Depressed visual field and mood are associated with sleep disorder in glaucoma patients.
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ABSTRACT:
SUBMITTER: Ayaki M
PROVIDER: S-EPMC4863426 | biostudies-other | 2016
REPOSITORIES: biostudies-other
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Project description:Our goal was to examine associations of infant sleep and feeding patterns with maternal sleep and mood among women at risk for postpartum depression. Participants were 30 women (age?±?SD?=?28.3?±?5.1 years) with a history of MDD (but not in a mood episode at enrollment) who completed daily sleep diaries, wore wrist actigraphs to estimate sleep, and had their mood assessed with the Hamilton Depression Rating Scale (HAM-D-17) during four separate weeks of the perinatal period (33 weeks pregnancy and weeks 2, 6, and 16 postpartum). They logged their infants' sleep and feeding behaviors daily and reported postnatal stress on the Childcare Stress Inventory (CSI) at week 16. Mothers' actigraphically estimated sleep showed associations with infant sleep and feeding patterns only at postpartum week 2. Shorter duration of the longest infant-sleep bout was associated with shorter maternal sleep duration (p?=?.02) and lower sleep efficiency (p?=?.04), and maternal sleep efficiency was negatively associated with the number of infant-sleep bouts (p?=?.008) and duration of infant feeding (p?=?.008). Neither infant sleep nor feeding was associated with maternal sleep at 6 or 16 weeks, but more disturbed infant sleep and more frequent feeding at 6 weeks were associated with higher HAM-D scores at 6 and 16 weeks and higher CSI scores. Sleep in the mother-infant dyad is most tightly linked in the early postpartum weeks, but mothers continue to experience disturbed sleep and infant sleep and feeding behaviors continue to be associated with mothers' depressive symptoms and stress ratings as long as 16 weeks postpartum. These data imply that interventions designed to improve maternal sleep and postpartum mood should include both mothers and infants because improving infant sleep alone is not likely to improve maternal sleep, and poor infant sleep is linked to postpartum depression and stress.
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Project description:High rates of sleep disturbances occur in depression. Sleep disturbances are linked to heightened inflammation. We sought to determine if sleep disturbances explain a portion of the putative inflammation - depression association among older adults. In late life, age-related immunoregulation changes may modify the inflammation-depression relationship.Cross-sectional associations of a panel of serum inflammatory markers with probable depression (measured with the Geriatric Depression Scale) were assessed among 2560 community-dwelling older men. We tested whether inflammatory marker - probable depression associations were independent of chronic diseases, as well as objective and subjectively measured sleep disturbances. We also tested whether inflammation-probable depression associations were moderated by age.Inflammatory markers were not independently associated with higher odds of probable depression. A significant age by C-reactive protein (CRP) interaction (p=0.01) was detected such that the strength of the CRP-probable depression association decreased with age. When stratifying by the median age of 76, elevated odds of probable depression were found for men with CRP levels above the median only among the younger group (OR=2.08, 95% CI 1.18-3.69). In the final adjusted model, independent effects of chronic diseases and subjective sleep disturbances contributed to a total of 37% attenuation of the original OR (adjusted OR=1.68, 95% CI 0.911-3.10, p=.09).In late-life, associations between inflammatory markers and mood may be explained by both chronic diseases and subjectively reported sleep disturbances. Our findings indicate that the association of CRP with probable depression diminishes in strength with age.
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Project description:PurposeThe purpose of this study was to discover the aqueous humor proteomic changes associated with visual field indices in glaucoma patients.MethodsAqueous humor samples were analyzed using Liquid Chromatography Tandem Mass Spectrometry (LC-MS/MS). The visual fields were analyzed with the Humphrey Visual Field analyzer. Statistical analyses were performed to discover the relationship between the aqueous humor proteins and visual field parameters including Pattern Standard Deviation (PSD), Visual Field Index (VFI), Mean Deviation (MD) and Glaucoma Hemifield Test (GHT).ResultsIn total, 222 proteins were identified in 49 aqueous humor samples. A total of 11, 9, 7, and 6 proteins were significantly correlated with PSD, VFI, MD, and GHT respectively. These proteins include apolipoprotein D, members of complement pathway (C1S, C4A, C4B, C8B, and CD14), and immunoglobulin family (IKHV3-9, IGKV2-28).ConclusionSeveral proteins involved in immune responses (immunoglobulins and complement factors) and neurodegeneration (apolipoprotein D) were identified to be associated with abnormal visual field parameters. These findings provide targets for future studies investigating precise molecular mechanisms and new therapies for glaucomatous optic neuropathy.
