PropertyValue
is nif:broaderContext of
nif:broaderContext
is schema:hasPart of
schema:isPartOf
nif:isString
  • This study was a secondary analysis of data collected from a validated prospective state-wide clinical diabetic foot database in Queensland, Australia (Queensland High Risk Foot Form Database [12, 13]). The study received multi-site ethical approvals from two Australian Human Research Ethics Committees (HRECs); The Prince Charles Hospital (HREC/15/QPCH/177) and the Queensland University of Technology (1500000700). Furthermore, the study received legal approvals from the Queensland Statewide Diabetes Clinical Network Data Access committee and a Queensland Public Health Act 2005 waiver (QCHO/009321/RD006012) to use confidential de-identified information from the database for the purposes of this study. Thus, individual consent was not required or available for this study. Queensland is the third largest Australian state in terms of population, second largest in area and the most decentralised state with extremely diverse demography and geography [14]. Patients attending an outpatient Diabetic Foot Service in 13 of the 17 Hospital and Health Service areas in Queensland for treatment have their diabetic foot clinical data captured at each visit on a validated Queensland High Risk Foot Form (QHRFF) [12, 13, 15]. The QHRFF data is then collated and cleaned in the centralised QHRFF database for DFU healing and recurrence clinical benchmarking and research purposes [12, 13]. Eligible patients for this study were patients attending an aforementioned Diabetic Foot Service in Queensland for their first clinical visit that recorded an uninfected DFU between 1st January 2012 and 31st December 2013. The first clinical visit was defined as the first date the patient attended the Diabetic Foot Service between 1st January 2012 and 31st December 2013. A patient may have attended the service prior to 2012; however, this data was not captured for this study. A DFU was defined as a full thickness wound beneath the ankle on a patient with diabetes [4, 12]. An uninfected DFU was defined according to the International Working Group on the Diabetic Foot classification system as having no clinical signs or symptoms of infection [16, 17]. Patients were then followed from their first clinical visit until their DFU healed or if it did not heal for 12 months. Exclusion criteria included patients who did not have their infection status recorded at their first clinical visit (baseline) or at follow up visits prior to their DFU healing or if it did not heal prior to 12 months (follow up). For the purposes of this study the explanatory variables were those collected using the QHRFF at the patient’s first clinical visit. If data were missing for a variable, the second visit’s data was used for that variable(s) if available, provided the second visit was within one month of the first visit. The QHRFF data collection procedures, methods and definitions have been reported in detail elsewhere [12, 13, 18]. In brief, the QHRFF has been reported to be valid and reliable for the capture of multiple self-reported and clinically diagnosed variables when collected by clinicians with a range of diabetic foot disease experience [12]. The self-reported variables included: demographic (age, sex, indigenous status and residential postcode); diabetes history (diabetes type, diabetes duration, glycated haemoglobin (HbA1c) and blood glucose levels (BGLs) >15 mmol/L in the previous 14 days); medical history (hypertension, dyslipidaemia, cardiovascular disease, chronic kidney disease and smoking status); foot disease history (previous foot ulcer and previous amputation); and past foot treatment in the previous 14 days (by podiatrist, general practitioner, surgeon, physician, nurse, orthotists or other) [12]. Patient’s postcode of residence was transformed into the social determinant variables of socioeconomic status (according to the Australian Index of Relative Social Disadvantage [19]) and geographical remoteness status (according to the Accessibility/Remoteness Index of Australia [20]). The clinically diagnosed variables included: foot risk factors (peripheral neuropathy (PN), lack of protective sensation to a 10-gram monofilament on at least 2 of 3 plantar forefoot locations [21, 22]; peripheral arterial disease (PAD), toe systolic pressure <70 mmHg [21, 22]; foot deformity, scored at least 3 points on a 6-point foot deformity score [22]; suspected acute Charcot foot, red, hot, swollen, unilateral neuropathic foot joint without a DFU near the suspected Charcot joint [22]); foot ulcer characteristics (ulcer surface area (mm2); grade and depth, according to the University of Texas Diabetic Wound Classification System [4]; deep ulcers, scored a 2 (“wound penetrating to tendon or capsule”) or 3 (“wound penetrating to bone or joint”) [4]; and infection status according to the International Working Group on the Diabetic Foot classification system [16, 17]) [12]. DFU treatment provided on the first clinical visit was also recorded, including if the DFU was treated with: sharp debridement; appropriate wound dressings; prescribed antibiotics; optimum offloading in a cast walker; appropriate footwear; and patient education on DFU care [12, 22]. Lastly, foot ulcer healing time was captured and defined by subtracting the date of first clinical visit (as defined above) from the date the ulcer was recorded as healed (complete epithelialisation) [4, 12]. Ulcer healing time was categorised into: i) healed <3 months (<90 days since first visit), ii) healed between 3–12 months (91–365 days), iii) not healed at 12 months (ulcer had not healed at 365 days since first clinical visit). The primary outcome variable for this study was the development of a foot infection prior to when the DFU healed or if the DFU did not heal then prior to 12-months after the first clinical visit. Foot infection was defined according to the International Working Group on the Diabetic Foot classification system as at least two clinical signs or symptoms of infection in or around the DFU including purulence, erythema, pain, tenderness, warmth and/or induration [16, 17, 23]. Patients were also sub-grouped into the following types of DFU: neuropathic (PN and no PAD), ischaemic (PAD and no PN), neuro-ischaemic (PN and PAD), post-surgical (recent non-healed minor amputation procedure regardless of PN or PAD), other (none of the aforementioned DFU types) or unknown (PN, PAD or post-surgical was not recorded). For patients with multiple DFUs a combined surface area of the multiple DFU was calculated, and the DFU type, grade, depth and treatment characteristics for the worst DFU used [12]. Statistical analyses were performed with IBM SPSS 23.0 Statistics for Windows (SPSS Inc., Chicago, IL, USA) or GraphPad Software. Categorical variables were expressed as proportions (%) and continuous variables were expressed as a mean (standard deviation (SD)). Incidence was expressed as the proportion (%) of patients developing an infection of eligible patients; for overall patients, different DFU types, and ulcer healing time categories. For categorical variables Pearson’s chi-squared tests were used to test for any differences between groups (p<0.05) and Fisher’s exact test with Bonferroni corrections were used for post-hoc pairwise comparisons (p<0.005) [24, 25]. For continuous variables analysis of variance (ANOVA) with Tukey’s post-hoc test used were used to test for differences between groups (p<0.05) [24, 25]. Univariate logistic regression analyses were used to test for crude associations (p<0.1) [26]. All variables achieving a crude association were included in a multivariate logistic regression analysis to test for independent risk factors [26]. A backwards stepwise method was used to remove non-significant variables (p>0.05) at each step until only variables reaching statistical significance remained (p<0.05) [26, 27]. If collinearity was identified using a correlation matrix (>0.9) the variables with the lowest odds ratio was excluded [26]. Hosmer and Lemeshow goodness of fit, Omnibus degrees of freedom, Negelkerke pseudo R2 tests and significance were assessed at each step [26, 27]. Missing data were treated by excluding cases with missing data as the proportion of missing data were <5% in the model [26].
rdf:type