Methods
Patients and Setting
A total of 169 patients who were treated at the Comprehensive Wound Healing and Hyperbaric Center (Lake Success, NY), a tertiary facility of the Northwell Health system, participated in this retrospective study. The data for this study were obtained in conjunction with the development of the New York University School of Medicine’s Online Wound Electronic Medical Record to Decrease Limb Amputations in Persons with Diabetes (OWEMR) database. The OWEMR collects individual patient data from satellite locations across the country. Using this database, researchers can analyze similarities and differences between patients who undergo LEA.
This study utilized patient data specific to the Northwell Health facility. All of the patients in our study were enrolled under the criteria of the OWEMR database. In order to be included in the OWEMR database, patients had to be diagnosed with type 1 or type 2 diabetes; have a break in the skin ≥ 0.5 cm2; be 18 years of age or older; and have a measured hemoglobin A1c (HbA1c) value within the past 120 days. Study patients signed an informed consent and committed to being available for follow-up visits to the wound care facility for 6 months after entering the study. Patients were enrolled between 2012 and 2014, and each patient was monitored for a period of 6 months within this time period. Participants were treated with current standards of care using diet, lifestyle, and pharmacologic interventions. This study was approved by the Northwell Health System Institutional Review Board Human Research Protection Program (Manhasset, NY).
Data Collection
On their first visit to the facility, patients were given a physical examination and initial interview regarding their medical history. Clinicians were required to select 1 ulcer that would be examined for the duration of the study. The selection of the ulcer was based on a point system that awarded points for pedal pulses, the ability to be probed to the bone, the location of the ulcer (ie, located on the foot rather than a toe), and the presence of multiple ulcerations. The ulcer with the highest score was selected for the study. If numerous ulcers were evaluated with the same score, the largest and deepest was selected. Wagner classification of the wound was recorded at baseline and taken at each subsequent patient visit. In addition, peripheral sensation was assessed for signs of neuropathy using Semmes-Weinstein monofilament testing.
Once selected, the wound was clinically evaluated, samples for culture were obtained, and blood tests were performed to detect the presence of wound infection. The patient’s blood was drawn for a full laboratory analysis, including white blood cell (WBC) count and measurement of blood glucose and HbA1c levels. Bone biopsy, magnetic resonance imaging, and bone scans were used to detect the presence of osteomyelitis at the discretion of the health care provider. Wounds suspected of infection, underlying osteomyelitis, or gangrene at baseline were excluded. Patients would then return for follow-up visits at least once every 6 weeks, plus or minus 2 weeks, for a maximum of 6 months.
Statistical Analysis
Utilizing SAS version 9.3 (Cary, NC), descriptive statistics (minimum, maximum, mean, median, and SD) were calculated for the following variables: age, WBC count, wound area, HbA1c, blood glucose, and body mass index (BMI). These variables were collected for each patient as per the OWEMR protocol and provided a basis for which to compare patients who underwent amputation and those who did not. Twenty patients were lost to follow-up, and therefore we altered the window of our statistics from 6 months to 3 months to provide the most accurate data, as 6-month follow-up data were limited. The patients were classified into the following categories: healed, amputated, and unhealed/non-amputated. Descriptive statistics were calculated for these 3 groups, analyzing the same variables (age, WBC count, wound area, HbA1c, blood glucose, and BMI). Additional statistical computations were utilized in order to show the prevalence and frequency of our categorical variables: gender, race, ethnicity, osteomyelitis, gangrene, and peripheral vascular disease. The baseline values of WBC count, HbA1c, wound area, and BMI of the 3 groups were analyzed with descriptive statistics for comparison. A multinomial logistic regression was then performed using a 3-level outcome variable: healed, amputated, or unhealed/non-amputated. Each predictor variable was analyzed independently due to the small sample size.