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Project description:Purpose:To quantify visual field (VF) variability as a function of threshold sensitivity and location, and to compare weighted pointwise linear regression (PLR) with unweighted PLR and pointwise exponential regression (PER) for data fit and prediction ability. Methods:Two datasets were used for this retrospective study. The first was used to characterize and estimate VF variability, and included a total of 4,747 eyes of 3,095 glaucoma patients with six or more VFs and 3 years or more of follow-up. After performing PER for each series, standard deviation of residuals was quantified for each decibel of sensitivity as a measure of variability. A separate dataset was used to test and compare unweighted PLR, weighted PLR, and PER for data fit and prediction, and included 261 eyes of 176 primary open-angle glaucoma patients with 10 or more VFs and 6 years or more of follow-up. Results:The degree of variability changed as a function of threshold sensitivity with a zenith and a nadir at 33 and 11 dB, respectively. Variability decreased with eccentricity and was higher in the central 10° (P < 0.001). Differences among the methods for data fit were negligible. PER was the best model to predict future sensitivity values in the mid term and long term. Conclusions:VF variability increases with the severity of glaucoma damage and decreases with eccentricity. Weighted linear regression neither improves model fit nor prediction. PER exhibited the best prediction ability, which is likely related to the nonlinear nature of long-term glaucomatous perimetric decay. Translational Relevance:This study suggests that taking into account heteroscedasticity has no advantage in VF modeling.
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Project description:PURPOSE:To propose a new methodology for classifying patient-reported outcomes in glaucoma and for quantifying the amount of visual field damage associated with disability in the disease. DESIGN:Cross-sectional study. METHODS:A total of 263 patients with glaucoma were included. Vision-related disability was assessed by the National Eye Institute Visual Function Questionnaire (NEI VFQ-25). A latent class analysis (LCA) model was applied to analyze NEI VFQ-25 data and patients were divided into mutually exclusive classes according to their responses to the questionnaires. Differences in standard automated perimetry (SAP) mean deviation (MD) and integrated binocular mean sensitivity (MS) values between classes were investigated. The optimal number of classes was defined based on goodness-of-fit criteria, interpretability, and clinical utility. RESULTS:The model with 2 classes, disabled and nondisabled, had the best fit with an entropy of 0.965, indicating excellent separation of classes. The disabled group had 48 (18%) patients, whereas 215 (82%) patients were classified as nondisabled. The average MD of the better eye in the disabled group was -5.98 dB vs -2.51 dB in the nondisabled group (P < .001). For the worse eye, corresponding values were -13.36 dB and -6.05 dB, respectively (P < .001). CONCLUSION:Application of an LCA model allowed categorization of patient-reported outcomes and quantification of visual field levels associated with disability in glaucoma. A damage of approximately -6 dB for SAP MD, indicating relatively early visual field loss, may already be associated with significant disability if occurring in the better eye.
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Project description:Primary open-angle glaucoma (POAG) is characterized by a progressive optic neuropathy with visual field loss. To investigate the genetic variants associated with visual field loss in POAG, Japanese POAG patients (n = 426) and control subjects (n = 246) were genotyped for 22 genetic variants predisposing to POAG that can be classified into those associated with intraocular pressure (IOP) elevation (IOP-related genetic variants) and optic nerve vulnerability independent of IOP (optic nerve-related genetic variants). The genetic risk score (GRS) of the 17 IOP-related and five optic nerve-related genetic variants was calculated, and the associations between the GRS and the mean deviation (MD) of automated static perimetry as an indicator of the severity of visual field loss and pattern standard deviation (PSD) as an indicator of the focal disturbance were evaluated. There was a significant association (Beta = - 0.51, P = 0.0012) between the IOP-related GRS and MD. The severity of visual field loss may depend on the magnitude of IOP elevation induced by additive effects of IOP-related genetic variants. A significant association (n = 135, Beta = 0.65, P = 0.0097) was found between the optic nerve-related, but not IOP-related, GRS and PSD. The optic nerve-related (optic nerve vulnerability) and IOP-related (IOP elevation) genetic variants may play an important role in the focal and diffuse visual field loss respectively. To our knowledge, this is the first report to show an association between additive effects of genetic variants predisposing to POAG and glaucomatous visual field loss, including severity and focal/diffuse disturbance of visual field loss, in POAG.
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Project description:An objective method to predict individual visual field progression will contribute to realise personalised medication. The purpose of this study was to establish a predictive formula for glaucomatous visual field progression in patients with Primary open-angle glaucoma, mainly including normal tension glaucoma. This study was a large-scale, longitudinal and retrospective study including 498 eyes of 312 patients visiting from June 2009 to May 2015. In this analysis, 191 eyes of 191 patients meeting all eligible criteria were used. A predictive formula to calculate the rate of glaucomatous visual field progression (mean deviation slope) was obtained through multivariate linear regression analysis by adopting "Angle of Retinal Nerve Fibre Layer Defect" at the baseline, "Vertical Cup-Disc ratio" at the baseline, "Presence or absence of Disc Haemorrhage" during the follow-up period, and "Mean IOP change (%)" during the follow-up period as predictors. Coefficient of determination of the formula was 0.20. The discriminative ability of the formula was evaluated as moderate performance using receiver operating characteristic analysis, and the area under the curve was approximately 0.75 at all cut-off values. Internal validity was confirmed by bootstrapping. The predictive formula established by this type of approach might be useful for personalised medication.
