Ocular Comorbidities Contributing to Death in the US.
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ABSTRACT:
SUBMITTER: Huang RS
PROVIDER: S-EPMC10457708 | biostudies-literature | 2023 Aug
REPOSITORIES: biostudies-literature
Publications
Ocular Comorbidities Contributing to Death in the US.
Huang Ryan S RS Mihalache Andrew A Popovic Marko M MM Kertes Peter J PJ Wong David T DT Muni Rajeev H RH
JAMA network open 20230801 8
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Project description:BackgroundIdentifying modifiable risk factors for cognitive impairment in the early stages of Parkinson's disease (PD) and estimating their impact on cognitive status may help prevent dementia (PDD) and the design of cognitive trials.MethodsUsing a standard approach for the assessment of global cognition in PD and controlling for the effects of age, education and disease duration, we explored the associations between cognitive status, comorbidities, metabolic variables and lifestyle variables in 533 PD participants from the COPPADIS study.ResultsAmong the overall sample, 21% of participants were classified as PD-MCI (n = 114) and 4% as PDD (n = 26). The prevalence of hypertension, diabetes and dyslipidemia was significantly higher in cognitively impaired patients while no between-group differences were found for smoking, alcohol intake or use of supplementary vitamins. Better cognitive scores were significantly associated with regular physical exercise (p < 0.05) and cognitive stimulation (< 0.01). Cognitive performance was negatively associated with interleukin 2 (Il2) (p < 0.05), Il6 (p < 0.05), iron (p < 0.05), and homocysteine (p < 0.005) levels, and positively associated with vitamin B12 levels (p < 0.005).ConclusionsWe extend previous findings regarding the positive and negative influence of various comorbidities and lifestyle factors on cognitive status in early PD patients, and reinforce the need to identify and treat potentially modifiable variables with the intention of exploring the possible improvement of the global cognitive status of patients with PD.
| S-EPMC8653592 | biostudies-literature
Project description:AimTo assess the visual acuity at the end of life in glaucoma suspect patients, ocular hypertension, and patients treated for glaucoma and to find factors contributing to a reduced visual acuity in this cohort of deceased patients.MethodsIn a cohort of 3883 medically treated glaucoma patients, glaucoma suspect, or patients with ocular hypertension assembled in 2001-2004, 1639 were deceased. Patient data were collected from electronic and paper patient files. The files of 1378 patients were studied and the last measured visual acuity and ocular comorbidities influencing the visual acuity were extracted.ResultsOur results show that only 37.2% of patients had no visual impairment in either eye, 30.5% was visually impaired or blind in both eyes and 4.1% was blind in both eyes, all based on VA. The most common contributing factors for severe visual impairment or blindness (prevalence ≥ 1%) were: glaucoma, retinal vein occlusion, dry and exudative age-related macular degeneration, past retinal detachment, amblyopia, diabetic retinopathy, anterior ischemic optic neuropathy, trauma, decompensated cornea, past keratitis, enucleation, corneal transplantation, and macular hole.ConclusionsDespite the current advanced treatment modalities for glaucoma, 30.5% of patients had a VA < 0.5 in both eyes and 4.1% was blind in both eyes. However, this disability cannot be confidently attributed only to glaucoma. Besides glaucoma, most common contributing factors were among others retinal and macular diseases. Patient management in glaucoma should be based on more than lowering the intraocular pressure to prevent blindness at the end of life.
