scholarly journals Retinal Age as a Predictive Biomarker for Mortality Risk

2020 ◽  
Author(s):  
Zhuoting Zhu ◽  
Danli Shi ◽  
Guankai Peng ◽  
Zachary Tan ◽  
Xianwen Shang ◽  
...  
Keyword(s):  
Mortality Risk ◽  
Cox Regression ◽  
Chronological Age ◽  
Fundus Images ◽  
Tailored Interventions ◽  
Age Gap ◽  
Non Linear ◽  
One Year ◽  
The Uk ◽  
Accurate Quantification

SummaryBackgroundAgeing varies substantially, thus an accurate quantification of ageing is important. We developed a deep learning (DL) model that predicted age from fundus images (retinal age). We investigated the association between retinal age gap (retinal age-chronological age) and mortality risk in a population-based sample of middle-aged and elderly adults.MethodsThe DL model was trained, validated and tested on 46,834, 15,612 and 8,212 fundus images respectively from participants of the UK Biobank study alive on 28th February 2018. Retinal age gap was calculated for participants in the test (n=8,212) and death (n=1,117) datasets. Cox regression models were used to assess association between retinal age gap and mortality risk. A restricted cubic spline analyses was conducted to investigate possible non-linear association between retinal age gap and mortality risk.FindingsThe DL model achieved a strong correlation of 0·83 (P<0·001) between retinal age and chronological age, and an overall mean absolute error of 3·50 years. Cox regression models showed that each one-year increase in the retinal age gap was associated with a 2% increase in mortality risk (hazard ratio=1·02, 95% confidence interval:1·00-1·04, P=0·021). Restricted cubic spline analyses showed a non-linear relationship between retinal age gap and mortality (Pnon-linear=0·001). Higher retinal age gaps were associated with substantially increased risks of mortality, but only if the gap exceeded 3·71 years.InterpretationOur findings indicate that retinal age gap is a robust biomarker of ageing that is closely related to risk of mortality.FundingNational Health and Medical Research Council Investigator Grant, Science and Technology Program of Guangzhou.Research in contextEvidence before this studyAgeing at an individual level is heterogeneous. An accurate quantification of the biological ageing process is significant for risk stratification and delivery of tailored interventions. To date, cell-, molecular-, and imaging-based biomarkers have been developed, such as epigenetic clock, brain age and facial age. While the invasiveness of cellular and molecular ageing biomarkers, high cost and time-consuming nature of neuroimaging and facial ages, as well as ethical and privacy concerns of facial imaging, have limited their utilities. The retina is considered a window to the whole body, implying that the retina could provide clues for ageing.Added value of this studyWe developed a deep learning (DL) model that can detect footprints of aging in fundus images and predict age with high accuracy for the UK population between 40 and 69 years old. Further, we have been the first to demonstrate that each one-year increase in retinal age gap (retinal age-chronological age) was significantly associated with a 2% increase in mortality risk. Evidence of a non-linear association between retinal age gap and mortality risk was observed. Higher retinal age gaps were associated with substantially increased risks of mortality, but only if the retinal age gap exceeded 3·71 years.Implications of all the available evidenceThis is the first study to link the retinal age gap and mortality risk, implying that retinal age is a clinically significant biomarker of ageing. Our findings show the potential of retinal images as a screening tool for risk stratification and delivery of tailored interventions. Further, the capability to use fundus imaging in predicting ageing may improve the potential health benefits of eye disease screening, beyond the detection of sight-threatening eye diseases.

Mortality after proximal hip fracture in the Singapore population

2005 ◽  
Vol 15 (3) ◽  
pp. 166-170 ◽  
Author(s):  
K.H. Lin ◽  
Y.W. Lim ◽  
Y.J. Wu ◽  
K.S. Lam
Keyword(s):  
Hip Fracture ◽  
Mortality Risk ◽  
Cox Regression ◽  
Regional Hospital ◽  
Age Group ◽  
Risk Of Death ◽  
The Past ◽  
The Mean ◽  
One Year

The aims were to prospectively assess the mortality risk following proximal hip fractures, identify factors predictive of increased mortality and to investigate the time trends in mortality with comparison to previous studies. Prospectively collected data from 68 consecutive patients who had been admitted to a regional hospital from May 2001 to September 2001 were reviewed. The mean age of the patients was 79.3 years old (range, 55–98) and 72.1% females. Patients were followed prospectively to determine the mortality risk associated with hip fracture over a two-year follow-up period. The acute in-hospital mortality rate at six months, one year and two years was 5.9% (4/68), 14.7% (10/68), 20.6% (14/68) and 25% (17/68) respectively. One-year and two-year mortality for those patients who were 80 or older was significantly higher than for other patients and the number of co-morbid illnesses also had significant effect. Cox regression was performed to determine the significant predictors for survival time. It was noted that patients 80 years or older were at higher risk of death compared with those less than 80 years as well as those with higher number of co-morbid illnesses. Our mortality rates have not declined in the past 10 years when compared with previous local studies. We conclude that for this group of patients studied, their mortality at one year and two years could be predicted by their age group and their number of co-morbid illnesses.