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Project description:This study aimed to characterize the changes in the visual field (VF) patterns and disc morphology of patients with thyroid-associated orbitopathy (TAO) and open-angle glaucoma (OAG). A retrospective review of the medical records at the Tri-Service General Hospital in Taiwan identified 396 eyes of 198 patients with thyroid-associated glaucoma. A final follow-up of VF examination in 140 eyes revealed 114 eyes with VF defects, indicating disease progression. The characteristics of and changes in disc morphology, optical coherence tomography findings, and VF defects were statistically analyzed. The most common VF defects at the initial diagnosis and the end of the follow-up period were inferior partial arcuate (17%) and paracentral (15%) defects, respectively. The most common VF defect in patients with unspecific disc signs was an unspecific scotoma (13%). The most common optic disc feature was disc cupping (51%), followed by parapapillary atrophy (48%). The most frequent location of nerve fiber layer thinning was the inferotemporal region (48%). VF defects showed a significantly more pronounced progression in the non-nerve fiber bundle group than in the nerve fiber bundle group (p < 0.001). This study details the characteristics and progression of disc morphology and VF defects in patients with TAO and OAG.
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Project description:BackgroundTo develop a deep neural network able to differentiate glaucoma from non-glaucoma visual fields based on visual filed (VF) test results, we collected VF tests from 3 different ophthalmic centers in mainland China.MethodsVisual fields obtained by both Humphrey 30-2 and 24-2 tests were collected. Reliability criteria were established as fixation losses less than 2/13, false positive and false negative rates of less than 15%.ResultsWe split a total of 4012 PD images from 1352 patients into two sets, 3712 for training and another 300 for validation. There is no significant difference between left to right ratio (P?=?0.6211), while age (P?=?0.0022), VFI (P?=?0.0001), MD (P?=?0.0039) and PSD (P?=?0.0001) exhibited obvious statistical differences. On the validation set of 300 VFs, CNN achieves the accuracy of 0.876, while the specificity and sensitivity are 0.826 and 0.932, respectively. For ophthalmologists, the average accuracies are 0.607, 0.585 and 0.626 for resident ophthalmologists, attending ophthalmologists and glaucoma experts, respectively. AGIS and GSS2 achieved accuracy of 0.459 and 0.523 respectively. Three traditional machine learning algorithms, namely support vector machine (SVM), random forest (RF), and k-nearest neighbor (k-NN) were also implemented and evaluated in the experiments, which achieved accuracy of 0.670, 0.644, and 0.591 respectively.ConclusionsOur algorithm based on CNN has achieved higher accuracy compared to human ophthalmologists and traditional rules (AGIS and GSS2) in differentiation of glaucoma and non-glaucoma VFs.
| S-EPMC6172715 | biostudies-literature
Project description:PURPOSE:To develop a visual field (VF) feature model to predict the reversal of glaucoma hemifield test (GHT) results to within normal limits (WNL) after 2 consecutive outside normal limits (ONL) results. DESIGN:Retrospective cohort study. PARTICIPANTS:Visual fields of 44?503 eyes from 26?130 participants. METHODS:Eyes with 3 or more consecutive reliable VFs measured with the Humphrey Field Analyzer (Swedish interactive threshold algorithm standard 24-2) were included. Eyes with ONL GHT results for the 2 baseline VFs were selected. We extracted 3 categories of VF features from the baseline tests: (1) VF global indices (mean deviation [MD] and pattern standard deviation), (2) mismatch between baseline VFs, and (3) VF loss patterns (archetypes). Logistic regression was applied to predict the GHT results reversal. Cross-validation was applied to evaluate the model on testing data by the area under the receiver operating characteristic curve (AUC). We ascertained clinical glaucoma status on a patient subset (n = 97) to determine the usefulness of our model. MAIN OUTCOME MEASURES:Predictive models for GHT results reversal using VF features. RESULTS:For the 16?604 eyes with 2 initial ONL results, the prevalence of a subsequent WNL result increased from 0.1% for MD < -12 dB to 13.8% for MD ?-3 dB. Compared with models with VF global indices, the AUC of predictive models increased from 0.669 (MD ?-3 dB) and 0.697 (-6 dB ? MD < -3 dB) to 0.770 and 0.820, respectively, by adding VF mismatch features and computationally derived VF archetypes (P < 0.001 for both). The GHT results reversal was associated with a large mismatch between baseline VFs. Moreover, the GHT results reversal was associated more with VF archetypes of nonglaucomatous loss, severe widespread loss, and lens rim artifacts. For a subset of 97 eyes, using our model to predict absence of glaucoma based on clinical evidence after 2 ONL results yielded significantly better prediction accuracy (87.7%; P < 0.001) than predicting GHT results reversal (68.8%) with a prescribed specificity 67.7%. CONCLUSIONS:Using VF features may predict the GHT results reversal to WNL after 2 consecutive ONL results.
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