratic precipitates. The overall accuracy for anterior uveitides was 97.5% in the training set (95% confidence interval [CI] 96.3, 98.4) and 96.7% in the validation set (95% CI 92.4, 98.6). The misclassification rates for FUS were 4.7% in the training set and 5.5% in the validation set, respectively. Conclusions The criteria for Fuchs uveitis syndrome had a low misclassification rate and appeared to perform well enough for use in clinical and translational research.

Purpose To determine classification criteria for Vogt-Koyanagi-Harada (VKH) disease Design Machine learning of cases with VKH disease and 5 other panuveitides. Methods Cases of panuveitides were collected in an informatics-designed preliminary database, and a final database was constructed of cases achieving supermajority agreement on the diagnosis, using formal consensus techniques. Cases were split into a training set and a validation set. Machine learning using multinomial logistic regression was used on the training set to determine a parsimonious set of criteria that minimized the misclassification rate among the panuveitides. The resulting criteria were evaluated on the validation set. Results One thousand twelve cases of panuveitides, including 156 cases of early-stage VKH and 103 cases of late-stage VKH, were evaluated. Overall accuracy for panuveitides was 96.3% in the training set and 94.0% in the validation set (95% confidence interval 89.0, 96.8). Key criteria for early-stage VKH included: 1) exudative retinal detachment with characteristic appearance on fluorescein angiogram or optical coherence tomography or 2) panuveitis with ≥2 of 5 neurologic symptoms/signs. Key criteria for late-stage VKH included history of early-stage VKH and either: 1) sunset glow fundus or 2) uveitis and ≥1 of 3 cutaneous signs. The misclassification rates in the learning and validation sets for early-stage VKH were 8.0% and 7.7%, respectively, and for late-stage VKH 1.0% and 12%, respectively. Conclusions The criteria for VKH had a reasonably low misclassification rate and appeared to perform sufficiently well for use in clinical and translational research.

Purpose To determine classification criteria for juvenile idiopathic arthritis (JIA)-associated chronic anterior uveitis (CAU). Design Machine learning of cases with JIA CAU and 8 other anterior uveitides. Methods Cases of anterior uveitides were collected in an informatics-designed preliminary database, and a final database was constructed of cases achieving supermajority agreement on the diagnosis, using formal consensus techniques. Cases were split into a training set and a validation set. Machine learning using multinomial logistic regression was used on the training set to determine a parsimonious set of criteria that minimized the misclassification rate among the anterior uveitides. The resulting criteria were evaluated on the validation set. Results One thousand eighty-three cases of anterior uveitides, including 202 cases of JIA CAU, were evaluated by machine learning. The overall accuracy for anterior uveitides was 97.5% in the training set and 96.7% in the validation set (95% confidence interval 92.4, 98.6). Key criteria for JIA CAU included 1) chronic anterior uveitis (or if newly diagnosed insidious onset) and 2) JIA, except for the systemic, rheumatoid factor-positive polyarthritis, and enthesitis related arthritis variants. The misclassification rates for JIA CAU were 2.4% in the training set and 0% in the validation set, respectively. Conclusions The criteria for JIA CAU had a low misclassification rate and appeared to perform well enough for use in clinical and translational research.

Purpose To determine classification criteria for tubercular uveitis DESIGN: Machine learning of cases with tubercular uveitis and 14 other uveitides. Methods Cases of non-infectious posterior or panuveitis, and of infectious posterior or panuveitis were collected in an informatics-designed preliminary database, and a final database was constructed of cases achieving supermajority agreement on the diagnosis, using formal consensus techniques. Cases were analyzed by anatomic class, and each class was split into a training set and a validation set. Machine learning using multinomial logistic regression was used on the training set to determine a parsimonious set of criteria that minimized the misclassification rate among the intermediate uveitides. The resulting criteria were evaluated on the validation sets. Results Two hundred seventy-seven cases of tubercular uveitis were evaluated by machine learning against other uveitides. Key criteria for tubercular uveitis were a compatible uveitic syndrome, including: 1) anterior uveitis with iris nodules, 2) serpiginous-like tubercular choroiditis, 3) choroidal nodule (tuberculoma), 4) occlusive retinal vasculitis, and 5) in hosts with evidence of active systemic tuberculosis, multifocal choroiditis; and evidence of tuberculosis, including: 1) histologically- or microbiologically-confirmed infection, 2) positive interferon-Ɣ release assay test, or 3) positive tuberculin skin test. The overall accuracy of the diagnosis of tubercular uveitis versus other uveitides in the validation set was 98.2% (95% CI 96.5, 99.1). The misclassification rates for tubercular uveitis were: training set 3.4%; and validation set 3.6%. Conclusions The criteria for tubercular uveitis had a low misclassification rate and appeared to perform sufficiently well for use in clinical and translational research.

Purpose To determine classification criteria for varicella zoster virus (VZV) anterior uveitis DESIGN: Machine learning of cases with VZV anterior uveitis and 8 other anterior uveitides. Methods Cases of anterior uveitides were collected in an informatics-designed preliminary database, and a final database was constructed of cases achieving supermajority agreement on the diagnosis, using formal consensus techniques. Cases were split into a training set and a validation set. Machine learning using multinomial logistic regression was used on the training set to determine a parsimonious set of criteria that minimized the misclassification rate among the anterior uveitides. The resulting criteria were evaluated on the validation set. Results One thousand eighty-three cases of anterior uveitides, including 123 cases of VZV anterior uveitis, were evaluated by machine learning. The overall accuracy for anterior uveitides was 97.5% in the training set and 96.7% in the validation set (95% confidence interval 92.4, 98.6). Key criteria for VZV anterior uveitis included unilateral anterior uveitis with either 1) positive aqueous humor polymerase chain reaction assay for VZV; 2) sectoral iris atrophy in a patient ≥60 years of age; or 3) concurrent or recent dermatomal herpes zoster. The misclassification rates for VZV anterior uveitis were 0.9% in the training set and 0% in the validation set, respectively. Conclusions The criteria for VZV anterior uveitis had a low misclassification rate and appeared to perform sufficiently well for use in clinical and translational research.

Purpose To determine classification criteria for multifocal choroiditis with panuveitis (MFCPU) DESIGN: : Machine learning of cases with MFCPU and 8 other posterior uveitides. Methods Cases of posterior uveitides were collected in an informatics-designed preliminary database, and a final database was constructed of cases achieving supermajority agreement on diagnosis, using formal consensus techniques. Cases were split into a training set and a validation set. Machine learning using multinomial logistic regression was used on the training set to determine a parsimonious set of criteria that minimized the misclassification rate among the posterior uveitides. The resulting criteria were evaluated on the validation set. Results One thousand sixty-eight cases of posterior uveitides, including 138 cases of MFCPU, were evaluated by machine learning. Key criteria for MFCPU included: 1) multifocal choroiditis with the predominant lesions size >125 µm in diameter; 2) lesions outside the posterior pole (with or without posterior involvement); and either 3) punched-out atrophic chorioretinal scars or 4) more than minimal mild anterior chamber and/or vitreous inflammation. Overall accuracy for posterior uveitides was 93.9% in the training set and 98.0% (95% confidence interval 94.3, 99.3) in the validation set. The misclassification rates for MFCPU were 15% in the training set and 0% in the validation set. Conclusions The criteria for MFCPU had a reasonably low misclassification rate and appeared to perform sufficiently well for use in clinical and translational research.

