Outcomes and Characteristics of Wound Healing in an Outpatient Physical Therapy Clinic

Department

Physical Therapy

Document Type

Article

Publication Source

Wounds

Publication Date

2020-6

Volume

32

Issue

6

First Page

152

Last Page

158

Abstract

Introduction. Detailed understandings regarding the outcomes and characteristics of healing in wounds of different etiologies are lacking.

Objective. In the present study, data on 265 patients treated at an outpatient physical therapy wound care clinic were extracted.

Methods. Using Kaplan-Meier analyses, wound healing outcomes for different wound etiologies were evaluated and compared.

Results. The results revealed venous leg ulcers (VLUs) healed faster than non-VLUs, pressure ulcers (PUs), diabetic foot ulcers (DFUs), and arterial wounds but not faster than surgical and traumatic wounds (STWs). The estimated medians (mean for arterial wounds) of total treatment durations for complete wound closure were 87, 152, 100, 170, 525.44, 773 days in VLUs, non-VLUs, STWs, DFUs, arterial wounds, and PUs, respectively. Compared with patients with VLUs, patients with non-VLUs were younger (69.72 vs. 61.35, respectively), had a higher proportion of men (odds ratio [OR] = 2.26), were less likely to have more than 1 wound (OR = 0.25), reached complete wound closure upon discharge (OR = 0.41), or had a body mass index value greater than or equal to 25 (OR = 0.39).

Conclusions. Venous leg ulcers and other wound etiologies (ie, STWs, PUs, DFUs, and arterial wounds) appear to differ in wound healing outcomes and certain characteristics. These results may be of interest to clinicians, patients, health care policy makers, and insurers. Future research is warranted to compare wound healing outcomes and patient characteristics among different settings.

Keywords

outpatient physical therapy wound care, wound healing trajectories, venous leg ulcer, Kaplan-Meir analysis

https://www.woundsresearch.com/article/outcomes-and-characteristics-wound-healing-outpatient-physical-therapy-clinic

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