Abstract
Background
To evaluate the association of a structured out-of-hospital continuity of care intervention with diabetic ulcer healing and patient-reported outcomes in individuals with severe diabetic foot ulcers (DFUs), and to identify prognostic factors influencing healing.
Methods
This retrospective comparative study included 91 inpatients with severe DFUs (Wagner grades 4–5). The intervention group (n = 45) received a structured out-of-hospital care protocol comprising domiciliary visits, remote monitoring, and access to specialized care as needed. The control group (n = 46) was provided with standard post-discharge follow-up. Outcomes included ulcer healing status, time to complete wound closure, and health-related quality of life (HRQoL). Factors related to wound healing were assessed using Fine-Gray competing risks regression, with major amputation and death treated as competing events.
Results
Over a mean follow-up of 10.74 ± 9.05 months, the intervention group showed a higher ulcer healing rate compared to the control group (82.22% vs. 63.04%; difference 19.20%, 95% CI: 0.80% − 37.50%, p = 0.060). In the Fine-Gray competing risks analysis, the intervention group was associated with a significantly higher probability of healing (subdistribution hazard ratio = 1.74, 95% CI: 1.08–2.83, p = 0.024). Regarding HRQoL, a transient between-group difference in EQ-5D-5L was observed at 6 months (p = 0.029), but the group-by-time interaction was not significant (p = 0.220), indicating no sustained improvement.
Conclusion
In this exploratory retrospective study, structured out-of-hospital continuity of care was associated with a statistically non-significant increase in crude healing rates. After accounting for competing risks, a significant association was observed in the primary analysis. However, this effect was attenuated and no longer significant in additional baseline severity factors (ABI and ulcer location). A transient improvement in quality of life at 6 months was not sustained. Ulcer severity and peripheral artery disease were identified as independent prognostic factors. Larger prospective studies are needed to confirm these exploratory findings.
Supplementary Information
The online version contains supplementary material available at https://doi.org/10.1186/s12902-026-02431-7.
Keywords: Diabetic foot, Continuity of patient care, Quality of life
Background
As a severe and common chronic complication of diabetes, diabetic foot ulceration (DFU) contributes significantly to morbidity, mortality, and healthcare expenditures worldwide [1]. According to the International Working Group on the Diabetic Foot (IWGDF) [2], DFUs lead to approximately one million lower-limb amputations annually, significantly impairing health-related quality of life (HRQoL) and placing a heavy burden on healthcare systems. This challenge is especially acute in China, where the annual mortality rate among affected patients is as high as 14.4% [3]. Furthermore, DFU accounts for 39.5% of non-traumatic amputations [4], underscoring an urgent need for effective preventive and therapeutic strategies. This is especially relevant for patients with advanced-stage wounds (Wagner grades 4–5), who face the most dismal prognosis. Such ulcers are characterized by serious infection, extensive tissue necrosis, and frequent osseous involvement [5], leading to complex, prolonged, and costly healing processes [6].
Although comprehensive hospitals have widely implemented standardized multidisciplinary teams involving diabetologists, vascular surgeons, podiatrists, orthopedic specialists, and wound care nurses to provide integrated treatments including rigorous glucose control, vascular reconstruction, wound debridement, and nutritional counseling [7], many health systems still lack effective mechanisms for ensuring continuity of care beyond the hospital setting. This gap is especially critical for patients with Wagner grade 4–5 DFUs, who often experience limited mobility, loss of independence in daily activities, reliance on caregivers, fear of amputation, chronic pain and distressing symptoms such as foul odor and excessive exudation. These physical and psychological burden frequently contribute to anxiety or depression [8, 9], which may further impede wound healing [10] and diminish quality of life and personal dignity [11].
While multidisciplinary in-hospital management has demonstrated benefits over conventional care [12, 13], the potential of structured out-of-hospital continuity of care-particularly for severe DFU cases-remains underexplored. This model of coordinated continuity of care can complement standard foot care practices and has been associated with improved functional outcomes, enhanced quality of life and greater patient and family satisfaction. Therefore, this study is design to evaluate the impact of a structured out-of-hospital continuity of care program on wound healing rates and patient-reported outcomes in patients with Wagner grade 4–5 diabetic foot ulcers.
Methods and analysis
Study design and participants
This retrospective comparative study included 91 inpatients with Wagner grade 4 or 5 diabetic foot ulcers (DFUs) consecutively admitted to the Department of Endocrinology at Wuhan Central Hospital between June 2019 and December 2022. DFU severity was assessed at admission by an experienced endocrinologist using the Wagner classification system to ensure diagnostic consistency [14]. Inclusion criteria were: age ≥ 18 years, preserved cognitive ability, and provision of written informed consent. Patients requiring emergent amputation within 48 h were excluded. The study protocol was approved by the Ethics Committee of Wuhan Central Hospital (Approval No. WHZXKYL2019-001).
Participants were assigned to two groups based on the post-discharge care they received: the control group (n = 46) received conventional follow-up, while the intervention group (n = 45) received a structured out-of-hospital continuity of care program. Written informed consent was obtained prospectively from all enrolled patients at the time of hospital admission, as the study involved collection of patient‑reported outcomes and post‑discharge follow‑up data. All patients underwent standardized inpatient management, including debridement, revascularization, NPWT, skin grafting, and platelet gel therapy (Supplementary Table S1), and received equivalent pre‑discharge education.