To determine classification criteria for acute retinal necrosis (ARN).Machine learning of cases with ARN and 4 other infectious posterior uveitides / panuveitides.Cases of infectious posterior uveitides / panuveitides were collected in an informatics-designed preliminary database, and a final database was constructed of cases achieving supermajority agreement on diagnosis, using formal consensus techniques. Cases were split into a training set and a validation set. Machine learning using multinomial logistic regression was used on the training set to determine a parsimonious set of criteria that minimized the misclassification rate among the infectious posterior uveitides / panuveitides. The resulting criteria were evaluated on the validation set.Eight hundred three cases of infectious posterior uveitides / panuveitides, including 186 cases of ARN, were evaluated by machine learning. Key criteria for ARN included (1) peripheral necrotizing retinitis and either (2) polymerase chain reaction assay of an intraocular fluid specimen positive for either herpes simplex virus or varicella zoster virus or (3) a characteristic clinical appearance with circumferential or confluent retinitis, retinal vascular sheathing and/or occlusion, and more than minimal vitritis. Overall accuracy for infectious posterior uveitides / panuveitides was 92.1% in the training set and 93.3% (95% confidence interval 88.2, 96.3) in the validation set. The misclassification rates for ARN were 15% in the training set and 11.5% in the validation set.The criteria for ARN had a reasonably low misclassification rate and seemed to perform sufficiently well for use in clinical and translational research.

Purpose To determine classification criteria for Behcet disease uveitis. Design Machine learning of cases with Behcet disease and 5 other panuveitides. Methods Cases of panuveitides were collected in an informatics-designed preliminary database, and a final database was constructed of cases achieving supermajority agreement on the diagnosis, using formal consensus techniques. Cases were split into a training set and a validation set. Machine learning using multinomial logistic regression was used on the training set to determine a parsimonious set of criteria that minimized the misclassification rate among the intermediate uveitides. The resulting criteria were evaluated on the validation set. Results One thousand twelve of cases panuveitides, including 194 cases of Behcet disease with uveitis, were evaluated by machine learning. The overall accuracy for panuveitides was 96.3% in the training set and 94.0% in the validation set (95% confidence interval 89.0, 96.8). Key criteria for Behcet disease uveitis were a diagnosis of Behcet disease using the International Study Group for Behcet Disease criteria and a compatible uveitis, including: 1) anterior uveitis; 2) anterior chamber and vitreous inflammation; 3) posterior uveitis with retinal vasculitis and/or focal infiltrates; or 4) panuveitis with retinal vasculitis and/or focal infiltrates. The misclassification rates for Behcet disease uveitis were 0.6 % in the training set and 0% in the validation set, respectively. Conclusions The criteria for Behcet disease uveitis had a low misclassification rate and appeared to perform sufficiently well for use in clinical and translational research.

PURPOSE: To determine classification criteria for cytomegalovirus (CMV) retinitis. DESIGN: Machine learning of cases with CMV retinitis and 4 other infectious posterior/panuveitides. METHODS: Cases of infectious posterior/panuveitides were collected in an informatics-designed preliminary database, and a final database was constructed of cases achieving supermajority agreement on diagnosis, using formal consensus techniques. Cases were split into a training set and a validation set. Machine learning using multinomial logistic regression was used on the training set to determine a parsimonious set of criteria that minimized the misclassification rate among the infectious posterior/panuveitides. The resulting criteria were evaluated on the validation set. RESULTS: Eight hundred three cases of infectious posterior/panuveitides, including 211 cases of CMV retinitis, were evaluated by machine learning. Key criteria for CMV retinitis included: 1) necrotizing retinitis with indistinct borders due to numerous small satellites; 2) evidence of immune compromise; and either 3) a characteristic clinical appearance or 4) positive polymerase chain assay for CMV from an intraocular specimen. Characteristic appearances for CMV retinitis included: 1) wedge-shaped area of retinitis; 2) hemorrhagic retinitis; or 3) granular retinitis. Overall accuracy for infectious posterior/panuveitides was 92.1% in the training set and 93.3% (95% confidence interval 88.2, 96.3) in the validation set. The misclassification rates for CMV retinitis were 6.9% in the training set and 6.3% in the validation set. CONCLUSIONS: The criteria for CMV retinitis had a low misclassification rate and appeared to perform sufficiently well for use in clinical and translational research.

Purpose To determine classification criteria for sarcoidosis-associated uveitis DESIGN: Machine learning of cases with sarcoid uveitis and 15 other uveitides. Methods Cases of anterior, intermediate, and panuveitides were collected in an informatics-designed preliminary database, and a final database was constructed of cases achieving supermajority agreement on the diagnosis, using formal consensus techniques. Cases were analyzed by anatomic class, and each class was split into a training set and a validation set. Machine learning using multinomial logistic regression was used on the training sets to determine a parsimonious set of criteria that minimized the misclassification rate among the intermediate uveitides. The resulting criteria were evaluated on the validation sets. Results One thousand eighty-three anterior uveitides, 589 intermediate uveitides, and 1012 panuveitides, including 278 cases of sarcoidosis-associated uveitis, were evaluated by machine learning. Key criteria for sarcoidosis-associated uveitis included a compatible uveitic syndrome of any anatomic class and evidence of sarcoidosis, either 1) a tissue biopsy demonstrating non-caseating granulomata or 2) bilateral hilar adenopathy on chest imaging. The overall accuracy of the diagnosis of sarcoidosis-associated uveitis in the validation set was 99.7% (95% confidence interval 98.8, 99.9).The misclassification rates for sarcoidosis-associated uveitis in the training sets were: anterior uveitis 3.2%, intermediate uveitis 2.6%, and panuveitis 1.2%; in the validation sets the misclassification rates were: anterior uveitis 0%, intermediate uveitis 0%, and panuveitis 0%, respectively. Conclusions The criteria for sarcoidosis-associated uveitis had a low misclassification rate and appeared to perform sufficiently well for use in clinical and translational research.

Purpose To determine classification criteria for birdshot chorioretinitis. Design Machine learning of cases with birdshot chorioretinitis and 8 other posterior uveitides. Methods Cases of posterior uveitides were collected in an informatics-designed preliminary database, and a final database was constructed of cases achieving supermajority agreement on diagnosis, using formal consensus techniques. Cases were split into a training set and a validation set. Machine learning using multinomial logistic regression was used on the training set to determine a parsimonious set of criteria that minimized the misclassification rate among the infectious posterior/panuveitides. The resulting criteria were evaluated on the validation set. Results One thousand sixty-eight cases of posterior uveitides, including 207 cases of birdshot chorioretinitis, were evaluated by machine learning. Key criteria for birdshot chorioretinitis included a multifocal choroiditis with: 1) the characteristic appearance a bilateral multifocal choroiditis with cream-colored or yellow-orange, oval or round choroidal spots ("birdshot" spots); 2) absent to mild anterior chamber inflammation; and 3) absent to moderate vitreous inflammation; or multifocal choroiditis with positive HLA-A29 testing and either: 1) classic "birdshot spots" or 2) characteristic imaging on indocyanine green angiography. Overall accuracy for posterior uveitides was 93.9% in the training set and 98.0% (95% confidence interval 94.3, 99.3) in the validation set. The misclassification rates for birdshot chorioretinitis were 10% in the training set and 0% in the validation set. Conclusions The criteria for birdshot chorioretinitis had a low misclassification rate and appeared to perform sufficiently well for use in clinical and translational research.

