Identification of Risk Factors for Dupilumab-associated OculaSurface Disease in Patients with Atopic Dermatitis

This study identified risk factors for the development of dupilumab-associated ocular surface disease in patients with moderate-to-severe atopic dermatitis in a large prospective daily practice cohort. Data from the Dutch BioDay Registry were used to assess the risk of developing dupilumab-associated ocular surface di-sease, by performing univariate and multivariate logistic regression analyses. A total of 469 patients were included, of which 152/469 (32.4%) developed dupi-lumab-associated ocular surface disease. Multivariate analysis showed a statistically significant association of the development of dupilumab-associated ocular surface disease with a history of any eye disease (his-tory of self-reported episodic acute allergic conjunctivitis excluded) combined with the use of ophthalmic medication at the start of dupilumab (odds ratio 5.16, 95% confidence interval 2.30–11.56, p < 0.001). In conclusion, a history of any eye disease (history of self-reported episodic acute allergic conjunctivitis ex-cluded) combined with the use of ophthalmic medication at baseline was associated with the development of dupilumab-associated ocular surface disease in patients with atopic dermatitis

Ocular surface disease in moderate-to-severe atopic dermatitis patients and the effect of biological therapy

Atopic dermatitis (AD) is a chronic inflammatory skin disease for which new targeted therapies are currently available. Due to the increased rates of ocular surface disease (OSD) reported during treatment with these new targeted treatments, more insight into the occurrence and pathomechanism of OSD in moderate-to-severe AD patients is needed. Therefore, this review's first part highlights that most patients with moderate-to-severe AD already have characteristics of OSD before starting targeted treatment. Remarkably, not all AD patients with OSD report ocular symptoms. OSD in AD is associated with less conjunctival goblet cells (GC) compared to healthy controls. In addition, OSD severity in AD patients is associated with high AD activity, the presence of eyelid and/or facial eczema, and high levels of AD-related severity biomarkers in tear fluid. The second part of this review highlights that pre-existing ocular pathology (e.g. in combination with the use of ophthalmic medication or eyelid eczema) may be associated with the development of dupilumab-associated ocular surface disease (DAOSD). During dupilumab treatment, DAOSD (which can be new-onset OSD or worsening of pre-existing OSD) is observed in approximately one-third of the dupilumab-treated AD patients. Anti-inflammatory ophthalmic treatment improves DAOSD, and dose reduction of dupilumab may also be an effective treatment option. The pathomechanism of DAOSD is still not fully elucidated. In a prospective study low, but stable conjunctival GC numbers were observed in moderate-to-severe AD patients, before and during dupilumab treatment. However, the Mucin 5 AC (MUC5AC) expression of GCs decreased during dupilumab treatment, suggesting an impairment of the GC function by dupilumab treatment. In addition, higher dupilumab tear fluid levels were found in dupilumab-treated AD patients with moderate-to-severe OSD compared to patients with no or mild OSD, whereas the dupilumab serum levels are similar. Clinicians should be aware of the frequent occurrence of OSD in moderate-to-severe AD patients, and a low-threshold referral to an ophthalmologist is recommended

Prospective evaluation of clinical outcomes between pre‐cut corneal grafts prepared using a manual or automated technique: with one‐year follow‐up