To minimize selection bias, group assignment was based on the date of hospital admission, rather than clinician judgment or patient preference. Patients admitted between June 2019 and December 2019 were assigned to the control group (n = 46) and received conventional post-discharge follow-up. Those admitted between May 2020 and December 2022 were assigned to the intervention group (n = 45) and received the structured out-of-hospital continuity of care program. The initial COVID-19 outbreak period from January 2020 to April 2020 was excluded to avoid confounding due to pandemic-related healthcare disruptions. Since the intervention program was not available before its institutional implementation in May 2020, this temporal allocation ensured that all patients in the intervention period were uniformly exposed to the program.
Standardized inpatient management and pre-discharge education
All enrolled patients received standardized inpatient management following a structured diabetic foot care pathway. A multidisciplinary team (MDT)-including endocrinologists, podiatrists, vascular surgeons, orthopedic specialists, and wound care nurses-conducted comprehensive evaluations and developed individualized treatment plans.
Discharge was authorized only after patients satisfied all of the following criteria: (1) stabilization of gangrenous tissue with no progression of necrosis; (2) effective infection control, evidenced by the resolution of local signs (e.g., redness, swelling, purulent discharge) and systemic manifestations; (3) adequate pain management without reliance on potent analgesics; (4) hemodynamic stability, with no evidence of impending acute cardiovascular complications; and (5) improved nutritional status, reflected by sustained increases in serum albumin, hemoglobin, or other relevant biomarkers.
Before discharge, patients and their family caregivers received comprehensive education covering diabetes self-management, foot care, diet, exercise, hygiene, and adherence to prescribed wound care and medication regimens. Emphasis was placed on the importance of consistent follow-up and the implementation of individualized daily care plans.
Post-discharge follow-up
Both groups received a standardized telephone follow-up within three months post-discharge to evaluate glycemic control, wound healing status, and skin condition. Patients reporting uncontrolled glucose, impaired healing, or ulcer recurrence were promptly referred for hospital reassessment. Mortality outcomes were verified through interviews with primary caregiver.
Control group
Participants received usual post-discharge care, consisting of discharge instructions and advice to seek routine or problem-based care at community clinics or hospital outpatient departments (typically every 2 to 4 weeks), while retaining access to emergency services. This reflects the standard care pathway in the region.
Intervention group
In addition to standard follow-up, participants received a structured continuity-of-care program comprising: (1) Domiciliary visits: an initial assessment by a certified wound nurse within one week after discharge, followed by monthly visits for re-evaluation and basic dressing changes. Each visit lasted 30–60 min and followed standardized dressing protocols (saline irrigation, silver-containing or foam dressings). (2) Remote monitoring: weekly wound photograph upload via a dedicated We-Chat platform, with coordinator review within 48 h. Predefined escalation criteria (e.g., necrosis progression, purulence, fever) prompted on-site assessment within 24 h. (3) On-demand advanced care: bedside intervention within 24 h by specialized wound therapists for immobile or clinically deteriorating patients, including debridement and application of advanced dressings.
Study endpoints
The primary endpoint was time to complete ulcer healing, defined as total re-epithelialization of the ulcer site, absence of exudate or drainage, and no further need for dressing, confirmed at two consecutive clinical evaluations two weeks apart. Time to healing was analyzed using the Fine-Gray competing risks regression, with major amputation and all-cause death treated as competing events.
Secondary endpoints included:
Ulcer healing status (healed vs. not healed) at the last follow-up;
All-cause mortality and survival duration;
Health-related quality of life was measured using the EQ-5D-5L utility index (Chinese version, previously validated [15]), and pain intensity was assessed separately using a 100-mm Visual Analogue Scale (VAS) anchored at 0 (no pain) and 100 (worst possible pain), as recommended by the IWGDF guidelines [16]. The internal consistency of the five EQ-5D-5Ldimensions was assessed using Cronbach’s alpha coefficient based on baseline data from all 91 participants, yielding a value of 0.849, which indicates good internal consistency. As the pain VAS is a single-item measure, its internal consistency could not be computed.
Participants were monitored from enrollment until complete wound healing, death, major amputation, or loss to follow-up. Patients were classified into mutually exclusive outcome categories based on the earliest event observed during follow-up: ulcer healing, major amputation, death, or loss to follow-up. Data collection was terminated upon any of these events.
Data collection
Clinical data were systematically collected at baseline and throughout the follow-up period using a study-specific clinical questionnaire. A comprehensive set of variables were documented for all participants, including sociodemographic profile such as age, gender, educational attainment, marital status, and living situation (e.g., living alone or cohabiting with caregivers). Disease-specific history included duration of diabetes (years) and history of previous diabetic foot episodes (weeks). Comorbidity status were also assessed, including microvascular complications (including retinopathy, nephropathy, neuropathy) and macrovascular conditions (such as coronary artery disease, stroke).
Statistical analysis
Statistical analyses were performed using IBM SPSS Statistics (Version 26.0) and R (version 4.2.0) with the cmprsk package for competing risks regression. Normally distributed continuous variables are reported as mean ± standard deviation and were compared using independent samples t-tests. Non-normally distributed data are expressed as median (interquartile range) and analyzed with the Mann-Whitney U test. Categorical data are presented as number (percentage) and were examined using the chi-square test or Fisher’s exact test, as appropriate. A two-sided p-value of < 0.05 was considered statistically significant.