| S-EPMC8027869 | biostudies-literature
Project description:Traumatic brain injuries (TBI) of varied types are common across all populations and can cause visual problems. For military personnel in combat settings, injuries from blast exposures (bTBI) are prevalent and arise from a myriad of different situations. To model these diverse conditions, we are one of several groups modeling bTBI using mice in varying ways. Here, we report a refined analysis of retinal ganglion cell (RGC) damage in male C57BL/6J mice exposed to a blast-wave in an enclosed chamber. Ganglion cell layer thickness, RGC density (BRN3A and RBPMS immunoreactivity), cellular density of ganglion cell layer (hematoxylin and eosin staining), and axon numbers (paraphenylenediamine staining) were quantified at timepoints ranging from 1 to 17-weeks. RNA sequencing was performed at 1-week and 5-weeks post-injury. Earliest indices of damage, evident by 1-week post-injury, are a loss of RGC marker expression, damage to RGC axons, and increase in glial markers expression. Blast exposure caused a loss of RGC somas and axons-with greatest loss occurring by 5-weeks post-injury. While indices of glial involvement are prominent early, they quickly subside as RGCs are lost. The finding that axonopathy precedes soma loss resembles pathology observed in mouse models of glaucoma, suggesting similar mechanisms.
2024-08-14 | GSE274793 | GEO
Project description:Background/objectivesVision loss is a top disability in the United States (US). Patients commonly present with multiple ocular diseases, but the extent to which this places them at risk for vision loss, and if sex and race impacts this, is poorly understood. This exploratory analysis evaluated which ocular comorbidities and demographics are at highest risk for visual impairment.Subjects/methodsA retrospective cross-sectional study was conducted through the TriNetX Analytics Network, an aggregated network encompassing over 90 million insured and uninsured patients across 50 healthcare organizations from all regions in the US. Patients with diabetic retinopathy (DR), age-related macular degeneration (AMD), retinal vein occlusion (RVO), glaucoma, and uveitis were included in this study. Ocular diseases and visual impairment were determined through ICD-10 codes. Prevalence and odds ratios were calculated while stratifying by sex and racial demographics. Statistical analyses were completed using RStudio and Excel with 95% confidence intervals calculated.ResultsThe comorbid conditions with the highest prevalence of visual impairment were uveitis and RVO (39.94%), uveitis and neovascular AMD (37.61%), and uveitis and glaucoma (33.23%). The comorbidity with the highest odds for visual impairment was uveitis and RVO (POR 4.86; 95% CI 4.49, 5.26). Compared to white males, Black and Hispanic males were disproportionately affected by visual impairment across ocular comorbidities.ConclusionThis study quantified the prevalence and odds of visual impairment for unilateral and comorbid ocular disease, with the addition of uveitis causing the greatest increase. Black and Hispanic males were disproportionately affected by visual impairment across comorbid conditions.
| S-EPMC11543832 | biostudies-literature
Project description:Infection by the new corona virus strain SARS-CoV-2 and its related syndrome COVID-19 has been associated with more than two million deaths worldwide. Patients of higher age and with preexisting chronic health conditions are at an increased risk of fatal disease outcome. However, detailed information on causes of death and the contribution of pre-existing health conditions to death yet is missing, which can be reliably established by autopsy only. We performed full body autopsies on 26 patients that had died after SARS-CoV-2 infection and COVID-19 at the Charité University Hospital Berlin, Germany, or at associated teaching hospitals. We systematically evaluated causes of death and pre-existing health conditions. Additionally, clinical records and death certificates were evaluated. We report findings on causes of death and comorbidities of 26 decedents that had clinically presented with severe COVID-19. We found that septic shock and multi organ failure was the most common immediate cause of death, often due to suppurative pulmonary infection. Respiratory failure due to diffuse alveolar damage presented as immediate cause of death in fewer cases. Several comorbidities, such as hypertension, ischemic heart disease, and obesity were present in the vast majority of patients. Our findings reveal that causes of death were directly related to COVID-19 in the majority of decedents, while they appear not to be an immediate result of preexisting health conditions and comorbidities. We therefore suggest that the majority of patients had died of COVID-19 with only contributory implications of preexisting health conditions to the mechanism of death.
