Prospective observational cohort of algorithm-guided reassessment in diabetic foot: real-world outcomes and prognostic associations

Background: Diabetic foot is among the most frequent complications of diabetes mellitus (DM), with potentially dramatic consequences ranging from chronic wounds to major lower-limb amputations. The Tardivo Algorithm is a simple prognostic scoring system designed to support risk stratification and structured longitudinal reassessment in routine clinical care. Objective: To describe the real-world implementation and feasibility of dynamic risk reassessment using the Tardivo Algorithm in a prospective observational cohort of patients with diabetic foot managed in a vascular surgery outpatient setting, and to explore associations between baseline risk stratification and clinical outcomes. Methods: This prospective observational cohort study was conducted in a routine outpatient clinic for complex wounds. Adult patients with diabetic foot were classified according to the Tardivo Algorithm at baseline and underwent structured serial reassessments at each follow-up visit as part of usual multidisciplinary care. No comparator group was included. Patients were followed for 6-18 months, and outcomes were descriptively recorded as minor amputation, major amputation, wound in process of healing, or complete healing. Results: A total of 42 patients were followed for up to 18 months. Mean initial Tardivo score was 7.6 ± 4.8, with 19% classified as high risk (≥12 points). Limb preservation was observed in 94.3% of participants, and complete healing occurred in 57%, with a mean healing time of 5.05 ± 1.95 months. Higher baseline Tardivo scores were positively associated with peripheral arterial disease (r = 0.740; p < 0.001), while healing time correlated with both PAD (r = 0.547; p = 0.006) and prior amputations (r = 0.523; p = 0.009). These correlations were not independent in multivariable models. Findings reflect associations observed in a real-world, structured outpatient care model. Conclusion: In this prospective real-world cohort, structured application of the Tardivo Algorithm was feasible and allowed dynamic clinical monitoring. Clinical outcomes observed during follow-up are described within the context of this non-controlled design and should be interpreted as observational associations rather than indicators of therapeutic effect. Controlled studies are required to determine the independent impact of algorithm-guided reassessment and adjunctive therapies.

Authors

Institutions

Publication Details

Journal
Frontiers in Clinical Diabetes and Healthcare
Published
2026-04-15
DOI
https://doi.org/10.3389/fcdhc.2026.1799455
Primary Topic
Diabetic Foot Ulcer Assessment and Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Prospective observational cohort of algorithm-guided reassessment in diabetic foot: real-world outcomes and prognostic associations

Rafael Vilhena de Carvalho Fürst, Gabriela Tessaro Cremoneis, João Paulo Tardivo, Rodrigo Daminello Raimundo et al.
Frontiers in Clinical Diabetes and Healthcare
Diabetic Foot Ulcer Assessment and Management
article

Prospective observational cohort of algorithm-guided reassessment in diabetic foot: real-world outcomes and prognostic associations

Rafael Vilhena de Carvalho Fürst, Gabriela Tessaro Cremoneis, João Paulo Tardivo, Rodrigo Daminello Raimundo, Sidnei José Galego, Isabela Yones Nogara, Paula Stefany Santos Caetano, João Antônio Correa
article en

Abstract

Background: Diabetic foot is among the most frequent complications of diabetes mellitus (DM), with potentially dramatic consequences ranging from chronic wounds to major lower-limb amputations. The Tardivo Algorithm is a simple prognostic scoring system designed to support risk stratification and structured longitudinal reassessment in routine clinical care. Objective: To describe the real-world implementation and feasibility of dynamic risk reassessment using the Tardivo Algorithm in a prospective observational cohort of patients with diabetic foot managed in a vascular surgery outpatient setting, and to explore associations between baseline risk stratification and clinical outcomes. Methods: This prospective observational cohort study was conducted in a routine outpatient clinic for complex wounds. Adult patients with diabetic foot were classified according to the Tardivo Algorithm at baseline and underwent structured serial reassessments at each follow-up visit as part of usual multidisciplinary care. No comparator group was included. Patients were followed for 6-18 months, and outcomes were descriptively recorded as minor amputation, major amputation, wound in process of healing, or complete healing. Results: A total of 42 patients were followed for up to 18 months. Mean initial Tardivo score was 7.6 ± 4.8, with 19% classified as high risk (≥12 points). Limb preservation was observed in 94.3% of participants, and complete healing occurred in 57%, with a mean healing time of 5.05 ± 1.95 months. Higher baseline Tardivo scores were positively associated with peripheral arterial disease (r = 0.740; p < 0.001), while healing time correlated with both PAD (r = 0.547; p = 0.006) and prior amputations (r = 0.523; p = 0.009). These correlations were not independent in multivariable models. Findings reflect associations observed in a real-world, structured outpatient care model. Conclusion: In this prospective real-world cohort, structured application of the Tardivo Algorithm was feasible and allowed dynamic clinical monitoring. Clinical outcomes observed during follow-up are described within the context of this non-controlled design and should be interpreted as observational associations rather than indicators of therapeutic effect. Controlled studies are required to determine the independent impact of algorithm-guided reassessment and adjunctive therapies.

Frontiers in Clinical Diabetes and HealthcareVol. 7
Centro Universitário Cesmac (BR)
Openalex Percentile: Top 25%
Diabetic Foot Ulcer Assessment and Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.