Because major amputation and all‑cause death preclude observation of ulcer healing, these events were treated as competing events rather than as non‑informative censoring. The primary analysis for time to ulcer healing was therefore performed using the Fine‑Gray competing risks regression model. The cumulative incidence function (CIF) for ulcer healing was estimated, and between‑group differences were assessed using Gray’s test. Multivariable Fine‑Gray regression was used to identify independent predictors of healing. Based on clinical literature and to avoid overfitting (66 healing events in 91 patients), the final model included six prespecified covariates: Wagner grade (4 vs. 5), peripheral artery disease (present vs. absent), age, sex, DFU duration (weeks), and intervention group (structured care vs. control). Results are presented as subdistribution hazard ratios (SHR) with 95% confidence intervals (CIs). The proportional hazards assumption for the Fine‑Gray model was assessed graphically using Schoenfeld‑type residuals; no major violation was observed (global test P > 0.05). To assess the robustness of the primary Fine‑Gray model, a sensitivity analysis was conducted by additionally including ABI < 0.9 and ulcer location (midfoot/hindfoot/whole foot vs. forefoot) as covariates. The results remained consistent (Supplementary Table S3).
Longitudinal changes in EQ‑5D‑5L and VAS scores were analyzed using generalized estimating equations (GEE) with an exchangeable working correlation structure, selected based on the lowest QIC. The models included main effects for group (intervention vs. control), time (0, 6, 12 months), and their interaction, with robust standard errors (Huber‑White sandwich estimator). Missing data were assumed missing at random (MAR); the primary analysis used complete case analysis. A sensitivity analysis using multiple imputation (5 imputations) gave consistent results. Due to small sample sizes at 24 and 36 months, these time points were excluded from the longitudinal analysis.
All statistical models were checked for compliance with relevant assumptions. Results are reported with both effect estimates and p-values to support clinical interpretation.
Results
Baseline characteristics of all participants in the study
A total of 91 patients with Wagner grade 4 or 5 diabetic foot ulcers (DFU) were included in the study, with 45 assigned to the intervention group and 46 to the control group. As shown in Table 1, baseline characteristics were well balanced between the two groups, with no statistically significant differences in demographics, clinical features, metabolic indicators, comorbidities, or diabetic complications (all p > 0.05).
Table 1.
Demographics and baseline characteristics of patients with diabetic foot ulcer
| Total | Intervention group | Control group | p value | |
|---|---|---|---|---|
| (n = 91) | (n = 45) | (n = 46) | ||
| Age (year) | 66.85 ± 11.06 | 68.02 ± 9.64 | 65.70 ± 12.29 | 0.318 |
| Male, n (%) | 62 (68.13%) | 29 (64.44%) | 33 (71.74%) | 0.505 |
| Duration of diabetes (years) | 15.42 ± 8.45 | 15.64 ± 7.12 | 15.20 ± 9.65 | 0.801 |
| DFU duration (weeks) | 4.00 (2.00–10.00) | 4.00 (2.00–12.00) | 4.00 (2.00-10.50) | 0.154 |
| History of smoking, n (%) | 34 (37.36%) | 16 (35.56%) | 18 (39.13%) | 0.829 |
| History of alcohol consumption, n (%) | 14 (15.38%) | 5 (11.11%) | 9 (19.57%) | 0.358 |
| Baseline HbA1c (%) | 9.02 ± 2.27 | 8.70 ± 2.35 | 9.34 ± 2.16 | 0.183 |
| Baseline FBG (mmol/L) | 10.87 ± 5.03 | 10.74 ± 5.43 | 11.00 ± 4.66 | 0.808 |
| BMI (kg/m2) | 24.02 ± 3.71 | 24.26 ± 3.97 | 23.78 ± 3.46 | 0.544 |
| Baseline ABI | 0.92 ± 0.20 | 0.92 ± 0.20 | 0.93 ± 0.21 | 0.790 |
| ABI < 0.9, n (%) | 36 (39.56%) | 17 (37.78%) | 19 (41.30%) | 0.831 |
| History of lower extremity revascularization, n (%) | 27 (29.67%) | 13 (28.89%) | 14 (30.43%) | 1.000 |
| Type of DFU | 1.000 | |||
| Wagner grade 4, n (%) | 73 (80.22%) | 36 (80.00%) | 37 (80.43%) | |
| Wagner grade 5, n (%) | 18 (19.78%) | 9 (20.00%) | 9 (19.57%) | |
| Ulcer location | 1.000 | |||
| Fore-foot, n (%) | 60 (65.93%) | 30 (66.67%) | 30 (65.22%) | |
| Mid-foot/ Hind-foot/ Ankle/ Whole-foot, n (%) | 31 (34.07%) | 15 (33.33%) | 16 (34.78%) | |
| Marital status | 0.826 | |||
| Single, n (%) | 3 (3.30%) | 1 (2.22%) | 2 (4.35%) | |
| Married, n (%) | 65 (71.43%) | 32 (71.11%) | 33 (71.74%) | |
| Divorced/widowed, n (%) | 23 (25.27%) | 12 (26.67%) | 11 (23.91%) | |
| Living arrangement | 1.000 | |||
| Living alone, n (%) | 23 (25.27%) | 11 (24.44%) | 12 (26.09%) | |
| Living with caregivers, n (%) | 68 (74.7%) | 34 (75.6%) | 34 (73.9%) | |
| Education | 0.716 | |||
| Primary or below, n (%) | 25 (27.47%) | 14 (31.11%) | 11 (23.91%) | |
| Secondary or below, n (%) | 31 (34.07%) | 14 (31.11%) | 17 (36.96%) | |
| University or below, n (%) | 35 (38.46%) | 17 (37.78%) | 18 (39.13%) | |