Purpose: Posterior lamellar corneal surgery is considered the standard of care for irreversible endothelial cell dysfunction. Pre-cut grafts can be prepared either manually (Descemet stripping endothelial keratoplasty; DSEK) or mechanically (Descemet stripping automated endothelial keratoplasty; DSAEK). We performed a head-to-head clinical comparison between DSEK and DSAEK grafts. Methods: All DSEK and DSAEK procedures performed by two corneal specialists at the University Medical Center Utrecht from 1 January 2016 through 31 October 2016 were prospectively included. Pre-cut grafts were delivered by two eye banks, which either exclusively prepared the DSEK or DSAEK grafts. Preoperative and postoperative measurements were obtained, and all surgical events and adverse events were recorded. Results: A total of 21 DSEK and 53 DSAEK procedures were included for analysis; the two groups were similar at baseline, with the exception of graft endothelial cell density, which was 2531 ± 67 versus 2748 ± 148 cells/mm 2 , respectively (p < 0.001). At the one-year follow-up visit, corrected distance visual acuity and endothelial cell loss were similar between the groups. Mean pachymetry was significantly lower in the DSEK group (521 ± 39 versus 588 ± 59 μm; p < 0.001), whereas the rebubbling rate was significantly higher in the DSEK group (47.6% versus 18.9%; p = 0.001). Finally, three grafts in the DSEK group experienced failure compared to one graft in the DSAEK group (14% versus 1.9%, respectively). Conclusion: Manually dissected and microkeratome-dissected grafts performed similarly with respect to vision and endothelial cell loss assessed one year after surgery. The higher incidence of graft failure among manually dissected (i.e. DSEK) grafts may be attributable to reduced relative thickness compared to DSAEK grafts and/or the resulting differences in tissue handling and the surgeon's learning curve

Prospective evaluation of clinical outcomes between pre-cut corneal grafts prepared using a manual or automated technique : with one-year follow-up

Purpose: Posterior lamellar corneal surgery is considered the standard of care for irreversible endothelial cell dysfunction. Pre-cut grafts can be prepared either manually (Descemet stripping endothelial keratoplasty; DSEK) or mechanically (Descemet stripping automated endothelial keratoplasty; DSAEK). We performed a head-to-head clinical comparison between DSEK and DSAEK grafts. Methods: All DSEK and DSAEK procedures performed by two corneal specialists at the University Medical Center Utrecht from 1 January 2016 through 31 October 2016 were prospectively included. Pre-cut grafts were delivered by two eye banks, which either exclusively prepared the DSEK or DSAEK grafts. Preoperative and postoperative measurements were obtained, and all surgical events and adverse events were recorded. Results: A total of 21 DSEK and 53 DSAEK procedures were included for analysis; the two groups were similar at baseline, with the exception of graft endothelial cell density, which was 2531 ± 67 versus 2748 ± 148 cells/mm 2 , respectively (p < 0.001). At the one-year follow-up visit, corrected distance visual acuity and endothelial cell loss were similar between the groups. Mean pachymetry was significantly lower in the DSEK group (521 ± 39 versus 588 ± 59 μm; p < 0.001), whereas the rebubbling rate was significantly higher in the DSEK group (47.6% versus 18.9%; p = 0.001). Finally, three grafts in the DSEK group experienced failure compared to one graft in the DSAEK group (14% versus 1.9%, respectively). Conclusion: Manually dissected and microkeratome-dissected grafts performed similarly with respect to vision and endothelial cell loss assessed one year after surgery. The higher incidence of graft failure among manually dissected (i.e. DSEK) grafts may be attributable to reduced relative thickness compared to DSAEK grafts and/or the resulting differences in tissue handling and the surgeon's learning curve

Video Grading of Descemet Membrane Endothelial Keratoplasty Surgery to Identify Surgeon Risk Factors for Graft Detachment and Rebubbling: A Post Hoc Observational Analysis of the Advanced Visualization In Corneal Surgery Evaluation Trial

