2Accredited Practising Dietician, Nutrition and Dietetics, Flinders University, Bedford Park, South Australia, Australia
3Department of Vascular Surgery, Nutrition and Dietetics, Flinders University, Bedford Park, South Australia, Australia
4Head of Discipline, Nutrition and Dietetics, Flinders University, Bedford Park, South Australia, Australia
Methods: An invitation to complete an online 26-item questionnaire was distributed electronically by the Dietitians Association of Australia to all members. Each method used by participants for estimation of energy and protein requirements across the stages of PAD was applied to the relevant typical patient and the range of estimates reported.
Results: Twenty-two dietitians completed the questionnaire and reported caseloads inclusive of all stages of PAD and with relatively equal frequency. For estimation of energy requirements, the Schofield equations in addition to 120-125kJ/kg and 125-145kJ/kg were most frequently used. When applied to the typical patient, the estimates of requirements varied by over 5000kJ/day within each stage of PAD. For estimation of protein requirements it was common to apply the RDI (0.8-1g/kg/day) or account for minor surgery or sepsis (up to 1.5g/kg/day) for patients with rest pain or tissue loss. The estimates of protein requirements varied by up to 55g/day depending on the method used.
Conclusions: There was significant variation in energy and protein estimates both within and across the stages of PAD, which is possibly due to the little evidence available to inform dietitians on how to best treat patients with PAD. Further work is required to acquire a solid evidence base and subsequently communicate this for translation into practice.
Keywords: Energy requirements; Protein requirements; Peripheral arterial disease; Diet; Dietetic practice
On receipt of the completed questionnaires the predictive equations for estimating energy and protein requirements that were most commonly reported by participants were applied to a 'typical patient' to gain an insight into the range and potential overlap of estimations by stage of PAD. Data for the typical asymptomatic PAD patient (ICD I70.20, n=622), claudicant (ICD I70.21, n=384), patient with ischemic rest pain (ICD I70.22, n=86) and tissue loss (ICD I70.23, n=234) were obtained from the 45 and Up Study, the largest ongoing study of healthy ageing in the Southern Hemisphere and coordinated by the Sax Institute, New South Wales Australia [15]. The 'typical patient' for each stage of PAD based on the 45 and Up Study data was then used in all estimations of requirements in this study. Based on the information obtained regarding methods for energy and protein estimation, the authors developed a set of definitions based on evidence-based guidlines [16] for parameters used in estimation of energy and protein requirements. These are outlined in Table 2.
All de-identified data were imported from Survey Monkey into SPSS, version 19.0 (SPSS Inc, Chicago, IL, USA). Responses were displayed through the use of descriptive statistics to highlight trends. Continuous data were presented either as mean with 95% confidence intervals or median with Inter Quartile Range (IQR) depending on the distribution of the data. All categorical data were displayed as frequency and percentages of participants with each response.
The findings of the present study would indicate that evidence-based recommendations to guide dietitians when estimating the energy and protein requirements of patients with PAD would be worthwhile to improve consistency in approach. The study showed that dietitians in Australia recognise that there are additional dietary energy needs during times of wound healing however when these adjustments were applied to a typical patient it resulted in only 1,000kJ extra. It might be argued that dietitians would review this estimation by monitoring body weight over time, and in the case of chronic arterial ulcers, this would be considered a valid argument. It is not however a valid
|
Rutherford classification |
Mean age (yrs) of typical patient∞ |
Mean weight (kg) of typical patient∞ |
Stage 0 |
Asymptomatic |
73.9(M) 74.6(F) |
81.6(M) 67.2(F) |
Stage 1 |
Mild claudication |
|
|
Stage 2 |
Moderate claudication |
|
|
Stage 3 |
Severe claudication |
73.0(M) 74.2(F) † |
81.7(M) 66.4(F) † |
Stage 4 |
Ischemic pain at rest |
75.2(M) 77.1(F) |
79.4(M) 63.3(F) |
Stage 5 |
Ischemic ulceration not exceeding ulcer of the digits of the foot |
|
|
Stage 6 |
Severe ischemic ulcers or gangrene |
78.8(M) 81.8(F) ‡ |
79.7(M) 64.7(F) ‡ |
Parameter reported by survey participants |
Definition utilized by authors |
Actual Body Weight (ABW)
|
Current body weight on presentation |
Ideal Body Weight (IBW)
|
Body weight representative of Body Mass Index 22.5kg.m2
|
Adjusted ideal body weight (AiBW)
|
Weight at the mid-point between ABW and IBW
|
Weight loss factor (WLF) |
