Frailty Phenotypes and Relations With Surgical Outcomes: A Latent Class Analysis

Sadiq, Furqaan; Kronzer, Vanessa L.; Wildes, Troy S.; McKinnon, Sherry; Sharma, Anshuman; Helsten, Daniel L.; Scheier, Lawrence M.; Avidan, Michael S.; Abdallah, Arbi Ben

doi:10.1213/ane.0000000000003695

Cited by 16 publications

(22 citation statements)

References 53 publications

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“…1, Additional File 1 ). In accordance with earlier research [ 14 , 24 , 25 ], we labeled these domains as: mobility ( n = 4), instrumental health ( n = 6), emotional wellbeing ( n = 4), comorbidity ( n = 4), respiratory symptoms ( n = 3), cardiac symptoms ( n = 5), and physical activity ( n = 4). Indicators for each domain are outlined in Table 2 .…”

Section: Resultsmentioning

confidence: 98%

“…We used exploratory factor analysis to reduce the total number of items for estimation feasibility in the LPA. These results produced separable health domains that were interpreted on the basis of previous research [ 14 , 24 , 25 ]. The proportion of deficits accumulated in each domain was calculated for each participant and used as continuous observed indicators in the LPA.…”

Section: Introductionmentioning

confidence: 80%

“…Nevertheless, few studies have employed data-driven statistical techniques to distinguish frailty profiles based on multidomain deficit accumulation. Recently, Sadiq and colleagues [ 14 ] assembled 18 items related to physical, functional, emotional, and social deficits and subjected these data to an LCA. Findings revealed three discrete frailty profiles that differed primarily in overall severity: (a) not frail , which was characterized by minimal impairment across all morbidity indicators, (b) moderately frail , which was characterized by moderate physical and functional limitations, and (c) severely frail , which was characterized by severe limitations in physical, functional, and emotional health.…”

Section: Introductionmentioning

confidence: 99%

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Portals to frailty? Data-driven analyses detect early frailty profiles

et al. 2021

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Background Frailty is an aging condition that reflects multisystem decline and an increased risk for adverse outcomes, including differential cognitive decline and impairment. Two prominent approaches for measuring frailty are the frailty phenotype and the frailty index. We explored a complementary data-driven approach for frailty assessment that could detect early frailty profiles (or subtypes) in relatively healthy older adults. Specifically, we tested whether (1) modalities of early frailty profiles could be empirically determined, (2) the extracted profiles were differentially related to longitudinal cognitive decline, and (3) the profile and prediction patterns were robust for males and females. Methods Participants (n = 649; M age = 70.61, range 53–95) were community-dwelling older adults from the Victoria Longitudinal Study who contributed data for baseline multi-morbidity assessment and longitudinal cognitive trajectory analyses. An exploratory factor analysis on 50 multi-morbidity items produced 7 separable health domains. The proportion of deficits in each domain was calculated and used as continuous indicators in a data-driven latent profile analysis (LPA). We subsequently examined how frailty profiles related to the level and rate of change in a latent neurocognitive speed variable. Results LPA results distinguished three profiles: not-clinically-frail (NCF; characterized by limited impairment across indicators; 84%), mobility-type frailty (MTF; characterized by impaired mobility function; 9%), and respiratory-type frailty (RTF; characterized by impaired respiratory function; 7%). These profiles showed differential neurocognitive slowing, such that MTF was associated with the steepest decline, followed by RTF, and then NCF. The baseline frailty index scores were the highest for MTF and RTF and increased over time. All observations were robust across sex. Conclusions A data-driven approach to early frailty assessment detected differentiable profiles that may be characterized as morbidity-intensive portals into broader and chronic frailty. Early inventions targeting mobility or respiratory deficits may have positive downstream effects on frailty progression and cognitive decline.