| Comorbidities | ||||
| Hypertension, n (%) | 55 (60.44%) | 29 (64.44%) | 26 (56.52%) | 0.522 |
| Cardiovascular disease, n (%) | 33 (36.26%) | 20 (44.44%) | 13 (28.26%) | 0.130 |
| Stroke, n (%) | 39 (42.86%) | 19 (42.22%) | 20 (43.48%) | 1.000 |
| Heart Failure, n (%) | 21 (23.08%) | 12 (26.67%) | 9 (19.57%) | 0.464 |
| CKD Requiring RRT, n (%) | 14 (15.38%) | 6 (13.33%) | 8 (17.39%) | 0.773 |
| Complication | ||||
| Diabetic Retinopathy, n (%) | 38 (41.76%) | 20 (44.44%) | 18 (39.13%) | 0.673 |
| Diabetic Nephropathy, n (%) | 65 (71.43%) | 31 (68.89%) | 34 (73.91%) | 0.647 |
| Diabetic Peripheral Neuropathy, n (%) | 80 (87.91%) | 38 (84.44%) | 42 (91.30%) | 0.354 |
| Peripheral Artery Disease, n (%) | 63 (69.23%) | 34 (75.56%) | 29 (63.04%) | 0.257 |
Data are expressed as mean (standard deviation), median (interquartile range), or number (percentage)
Abbreviations: DFU, Diabetic foot ulcer; HbA1c, Glycated hemoglobin; FBG, Fasting blood glucose; BMI, Body mass index; CKD, Chronic kidney disease; RRT, Renal replacement therapy
Prognostic outcomes of all participants in the study
The participant flow throughout the study is presented in Fig. 1. Over a mean follow-up of 10.74 ± 9.05 months, ulcer healing was achieved in 66 patients (72.53%), while 7 patients (7.69%) died, 9 patients (9.89%) underwent major amputation, and 9 patients (9.89%) were lost to follow-up.
Fig. 1.
Flowchart of participant enrollment and follow-up. Over a mean follow-up of 10.74 ± 9.05 months, ulcer healing was achieved in 66 patients (72.53%). Other outcomes included death (7.69%), major amputation (9.89%), and loss to follow-up (9.89%).Patients were assigned to mutually exclusive outcome categories based on the earliest event observed during follow‑up: ulcer healing, major amputation, death, or loss to follow‑up. Loss to follow-up was primarily due to relocation, transfer for worsened conditions, or referral for complex comorbidity management
As summarized in Table 2, the ulcer healing rate was 82.22% (37/45) in the intervention group and 63.04% (29/46) in the control group, with an absolute difference of 19.2% (95% CI: 0.8%–37.5%, p = 0.060, Pearson’s chi‑square test). Best-case/worst-case sensitivity analyses for differential loss to follow-up are presented in Supplementary Table S2, and the results supported the robustness of the primary findings.
Table 2.
Comparison of primary follow-up outcomes between the intervention and control groups
| Outcome | Total | Intervention group | Control group | p value |
|---|---|---|---|---|
| (n = 91) | (n = 45) | (n = 46) | ||
| Ulcer healing (Primary endpoint) | ||||
| Events (Healed), n (%) | 66 (72.53%) | 37 (82.22%) | 29 (63.04%) | 0.060 |
| Competing events and censoring | ||||
| Major Amputation, n (%) | 9 (9.89%) | 4 (8.89%) | 5 (10.87%) | 1.000 |
| DFU-related death, n (%) | 2 (2.20%) | 1 (2.22%) | 1 (2.17%) | 1.000 |
| Non-DFU-related death, n (%) | 5 (5.49%) | 1 (2.22%) | 4 (8.70%) | 0.361 |
| Loss to follow-up, n (%) | 9 (9.89%) | 2 (4.44%) | 7 (15.22%) | 0.158 |
Data are n (%). The primary outcome (ulcer healing) was analyzed with the Kaplan-Meier method and compared using the log-rank test (P = 0.600). The P value for the final healing proportion (0.060) was derived from Pearson’s chi-square test. P values for other outcomes (major amputation, DFU-related death and non-DFU-related death, loss to follow-up) were derived from Fisher’s exact test. Patients who underwent major amputation, died, were lost to follow-up, or remained unhealed were censored in the time-to-event analysis
Abbreviations: DFU, Diabetic foot ulcer
No significant between-group differences were observed for other outcomes, including DFU-related mortality (2.22% vs. 2.17%; p = 1.000), non-DFU-related mortality (2.22% vs. 8.70%; p = 0.361), amputation rate (8.89% vs. 10.87%; p = 1.000), or loss to follow-up (4.44% vs. 15.22%; p = 0.158).
The competing risks analysis (Fig. 2) revealed no significant difference in the cumulative incidence of ulcer healing between the two groups (Gray’s test, p = 0.245).
Fig. 2.
Competing risks cumulative incidence curves for ulcer healing. Major amputation and all-cause death were treated as competing events. Solid line: intervention group; dashed line: control group. Gray’s test for between-group difference was not significant (p = 0.245). Tick marks indicate censored observations
Longitudinal changes in patient-reported outcomes
Longitudinal changes in patient-reported outcomes were evaluated using the EQ-5D-5L utility index for health-related quality of life and the Visual Analogue Scale (VAS) for self-reported pain intensity. Generalized Estimating Equations (GEE) with an exchangeable correlation structure were used, adjusting for diabetes duration, DFU duration, ABI, and age.
