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#frailty

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Christos Argyropoulos MD, PhD

Surviving the #frailty of time to event analysis in massive datasets with Generalized Additive Models (and the help of Simon Laplace)

arxiv.org/abs/2503.10823

#rstats
(I wish I didn't have to finish 2 PPT this weekend - it screwed finishing with the #github repo)

arXiv.orgSurviving the frailty of time to event analysis in massive datasets with Generalized Additive Models (and the help of Simon Laplace)Analyses of time to event datasets have been invariably based on the Cox proportional hazards model (PHM). Reformulations of the PHM as a Poisson Generalized Additive Model (GAM) or as a Generalized Linear Mixed Model (GLMM) have been proposed in the literature, aiming to increase the flexibility of the PHM and allow its use in situations in which complex spatiotemporal relationships have to be taken into account when modeling survival. In this report, we provide a unified framework for considering these previous attempts and consider the implementation in software for GAM and GLMM in the R programming language. The connection between GAM/GLMM and the PHM is leveraged to provide computationally efficient implementations for a subclass of survival models that incorporate individual random effects ('frailty models'). Frailty models provide a unified method to address repeated events, correlated outcomes and also time varying visitation schedules when analyzing Electronic Health Record data. However the current implementation of frailty models in software facilities for the Cox model does not scale because of long computation times; conversely the direct implementation of individual random effects in GAM/GLMM software does not scale well with memory usage. We propose a two stage method for survival models with frailty based on the Laplace approximation. Using a D-optimal experimental design to simulate the performance of the proposed method across simulated datasets we illustrate that the proposed method can circumvent the limitations of existing implementations, opening up the possibility to model datasets of hundred of thousands to million individuals using high end workstations from within R.
Public
Christos Argyropoulos MD PhD

Surviving the #frailty of time to event analysis in massive datasets with Generalized Additive Models (and the help of Simon Laplace)

arxiv.org/abs/2503.10823

#rstats
(I wish I didn't have to finish 2 PPT this weekend - it screwed finishing with the #github repo)

arXiv.orgSurviving the frailty of time to event analysis in massive datasets with Generalized Additive Models (and the help of Simon Laplace)Analyses of time to event datasets have been invariably based on the Cox proportional hazards model (PHM). Reformulations of the PHM as a Poisson Generalized Additive Model (GAM) or as a Generalized Linear Mixed Model (GLMM) have been proposed in the literature, aiming to increase the flexibility of the PHM and allow its use in situations in which complex spatiotemporal relationships have to be taken into account when modeling survival. In this report, we provide a unified framework for considering these previous attempts and consider the implementation in software for GAM and GLMM in the R programming language. The connection between GAM/GLMM and the PHM is leveraged to provide computationally efficient implementations for a subclass of survival models that incorporate individual random effects ('frailty models'). Frailty models provide a unified method to address repeated events, correlated outcomes and also time varying visitation schedules when analyzing Electronic Health Record data. However the current implementation of frailty models in software facilities for the Cox model does not scale because of long computation times; conversely the direct implementation of individual random effects in GAM/GLMM software does not scale well with memory usage. We propose a two stage method for survival models with frailty based on the Laplace approximation. Using a D-optimal experimental design to simulate the performance of the proposed method across simulated datasets we illustrate that the proposed method can circumvent the limitations of existing implementations, opening up the possibility to model datasets of hundred of thousands to million individuals using high end workstations from within R.
Public
Christos Argyropoulos MD, PhD

The #Perl DRAM monitor has worked flawlessly for 6 wks now, gathering memory use data for the performance oriented #survival analysis #frailty code I wrote in #rstats. Only a few loose ends to finish the preprint & #github repo

chrisarg.github.io/Killing-It-

chrisarg.github.io/Killing-It-

Killing-It-with-PERL · Profiling Peak DRAM Use in R With Perl - Part 2In the second part of this we implement the solution that was outlines at the end of Part 1: utilize a Perl application that probes the operating system in real time for the RSS (Resident Set Size), i.e. the DRAM footprint of an application fire the application from within R as a separate process, provide it with the PID (Process ID) of the R session and put it in the background do the long, memory hungry application upon the end of the calculation kill the Perl application and obtain DRAM usage for use within R
Public
Matteo Cesari