PURPOSE: The aim of this study was to explore video-graded intraoperative risk factors for graft detachment (GD) and rebubbling in Descemet membrane endothelial keratoplasty surgery. METHODS: A post hoc analysis of 65 eyes of 65 pseudophakic subjects with Fuchs endothelial dystrophy that underwent Descemet membrane endothelial keratoplasty surgery as part of the Advanced Visualization In Corneal Surgery Evaluation trial. All surgical recordings were assessed by 2 graders using a structured assessment form. A multinominal regression was performed to estimate the independent effect of video-graded intraoperative factors on the incidence of GD and rebubbling. Secondary outcomes are corrected distance visual acuity and endothelial cell density. RESULTS: In total, 33 GDs were recorded, of which 17 required rebubbling. No significant predictors for GD or rebubbling were identified. However, the results revealed 2 clinically relevant patterns. An unfavorable graft configuration (ie, wrinkled, tight scroll, or taco-shaped) and a gas-bubble size smaller than the graft diameter were associated with an increased risk of GD [odds ratio (OR) 2.5 and OR 2.26, respectively] and rebubbling (OR 2.0 and OR 2.60, respectively). Inversely, a larger gas-bubble size was associated with a reduced risk of GD (OR 0.37) and rebubbling (OR 0.36). At 3 and 6 months postoperatively, corrected distance visual acuity was poorer in subjects requiring a rebubbling and endothelial cell density loss was higher in subjects with a partial GD. CONCLUSIONS: Our analysis revealed that the gas-bubble size and graft shape/geometry seem to be relevant clinical factors for GD and rebubbling, whereas descemetorhexis difficulty, degree of graft manipulation, graft overlap, and surgical iridectomy were not associated with an increased risk

A machine learning approach to explore predictors of graft detachment following posterior lamellar keratoplasty: a nationwide registry study

Machine learning can be used to explore the complex multifactorial patterns underlying postsurgical graft detachment after endothelial corneal transplantation surgery and to evaluate the marginal effect of various practice pattern modulations. We included all posterior lamellar keratoplasty procedures recorded in the Dutch Cornea Transplant Registry from 2015 through 2018 and collected the center-specific practice patterns using a questionnaire. All available data regarding the donor, recipient, surgery, and practice pattern, were coded into 91 factors that might be associated with the occurrence of a graft detachment. In this research, we used three machine learning methods; a regularized logistic regression (lasso), classification tree analysis (CTA), and random forest classification (RFC), to select the most predictive subset of variables for graft detachment. A total of 3647 transplants were included in our analysis and the overall prevalence of graft detachment was 9.9%. In an independent test set the area under the curve for the lasso, CTA, and RFC was 0.70, 0.65, and 0.72, respectively. Identified risk factors included: a Descemet membrane endothelial keratoplasty procedure, prior graft failure, and the use of sulfur hexafluoride gas. Factors with a reduced risk included: performing combined procedures, using pre-cut donor tissue, and a pre-operative laser iridotomy. These results can help surgeons to review their practice patterns and generate hypotheses for empirical research regarding the origins of graft detachments

The diagnostic value of nasal microbiota and clinical parameters in a multi-parametric prediction model to differentiate bacterial versus viral infections in lower respiratory tract infections

Background The ability to accurately distinguish bacterial from viral infection would help clinicians better target antimicrobial therapy during suspected lower respiratory tract infections (LRTI). Although technological developments make it feasible to rapidly generate patient-specific microbiota profiles, evidence is required to show the clinical value of using microbiota data for infection diagnosis. In this study, we investigated whether adding nasal cavity microbiota profiles to readily available clinical information could improve machine learning classifiers to distinguish bacterial from viral infection in patients with LRTI. Results Various multi-parametric Random Forests classifiers were evaluated on the clinical and microbiota data of 293 LRTI patients for their prediction accuracies to differentiate bacterial from viral infection. The most predictive variable was C-reactive protein (CRP). We observed a marginal prediction improvement when 7 most prevalent nasal microbiota genera were added to the CRP model. In contrast, adding three clinical variables, absolute neutrophil count, consolidation on X-ray, and age group to the CRP model significantly improved the prediction. The best model correctly predicted 85% of the 'bacterial' patients and 82% of the 'viral' patients using 13 clinical and 3 nasal cavity microbiota genera (Staphylococcus, Moraxella, and Streptococcus). Conclusions We developed high-accuracy multi-parametric machine learning classifiers to differentiate bacterial from viral infections in LRTI patients of various ages. We demonstrated the predictive value of four easy-to-collect clinical variables which facilitate personalized and accurate clinical decision-making. We observed that nasal cavity microbiota correlate with the clinical variables and thus may not add significant value to diagnostic algorithms that aim to differentiate bacterial from viral infections