For EQ‑5D‑5L, GEE analysis revealed a significant group‑by‑time interaction (Wald χ² = 8.371, p = 0.015), indicating divergent trajectories of health‑related quality of life between the two groups over the 12‑month follow‑up. Simple effects analysis (Table 3; Fig. 3A) showed that the intervention group had a significantly higher adjusted mean EQ‑5D‑5L score at 6 months (adjusted mean difference = 0.17, 95% CI: 0.04–0.30, p = 0.014), whereas no significant differences were observed at baseline (adjusted mean difference = − 0.03, 95% CI: − 0.14–0.09, p = 0.626) or at 12 months (adjusted mean difference = − 0.01, 95% CI: − 0.21–0.20, p = 0.958).
Table 3.
Comparison of EQ-5D-5L scores between intervention and control groups over time
| Time-point | Intervention group | Control group | Adjusted mean difference (95% CI) | p value * | ||
|---|---|---|---|---|---|---|
| n ‡ | mean ± SD | n ‡ | mean ± SD | |||
| Baseline | 45 | 0.48 ± 0.27 | 46 | 0.51 ± 0.28 | -0.03(-0.14, 0.09) | 0.626 |
| Month 6 | 31 | 0.74 ± 0.20 | 30 | 0.57 ± 0.34 | 0.17 (0.04, 0.30) | 0.014 |
| Month 12 | 14 | 0.53 ± 0.26 | 7 | 0.56 ± 0.28 | -0.01 (-0.21, 0.20) | 0.958 |
| Month 24† | 8 | 0.53 ± 0.19 | 1 | 0.38 | NA | NA |
| Month 36† | 1 | 0.51 | 0 | NA | NA | NA |
* p-values from GEE with simple effects analysis, exchangeable correlation structure, adjusted for diabetes duration, DFU duration, ABI, and age
†Statistical comparison not performed due to insufficient sample size (n < 5 in one group)
Fig. 3.
Longitudinal changes in patient-reported outcomes during the 36-month follow-up. (A) Health-related quality of life (EQ-5D-5L utility index). (B) Self-reported pain intensity (Visual Analogue Scale, VAS). Data are presented as mean ± standard deviation. The varying sample sizes across time points reflect participant attrition over the extended follow-up period (see participant flow diagram, Fig. 1). Between-group differences at individual time points were estimated using Generalized Estimating Equations (GEE). Formal comparisons at Months 24 and 36 were not performed due to limited sample size (N < 2 in at least one group)
For pain intensity (Table 4; Fig. 3B), the group‑by‑time interaction was not significant (Wald χ² = 4.209, p = 0.122). Simple effects analysis confirmed no significant between‑group differences at any time point (baseline: adjusted mean difference = 1.78, 95% CI: − 3.63–7.18, p = 0.519; 6 months: − 6.28, 95% CI: − 15.52–2.95, p = 0.182; 12 months: 7.21, 95% CI: − 6.72–21.15, p = 0.310).
Table 4.
Comparison of visual analogue scale (VAS) scores between intervention and control groups over time
| Time-point | Intervention group | Control group | Adjusted mean difference (95% CI) | p value * | ||
|---|---|---|---|---|---|---|
| n ‡ | mean ± SD | n ‡ | mean ± SD | |||
| Baseline | 45 | 41.78 ± 12.75 | 46 | 40.00 ± 13.82 | 1.78 (-3.63, 7.18) | 0.519 |
| Month 6 | 31 | 32.42 ± 18.75 | 30 | 39.00 ± 19.71 | -6.28 (-15.52, 2.95) | 0.182 |
| Month 12 | 14 | 45.29 ± 20.25 | 7 | 37.86 ± 14.10 | 7.21 (-6.72, 21.15) | 0.310 |
| Month 24† | 8 | 57.50 ± 18.71 | 1 | 60.00 | NA | |
| Month 36† | 1 | 40.00 | 0 | NA | NA | |
* p-values from GEE with simple effects analysis, exchangeable correlation structure, adjusted for diabetes duration, DFU duration, ABI, and age
† Statistical comparison not performed due to insufficient sample size (n < 5 in one group)
Comparison of baseline characteristics by healing status
Baseline characteristics stratified by ulcer healing status are presented in Table 5. Most demographic and clinical features, including age, sex, duration of diabetes, BMI, glycemic control and histories of hypertension or cardiovascular disease were comparable between healed and unhealed groups. However, several factors were significantly associated with poor healing outcomes. Patients in the unhealed group had a higher proportion of Wagner grade 5 ulcers (52.00% vs. 7.58%, p < 0.001), significantly higher rates of chronic kidney disease requiring renal replacement therapy (40.00% vs. 6.06%, P < 0.001), and peripheral artery disease (92.00% vs. 60.61%, p = 0.004). Educational attainment was also significantly lower in the unhealed group (p = 0.025). Although ulcers in the unhealed group tended to have longer duration at baseline (median 8.00 weeks vs. 4.00 weeks), this difference was not statistically significant (p = 0.073).
Table 5.