Integrated #care for older people (ICOPE)‎: guidance for person-centred assessment and pathways in primary care, 2nd edition

#ICOPE aims to reorient #health and #social services towards person-centred and coordinated care. It supports the delivery of integrated care for older people within the context of a PHC-oriented #health system

#Geriatrics #Aging #Ageing #Frailty #IntegratedCare #WHO #MedMastodon

Available here👇
iris.who.int/handle/10665/3801

Public
Matteo Cesari

Enhancing #Emergency care for older persons: the role and impact of the electronic #Frailty Index

"...The integration of the eFI into ED settings can enable more precise risk stratification and resource allocation, significantly improving patient management and #healthcare delivery for older persons in these urgent care contexts..."

#Geriatrics #Health #Care #Medicine #MedMastodon #Ageing #Aging

link.springer.com/article/10.1

SpringerLinkEnhancing emergency care for older persons: the role and impact of the electronic Frailty Index - GeroScienceAs the elderly population expands, enhancing emergency department (ED) care by assessing frailty becomes increasingly vital. To address this, we developed a novel electronic Frailty Index (eFI) from ED health records, specifically designed to assess frailty and predict hospitalization, in-hospital mortality, ICU admissions, and 30-day ED readmissions. This retrospective, single-center study included patients 65 years old or older who presented to the ED of IRCCS Humanitas Research Hospital in Milan, Italy, between January 2015 and December 2019. Frailty was assessed using a novel electronic Frailty Index (eFI), based on the cumulative deficit model, incorporating 45 health deficits to quantify frailty. Patients were divided into four quartiles based on eFI scores to explore the association between frailty levels and adverse outcomes, including hospitalization, in-hospital mortality, ICU admission, and 30-day ED readmission. The study included 21,537 patients (mean age 77.4, 50.7% males). The median eFI score was 0.16. Hospitalization rates rose significantly with frailty, from 20% in the least frail quartile to 43% in the most frail. Similarly, in-hospital mortality and ICU admissions increased markedly with higher eFI scores, with mortality rates climbing from 0.44 to 5.0% across quartiles. The 30-day ED readmission rates significantly rose from 9.9 to 19.8%. For every 0.01 increase in eFI score, the odds of hospitalization, in-hospital mortality, ICU admission, and 30-day ED readmission significantly increased (P < 0.0001). Specifically, the adjusted odds ratios (OR) for hospitalization, in-hospital mortality, ICU admission, and ED readmission rose to 3.55, 14.15, 4.70, and 2.22, respectively (P < 0.0001), in the most frail compared to the least frail quartile. The integration of the eFI into ED settings can enable more precise risk stratification and resource allocation, significantly improving patient management and healthcare delivery for older persons in these urgent care contexts.
Public
Auscandoc

Characteristics of older patients undergoing in the UK: SNAP-3, a snapshot observational study - PubMed pubmed.ncbi.nlm.nih.gov/397654 “In the UK, one in five older patients undergoing surgery is living with , and almost two-thirds of older patients are living with . These data highlight the importance of frailty screening. “

PubMedCharacteristics of older patients undergoing surgery in the UK: SNAP-3, a snapshot observational study - PubMedIn the UK, one in five older patients undergoing surgery is living with frailty, and almost two-thirds of older patients are living with multimorbidity. These data highlight the importance of frailty screening. In addition, they can serve to guide resource allocation and provide comparative estimate …
Public *
David Haigh

Aim to be a zero.

Try to be useful.

Plan for the things that can kill you.

Sweat the small stuff.

Work the problem.

Keep a sense of wonder.

This book, recommended by a friend, offers amazing life lessons, grounded in #humanity, #frailty, and #humility, driven from a perspective most of us only dream of - #astronaut and space station commander Chris Hatfield.

I wish more of our #leaders would give it a read and give it a try. #Canada would be a better country if we all did.

Cover of "An Astronaut's Guide to Life On Earth" by Chris Hatfield
Public
Simon Mooijaart

🥳 Huge congratulations to Estelle Tran Van Hoi for pulling of this impressive paper

📔 Blood based immune #biomarkers associated with clinical #frailty scale in older patients with melanoma receiving checkpoint inhibitor #immunotherapy

❓What is association with outcomes?