scholarly journals Religious affiliation and the risk of COVID 19 related mortality; a retrospective analysis of variation in pre and post lockdown risk by religious group in England and Wales

2020 ◽  
Author(s):  
Charlotte Hannah Gaughan ◽  
Daniel Ayoubkhani ◽  
Vahe Nafilyan ◽  
Peter Goldblatt ◽  
Chris White ◽  
...  
Keyword(s):  
Mortality Risk ◽  
Cox Regression ◽  
Religious Affiliation ◽  
Religious Groups ◽  
England And Wales ◽  
Risk Of Death ◽  
Before And After ◽  
The Difference ◽  
Behavioural Factors ◽  
The Uk

AbstractBackgroundCOVID 19 mortality risk is associated with demographic and behavioural factors; furthermore religious gatherings have been linked with the spread of COVID. We sought to understand the variation in the risk of COVID 19 related death across religious groups in the UK both before and after lockdown.MethodsWe conducted a retrospective cohort study of usual residents in England and Wales enumerated at the 2011 Census (n = 48,422,583), for risk of death involving COVID-19 using linked death certificates. Cox regression models were estimated to compare risks between religious groups. Time dependent religion coefficients were added to the model allowing hazard ratios (HRs) pre and post lockdown period to be estimated separately.ResultsCompared to Christians all religious groups had an elevated risk of death involving COVID-19; the largest age adjusted HRs were for Muslim and Jewish males at 2.5 (95% confidence interval 2.3-2.7) and 2.1 (1.9-2.5), respectively. The corresponding HRs for Muslim and Jewish females were 1.9 (1.7-2.1) and 1.5 (1.7-2.1). The difference in risk between groups contracted after lockdown. Those who affiliated with no religion had the lowest risk of COVID 19 related death before and after lockdown.ConclusionThe majority of the variation in COVID 19 mortality risk was explained by controlling for socio demographic and geographic determinants; however, Jews remained at a higher risk of death compared to all other groups. Lockdown measures were associated with reduced differences in COVID 19 mortality rates between religious groups, further research is required to understand the causal mechanisms.

scholarly journals Association of Retinal Age Gap with Arterial Stiffness and Incident Cardiovascular Disease

2022 ◽  
Author(s):  
Zhuoting Zhu ◽  
Yifan Chen ◽  
Wei Wang ◽  
Yueye Wang ◽  
Wenyi Hu ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Deep Learning ◽  
Arterial Stiffness ◽  
Regression Models ◽  
Cubic Splines ◽  
Fundus Images ◽  
Age Gap ◽  
One Year ◽  
Restricted Cubic Splines ◽  
Incident Cardiovascular Disease

Background: Retinal parameters could reflect systemic vascular changes. With the advances of deep learning technology, we have recently developed an algorithm to predict retinal age based on fundus images, which could be a novel biomarker for ageing and mortality. Objective: To investigate associations of retinal age gap with arterial stiffness index (ASI) and incident cardiovascular disease (CVD). Methods: A deep learning (DL) model was trained based on 19,200 fundus images of 11,052 participants without any past medical history at baseline to predict the retinal age. Retinal age gap (retinal age predicted minus chronological age) was generated for the remaining 35,917 participants. Regression models were used to assess the association between retinal age gap and ASI. Cox proportional hazards regression models and restricted cubic splines were used to explore the association between retinal age gap and incident CVD. Results: We found each one-year increase in retinal age gap was associated with increased ASI (β=0.002, 95% confidence interval [CI]: 0.001-0.003, P<0.001). After a median follow-up of 5.83 years (interquartile range [IQR]: 5.73-5.97), 675 (2.00%) developed CVD. In the fully adjusted model, each one-year increase in retinal age gap was associated with a 3% increase in the risk of incident CVD (hazard ratio [HR]=1.03, 95% CI: 1.01-1.06, P=0.012). In the restricted cubic splines analysis, the risk of incident CVD increased significantly when retinal age gap reached 1.21 (HR=1.05; 95% CI, 1.00-1.10; P-overall <0.0001; P-nonlinear=0.0681). Conclusion: We found that retinal age gap was significantly associated with ASI and incident CVD events, supporting the potential of this novel biomarker in identifying individuals at high risk of future CVD events.