Comparison of baseline characteristics between patients with healed and unhealed diabetic foot ulcers
| Healed group | Unhealed group | p value | |
|---|---|---|---|
| (n = 66) | (n = 25) | ||
| Post-Discharge Follow-up intervention | 0.060 | ||
| Control group | 29 (43.94%) | 17 (68.00%) | |
| Intervention group | 37 (56.06%) | 8 (32.00%) | |
| Age (year) | 66.45 ± 10.99 | 67.88 ± 11.39 | 0.586 |
| Male (%) | 44 (66.67%) | 18 (72.00%) | 0.802 |
| Duration of diabetes (years) | 15.95 ± 8.33 | 14.00 ± 8.78 | 0.327 |
| DFU duration (weeks) | 4.00 (2.00-8.50) | 8.00 (2.50–14.00) | 0.073 |
| History of smoking (%) | 25 (37.88%) | 9 (36.00%) | 1.000 |
| History of alcohol consumption (%) | 9 (13.63%) | 5 (20.00%) | 0.519 |
| Baseline HbA1c (%) | 8.94 ± 2.38 | 9.25 ± 1.94 | 0.556 |
| Baseline FBG (mmol/L) | 11.09 ± 5.05 | 10.28 ± 5.03 | 0.496 |
| BMI (kg/m2) | 23.96 ± 3.79 | 24.18 ± 3.56 | 0.797 |
| Baseline ABI | 0.96 ± 0.18 | 0.83 ± 0.23 | 0.007 |
| ABI < 0.9, n (%) | 21 (31.82%) | 15 (60.00%) | 0.018 |
| History of lower extremity revascularization, n (%) | 17 (25.76%) | 10 (40.00%) | 0.206 |
| Type of DFU | <0.001 | ||
| Wagner grade 4 | 61 (92.42%) | 12 (48.00%) | |
| Wagner grade 5 | 5 (7.58%) | 13 (52.00%) | |
| Ulcer location | <0.001 | ||
| Fore-foot, n (%) | 53 (80.30%) | 7 (28.00%) | |
| Mid-foot/ Hind-foot/ Ankle/ Whole-foot, n (%) | 13 (19.70%) | 18 (72.00%) | |
| Marital status | 0.226 | ||
| Single | 3 (4.55%) | 0 (0.00%) | |
| Married | 49 (74.24%) | 16 (64.00%) | |
| Divorced/widowed | 14 (21.21%) | 9 (36.00%) | |
| Living arrangement | 0.421 | ||
| Living alone | 15 (22.73%) | 8 (32.00%) | |
| Living with caregivers | 51 (77.27%) | 17 (68.00%) | |
| Education | 0.025 | ||
| Primary or below | 16 (24.24%) | 9 (36.00%) | |
| Secondary or below | 19 (28.79%) | 12 (48.00%) | |
| University or below | 31 (46.97%) | 4 (16.00%) | |
| Comorbidities | |||
| Hypertension | 39 (59.09%) | 16 (64.00%) | 0.269 |
| Cardiovascular disease | 22 (33.33%) | 11 (44.00%) | 0.464 |
| Stroke | 25 (37.88%) | 14 (56.00%) | 0.156 |
| Heart Failure | 13 (19.70%) | 8 (32.00%) | 0.267 |
| CKD Requiring RRT | 4 (6.06%) | 10 (40.00%) | <0.001 |
| Complication | |||
| Diabetic Retinopathy | 26 (39.39%) | 12 (48.00%) | 0.484 |
| Diabetic Nephropathy | 45 (68.18%) | 20 (80.00%) | 0.310 |
| Diabetic Peripheral Neuropathy | 57 (86.36%) | 23 (92.00%) | 0.721 |
| Peripheral Artery Disease | 40 (60.61%) | 23 (92.00%) | 0.004 |
Data are expressed as mean (standard deviation), median (interquartile range), or number (percentage)
Abbreviations: DFU, Diabetic foot ulcer; HbA1c, Glycated hemoglobin; FBG, Fasting blood glucose; BMI, Body mass index; CKD, Chronic kidney disease; RRT, Renal replacement therapy
Factors associated with diabetic foot ulcer healing
In the Fine-Gray competing risks regression (Table 6), after adjusting for Wagner grade, peripheral artery disease, age, sex, and DFU duration, the intervention group showed a significantly higher subdistribution hazard of ulcer healing compared with the control group (SHR = 1.74, 95% CI: 1.08–2.83, p = 0.024). Wagner grade 5 (SHR = 0.17, 95% CI: 0.08–0.40, p < 0.001) and peripheral artery disease (SHR = 0.51, 95% CI: 0.30–0.89, p = 0.017) were independently associated with a lower probability of healing. Age, sex, and DFU duration were not significant predictors.
Table 6.
Fine-gray competing risks regression analyses of factors associated with diabetic foot ulcer healing
| Variable | Fine-Gray SHR (95%CI) | P value |
|---|---|---|
| Wagner grade 5 (vs. grade 4) | 0.17 (0.08–0.40) | < 0.001 |
| Peripheral artery disease | 0.51 (0.30–0.89) | 0.017 |
| Age (per year) | 0.99 (0.97–1.02) | 0.52 |
| Male (vs. female) | 1.18 (0.63–2.20) | 0.60 |
| DFU duration (per week) | 1.00 (0.99–1.00) | 0.18 |
| Intervention (vs. control) | 1.74 (1.08–2.83) | 0.024 |
Abbreviations: SHR, subdistribution hazard ratio; CI, confidence interval. Fine‑Gray model treated major amputation and death as competing events. Multivariable model included all listed variables
A sensitivity analysis additionally adjusting for ABI < 0.9 and ulcer location (mid-foot/hind-foot/whole foot vs. forefoot) showed that the intervention effect was attenuated and no longer statistically significant (SHR = 1.57, 95% CI: 0.97–2.54, p = 0.067; Supplementary Table S3). This attenuation suggests that part of the observed benefit may be partially explained by differences in baseline severity factors, particularly vascular status and anatomical location. Ulcer location showed a borderline‑significant effect (SHR = 0.48, 95% CI: 0.23–1.01, p = 0.054), suggesting worse healing in ulcers involving the midfoot, hindfoot, or whole foot.
