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The Application of Digital Frailty Screening to Triage Nonhealing and Complex Wounds

Objective: We investigated the association between the complexity of diabetic foot ulcers (DFUs) and frailty. Research Design and Methods: Individuals (n = 38) with Grade 2 Wagner DFU were classified into 3 groups based on the Society for Vascular Surgery risk-stratification for major limb amputatio...

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Published in:Journal of diabetes science and technology 2024-03, Vol.18 (2), p.389-396
Main Authors: Mishra, Ram Kinker, Bara, Rasha O., Zulbaran-Rojas, Alejandro, Park, Catherine, Fernando, Malindu E., Ross, Jeffrey, Lepow, Brian, Najafi, Bijan
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cited_by cdi_FETCH-LOGICAL-c3544-5004ab089dcbd37fed5d7ce8fa0457301ef0ad5790afd61a759c66000ca43ee53
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container_end_page 396
container_issue 2
container_start_page 389
container_title Journal of diabetes science and technology
container_volume 18
creator Mishra, Ram Kinker
Bara, Rasha O.
Zulbaran-Rojas, Alejandro
Park, Catherine
Fernando, Malindu E.
Ross, Jeffrey
Lepow, Brian
Najafi, Bijan
description Objective: We investigated the association between the complexity of diabetic foot ulcers (DFUs) and frailty. Research Design and Methods: Individuals (n = 38) with Grade 2 Wagner DFU were classified into 3 groups based on the Society for Vascular Surgery risk-stratification for major limb amputation as Stage 1 at very low risk (n = 19), Stage 2 at low risk (n = 9), and Stage 3 to 4 at moderate-to-high risk (n = 10) of major limb amputation. Frailty status was objectively assessed using a validated digital frailty meter (FM). The FM works by quantifying weakness, slowness, rigidity, and exhaustion over a 20-second repetitive elbow flexion-extension exercise using a wrist-worn sensor. FM generates a frailty index (FI) ranging from 0 to 1; higher values indicate progressively greater severity of frailty. Skin perfusion pressure (SPP), albumin, and tissue oxygenation level (SatO2) were also measured. One-way analysis of variance (ANOVA) was used to identify group effect for wound complexity. Pearson’s correlation coefficient was used to assess the associations with frailty and clinical endpoints. Results: Frailty index was higher in Stage 3 and 4 as compared to Stage 1 (d = 1.4, P < .01) and Stage 2 (d = 1.2, P < .01). Among assessed frailty phenotypes, exhaustion was correlated with SPP (r = −0.63, P < .01) and albumin (r = −0.5, P < .01). Conclusion: Digital biomarkers of frailty may predict complexity of DFU and thus triage individuals who can be treated more simply in their primary clinic versus higher risk patients who require prompt referral to multidisciplinary, more complex care.
doi_str_mv 10.1177/19322968221111194
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Research Design and Methods: Individuals (n = 38) with Grade 2 Wagner DFU were classified into 3 groups based on the Society for Vascular Surgery risk-stratification for major limb amputation as Stage 1 at very low risk (n = 19), Stage 2 at low risk (n = 9), and Stage 3 to 4 at moderate-to-high risk (n = 10) of major limb amputation. Frailty status was objectively assessed using a validated digital frailty meter (FM). The FM works by quantifying weakness, slowness, rigidity, and exhaustion over a 20-second repetitive elbow flexion-extension exercise using a wrist-worn sensor. FM generates a frailty index (FI) ranging from 0 to 1; higher values indicate progressively greater severity of frailty. Skin perfusion pressure (SPP), albumin, and tissue oxygenation level (SatO2) were also measured. One-way analysis of variance (ANOVA) was used to identify group effect for wound complexity. Pearson’s correlation coefficient was used to assess the associations with frailty and clinical endpoints. Results: Frailty index was higher in Stage 3 and 4 as compared to Stage 1 (d = 1.4, P &lt; .01) and Stage 2 (d = 1.2, P &lt; .01). Among assessed frailty phenotypes, exhaustion was correlated with SPP (r = −0.63, P &lt; .01) and albumin (r = −0.5, P &lt; .01). Conclusion: Digital biomarkers of frailty may predict complexity of DFU and thus triage individuals who can be treated more simply in their primary clinic versus higher risk patients who require prompt referral to multidisciplinary, more complex care.