EWGSOP 2 vs. EWGSOP 1: impact on the prevalence of sarcopenia and its outcomes

peer reviewe

Neurofilament light chain concentration in an aging population.

BACKGROUND: Neurofilament light chain (NF-L) concentration is recognized to be modified in neurological diseases and traumatic brain injuries, but studies in the normal aging population are lacking. It is, therefore, urgent to identify influencing factors of NF-L concentration in the aging population. METHOD: We assessed NF-L concentration in sera of a large cohort of 409 community-dwelling adults aged over 65 years. We studied the association between NF-L and various physiological factors but also with self-reported comorbidities or life-style habits. RESULTS: We showed that NF-L concentration in serum was tightly associated with cystatin C concentration (r = 0.501, p  5 points) in both univariate and multivariate analysis. Finally, we are providing reference ranges by age categories for subjects with or without altered renal function. CONCLUSION: NF-L concentration in the aging population is not driven by the increasing number of comorbidities or depression. Yet, NF-L blood concentration is dependent on kidney function and NF-L interpretation in patients suffering from renal failure should be taken with caution

Intrinsic capacity and its association with mortality over 3 years in nursing homes: Results of the SENIOR cohort

peer reviewe

An Assessment of the Toulouse Saint Louis University Mini Falls Assessment Tool to Predict Incident Falls among Older Adults Residing in Nursing Homes: A 6-Month Prospective Study

OBJECTIVES: Toulouse Saint Louis University Mini Falls Assessment (TSLUMFA) tool has been designed to predict falls. It was initially validated in a geriatric clinic in 2018. The primary objective was to evaluate the predictive capacity of the TSLUMFA for incident falls in older adults residing in nursing homes. The secondary objective was to determine the TSLUMFA optimal cut-off value identifying those older adults with a high-risk of falling. SETTINGS: A longitudinal study was carried out over a period of six months. PARTICIPANTS: 93 older adults residing in nursing homes were evaluated for the present study. MEASUREMENTS: The TSLUMFA (made up of 7 criteria) was administered at baseline, and incident falls were recorded based on a registry of falls. Comparisons of TSLUMFA scores between fallers and non-fallers were performed using the U Mann-Whitney test or Chi². Correlation between the total TSLUMFA score (/30 points) and incident fall(s) was explored using the Cox proportional hazard model. ROC analysis enabled an optimal cut-off value to be established to identify those adults at the highest-risk of falling. RESULTS: In the study, 93 older adults (61.3% women) with a median age of 80 (69-87) years were included. The median total TSLUMFA score was 21 (19-24.5) points. During the 6-month study period, 38 subjects (40.9%) experienced at least one fall. The total TSLUMFA score in older adults with incident fall(s) was significantly lower than in those who did not fall (20 (15.75-22.25) points versus 23 (20-25) points and a p-value of <0.001). For each 1-point higher score at the total TSLUMFA a 9% less chance of falling was observed during the study period (p-value = 0.006). The AUC was 0.736 (95%CI: 0.617-0.822) and p-value <0.001, clearly demonstrating its interesting performance as a screening tool. A score of ≤ 21 points was identified as the optimal cut-off to identify those older adults at a higher-risk of falling. CONCLUSION: The TSLUMFA performed well and successfully identified older adults with a high risk of falling in a nursing home setting. Further comparisons with existing tools are warranted

An assessment of the Toulouse Saint Louis University mini falls assessment tool to predict incident falls among older adults residing in nursing homes: a 6-month prospective study

peer reviewe

Assessment of the performance of the SarQoL questionnaire in screening for sarcopenia in older people