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Section: Resultsmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 80%

Section: Introductionmentioning

confidence: 99%

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Portals to frailty? Data-driven analyses detect early frailty profiles

et al. 2021

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“…Some of them have used cluster analytical techniques, while others have used latent class analytic techniques. All these studies have had different scopes, for example using samples from the general population [ 13 , 14 , 15 ], only a part of the general population such as women [ 16 ], or patients of a hospital [ 17 ]. Additionally, the studies on frailty profiles have used a variety of indicators to get the profiles.…”

Section: Introductionmentioning

confidence: 99%

“…Additionally, the studies on frailty profiles have used a variety of indicators to get the profiles. Some of these studies only used Fried’s criteria [ 13 , 14 , 15 , 16 , 18 ], while others included psychosocial indicators of frailty and/or related problems [ 3 , 11 , 17 , 19 ].…”

Section: Introductionmentioning

confidence: 99%

Frailty Status Typologies in Spanish Older Population: Associations with Successful Aging

Tomás

Sentandreu‐Mañó

Fernández

2020

IJERPH

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Background: Defining frailty typologies would contribute to guiding specific care interventions. These typologies could additionally be related to different health outcomes. This study aims at identifying subgroups of frail older adults based on the physical frailty phenotype and examining the relationships of these frailty profiles with quality of life and perceived health. Methods: This study relies on data from the SHARE project, namely a representative sample of 1765 Spanish-dwelling older adults identified as frail or pre-frail. Analysis included general descriptive statistics, exploratory latent class analysis (LCA) to determine the number of frailty subgroups, and LCA with covariates to examine differential relationships with markers of successful aging. Results: Statistical criteria and interpretability of the classes suggested that the LCA model with four classes should be retained. Class 1 was identified as the “frail people” group, Class 2 “activity problems” group, Class 3 “fatigued” group, and those belonging to Class 4 “lack of strength” group. Final LCA with covariates showed lower levels of quality of life and perceived health of the “frail” as compared to other frailty subgroups. Conclusion: This study revealed four different patterns of frailty attributes and further offered evidence on individuals’ differential status of health regarding distinct frailty conditions.

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Significance of osteopenia in elderly patients undergoing emergency gastrointestinal surgery

Takano

Tsukihara

Kai

et al. 2022

Annals of Gastroent Surgery

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Aim Frailty assessment in elderly patients is crucial to predict the postoperative course, considering that frailty is highly associated with postoperative complications and mortality. The aim of this study was to evaluate the value of osteopenia as a risk factor for severe postoperative complications in elderly patients who underwent emergency gastrointestinal surgery. Methods This study comprised 103 elderly patients who underwent emergency gastrointestinal surgery. Osteopenia was diagnosed by measuring bone mineral density, which was calculated as the average pixel density in the midvertebral core at the 11th thoracic vertebra on the preoperative plain computed tomography image. We retrospectively investigated the relationship between preoperative osteopenia and severe postoperative complications (Clavien–Dindo classification ≥III). Univariate and multivariate analyses were performed to evaluate the risk factors for severe postoperative complications. Results Twenty‐three patients (22.3%) developed severe postoperative complications. The optimal cutoff value of bone mineral density for severe postoperative complications was 119.5 Hounsfield unit (HU) and 39 patients (37.9%) were diagnosed with osteopenia. The univariate analysis revealed that the American Society of Anesthesiologists Physical Status of ≥3 (P = .0084), hemoglobin levels (P = .0026), albumin levels (P < .001), sarcopenia (P = .015), and osteopenia (P < .001) were significantly associated with severe postoperative complications. The multivariate analysis showed that osteopenia (P = .014) was an independent risk factor for severe postoperative complications. Conclusion Osteopenia may be a risk factor for severe postoperative complications in elderly patients after emergency gastrointestinal surgery.

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Frailty Phenotypes and Relations With Surgical Outcomes: A Latent Class Analysis

Cited by 16 publications

References 53 publications

Portals to frailty? Data-driven analyses detect early frailty profiles

Portals to frailty? Data-driven analyses detect early frailty profiles

Frailty Status Typologies in Spanish Older Population: Associations with Successful Aging

Significance of osteopenia in elderly patients undergoing emergency gastrointestinal surgery

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