Socioeconomic position and one-year mortality risk among patients with heart failure: A nationwide register-based cohort study

2019 ◽  
Vol 27 (1) ◽  
pp. 79-88 ◽  
Author(s):  
Julie Andersen ◽  
Thomas Alexander Gerds ◽  
Gunnar Gislason ◽  
Morten Schou ◽  
Christian Torp-Pedersen ◽  
...  
Keyword(s):  
Heart Failure ◽  
Mortality Risk ◽  
Socioeconomic Position ◽  
Educational Level ◽  
Cox Regression ◽  
National Health System ◽  
Risk Difference ◽  
Patients With Heart Failure ◽  
One Year ◽  
Income Quartile

Aims We sought to determine whether socioeconomic position affects the survival of patients with heart failure treated in a national healthcare system. Methods We linked national Danish registers, identified 145,690 patients with new-onset heart failure between 2000 and 2015, and obtained information on education and income levels. We analysed differences in survival by income quartile and educational level using multiple Cox regression, stratified by sex. We standardised one-year mortality risks according to income level by age, year of diagnosis, cohabitation status, educational level, comorbidities and medical treatment of all patients. We standardised one-year mortality risk according to educational level by age and year of diagnosis. Results One-year mortality was inversely related to income. In women the standardised average one-year mortality risk was 28.0% in the lowest income quartile and 24.3% in the highest income quartile, a risk difference of −3.8% (95% confidence interval (CI) −4.9% to −2.6%). In men the standardised one-year mortality risk was 26.1% in the lowest income quartile and 20.2% in the highest income quartile, a risk difference of −5.8% (95% CI −6.8% to −4.9%). Similar gradients in standardised mortality were present between the highest and lowest educational levels: −6.6% (95% CI −9.6% to −3.5%) among women and −5.0% (95% CI −6.3% to −3.7%) among men. Conclusions Income and educational level affect the survival of patients with heart failure, even in a national health system. Research is needed to investigate how socioeconomic differences affect survival.

LO21: One-year mortality of patients treated in the emergency department for an opioid overdose: a single-centre retrospective cohort study

CJEM ◽  
2019 ◽  
Vol 21 (S1) ◽  
pp. S14
Author(s):  
A. Jiang ◽  
J. Godwin ◽  
J. Moe ◽  
J. Buxton ◽  
A. Crabtree ◽  
...  
Keyword(s):  
Risk Factors ◽  
Emergency Department ◽  
Mortality Rate ◽  
Mortality Risk ◽  
Cox Regression ◽  
Opioid Overdose ◽  
Housing Status ◽  
Cox Regression Analysis ◽  
Index Visit ◽  
One Year

Introduction: Opioid overdoses (OODs) have become a public health emergency, yet little is known about their long-term outcomes following an OD. We determined the one-year all-cause mortality and associated risk factors in a cohort of patients treated in an urban emergency department (ED) for an OOD. Methods: We reviewed records of all patients who visited St. Paul's Hospital ED from January 2013 to August 2017 and had a discharge diagnosis of OOD or had received naloxone in the ED as per pharmacy records. Patients with a suspected OOD were identified on structured chart review. A patient's first visit for an OOD during the study period was used as the index visit, with subsequent visits excluded. The primary outcome was mortality during the year after the index visit. Mortality was assessed by linking patient electronic medical records with Vital Statistics data. Deaths that occurred in the ED on the index visit were excluded. Patients admitted to hospital following ED treatment were included in this study. We described patient characteristics, calculated mortality rates, and used Cox regression to identify risk factors. Results: A total of 2239 patients visited the ED for an OOD during the study period, with a median patient age of 37 years (IQR 29, 49). Males comprised 73% of patients, while 28% had no fixed address, and 21% received take-home naloxone at the index visit. In total, 137 patients (6.1%) died within 1 year of the index visit. Eighty-one deaths (3.6%) occurred within 6 months, including 24 deaths (1.1%) that occurred within 1 month. The highest mortality rate occurred in 2017, with 8.0% of patients entering the cohort that year dying within 1 year. Gender did not significantly impact mortality risk. A Cox regression analysis controlled for gender, housing status, and whether take-home naloxone was provided at the index visit indicated that advancing age (adjusted hazards ratio [AHR] 1.03; 95%CI: 1.01-1.04 for each year increase in age) and the index visit calendar year (AHR 1.30; 95%CI: 1.10-1.54 for each yearly increase in the study period) were significant factors for mortality within 1 year. Conclusion: The mortality rate following an opioid OD treated in the ED is high, with over 6% of patients in our study dying within 1 year. The rising mortality risk with increasing calendar year may reflect the growing harms of fentanyl-related OODs. Patients visiting the ED for an OOD should be considered high risk and offered preventative treatment and referrals prior to discharge.