| S-EPMC7895917 | biostudies-literature
Project description:AimsPre-existing cardiovascular diseases (CVDs) have been proposed to identify patients at higher risk of adverse coronavirus disease 2019 (COVID-19) outcomes, but existing evidence is conflicting. Thus, it is unclear whether pre-existing CVDs are independently important predictors for severe COVID-19.Methods and resultsIn a nationwide Danish cohort of hospital-screened COVID-19 patients aged ≥40, we investigated if pre-existing CVDs predict the 30-day risk of (i) composite outcome of severe COVID-19 and (ii) all-cause mortality. We estimated 30-day risks using a Cox regression model including age, sex, each CVD comorbidity, chronic obstructive pulmonary disease-asthma, diabetes, and chronic kidney disease. To illustrate CVD comorbidities' importance, we evaluated the predicted risks of death and severe infection, for each sex, along ages 40-85. In total, 4090 COVID-19 hospital-screened patients were observed as of 26 August 2020; 22.1% had ≥1 CVD, 23.7% had severe infection within 30 days and 12.6% died. Predicted risks of both outcomes at age 75 among men with single CVD comorbidities did not differ in clinically meaningful amounts compared with men with no comorbidities risks for the composite outcome of severe infection; women with heart failure (28.2%; 95% CI 21.1-37.0%) or atrial fibrillation (30.0%; 95% CI: 24.2-36.9%) showed modest increases compared with women with no comorbidities (24.0%; 95% CI: 21.4-26.9%).ConclusionsThe results showing only modest effects of CVDs on increased risks of poor COVID-19 outcomes are important in allowing public health authorities and clinicians to provide more tailored guidance to cardiovascular patients, who have heretofore been grouped together as high risk due to their disease status.
| S-EPMC7665490 | biostudies-literature
Project description:Background Little is known about the contemporary mortality experience among adults with congenital heart disease (CHD). The objectives of this study were to assess the age at death, presence of cardiovascular comorbidities, and most common causes of death among adults with CHD in a contemporary cohort within the United States. Methods and Results Patients with CHD who had a healthcare encounter between 2008 and 2013 at 1 of 5 comprehensive CHD centers in North Carolina were identified by International Classification of Diseases, Ninth Revision (ICD-9), code. Only patients who could be linked to a North Carolina death certificate between 2008 and 2016 and with age at death ≥20 years were included. Median age at death and underlying cause of death based on death certificate data were analyzed. The prevalence of acquired cardiovascular risk factors was determined from electronic medical record data. Among the 629 included patients, the median age at death was 64.2 years. Those with severe CHD (n=157, 25%), shunts (n=202, 32%), and valvular lesions (n=174, 28%) had a median age at death of 46.0, 65.0, and 73.3 years, respectively. Cardiovascular death was most common in adults with severe CHD (60%), with 40% of those deaths caused by CHD. Malignancy and ischemic heart disease were the most common causes of death in adults with nonsevere CHD. Hypertension and hyperlipidemia were common comorbidities among all CHD severity groups. Conclusions The most common underlying causes of death differed by lesion severity. Those with severe lesions most commonly died from underlying CHD, whereas those with nonsevere disease more commonly died from non-CHD causes.
| S-EPMC7660712 | biostudies-literature
Project description:ObjectivesSystemic autoimmune diseases (SAIDs) have chronic trajectories and share characteristics of self-directed inflammation, as well as aspects of clinical expression. Nonetheless, burden-of-disease studies rarely investigate them as a distinct category. This study aims to assess the mortality rate of SAIDs as a group and to evaluate co-occurring causes of death.MethodsWe used death certificate data in the Netherlands, 2013-2017 (N = 711 247), and constructed a SAIDs list at the fourth-position ICD-10 level. The mortality rate of SAIDs as underlying cause of death (CoD), non-underlying CoD, and any-mention CoD was calculated. We estimated age-sex-standardized observed/expected (O/E) ratios to assess comorbidities in deaths with SAID relative to the general deceased population.ResultsWe observed 3335 deaths with SAID on their death certificate (0.47% of all deaths). The mortality rate of SAID was 14.6 per million population as underlying CoD, 28.0 as non-underlying CoD, and 39.7 as any-mention CoD. The mortality rate was higher for females and increased exponentially with age. SAID-related deaths were positively associated with all comorbidities except for solid neoplasms and mental conditions. Particularly strong was the association with diseases of the musculoskeletal system (O/E = 3.38; 95% CI: 2.98, 3.82), other diseases of the genitourinary system (O/E = 2.73; 95% CI: 2.18, 3.38), influenza (O/E = 2.71; 95% CI: 1.74, 4.03), blood diseases (O/E = 2.02; 95% CI: 1.70, 2.39), skin and subcutaneous tissue diseases (O/E = 1.95; 95% CI: 1.54, 2.45), and infectious diseases (O/E = 1.85; 95% CI: 1.70, 2.01).ConclusionSystemic autoimmune diseases constitute a rare group of causes of death, but contribute to mortality through multiple comorbidities. Classification systems could be adapted to better encompass these diseases as a category.