Discussion
Diabetic foot ulcers (DFUs) represent a severe complication of diabetes, arising from a complex interplay of neuropathy, vascular impairment, and chronic hyperglycemia. These pathophysiological factors contribute to sensory loss, infection susceptibility, recurrent ulceration, and tissue necrosis, often leading to extended hospitalizations, increased amputation risk, substantial healthcare costs, and long-term disability [17]. The 2019 IWGDF guidelines emphasize structured outpatient care and patient education as fundamental to DFU prevention [18]. Growing evidence further indicates that a coordinated continuum of care beyond the hospital setting provides considerable advantages, including improved glycemic control, reduced infection rates, enhanced wound healing, and decreased overall medical costs [19, 20].
However, existing evidence predominantly focuses on mild or moderate DFUs, with limited research into multidisciplinary continuity of care for severe cases (Wagner grades 4–5). These patients face significantly elevated risk of amputation, mortality and functional decline due to advanced diabetes-related complications. The frequent presence of persistent pain, physical disability, and severely diminished quality of life in this subgroup underscores the necessity to transition from a purely healing-oriented model toward an integrated palliative-supportive care framework. Such approaches emphasize wound stabilization, effective symptom management, and maintenance of functional well-being, particularly when complex comorbidities preclude aggressive curative treatment.
To address this evidence gap, we implemented a structured out-of-hospital continuity of care program specifically tailored for patients with Wagner grade 4–5 DFUs. In addition to standard care, the intervention group received a multifaceted supportive program consisting of standardized monthly home visits by wound-certified nurses initiated within one week post-discharge; continuous telemonitoring via a dedicated mobile platform to enable real-time coordination and support; and on-demand advanced bedside care within 24 h for homebound or clinically deteriorating patients.
Although the crude healing rate difference was not statistically significant (82.22% vs. 63.04%; difference 19.2%, 95% CI: 0.8%–37.5%, p = 0.060), Fine‑Gray competing risks model, which accounted for major amputation and death as competing events, demonstrated a statistically significant benefit of the intervention (SHR = 1.74, 95% CI: 1.08–2.83, p = 0.024). The non‑significant crude comparison likely reflects limited statistical power due to the modest sample size (post‑hoc power 58.2%) and the lack of adjustment for important prognostic factors such as Wagner grade and peripheral artery disease. Accordingly, the competing risks model provides a more reliable estimate of the intervention effect. However, the intervention effect should be interpreted with caution. In a sensitivity analysis additionally adjusting for ABI < 0.9 and ulcer location (midfoot/hindfoot/whole foot vs. forefoot), the effect was attenuated and no longer statistically significant (SHR = 1.57, 95% CI: 0.97–2.54, p = 0.067). This attenuation suggests that part of the observed benefit may be attributable to differences in baseline disease severity, particularly vascular status and anatomical location, rather than the intervention alone. Therefore, the association should not be considered fully robust across all model specifications, and the findings should be regarded as exploratory until confirmed in larger prospective studies.
Regarding health-related quality of life, the generalized estimating equations (GEE) analysis revealed that the group-by-time interaction was not significant (Wald χ² = 4.414, p = 0.220), indicating no sustained difference between groups over the 12-month follow-up. Although a statistically significant between-group difference in EQ‑5D‑5L was observed at the 6‑month time point alone (intervention: 0.74 ± 0.20 vs. control: 0.57 ± 0.34; p = 0.029), Given the non-significant overall interaction, this isolated finding should be interpreted as transient and exploratory. Several factors may explain this transient benefit. The intensive support and structured education provided in the early months post-discharge likely enhanced illness awareness, self-care practices, and perceived support among patients and caregivers. Evidence suggests that illness beliefs play a critical role in shaping self-care behaviors in patients with diabetic foot ulcers [21]. Specifically, perceptions of personal identity, control over the illness, and coherence of the condition have been shown to predict adherence to foot self-care practices [22]. Effective improvement in diabetic foot outcomes requires not only foot care education and skill training but also strategies that enable behavioral change and reinforce motivation. Furthermore, structured educational interventions enhance the ability of family members to provide effective wound care, including appropriate cleaning and dressing techniques [23]. As the intervention intensity decreased over time and patients faced the chronic, progressive nature of severe DFU, these initial improvements diminished. The reduced sample size at later time points due to healing, death, or loss to follow‑up further limited our ability to detect sustained differences.
The markedly lower loss to follow-up in the intervention group (4.44% vs. 15.22%) suggests that structured continuity of care may have improved participant engagement, although this differential could also introduce attrition bias. Importantly, the transient quality-of-life benefit is consistent with the core principles of integrated palliative care [24], which prioritize functional capacity, patient and family satisfaction, and quality of life over purely biological endpoints such as ulcer closure alone. Nevertheless, the exploratory nature of these findings and the potential for measurement bias (self-reported, unblinded outcomes) should be considered.
It is worth emphasizing that our study was carried out during the COVID-19 pandemic, a period when routine hospital follow-ups were frequently disrupted or delayed. The telemonitoring component of the intervention group provided essential support to patients, enabling timely clinical guidance and continuous support. Participants were encouraged to contact study physicians immediately if they encountered any difficulties, which helped ensure prompt intervention and clinical re-evaluation when needed. This approach is consistent with existing evidence supporting the role of telemedicine in improving patient outcomes [25]. Remote wound assessment via image-based communication empowered patients by facilitating timely feedback and reducing the need for emergency visits [26]. However, remote support must be complemented by professional oversight, particularly in complex cases such as Wagner grade 4–5 ulcers, where inappropriate home care may delay healing or increase infection risk [27].