Deficit of 2143kJ/day from the estimated energy requirements to induce 0.5kg weight loss/week. |
|
Asymptomatic |
Claudication |
Rest pain |
Tissue Loss |
||||
|
Male |
Female |
Male |
Female |
Male |
Female |
Male |
Female |
EER (Schofield x 1.2) |
7747 |
6369 |
7757 |
6332 |
7617 |
6192 |
7638 |
6257 |
EER (Schofield x 1.2, WLF 0.5kg)
|
5604 |
4226 |
5614 |
4189 |
5474 |
4049 |
5495 |
4114 |
Non-ambulatory or sedentary, not hypermetabolic (100-120kj/kg |
8158-9790 |
6719 - 8063
|
8174-9809
|
6637-7964
|
7936-9523 |
6330-7596 |
7972-9566 |
6472-7766 |
Slightly hypermetabolic, post-operative, repletion, infection(120-145kj/kg)
|
- |
- |
9809-11853 |
7964-9624 |
9523-11507 |
7596-9179 |
9566-11559 |
7766-9384 |
Hypermetabolic, severely stressed, malabsorption, major trauma, sepsis (145-160kj/kg) |
- |
- |
- |
- |
- |
- |
11559-12755 |
9384-10355 |
120-125kj/kg |
9790-10198 |
8063-8399 |
9809-10218 |
7964-8296 |
9523-9920 |
7596-7913 |
9566-9965 |
7766-8090 |
125-145kj/kg |
10198-11829 |
8399-9743 |
10218-11853 |
8296-9624 |
9920-11507 |
7913-9179 |
9965-11559 |
8090-9384 |
Method of estimation |
Asymptomatic |
Claudication |
Rest pain |
Tissue Loss |
||||
|
Male |
Female |
Male |
Female |
Male |
Female |
Male |
Female |
EPR (RDI 0.8g/kg) |
65.2 |
53.8 |
65.4 |
53.1 |
63.5 |
50.6 |
63.8 |
51.8 |
EPR (RDI 0.85g/kg) |
69.3 |
57.1 |
69.5 |
56.4 |
- |
- |
- |
- |
EPR (RDI 1g/kg) |
81.5 |
67.2 |
81.7 |
66.4 |
79.4 |
63.3 |
79.7 |
64.7 |
Minor Surgery (1g/kg) |
81.5 |
67.2 |
81.7 |
66.4 |
79.4 |
63.3 |
79.7 |
64.7 |
Minor Surgery (1.2g/kg) |
97.8 |
80.6 |
98.1 |
79.6 |
95.2 |
76.0 |
95.7 |
77.7 |
Sepsis (1.2-/kg) |
- |
- |
- |
- |
95.2 |
76.0 |
95.7 |
77.7 |
Sepsis (-1.5g/kg) |
- |
- |
- |
- |
119.0 |
95.0 |
119.6 |
97.1 |
Unlike estimates of energy requirements, some dietitians in this study did report that they were likely to adjust dietary protein requirements with stage of PAD. Despite this, when the adjustment factors reported were applied to the typical patient, the dietary protein requirements for those with sepsis, rest pain or tissue loss were similar to estimates for asymptomatic PAD patients and those with claudication. Conventional management of these patients is supervised exercise training and emerging evidence suggests that repeated exposure to ischemic reperfusion injury initiates muscle atrophy, specifically in the symptomatic leg [19]. Accurate dietary protein estimates and prescription is likely critical in the prevention of this adverse outcome.
It is important to declare that this study is not devoid of limitations and hence interpretation of the findings should be considered with caution. The small sample of dietitians (n=22) who responded to the questionnaire is one important limitation that may impact on the generalisability of the findings. The widely accepted Dillman Protocol for Web-Based Surveys [13] was used with the intention to maximise response rates through the use of reminder emails and simple questionnaire design. The sample included dietitians Australia-wide and it is interesting to note that their characteristics were not dissimilar to those of the DAA member population according to the 2011 DAA Annual Report [20]. Some of the assumptions made in the calculations of requirements for the typical patients may not be truly reflective of the intentions of those completing the questionnaire. We multiplied BMR by an activity factor of 1.2 across all stages of PAD for our estimations of energy requirements however it could be argued that a higher activity factor would be more applicable for asymptomatic patients. Notwithstanding the validity of this argument, the net result of a higher activity factor would be minimal (~500kJ for an increase to 1.3) and it would not affect our findings relating to the large variation in estimating requirements of both energy and protein within each stage of PAD.
The accurate determination of dietary energy and protein requirements for PAD patients should be a priority area of research. The rate of growth in the aging population of western countries, in conjunction with a rise in Type 2 diabetes mellitus and overweight/obesity will see the number of PAD patients increase within the next decade and beyond. There was significant variation in energy and protein estimates within this study which is possibly due to the little evidence available to inform dietitians on how to best treat this patient group. Therefore, the creation of new evidence from well designed studies with larger sample sizes investigating the energy and protein requirements, and the development and communication of evidence-based guidelines on how to adequately provide nutritional care to PAD patients is an urgent area for further research. In the interim, dietitians should use available equations for estimating requirements with caution and closely monitor the nutritional intake and nutritional status of this patient group allowing adjustment of estimates over time.
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