🔗 doi.org/10.1186/s12979-024-004

BioMed CentralBlood based immune biomarkers associated with clinical frailty scale in older patients with melanoma receiving checkpoint inhibitor immunotherapy - Immunity & AgeingIntroduction Immunotherapy with checkpoint inhibition (ICI) is increasingly prescribed to older patients with cancer. High age, especially in combination with frailty, has been associated to immune senescence, which is the age-related decline in immune function, thereby possibly hindering ICI effectiveness. This cross-sectional study aimed to assess whether blood cell immune senescence markers are associated with age, frailty and response to anti-PD-1 treatment in older patients with metastatic melanoma. Methods In a prospective observational study, sixty patients with stage IIIC or IV melanoma undergoing anti-PD1 treatment were categorized into young (< 65 years; n = 22), old (> 65 years) without frailty (n = 19), and old with frailty (n = 19). In-depth immune cell phenotyping was performed in baseline blood samples (prior to treatment) using multispectral flow cytometry and compared between groups and with immunotherapy treatment response. Antigen-presenting cell capacity was evaluated using mixed lymphocyte reaction and T cell proliferative potential was assessed using PHA proliferation assay. Results No significant differences in treatment response rates were observed across age groups. Older patients, irrespective of frailty, showed lower levels of naïve CD8 + T cells, with the old and frail group also exhibiting reduced tissue-resident effector memory CD8 + T cells and CD8 + mucosal associated invariant T (MAIT) cells. These differences were not associated with treatment outcomes. T cell proliferation and antigen-presenting cell capacities did not differ across groups. Conclusion Several ageing and frailty associated changes were detected among circulating immune cells in blood but were not associated with response to immunotherapy in our study. While these findings suggest that the level of frailty and ageing may not necessarily preclude the efficacy of ICI therapy, further investigation is needed to fully understand the impact of frailty and ageing on immunotherapy.
#geriatrics#cancer#oncology
Public
Ecology & Evolution of Health

Congratulations to Thomas Beneteau for his in-depth analysis of the #incidence and #duration of #HPV infections in young women using multivariate #Cox regression models with #frailty effects.

This work based on the #PAPCLEAR #cohort in #Montpellier and the #EVOLPROOF project is now published in #InfectiousDiseases.

#DM for a #PDF version until we can opt for #GreenOpenAccess.

doi.org/10.1080/23744235.2024.

Public
Matteo Cesari

Exploring the Role of #Antibiotics in Hospice #Care - The Journal of #Frailty & #Aging

There is still much work to do to improve #antibiotic prescriptions in #hospice care...

#Geriatrics #PalliativeCare #Health #Medicine #MedMastodon

link.springer.com/article/10.1

SpringerLinkExploring the Role of Antibiotics in Hospice Care - The Journal of Frailty & AgingBackground The decision regarding the use of antibiotics in hospice care, whether to initiate, defer, or discontinue therapy, presents challenges. This study aims to explore the characteristics of terminally ill patients associated with antimicrobial use in hospice. Methods Data are from a registry study enrolling patients admitted to hospice after discharge from a hospital. Three-hundred-sixty-six persons aged 18 and older were considered for the present analysis. Collected data encompassed demographic information, medical history, and outcomes assessed through a comprehensive geriatric assessment. Results Among the patients admitted to the hospice, 242 individuals did not receive antibiotics (Group A), and 91 (24.6%) were already undergoing antibiotic therapy at admission. Of these, 59 (65.6%) patients (Group B) continued the treatment, while 32 (35.6%; Group C) discontinued it. Additionally, 33 patients (Group D) initiated an antibiotic treatment during their hospice stay. Patients undergoing antibiotic therapy (Group D) presented higher residual functions than the other groups, especially compared to Group C (p<0.001). The four groups also differed in mortality risk. In particular, Cox proportional hazard models indicated that Group D presented a lower risk of death than Group A, even after adjustment for age, sex, estimated poor prognosis and two different performance status (PS ECOG, Karnofsky PS). Conclusion A relatively high number of persons admitted to the hospice receive antibiotic therapy without apparent benefit. The decision to prescribe antibiotics in hospice care appears to be based on the patient’s functional performance and estimated prognosis.
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