</description><identifier>ISSN: 1932-2968</identifier><identifier>EISSN: 1932-2968</identifier><identifier>EISSN: 1932-3107</identifier><identifier>DOI: 10.1177/19322968221111194</identifier><identifier>PMID: 35856398</identifier><language>eng</language><publisher>Los Angeles, CA: SAGE Publications</publisher><subject>Albumins ; Ambulatory Care Facilities ; Amputation, Surgical ; Frailty - diagnosis ; Humans ; Original ; Triage</subject><ispartof>Journal of diabetes science and technology, 2024-03, Vol.18 (2), p.389-396</ispartof><rights>2022 Diabetes Technology Society</rights><rights>2022 Diabetes Technology Society 2022 Diabetes Technology Society</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3544-5004ab089dcbd37fed5d7ce8fa0457301ef0ad5790afd61a759c66000ca43ee53</citedby><cites>FETCH-LOGICAL-c3544-5004ab089dcbd37fed5d7ce8fa0457301ef0ad5790afd61a759c66000ca43ee53</cites><orcidid>0000-0002-3663-6882 ; 0000-0001-9441-683X ; 0000-0001-8464-8696 ; 0000-0001-6108-893X ; 0000-0002-0320-8101</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,780,784,885,27924,27925,79364</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35856398$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Mishra, Ram Kinker</creatorcontrib><creatorcontrib>Bara, Rasha O.</creatorcontrib><creatorcontrib>Zulbaran-Rojas, Alejandro</creatorcontrib><creatorcontrib>Park, Catherine</creatorcontrib><creatorcontrib>Fernando, Malindu E.</creatorcontrib><creatorcontrib>Ross, Jeffrey</creatorcontrib><creatorcontrib>Lepow, Brian</creatorcontrib><creatorcontrib>Najafi, Bijan</creatorcontrib><title>The Application of Digital Frailty Screening to Triage Nonhealing and Complex Wounds</title><title>Journal of diabetes science and technology</title><addtitle>J Diabetes Sci Technol</addtitle><description>Objective: We investigated the association between the complexity of diabetic foot ulcers (DFUs) and frailty. Research Design and Methods: Individuals (n = 38) with Grade 2 Wagner DFU were classified into 3 groups based on the Society for Vascular Surgery risk-stratification for major limb amputation as Stage 1 at very low risk (n = 19), Stage 2 at low risk (n = 9), and Stage 3 to 4 at moderate-to-high risk (n = 10) of major limb amputation. Frailty status was objectively assessed using a validated digital frailty meter (FM). The FM works by quantifying weakness, slowness, rigidity, and exhaustion over a 20-second repetitive elbow flexion-extension exercise using a wrist-worn sensor. FM generates a frailty index (FI) ranging from 0 to 1; higher values indicate progressively greater severity of frailty. Skin perfusion pressure (SPP), albumin, and tissue oxygenation level (SatO2) were also measured. One-way analysis of variance (ANOVA) was used to identify group effect for wound complexity. Pearson’s correlation coefficient was used to assess the associations with frailty and clinical endpoints. Results: Frailty index was higher in Stage 3 and 4 as compared to Stage 1 (d = 1.4, P &lt; .01) and Stage 2 (d = 1.2, P &lt; .01). Among assessed frailty phenotypes, exhaustion was correlated with SPP (r = −0.63, P &lt; .01) and albumin (r = −0.5, P &lt; .01). 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Research Design and Methods: Individuals (n = 38) with Grade 2 Wagner DFU were classified into 3 groups based on the Society for Vascular Surgery risk-stratification for major limb amputation as Stage 1 at very low risk (n = 19), Stage 2 at low risk (n = 9), and Stage 3 to 4 at moderate-to-high risk (n = 10) of major limb amputation. Frailty status was objectively assessed using a validated digital frailty meter (FM). The FM works by quantifying weakness, slowness, rigidity, and exhaustion over a 20-second repetitive elbow flexion-extension exercise using a wrist-worn sensor. FM generates a frailty index (FI) ranging from 0 to 1; higher values indicate progressively greater severity of frailty. Skin perfusion pressure (SPP), albumin, and tissue oxygenation level (SatO2) were also measured. One-way analysis of variance (ANOVA) was used to identify group effect for wound complexity. Pearson’s correlation coefficient was used to assess the associations with frailty and clinical endpoints. Results: Frailty index was higher in Stage 3 and 4 as compared to Stage 1 (d = 1.4, P &lt; .01) and Stage 2 (d = 1.2, P &lt; .01). Among assessed frailty phenotypes, exhaustion was correlated with SPP (r = −0.63, P &lt; .01) and albumin (r = −0.5, P &lt; .01). 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source Sage Journals Online
subjects Albumins
Ambulatory Care Facilities
Amputation, Surgical
Frailty - diagnosis
Humans
Original
Triage
title The Application of Digital Frailty Screening to Triage Nonhealing and Complex Wounds
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