scholarly journals 699 Sleep Health Traits and COVID-19: Mortality Risk from the UK Biobank

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A273-A273
Author(s):  
Xi Zheng ◽  
Ma Cherrysse Ulsa ◽  
Peng Li ◽  
Lei Gao ◽  
Kun Hu
Keyword(s):  
Risk Factors ◽  
Sleep Apnea ◽  
Sleep Duration ◽  
Sex Education ◽  
Mortality Risk ◽  
Self Report ◽  
Severe Illness ◽  
Uk Biobank ◽  
Sleep Health ◽  
The Uk

Abstract Introduction While there is emerging evidence for acute sleep disruption in the aftermath of coronavirus disease 2019 (COVID-19), it is unknown whether sleep traits contribute to mortality risk. In this study, we tested whether earlier-life sleep duration, chronotype, insomnia, napping or sleep apnea were associated with increased 30-day COVID-19 mortality. Methods We included 34,711 participants from the UK Biobank, who presented for COVID-19 testing between March and October 2020 (mean age at diagnosis: 69.4±8.3; range 50.2–84.6). Self-reported sleep duration (less than 6h/6-9h/more than 9h), chronotype (“morning”/”intermediate”/”evening”), daytime dozing (often/rarely), insomnia (often/rarely), napping (often/rarely) and presence of sleep apnea (ICD-10 or self-report) were obtained between 2006 and 2010. Multivariate logistic regression models were used to adjust for age, sex, education, socioeconomic status, and relevant risk factors (BMI, hypertension, diabetes, respiratory diseases, smoking, and alcohol). Results The mean time between sleep measures and COVID-19 testing was 11.6±0.9 years. Overall, 5,066 (14.6%) were positive. In those who were positive, 355 (7.0%) died within 30 days (median = 8) after diagnosis. Long sleepers (&gt;9h vs. 6-9h) [20/103 (19.4%) vs. 300/4,573 (6.6%); OR 2.09, 95% 1.19–3.64, p=0.009), often daytime dozers (OR 1.68, 95% 1.04–2.72, p=0.03), and nappers (OR 1.52, 95% 1.04–2.23, p=0.03) were at greater odds of mortality. Prior diagnosis of sleep apnea also saw a two-fold increased odds (OR 2.07, 95% CI: 1.25–3.44 p=0.005). No associations were seen for short sleepers, chronotype or insomnia with COVID-19 mortality. Conclusion Data across all current waves of infection show that prior sleep traits/disturbances, in particular long sleep duration, daytime dozing, napping and sleep apnea, are associated with increased 30-day mortality after COVID-19, independent of health-related risk factors. While sleep health traits may reflect unmeasured poor health, further work is warranted to examine the exact underlying mechanisms, and to test whether sleep health optimization offers resilience to severe illness from COVID-19. Support (if any) NIH [T32GM007592 and R03AG067985 to L.G. RF1AG059867, RF1AG064312, to K.H.], the BrightFocus Foundation A2020886S to P.L. and the Foundation of Anesthesia Education and Research MRTG-02-15-2020 to L.G.

scholarly journals Cystatin C predicts long term mortality better than creatinine in a nationwide study of intensive care patients

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Johanna Helmersson-Karlqvist ◽  
Miklos Lipcsey ◽  
Johan Ärnlöv ◽  
Max Bell ◽  
Bo Ravn ◽  
...  
Keyword(s):  
Intensive Care ◽  
Critically Ill ◽  
Risk Prediction ◽  
Cystatin C ◽  
Mortality Risk ◽  
Critically Ill Patients ◽  
Cox Regression ◽  
Sample Tube ◽  
Long Term Mortality