PURPOSE: To determine classification criteria for syphilitic uveitis DESIGN: Machine learning of cases with syphilitic uveitis and 24 other uveitides. METHODS: Cases of anterior, intermediate, posterior, and panuveitides were collected in an informatics-designed preliminary database, and a final database was constructed of cases achieving supermajority agreement on the diagnosis, using formal consensus techniques. Cases were analyzed by anatomic class, and each class was split into a training set and a validation set. Machine learning using multinomial logistic regression was used on the training set to determine a parsimonious set of criteria that minimized the misclassification rate among the different uveitic classes. The resulting criteria were evaluated on the validation set. RESULTS: Two hundred twenty-two cases of syphilitic uveitis were evaluated by machine learning with cases evaluated against other uveitides in the relevant uveitic class. Key criteria for syphilitic uveitis included a compatible uveitic presentation, (1) anterior uveitis, 2) intermediate uveitis, or 3) posterior or panuveitis with retinal, retinal pigment epithelial, or retinal vascular inflammation) and evidence of syphilis infection with a positive treponemal test. The Centers for Disease Control and Prevention reverse screening algorithm for syphilis testing is recommended. The misclassification rates for syphilitic uveitis in the training sets were: anterior uveitides 0%, intermediate uveitides 6.0%, posterior uveitides 0%, panuveitides 0%, and infectious posterior/panuveitides 8.6%. The overall accuracy of the diagnosis of syphilitic uveitis in the validation set was 100% (99% CI 99.5, 100) – i.e. the validation sets misclassification rates were 0% for each uveitic class. CONCLUSIONS: The criteria for syphilitic uveitis had a low misclassification rate and appeared to perform sufficiently well for use in clinical and translational research.

Background/Aims: The recommendations on the time interval between pre-cleaning and reprocessing of endoscopes differ in international guidelines, with a low level of evidence. The aim of this study was to investigate the influence of postponing reprocessing on the reprocessing quality after pre-cleaning the flexible endoscopes.Methods: We reprocessed 124 standardized test tubes simulating endoscope channels after soiling and contamination and determined the reprocessing performance. In addition, we examined contaminated gastroscopes, colonoscopes, and bronchoscopes. The duration of interim storage after pre-cleaning was 16 h for 100 test tubes and up to 24 h for 18 endoscopes. We determined the residual protein content and germ load as markers for cleaning and disinfection performance. In addition, we determined biofilm formation by photometry of crystal violet staining.Results: All test tubes and flexible endoscopes showed residual protein content and germ load significantly below legally prescribed threshold values, independent of the interval between pre-cleaning and reprocessing.Conclusions: Our findings indicate that flexible endoscopes could be stored overnight after pre-cleaning without any influence on the quality of reprocessing. While ensuring patient safety, this could simplify logistical processes and enable cost savings.

PURPOSE: To evaluate the long-term outcomes of uveitic macular edema DESIGN: Longitudinal follow-up of a cohort of participants in a randomized clinical trial PARTICIPANTS: 248 eyes of 177 participants with uveitic macular edema enrolled in the Multicenter Uveitis Steroid Treatment Trial and Follow-up Study METHODS: Optical coherence tomography (OCT) measurements, taken at baseline and annually, were graded by reading-center graders masked to clinical data. Macular edema was defined as a center point macular thickness (CMT) ≥240 μm on time-domain OCT or time-domain OCT equivalent. Resolution of macular edema was defined as normalization of macular thickness on OCT. Relapse of macular edema was defined as increase in macular thickness to ≥240 μm in an eye that previously had resolution. Visual acuity was measured at each visit with logarithmic visual acuity charts. MAIN OUTCOME MEASURES: Resolution and relapse of macular edema. Visual acuity. RESULTS: Among 227 eyes with macular edema followed ≥1 year, the cumulative percent of eyes with macular edema resolving at any point during 7 years was 94% (95% confidence interval [CI]: 89%, 97%). Epiretinal membranes on OCT were associated with a lower likelihood of macular edema resolution (hazard ratio [HR] 0.74; 95% CI 0.55, 1.01; P=0.05). Among 177 eyes with resolved macular edema, the cumulative percent with relapse within 7 years was 43% (95% CI: 32%, 51%). Eyes in which macular edema resolved gained a mean of 6.24 letters (95% CI: 4.40, 8.09, P< 0.001) compared to eyes that remained free from macular edema during the 1-year follow-up intervals, whereas eyes where macular edema did not resolve experienced no gain in vision (mean change −1.30 letters; 95% CI: −2.70, 0.09, P=0.065), and eyes that developed macular edema during the year (either incident or relapsed) experienced a mean loss of −8.65 letters (95% CI: −11.5, −5.84, P< 0.001). CONCLUSIONS: Given sufficient time and treatment, nearly all uveitic macular edema resolves, but episodes of relapse were common. Visual acuity results were better among eyes with resolved macular edema, suggesting that control of inflammation and resolution of macular edema might be visually-relevant treatment targets.

We evaluated the associations of clinical and demographic characteristics with visual acuity (VA) with over 5 years in a subspecialty noninfectious uveitis population.Retrospective data from 5,530 ...

Topic An international, expert-led consensus initiative organized by the Collaborative Ocular Tuberculosis Study (COTS), along with the International Ocular Inflammation Society and the International Uveitis Study Group, systematically developed evidence- and experience-based recommendations for the treatment of tubercular choroiditis. Clinical relevance The diagnosis and management of tubercular uveitis (TBU) pose a significant challenge. Current guidelines and literature are insufficient to guide physicians regarding the initiation of antitubercular therapy (ATT) in patients with TBU. Methods An international expert steering subcommittee of the COTS group identified clinical questions and conducted a systematic review of the published literature on the use of ATT for tubercular choroiditis. Using an interactive online questionnaire, guided by background knowledge from published literature, 81 global experts (including ophthalmologists, pulmonologists, and infectious disease physicians) generated preliminary consensus statements for initiating ATT in tubercular choroiditis, using Oxford levels of medical evidence. In total, 162 statements were identified regarding when to initiate ATT in patients with tubercular serpiginous-like choroiditis, tuberculoma, and tubercular focal or multifocal choroiditis. The COTS group members met in November 2018 to refine these statements by a 2-step modified Delphi process. Results Seventy consensus statements addressed the initiation of ATT in the 3 subtypes of tubercular choroiditis, and in addition, 10 consensus statements were developed regarding the use of adjunctive therapy in tubercular choroiditis. Experts agreed on initiating ATT in tubercular choroiditis in the presence of positive results for any 1 of the positive immunologic tests along with radiologic features suggestive of tuberculosis. For tubercular serpiginous-like choroiditis and tuberculoma, positive results from even 1 positive immunologic test were considered sufficient to recommend ATT, even if there were no radiologic features suggestive of tuberculosis. Discussion Consensus guidelines were developed to guide the initiation of ATT in patients with tubercular choroiditis, based on the published literature, expert opinion, and practical experience, to bridge the gap between clinical need and available medical evidence.