Multivariable Fine-Gray competing risks regression identified Wagner grade 5 (SHR = 0.17, 95% CI: 0.08–0.40, p < 0.001) and peripheral artery disease (SHR = 0.51, 95% CI: 0.30–0.89, p = 0.017) as independent prognostic factors significantly associated with impaired ulcer healing. These results are consistent with previous research confirming that wound severity and impaired vascular perfusion are key determinants of poor prognosis [28, 29]. The results highlight the importance of early vascular assessment and precise wound staging in high-risk patients and support the integration of individualized risk stratification into structured continuity-of-care frameworks.
Several limitations should be noted. First, this was a single-center retrospective study with a moderate sample size, no a priori sample size calculation was performed. Post-hoc power analysis based on the observed healing rates yielded an achieved power of only 58.2%, indicating that the study was underpowered to detect a statistically significant difference at α = 0.05. Consequently, the findings may not be generalizable to other settings or populations. Second, blinding of patients and care providers was not feasible due to the nature of the intervention, potentially introducing performance and detection bias, particularly for subjective patient-reported outcomes. Third, several potential confounders were not measured, including caregivers’ wound care proficiency, medication adherence, geographic proximity to the hospital, and more detailed ischemia parameters (e.g., toe pressures, TcPO₂). Therefore, residual confounding cannot be excluded. Additionally, we assumed linearity for continuous covariates (age and DFU duration) without formal testing. Fourth, the differential loss to follow-up (higher in the control group), although not statistically significant, may have introduced attrition bias affecting outcome estimates. Additionally, adherence and implementation fidelity were not systematically recorded; variability in home visit frequency and remote platform use could have influenced outcomes. Fifth, the relatively limited number of complete healing events, particularly among patients with Wagner grade 5 ulcers, may influence the reliability of prognostic analyses. Furthermore, the study was conducted during the COVID-19 pandemic, which may have disrupted routine follow-up and access to care. Although we excluded the initial outbreak period (from January to April 2020) and telemonitoring may have mitigated some barriers, residual pandemic-related confounding cannot be ruled out. To address these limitations, future research should adopt the WIfI (Wound, Ischemia, foot Infection) classification, use prospective multi‑center designs with larger sample sizes, and systematically collect vascular parameters such as toe pressures and TcPO₂.
Despite these limitations, our study contributes meaningful insights into the role of structured out-of-hospital continuity of care in severe DFU management and underscores the prognostic relevance of integrating palliative support with conventional treatment pathways. Further research involving multi-center cohorts, larger samples, extended follow-up durations, and standardized caregiver training are warranted to confirm these findings.
In conclusion, the primary analysis suggested a potential benefit of the intervention, but this finding was not robust across sensitivity analyses and should be regarded as exploratory. A transient improvement in quality of life at 6 months was observed but not sustained. Structured out-of-hospital continuity of care appears feasible, but larger prospective studies are needed to confirm its effectiveness.
Supplementary Information
Below is the link to the electronic supplementary material.
Acknowledgements
We sincerely thank all the participants who took part in this study and adhered to the follow-up schedule. Their time and commitment made this research possible. We also express our deep gratitude to the nurses at the Diabetic Foot Center of Wuhan Central Hospital for their invaluable assistance in patient care, data collection, and coordination during the study period. We additionally thank all the staff and colleagues who supported this work.
Abbreviations
- DFU
Diabetic foot ulcer
- IWGDF
International Working Group on the Diabetic Foot
- HRQoL
Health-related quality of life
- MDT
Multidisciplinary team
- VAS
Visual Analogue Scale
- SHR
Subdistribution hazard ratio
- HR
Hazard ratios
- CIs
Confidence intervals
- GEE
Generalized Estimating Equations
- MAR
Missing at random
- QIC
Quasi-likelihood under independence model criterion
- CIF
Cumulative incidence function
- ABI
Ankle‑brachial index
- HbA1c
Glycated hemoglobin
- FBG
Fasting blood glucose
- BMI
Body mass index
- CKD
Chronic kidney disease
- RRT
Renal replacement therapy
- PTA
Percutaneous transluminal angioplasty
- NPWT
Negative-pressure wound therapy
- WIfI
Wound, Ischemia, foot Infection
Author contributions
The study protocol and the initial manuscript draft were prepared by Wei Wei. The work was planned, supervised, and critically revised by Shi Zhao, who also served as the principal investigator and guarantor of this study. Lan Yi contributed to project administration, data curation, and conceptualization. All authors reviewed and approved the final version of the manuscript prior to submission.
Funding
This study was supported by the Intramural Research Grant of Wuhan Central Hospital (No. 26YJ28).
Data availability
All datasets generated during the current study are not publicly available but are available from the corresponding author on reasonable request.
Declarations
Ethics approval and consent to participate
The research protocol received approval from the Ethics Committee of Wuhan Central Hospital (Approval No. WHZXKYL2019-001). All methods were carried out in accordance with relevant guidelines and regulations.
Consent to participants
All participants provided written informed consent.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Wei Wei and Shi Zhao contributed equally to this work.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
All datasets generated during the current study are not publicly available but are available from the corresponding author on reasonable request.