| S-EPMC7937014 | biostudies-literature
Project description:Background and aimsA substantial share of fatal drug overdoses is missing information on specific drug involvement, leading to under-reporting of opioid-related death rates and a misrepresentation of the extent of the opioid epidemic. We aimed to compare methodological approaches to predicting opioid involvement in unclassified drug overdoses in US death records and to estimate the number of fatal opioid overdoses from 1999 to 2016 using the best-performing method.DesignThis was a secondary data analysis of the universe of drug overdoses in 1999-2016 obtained from the National Center for Health Statistics Detailed Multiple Cause of Death records.SettingUnited States.CasesA total of 632 331 drug overdose decedents. Drug overdoses with known drug classification comprised 78.2% of the cases (n = 494 316) and unclassified drug overdoses (ICD-10 T50.9) comprised 21.8% (n = 138 015).MeasurementsKnown opioid involvement was defined using ICD-10 codes T40.0-40.4 and T40.6, recorded in the set of contributing causes. Opioid involvement in unclassified drug overdoses was predicted using multiple methodological approaches: logistic regression and machine learning techniques, inclusion/exclusion of contributing causes of death and inclusion/exclusion of county-level characteristics. Having selected the model with the highest predictive ability, we calculated corrected estimates of opioid-related mortality.FindingsLogistic regression and random forest models performed similarly. Including contributing causes substantially improved predictive accuracy, while including county characteristics did not. Using a superior prediction model, we found that 71.8% of unclassified drug overdoses in 1999-2016 involved opioids, translating into 99 160 additional opioid-related deaths, or approximately 28% more than reported. Importantly, there was a striking geographic variation in undercounting of opioid overdoses.ConclusionsIn modeling opioid involvement in unclassified drug overdoses, highest predictive accuracy is achieved using a statistical model-either logistic regression or a random forest ensemble-with decedent characteristics and contributing causes of death as predictors.
| S-EPMC9745785 | biostudies-literature
Project description:Traumatic brain injuries (TBI) of varied types are common across all populations and can cause visual problems. For military personnel in combat settings, injuries from blast exposures (bTBI) are prevalent and arise from a myriad of different situations. To model these diverse conditions, we are one of several groups modeling bTBI using mice in varying ways. Here, we report a refined analysis of retinal ganglion cell (RGC) damage in male C57BL/6J mice exposed to a blast-wave in an enclosed chamber. Ganglion cell layer thickness, RGC density (BRN3A and RBPMS immunoreactivity), cellular density of ganglion cell layer (hematoxylin and eosin staining), and axon numbers (paraphenylenediamine staining) were quantified at timepoints ranging from 1 to 17-weeks. RNA sequencing was performed at 1-week and 5-weeks post-injury. Earliest indices of damage, evident by 1-week post-injury, are a loss of RGC marker expression, damage to RGC axons, and increase in glial markers expression. Blast exposure caused a loss of RGC somas and axons-with greatest loss occurring by 5-weeks post-injury. While indices of glial involvement are prominent early, they quickly subside as RGCs are lost. The finding that axonopathy precedes soma loss resembles pathology observed in mouse models of glaucoma, suggesting similar mechanisms.
| S-EPMC8175471 | biostudies-literature