PURPOSE: To evaluate long-term risk and outcomes of glaucoma in eyes with intermediate, posterior, and panuveitis managed with systemic or fluocinolone acetonide (0.59 mg, “implant”) therapy. DESIGN: Prospective Follow-up of the Multicenter Uveitis Steroid Treatment (MUST) Clinical Trial Cohort METHODS: Patients with intermediate, posterior or panuveitis randomized to implant or systemic therapy (corticosteroid plus immunosuppression in >90%) were followed prospectively for glaucoma incidence and outcome. RESULTS: Among 405 uveitic at-risk eyes of 232 patients (median follow-up=6.9 years), 40% (79/196) of eyes assigned and treated with implant and 8% (17/209) of eyes assigned and treated with systemic therapy (censoring eyes receiving an implant upon implantation) developed glaucoma (Hazard Ratio (HR)=5.9 (95% CI: 3.2, 10.8); p

Objective Patients who experience spontaneous abortion often present to the emergency department (ED), which may restrict the physician's recommendations for and the patient's choice of therapy. With support provided by an early pregnancy assessment clinic (EPAC), expectant and medical management may become more feasible options for spontaneous abortion. This study aimed to compare the therapeutic choices before and after the establishment of an EPAC and hypothesized that the proportion of miscarriages treated expectantly or medically would increase. Methods We conducted a retrospective cohort study that compared patients presenting to the ED and the EPAC with spontaneous abortion. We excluded patients with hemodynamic instability, complete abortions, ectopic pregnancies, and molar pregnancies. The primary outcome was the initial chosen treatment. The retrospective chart review included demographics, type of spontaneous abortion and management, procedural dictations, ED notes, and EPAC clinic documentation. Secondary end points included wait times, repeat visits, and success rates for the initial treatment option. Results We reviewed 103 ED and 92 EPAC patient records. Patients in the ED were 1.52 times more likely to choose surgery over expectant or medical management (P = 0.004). Patients in the ED were 1.41 times more likely to have surgery as their final treatment compared with patients in the EPAC (P = 0.006). There were no significant differences in length of stay, number of visits required, or adverse outcomes. Conclusion Our study demonstrates that an EPAC results in more patients choosing and successfully being treated by expectant or medical management for spontaneous abortion.

Anamie kommt bei alteren Menschen haufig vor; unter stationar-geriatrischen Patienten ist meist jeder Zweite betroffen. Bei elektiven chirurgischen Eingriffen wie endoprothetischen Versorgungen alterer Menschen ist daher die Chance gros, dass bereits praoperativ eine Anamie vorliegt. Leider gibt es bisher keine generellen Empfehlungen zum perioperativen Management der Anamie beim alteren Menschen. Die existierenden Empfehlungen der Patient Blood Management (PBM) network cooperation beziehen sich ebenso wie die aktuelle AWMF-S3-Leitlinie „Praoperative Anamie“ auf alle Altersgruppen >18 Jahre, die wachsende Gruppe der hochaltrigen alterstraumatologischen Patienten wird jedoch nicht gesondert berucksichtigt. Das ist umso problematischer, als dass die Anamie im Alter Besonderheiten aufweist, die sie in Diagnostik und Therapie von der Anamie bei jungeren Menschen unterscheidet. Das diesjahrige Symposium der AG Anamie der Deutschen Gesellschaft fur Geriatrie (DGG) greift in mehreren interdisziplinaren Beitragen die aktuelle Problematik des optimalen PBM beim alteren Patienten auf und regt die Diskussion zur Entwicklung von Handlungsempfehlungen an.

PURPOSE: To estimate the incidence of corneal endothelial transplantation and identify risk factors among patients with non-infectious ocular inflammation. DESIGN: Retrospective cohort study. METHODS: Adult patients attending United States tertiary uveitis care facilities diagnosed with non-infectious ocular inflammation were identified from the Systemic Immunosuppressive Therapy for Eye Diseases Cohort Study. Time-to-event analysis was used to estimate the incidence of corneal endothelial transplantation (CET), including penetrating keratoplasty, Descemet stripping endothelial keratoplasty, or Descemet Membrane Endothelial Keratoplasty procedures. The incidence of CET was calculated; potential risk factors for CET were also evaluated using Cox regression, accounting for correlation between eyes of the same patient. RESULTS: Overall, 14,264 eyes met eligibility criteria for this analysis with a median follow-up 1.8 eye-years. The Kaplan-Meier estimated incidence of CET within 10 years was 1.10% (95% CI, 0.68%–1.53%). Risk factors for CET included age >60 years vs.

The number of people with HIV (PWH) aged 50 years or older continues to steadily increase. The convergence of age- and HIV-related complications in these individuals presents a challenge for both patients and clinicians alike. New findings continue to emerge, as numerous researchers evaluate the combined impact of these two factors on quality of life, physiological systems, and mental health in PWH. Since its first occurrence in 2009, the International Workshop on HIV and Aging has served as a multidisciplinary meeting to share basic biomedical data, clinical trial results, treatment strategies, and epidemiological recommendations, toward better understanding and outcomes among like-minded scientific professionals. In this article, we share a selection of key findings presented in plenary talks at the 11th Annual International Workshop on HIV and Aging, held virtually from September 30, 2020 to October 2, 2020. We will also address the future directions of HIV and aging research, to further assess how the aging process intersects with chronic HIV.

We explored rates of premature births and neonatal intensive care unit (NICU) admissions at the Mount Sinai Hospital after the implementation of COVID-19 lockdown measures (March 16, 2020) and phase one reopening (June 8, 2020), comparing them to those of the same time periods from 2012-2019. Mount Sinai Hospital is in New York City (NYC), an early epicenter of COVID-19 in the United States, which was heavily impacted by the pandemic during the study period. Among 43,963 singleton births, we observed no difference in either outcome after the implementation of lockdown measures when compared to the same trends in prior years (p=0.09-0.35). Of interest, we observed a statistically significant decrease in premature births after NYC phase one reopening compared to those of the same time period in 2012-2019 across all time windows (p=0.0028-0.049), and a statistically significant decrease in NICU admissions over the largest time window (2.75 months) compared to prior years (p=0.0011).

Pancreatic ductal adenocarcinoma (PDAC) is characterized by high drug resistance and poor prognosis. Novel therapeutic and stratification strategies are urgently needed. Here, we present an integration of in-depth genomic and transcriptomic characterization with drug screening and clinical outcome based on a catalogue of 51 patient-derived tumor organoids (PDOs) from resected PDAC. Known PDAC molecular subtypes and their prognostic value are conserved in organoids. Integration of transcriptomic and drug response profiles suggest a metabolism-mediated modulations of drug resistance. Copy number alterations on chromosome 13q and wild-type status of TP53 emerged as potential novel genomic biomarkers for sensitivity to 5-FU and oxaliplatin treatment, respectively. Functional testing of targeted drugs in PDOs revealed its additional value for genome-driven personalized oncology. Co-deletion of TP53/POLR2A increased vulnerability to RNA polymerase II inhibition, pointing to a promising target for personalized treatment in PDAC.SignificancePatient-derived PDAC organoids hold great promise as surrogate tumor models for personalized oncology. By integrating highly granular molecular, drug sensitivity and clinical data, we demonstrate that PDOs are valid models for molecular characterization and response prediction that also enable identification of novel drug sensitivity biomarkers and resistance mechanisms in PDAC.