AbstractDecreased glomerular filtration rate (GFR) is linked to poor survival. The predictive value of creatinine estimated GFR (eGFR) and cystatin C eGFR in critically ill patients may differ substantially, but has been less studied. This study compares long-term mortality risk prediction by eGFR using a creatinine equation (CKD-EPI), a cystatin C equation (CAPA) and a combined creatinine/cystatin C equation (CKD-EPI), in 22,488 patients treated in intensive care at three University Hospitals in Sweden, between 2004 and 2015. Patients were analysed for both creatinine and cystatin C on the same blood sample tube at admission, using accredited laboratory methods. During follow-up (median 5.1 years) 8401 (37%) patients died. Reduced eGFR was significantly associated with death by all eGFR-equations in Cox regression models. However, patients reclassified to a lower GFR-category by using the cystatin C-based equation, as compared to the creatinine-based equation, had significantly higher mortality risk compared to the referent patients not reclassified. The cystatin C equation increased C-statistics for death prediction (p < 0.001 vs. creatinine, p = 0.013 vs. combined equation). In conclusion, this data favours the sole cystatin C equation rather than the creatinine or combined equations when estimating GFR for risk prediction purposes in critically ill patients.

scholarly journals Soluble urokinase-type plasminogen activator receptor (suPAR) is a risk indicator for eGFR loss in kidney transplant recipients

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ulrich Jehn ◽  
Katharina Schütte-Nütgen ◽  
Ute Henke ◽  
Hermann Pavenstädt ◽  
Barbara Suwelack ◽  
...  
Keyword(s):  
Kidney Transplantation ◽  
Cox Regression ◽  
Kidney Diseases ◽  
Prognostic Significance ◽  
Risk Indicator ◽  
Kidney Transplant Recipients ◽  
Supar Level ◽  
Type Plasminogen Activator ◽  
Urokinase Type Plasminogen Activator ◽  
One Year

AbstractThe prognostic significance of suPAR in various kidney diseases has recently been demonstrated. Its role in transplantation-specific outcomes is still largely unknown. Therefore, we prospectively investigated the prognostic relevance of suPAR in patients before and one year after kidney transplantation (KTx). We included 100 patients who had received a kidney transplantation between 2013 and 2015. The plasma concentration of suPAR was measured by ELISA assay. In recipients of living donations (LD), pre-transplant suPAR levels were significantly lower than those of recipients of deceased donations (DD). After KTx, suPAR levels significantly declined in LD and DD recipients, without a detectable difference between both groups any more. Higher suPAR levels in recipients one year after KTx were associated with a more severe eGFR loss in the following three years in multivariable cox-regression (n = 82, p = 0.021). suPAR-levels above 6212 pg/ml one year after KTx are associated with eGFR loss > 30%, which occurred almost twice as fast as in patients with suPAR ≤ 6212 pg/ml (p < 0.001). Hence, suPAR level at one year mark might be a risk indicator of increased eGFR loss.

scholarly journals Improved renal allograft survival for pre-emptive paediatric renal transplant recipients in the UK

2021 ◽  
pp. archdischild-2020-321277
Author(s):  
Matko Marlais ◽  
Kate Martin ◽  
Stephen D Marks
Keyword(s):  
Peritoneal Dialysis ◽  
Renal Transplant ◽  
Renal Allograft ◽  
Cox Regression ◽  
Renal Transplant Recipients ◽  
Transplant Recipients ◽  
Allograft Survival ◽  
Significant Difference ◽  
Donor Type ◽  
The Uk

BackgroundThe aim of this study was to investigate whether being on dialysis at the time of renal transplantation affected renal allograft survival in paediatric renal transplant recipients (pRTRs).MethodsRetrospective study of UK Transplant Registry (National Health Service Blood and Transplant) data on all children (aged <18 years) receiving a kidney-only transplant from 1 January 2000 to 31 December 2015. Kaplan-Meier estimates of patient and renal allograft survival calculated and Cox regression modelling accounting for donor type. The relationship between time on dialysis and renal allograft survival was examined.Results2038 pRTRs were analysed: 607 (30%) were pre-emptively transplanted, 789 (39%) and 642 (32%) on peritoneal dialysis and haemodialysis, respectively, at the time of transplantation. Five-year renal allograft survival was significantly better in the pre-emptively transplanted group (90.6%) compared with those on peritoneal dialysis and haemodialysis (86.4% and 85.7%, respectively; p=0.02). After accounting for donor type, there was a significantly lower hazard of 5-year renal allograft failure in pre-emptively transplanted children (HR 0.742, p=0.05). Time spent on dialysis pre-transplant negatively correlated with renal allograft survival (p=0.002). There was no significant difference in 5-year renal allograft survival between children who were on dialysis for less than 6 months and children transplanted pre-emptively (87.5% vs 90.5%, p=0.25).ConclusionsPre-emptively transplanted children have improved 5-year renal allograft survival, compared with children on dialysis at the time of transplantation. Although increased time spent on dialysis correlated with poorer renal allograft survival, there was no evidence that short periods of dialysis pre-transplant affected renal allograft survival.

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