Background: Because of its low prevalence and the need for physical tests to establish a diagnosis, recruiting sarcopenic people for clinical studies can be a resource-intensive process. Aims: We investigated whether the SarQoL®, a 55-item questionnaire designed to measure quality of life in sarcopenia, could be used to identify older people with a high likelihood of being sarcopenic, and to compare its performance to the SARC-F tool. Methods: We performed a secondary analysis of data from older, community-dwelling participants of the SarcoPhAge study, evaluated for sarcopenia according to the EWGSOP2 criteria, and who completed the SarQoL® and SARC-F questionnaires. We determined the optimal threshold to distinguish between sarcopenic and non-sarcopenic people with the Youden index. Screening performance was evaluated with the area under the curve (AUC) and by calculating sensitivity and specificity. Results: The analysis of 309 participants provided an optimal threshold value of ≤ 52.4 points for identifying people with sarcopenia with the SarQoL® questionnaire, which resulted in a sensitivity of 64.7% (41.1–84.2%), a specificity of 80.5% (75.7–84.7%) and an AUC of 0.771 (0.652–0.889). Compared to the SARC-F, the SarQoL® has greater sensitivity (64.7% vs 52.39%), but slightly lower specificity (80.5% vs. 86.6%). Discussion: The SarQoL® questionnaire showed acceptable screening accuracy, on par with the SARC-F. The optimal threshold of ≤ 52.4 points should be confirmed in other cohorts of older people. Conclusions: This exploratory study showed that the SarQoL® could potentially be applied in a screening strategy, with the added benefit of providing a measure of QoL at the same time

Intrinsic Capacity Defined Using Four Domains and Mortality Risk: A 5-Year Follow-Up of the SarcoPhAge Cohort

peer reviewedObjectives: The concept of 'intrinsic capacity' (IC) offers a new way to approach another concept, that of 'healthy aging'. The first objective of the present study was to assess the ability of the construct of 'intrinsic capacity' to predict death. The second objective was to assess whether deteriorations in intrinsic capacity, measured over 1 and 2 years, are predictive of death. Design: The present analysis was based on a prospective cohort study. Setting: Community-dwelling participants. Participants: The study recruited older adults aged 65 years and older. Measurements: Intrinsic capacity (IC) encompasses five domains: sensorial (not evaluated here), cognition (Mini-Mental State Examination), nutrition (Mini-Nutritional Assessment), mobility (Short Physical Performance Battery), and psychological (Geriatric Depression Scale). Each domain was considered satisfactory when its assessment, for an individual, was above the threshold defined by the initial validation of the domain assessment tool. To explore the relationship between IC and mortality risk, a Cox model was applied. The predictive value of the dynamic aspects (i.e., changes over 1 year and 2 years) was investigated using the following categorization of IC: stable, deteriorated, improved. Results: The sample was composed of 481 volunteers aged 73.4±6.12 years (60.1% women). Two satisfactory IC domains appeared to be significantly associated with reduced mortality risk: the satisfactory mobility domain (adjusted HR=0.45 [0.26-0.79]) and the satisfactory psychological domain (adjusted HR = 0.56 [1.04-3.09]). When considering intrinsic capacity as a whole construct, using a composite Z-score, we noticed that the risk of death was decreased by 49% for an increase of 1 standard deviation in IC. Changes in intrinsic capacity in the mobility and psychological domains led to an increased risk of death (from 2.74 to 4.18-fold). Conclusion: The concept of intrinsic capacity seems highly relevant in order to assess older adults' health and well-being. This concept should be considered for integration into clinical practice

Clinical prediction models for diagnosis of COVID-19 among adult patients: a validation and agreement study.

peer reviewed[en] BACKGROUND: Since the beginning of the pandemic, hospitals have been constantly overcrowded, with several observed waves of infected cases and hospitalisations. To avoid as much as possible this situation, efficient tools to facilitate the diagnosis of COVID-19 are needed. OBJECTIVE: To evaluate and compare prediction models to diagnose COVID-19 identified in a systematic review published recently using performance indicators such as discrimination and calibration measures. METHODS: A total of 1618 adult patients present at two Emergency Department triage centers and for whom qRT-PCR tests had been performed were included in this study. Six previously published models were reconstructed and assessed using diagnostic tests as sensitivity (Se) and negative predictive value (NPV), discrimination (Area Under the Roc Curve (AUROC)) and calibration measures. Agreement was also measured between them using Kappa's coefficient and IntraClass Correlation Coefficient (ICC). A sensitivity analysis has been conducted by waves of patients. RESULTS: Among the 6 selected models, those based only on symptoms and/or risk exposure were found to be less efficient than those based on biological parameters and/or radiological examination with smallest AUROC values ( 0.75 for Se and NPV but poor agreement (Kappa and ICC < 0.5) between them. The results of the first wave were similar to those of the second wave. CONCLUSION: Although quite acceptable and similar results were found between all models, the importance of radiological examination was also emphasized, making it difficult to find an appropriate triage system to classify patients at risk for COVID-19