Purpose To compare mycophenolate mofetil (MMF) to methotrexate (MTX) as corticosteroid-sparing therapy for ocular inflammatory diseases. Design Retrospective analysis of cohort study data. Methods Participants were identified from the Systemic Immunosuppressive Therapy for Eye Diseases Cohort Study. Demographic and clinical characteristics were obtained via medical record review. The study included 352 patients who were taking single-agent immunosuppression with MTX or MMF at 4 tertiary uveitis clinics. Marginal structural models (MSM)-derived statistical weighting created a virtual population with covariates and censoring patterns balanced across alternative treatments. With this methodological approach, the results estimate what would have happened had none of the patients stopped their treatment. Survival analysis with stabilized MSM-derived weights simulated a clinical trial comparing MMF vs MTX for noninfectious inflammatory eye disorders. The primary outcome was complete control of inflammation on prednisone ≤10 mg/day, sustained for ≥30 days. Results The time to success was shorter (more favorable) for MMF than MTX (hazard ratio = 0.68, 95% confidence interval: 0.46-0.99). Adjusting for covariates, the proportion achieving success was higher at every point in time for MMF than MTX from 2 to 8 months, then converges at 9 months. The onset of corticosteroid-sparing success took more than 3 months for most patients in both groups. Outcomes of treatment (MMF vs MTX) were similar across all anatomic sites of inflammation. The incidence of stopping therapy for toxicity was similar in both groups. Conclusions Our results suggest that, on average, MMF may be faster than MTX in achieving corticosteroid-sparing success in ocular inflammatory diseases.

Das diesjahrige Symposium der AG Anamie der Deutschen Gesellschaft fur Geriatrie (DGG) hatte das Ziel, die Multikausalitat der Anamie im hoheren Lebensalter zu verdeutlichen und Parallelen mit der Definition geriatrischer Syndrome herauszuarbeiten. Dafur wurden sowohl nutritive als auch maligne Anamieursachen diskutiert als auch Hypothesen zur Einflussnahme von oxidativem Stress auf die Anamieentwicklung hervorgehoben. Der Bedarf an weiterfuhrender Forschung konnte am Beispiel perioperativer Therapiestrategien bei alteren Menschen verdeutlicht werden.

Purpose To evaluate the comparative effectiveness of 3 regional corticosteroid injections for uveitic macular edema (ME): periocular triamcinolone acetonide (PTA), intravitreal triamcinolone acetonide (ITA), and the intravitreal dexamethasone implant (IDI). Design Multicenter, randomized clinical trial. Participants Patients with uveitic ME. Methods Patients were randomized 1:1:1 to receive 1 of the 3 therapies. Patients with bilateral ME were assigned the same treatment for both eyes. Main Outcome Measures The primary outcome was the proportion of baseline (PropBL) central subfield thickness (CST) at 8 weeks (CST at 8 weeks/CST at baseline) assessed with OCT by masked readers. Secondary outcomes included ≥20% improvement and resolution of ME, best-corrected visual acuity (BCVA), and intraocular pressure (IOP) events over 24 weeks. Results All treatment groups demonstrated improved CST during follow-up. At 8 weeks, each group had clinically meaningful reductions in CST relative to baseline (PropBL: 0.77, 0.61, and 0.54, respectively, which translates to reductions of 23%, 39%, and 46% for PTA, ITA, and IDI, respectively). Intravitreal triamcinolone acetonide (PropBL ITA/PropBL PTA, hazard ratio [HR], 0.79; 99.87% confidence interval [CI], 0.65–0.96) and IDI (PropBL IDI/PropBL PTA, HR, 0.69; 99.87% CI, 0.56–0.86) had larger reductions in CST than PTA (P Conclusions Intravitreal triamcinolone acetonide and the IDI were superior to PTA for treating uveitic ME with modest increases in the risk of IOP elevation. This risk did not differ significantly between intravitreal treatments.

Silicon-hydrogen bonds play a crucial role in modern microelectronics, especially regarding reliability. At the semiconductor-oxide interface these bonds are broken via interaction with energetic charge carriers, which spoils a MOSFET's performance, for example. This study develops a consistent physical picture of that phenomenon through a bottom-up approach based on quantum mechanical formulations, and also unravels the disparity of that effect in $n\ensuremath{-}$ and $p\ensuremath{-}$MOSFETs. The model is free of empirical parameters and can easily be extended to emerging material combinations.

Devices used in healthcare applications frequently require powering. With the rapid development of implantable devices for disease treatment, as well as smart digital devices dedicated for healthcare operations, wireless charging of these systems is critical. The majority of wireless powering currently uses electromagnetic fields. This work describes the in vivo demonstration of Ultrasound Power Delivery (UPD) for charging Li-ion batteries, adequate for a gastro-esophageal junction (GEJ) neurostimulator device, while fulfilling the charging module’s space budget of 1.2 cc. Using the same 1 – 3 MHz UPD approach, this work describes the feasibility of charging batteries for smart devices intended for dedicated applications in a healthcare environment, with similar specifications as the wireless Qi-standard version 1.0.

Purpose To determine classification criteria for tubulointerstitial nephritis with uveitis (TINU) DESIGN: Machine learning of cases with TINU and 8 other anterior uveitides. Methods Cases of anterior uveitides were collected in an informatics-designed preliminary database, and a final database was constructed of cases achieving supermajority agreement on the diagnosis, using formal consensus techniques. Cases were split into a training set and a validation set. Machine learning using multinomial logistic regression was used on the training set to determine a parsimonious set of criteria that minimized the misclassification rate among the anterior uveitides. The resulting criteria were evaluated on the validation set. Results One thousand eighty-three cases of anterior uveitides, including 94 cases of TINU, were evaluated by machine learning. The overall accuracy for anterior uveitides was 97.5% in the training set and 96.7% in the validation set (95% confidence interval 92.4, 98.6). Key criteria for TINU included anterior chamber inflammation and evidence of tubulointerstitial nephritis with either 1) a positive renal biopsy or 2) evidence of nephritis (elevated serum creatinine and/or abnormal urine analysis) and an elevated urine β-2 microglobulin. The misclassification rates for TINU were 1.2% in the training set and 0% in the validation set, respectively. Conclusions The criteria for TINU had a low misclassification rate and appeared to perform well enough for use in clinical and translational research.

Objective Minimal evidence exists on the continuation of contraception following termination of pregnancy. Continuation of effective contraception is important because it has been found to reduce unintended pregnancies. This study aims to determine the rate of continuation and choice of contraception following termination of pregnancy. Methods A cross-sectional analytic study was undertaken of 400 patients undergoing termination of pregnancy over 2 years. Demographic information and contraception choice prior to, at time of, and 6 months following termination were collected. Data were analyzed to assess relationships between patient characteristics and contraceptive choice. Results Prior to termination, 58.5% of patients were not using contraception and 22.4% used a less effective method (e.g., barrier or fertility awareness). Following termination, 99.7% of patients chose a method of contraception, and 95.2% chose a more effective method (e.g., long acting reversible contraception, permanent sterilization, combined hormonal contraceptives, progesterone-only contraceptive). Six months following termination, 85.8% of patients were using contraception. A more effective method was continued by 37.8%. There were no significant relationships between choice of contraception and age, previous pregnancies, or social determinants of health. Patients living with their sexual partner were significantly more likely to switch to a less effective method of contraception at 6 months. Conclusions Following termination of pregnancy, almost all patients chose a method of contraception and most continued using contraception 6 months following termination.

PURPOSE: To determine classification criteria for serpiginous choroiditis. DESIGN: Machine learning of cases with serpiginous choroiditis and 8 other posterior uveitides. METHODS: Cases of posterior uveitides were collected in an informatics-designed preliminary database, and a final database was constructed of cases achieving supermajority agreement on diagnosis, using formal consensus techniques. Cases were split into a training set and a validation set. Machine learning using multinomial logistic regression was used on the training set to determine a parsimonious set of criteria that minimized the misclassification rate among the infectious posterior uveitides / panuveitides. The resulting criteria were evaluated on the validation set. RESULTS: One thousand sixty-eight cases of posterior uveitides, including 122 cases of serpiginous choroiditis, were evaluated by machine learning. Key criteria for serpiginous choroiditis included (1) choroiditis with an ameboid or serpentine shape; (2) characteristic imaging on fluorescein angiography or fundus autofluorescence; (3) absent to mild anterior chamber and vitreous inflammation; and (4) the exclusion of tuberculosis. Overall accuracy for posterior uveitides was 93.9% in the training set and 98.0% (95% confidence interval 94.3, 99.3) in the validation set. The misclassification rates for serpiginous choroiditis were 0% in both the training set and the validation set. CONCLUSIONS: The criteria for serpiginous choroiditis had a low misclassification rate and seemed to perform sufficiently well for use in clinical and translational research.

PURPOSE: To determine classification criteria for cytomegalovirus (CMV) anterior uveitis DESIGN: Machine learning of cases with CMV anterior uveitis and 8 other anterior uveitides. METHODS: Cases of anterior uveitides were collected in an informatics-designed preliminary database, and a final datafubase was constructed of cases achieving supermajority agreement on the diagnosis, using formal consensus techniques. Cases were split into a training set and a validation set. Machine learning using multinomial logistic regression was used on the training set to determine a parsimonious set of criteria that minimized the misclassification rate among the anterior uveitides. The resulting criteria were evaluated on the validation set. RESULTS: One thousand eighty-three of cases of anterior uveitides, including 89 cases of CMV anterior uveitis, were evaluated by machine learning. The overall accuracy for anterior uveitides was 97.5% in the training set and 96.7% in the validation set (95% confidence interval 92.4, 98.6). Key criteria for CMV anterior uveitis included unilateral anterior uveitis with a positive aqueous humor polymerase chain reaction assay for CMV. No clinical features reliably diagnosed CMV anterior uveitis. The misclassification rates for CMV anterior uveitis were 1.3 % in the training set and 0% in the validation set, respectively. CONCLUSIONS: The criteria for CMV anterior uveitis had a low misclassification rate and appeared to perform sufficiently well for use in clinical and translational research.

PURPOSE: To determine classification criteria for herpes simplex virus (HSV) anterior uveitis DESIGN: Machine learning of cases with HSV anterior uveitis and 8 other anterior uveitides. METHODS: Cases of anterior uveitides were collected in an informatics-designed preliminary database, and a final database was constructed of cases achieving supermajority agreement on the diagnosis, using formal consensus techniques. Cases were split into a training set and a validation set. Machine learning using multinomial logistic regression was used on the training set to determine a parsimonious set of criteria that minimized the misclassification rate among the anterior uveitides. The resulting criteria were evaluated on the validation set. RESULTS: One thousand eighty-three of cases of anterior uveitides, including 101 cases of HSV anterior uveitis, were evaluated by machine learning. The overall accuracy for anterior uveitides was 97.5% in the training set and 96.7% in the validation set (95% confidence interval 92.4, 98.6). Key criteria for HSV anterior uveitis included unilateral anterior uveitis with either 1) positive aqueous humor polymerase chain reaction assay for HSV; 2) sectoral iris atrophy in a patient ≤50 years of age; or 3) HSV keratitis. The misclassification rates for HSV anterior uveitis were 8.3% in the training set and 17% in the validation set, respectively. CONCLUSIONS: The criteria for HSV anterior uveitis had a reasonably low misclassification rate and appeared to perform well enough for use in clinical and translational research.

Purpose To determine classification criteria for acute posterior multifocal placoid pigment epitheliopathy (APMPPE). Design Machine learning of cases with APMPPE and 8 other posterior uveitides. Methods Cases of posterior uveitides were collected in an informatics-designed preliminary database, and a final database was constructed of cases achieving supermajority agreement on diagnosis, using formal consensus techniques. Cases were split into a training set and a validation set. Machine learning using multinomial logistic regression was used on the training set to determine a parsimonious set of criteria that minimized the misclassification rate among the infectious posterior/panuveitides. The resulting criteria were evaluated on the validation set. Results One thousand sixty-eight cases of posterior uveitides, including 82 cases of APMPPE, were evaluated by machine learning. Key criteria for APMPPE included: 1) choroidal lesions with a plaque-like or placoid appearance and 2) characteristic imaging on fluorescein angiography (lesions "block early and stain late diffusely"). Overall accuracy for posterior uveitides was 92.7% in the training set and 98.0% (95% confidence interval 94.3, 99.3) in the validation set. The misclassification rates for APMPPE were 5% in the training set and 0% in the validation set. Conclusions The criteria for APMPPE had a low misclassification rate and appeared to perform sufficiently well for use in clinical and translational research.

OBJECTIVES The aim of the study was to evaluate risk factors for mortality, including health care insurance status, among patients with AIDS in the era of modern combination antiretroviral therapy (cART). METHODS This study was part of the prospective, multicentre, observational Longitudinal Study of the Ocular Complications of AIDS (LSOCA). Patients were classified as having private health care insurance, Medicare, Medicaid, or no insurance. Hazard ratios (HRs) for death were calculated using proportional hazards regression models and staggered entries, anchored to the AIDS diagnosis date. RESULTS Among 2363 participants with AIDS, 97% were treated with cART. At enrolment, 31% of participants had private insurance, 29% had Medicare, 24% had Medicaid, and 16% were uninsured. Noninfectious, age-related diseases, such as hypertension, diabetes, and renal disease, were more frequent among persons with Medicare than among those with private insurance. Compared with those who were privately insured, mortality was greater among participants with Medicare [adjusted HR (HRadj ) 1.35; 95% confidence interval (CI) 1.08-1.67; P = 0.008]. Among participants with a suppressed HIV viral load, compared with those who were privately insured, HRadj values for mortality were 1.93 (95% CI 1.08-3.44; P = 0.02) for those with Medicare and 2.09 (95% CI 1.02-4.27; P = 0.04) for those with Medicaid. Mortality among initially uninsured participants was not significantly different from that for privately insured participants, but these participants typically obtained ART and insurance during follow-up. Compared with privately insured participants, time-updated HRadj values for mortality were 1.34 (95% CI 1.05-1.70; P = 0.02) for those with Medicare, 1.34 (95% CI 1.01-1.80; P = 0.05) for those with Medicaid, and 1.35 (95% CI 0.97-1.88; P = 0.05) for those who were uninsured. CONCLUSIONS In persons with AIDS, compared with those with private insurance, those with public insurance had increased mortality, possibly as a result of a greater burden of noninfectious, age-related diseases.

Introduction Congenital facial weakness (CFW) can result from facial nerve paresis with or without other cranial nerve and systemic involvement, or generalized neuropathic and myopathic disorders. Moebius syndrome is one type of CFW. In this study we explored the utility of electrodiagnostic studies (EDx) in the evaluation of individuals with CFW. Methods Forty-three subjects enrolled prospectively into a dedicated clinical protocol and had EDx evaluations, including blink reflex and facial and peripheral nerve conduction studies, with optional needle electromyography. Results MBS and hereditary congenital facial paresis (HCFP) subjects had low-amplitude cranial nerve 7 responses without other neuropathic or myopathic findings. Carriers of specific pathogenic variants in TUBB3 had, in addition, a generalized sensorimotor axonal polyneuropathy with demyelinating features. Myopathic findings were detected in individuals with Carey-Fineman-Ziter syndrome, myotonic dystrophy, other undefined myopathies, or CFW with arthrogryposis, ophthalmoplegia, and other system involvement. Discussion EDx in CFW subjects can assist in characterizing the underlying pathogenesis, as well as guide diagnosis and genetic counseling.

PURPOSE: To determine the incidence of and predictive factors for cataract in intermediate uveitis. DESIGN: Retrospective cohort study METHODS: Patients were identified from the Systemic Immunosuppressive Therapy for Eye Diseases (SITE) Cohort Study, in which medical records were reviewed to determine demographic and clinical data of every eye/patient at every visit at five participating United States tertiary care uveitis centers. The primary outcome was development of vision-compromising cataract as defined by a decrease in visual acuity to 20/40 or less, or requiring cataract surgery. Survival analysis assessed visually defined cataract to avoid bias due to timing of surgery vis-à-vis inflammatory status. RESULTS: Among 2,190 eyes of 1,302 patients with intermediate uveitis the cumulative incidence of cataract formation was 7.6% by one year (95% CI=6.2–9.1%), increasing to 36.6% by ten years (95% CI=31.2–41.6%). Increased cataract risk was observed in eyes with concurrent anterior uveitis causing posterior synechiae (HR=2.68, 95% CI=2.00–3.59, p

Breast-conserving surgery, also known as lumpectomy, is an early stage breast cancer treatment that aims to spare as much healthy breast tissue as possible. A risk associated with lumpectomy is the presence of cancer positive margins post operation. Surgical navigation has been shown to reduce cancer positive margins but requires manual segmentation of the tumor intraoperatively. In this paper, we propose an end-to-end solution for automatic contouring of breast tumor from intraoperative ultrasound images using two convolutional neural network architectures, the U-Net and residual U-Net. The networks are trained on annotated intraoperative breast ultrasound images and evaluated on the quality of predicted segmentations. This work brings us one step closer to providing surgeons with an automated surgical navigation system that helps reduce cancer-positive margins during lumpectomy.

The FaceBase Consortium was established by the National Institute of Dental and Craniofacial Research in 2009 as a ‘big data’ resource for the craniofacial research community. Over the past decade, researchers have deposited hundreds of annotated and curated datasets on both normal and disordered craniofacial development in FaceBase, all freely available to the research community on the FaceBase Hub website. The Hub has developed numerous visualization and analysis tools designed to promote integration of multidisciplinary data while remaining dedicated to the FAIR principles of data management (findability, accessibility, interoperability and reusability) and providing a faceted search infrastructure for locating desired data efficiently. Summaries of the datasets generated by the FaceBase projects from 2014 to 2019 are provided here. FaceBase 3 now welcomes contributions of data on craniofacial and dental development in humans, model organisms and cell lines. Collectively, the FaceBase Consortium, along with other NIH-supported data resources, provide a continuously growing, dynamic and current resource for the scientific community while improving data reproducibility and fulfilling data sharing requirements.

There is a broad differential for patients presenting with congenital facial weakness, and initial misdiagnosis unfortunately is common for this phenotypic presentation. Here we present a framework to guide evaluation of patients with congenital facial weakness disorders to enable accurate diagnosis. The core categories of causes of congenital facial weakness include: neurogenic, neuromuscular junction, myopathic, and other. This diagnostic algorithm is presented, and physical exam considerations, additional follow-up studies and/or consultations, and appropriate genetic testing are discussed in detail. This framework should enable clinical geneticists, neurologists, and other rare disease specialists to feel prepared when encountering this patient population and guide diagnosis, genetic counseling, and clinical care. Supplementary Information The online version contains supplementary material available at 10.1186/s13023-021-01736-1.

Acquired thrombotic thrombocytopenic purpura (aTTP) is a rare but life-threatening condition. In 2018, the nanobody caplacizumab was approved for the treatment of adults experiencing an acute episode of aTTP, in conjunction with plasma exchange (PEX) and immunosuppression for a minimum of 30 days after stopping daily PEX. We performed a retrospective, observational analysis on the use of caplacizumab in 60 patients from 29 medical centers in Germany during acute disease management. Caplacizumab led to a rapid normalization of the platelet count (median, 3 days; mean 3.78 days). One patient died after late treatment initiation due to aTTP-associated complications. In 2 patients with initial disease presentation and in 4 additional patients with laboratory signs of an exacerbation or relapse after the initial therapy, PEX-free treatment regimens could be established with overall favorable outcome. Caplacizumab is efficacious in the treatment of aTTP independent of timing and ancillary treatment modalities. Based on this real-world experience and published literature, we propose to administer caplacizumab immediately to all patients with an acute episode of aTTP. Treatment decisions regarding the use of PEX should be based on the severity of the clinical presentation and known risk factors. PEX might be dispensable in some patients.

Introduction of the nanobody caplacizumab was shown to be effective in the treatment of acquired thrombotic thrombocytopenic purpura (aTTP) in the acute setting. The official recommendations include plasma exchange (PEX), immunosuppression, and the use of caplacizumab for a minimum of 30 days after stopping daily PEX. This study was a retrospective, observational analysis of the use of caplacizumab in 60 patients from 29 medical centers in Germany. Immunosuppressive treatment led to a rapid normalization of ADAMTS13 activities (calculated median, 21 days). In 35 of 60 patients, ADAMTS13 activities started to normalize before day 30 after PEX; in 11 of 60 patients, the treatment was extended beyond day 30; and in 5 patients, it was extended even beyond day 58 due to persistent autoimmune activity. In 34 of 60 instances, caplacizumab was stopped before day 30 with a favorable outcome whenever ADAMTS13 activities were >10%. In contrast, 11 of 34 patients with ADAMTS13 activities

Purpose To determine classification criteria for spondyloarthritis/HLA-B27-associated anterior uveitis DESIGN: Machine learning of cases with spondyloarthritis/HLA-B27-associated anterior uveitis and 8 other anterior uveitides. Methods Cases of anterior uveitides were collected in an informatics-designed preliminary database, and a final database was constructed of cases achieving supermajority agreement on the diagnosis, using formal consensus techniques. Cases were split into a training set and a validation set. Machine learning using multinomial logistic regression was used on the training set to determine a parsimonious set of criteria that minimized the misclassification rate among the anterior uveitides. The resulting criteria were evaluated on the validation set. Results One thousand eighty-three cases of anterior uveitides, including 184 cases of spondyloarthritis/HLA-B27-associated anterior uveitis, were evaluated by machine learning. The overall accuracy for anterior uveitides was 97.5% in the training set (95% confidence interval [CI] 96.3, 98.4) and 96.7% in the validation set (95% CI 92.4, 98.6). Key criteria for spondyloarthritis/HLA-B27-associated anterior uveitis included 1) acute or recurrent acute unilateral or unilateral alternating anterior uveitis with either spondyloarthritis or a positive test for HLA-B27 or 2) chronic anterior uveitis with a history of the classic course and either spondyloarthritis or HLA-B27 or 3) anterior uveitis with both spondyloarthritis and HLA-B27. The misclassification rates for spondyloarthritis/HLA-B27-associated anterior uveitis were 0% in the training set and 3.6% in the validation set, respectively. Conclusions The criteria for spondyloarthritis/HLA-B27-associated anterior uveitis had a low misclassification rate and appeared to perform well enough for use in clinical and translational research.

PURPOSE: To determine classification criteria for sympathetic ophthalmia DESIGN: Machine learning of cases with sympathetic ophthalmia and 5 other panuveitides. METHODS: Cases of panuveitides were collected in an informatics-designed preliminary database, and a final database was constructed of cases achieving supermajority agreement on the diagnosis, using formal consensus techniques. Cases were split into a training set and a validation set. Machine learning using multinomial logistic regression was used on the training set to determine a parsimonious set of criteria that minimized the misclassification rate among the panuveitides. The resulting criteria were evaluated on the validation set. RESULTS: One thousand twelve cases of panuveitides, including 110 cases of sympathetic ophthalmia, were evaluated by machine learning. The overall accuracy for panuveitides was 96.3% in the training set and 94.0% in the validation set (95% confidence interval 89.0, 96.8). Key criteria for sympathetic ophthalmia included bilateral uveitis with 1) a history of unilateral ocular trauma or surgery and 2) an anterior chamber and vitreous inflammation or a panuveitis with choroidal involvement. The misclassification rates for sympathetic ophthalmia were 4.2 % in the training set and 6.7% in the validation set, respectively. CONCLUSIONS: The criteria for sympathetic ophthalmia had a low misclassification rate and appeared to perform sufficiently well for use in clinical and translational research. PRECIS: Using a formalized approach to developing classification criteria, including informatics-based case collection, consensus-technique-based case selection, and machine learning, classification criteria for sympathetic ophthalmia were developed. Key criteria included bilateral uveitis with a history of unilateral ocular trauma or surgery and either anterior chamber and vitreous inflammation or panuveitis with choroidal involvement. The resulting criteria had a low misclassification rate.

Purpose : To determine classification criteria for intermediate uveitis, non-pars planitis type (IU- NPP, also known as undifferentiated intermediate uveitis) Design : Machine learning of cases with IU-NPP and 4 other intermediate uveitides. Methods : Cases of intermediate uveitides were collected in an informatics-designed preliminary database, and a final database was constructed of cases achieving supermajority agreement on the diagnosis, using formal consensus techniques. Cases were split into a training set and a validation set. Machine learning using multinomial logistic regression was used on the training set to determine a parsimonious set of criteria that minimized the misclassification rate among the intermediate uveitides. The resulting criteria were evaluated on the validation set. Results : Five hundred eighty-nine of cases of intermediate uveitides, including 114 cases of IU-NPP, were evaluated by machine learning. The overall accuracy for intermediate uveitides was 99.8% in the training set and 99.3% in the validation set (95% confidence interval 96.1, 99.9). Key criteria for IU-NPP included unilateral or bilateral intermediate uveitis with neither 1) snowballs in the vitreous nor 2) snowbanks on the pars plana. Other key exclusions included: 1) multiple sclerosis, 2) sarcoidosis, and 3) syphilis. The misclassification rates for pars planitis were 0 % in the training set and 0% in the validation set, respectively. Conclusions : The criteria for IU-NPP had a low misclassification rate and appeared to perform well enough for use in clinical and translational research.

PURPOSE: To determine classification criteria for multiple evanescent white dot syndrome (MEWDS).DESIGN: Machine learning of cases with MEWDS and 8 other posterior uveitides.METHODS: Cases of posterior uveitides were collected in an informatics-designed preliminary database, and a final database was constructed of cases achieving supermajority agreement on diagnosis, using formal consensus techniques. Cases were split into a training set and a validation set. Machine learning using multinomial logistic regression was used on the training set to determine a parsimonious set of criteria that minimized the misclassification rate among the infectious posterior/panuveitides. The resulting criteria were evaluated on the validation set.RESULTS: One thousand sixty-eight cases of posterior uveitides, including 51 cases of MEWDS, were evaluated by machine learning. Key criteria for MEWDS included: 1) multifocal gray white chorioretinal spots with foveal granularity; 2) characteristic imaging on fluorescein angiography ("wreath-like" hyperfluorescent lesions) and/or optical coherence tomography (hyper-reflective lesions extending from retinal pigment epithelium through ellipsoid zone into the retinal outer nuclear layer); and 3) absent to mild anterior chamber and vitreous inflammation. Overall accuracy for posterior uveitides was 93.9% in the training set and 98.0% (95% confidence interval 94.3, 99.3) in the validation set. The misclassification rates for MEWDS were 7% in the training set and 0% in the validation set.CONCLUSIONS: The criteria for MEWDS had a low misclassification rate and appeared to perform sufficiently well for use in clinical and translational research.

Purpose To develop an agreed upon set of outcomes known as a “core outcome set” (COS) for noninfectious uveitis of the posterior segment (NIU-PS) clinical trials. Design Mixed-methods study design comprising a systematic review and qualitative study followed by a 2-round Delphi exercise and face-to-face consensus meeting. Participants Key stakeholders including patients diagnosed with NIU-PS, their caregivers, and healthcare professionals involved in decision-making for patients with NIU-PS, including ophthalmologists, nurse practitioners, and policymakers/commissioners. Methods A long list of outcomes was developed based on the results of (1) a systematic review of clinical trials of NIU-PS and (2) a qualitative study of key stakeholders including focus groups and interviews. The long list was used to generate a 2-round Delphi exercise of stakeholders rating the importance of outcomes on a 9-point Likert scale. The proportion of respondents rating each item was calculated, leading to recommendations of “include,” “exclude,” or “for discussion” that were taken to a face-to-face consensus meeting of key stakeholders at which they agreed on the final COS. Main Outcome Measure Items recommended for inclusion in the COS for NIU-PS. Results A total of 57 outcomes grouped in 11 outcome domains were presented for evaluation in the Delphi exercise, resulting in 9 outcomes directly qualifying for inclusion and 15 outcomes being carried forward to the consensus meeting, of which 7 of 15 were agreed on for inclusion. The final COS contained 16 outcomes organized into 4 outcome domains comprising visual function, health-related quality of life, treatment side effects, and disease control. Conclusions This study builds on international work across the clinical trials community and our qualitative research to construct the world’s first COS for NIU-PS. The COS provides a list of outcomes that represent the priorities of key stakeholders and provides a minimum set of outcomes for use in all future NIU-PS clinical trials. Adoption of this COS can improve the value of future uveitis clinical trials and reduce noninformative research. Some of the outcomes identified do not yet have internationally agreed upon methods for measurement and should be the subject of future international consensus development.