LLA is most frequently performed in older patients with vascular disease, a population that is, for the most part, under-represented in research [1]. Multiple co-morbidities and cognitive decline can prevent this sub-population from meeting required inclusion criteria. The issue of bias in studies of elderly people is well recognized [1]–[4]. The same is true of amputation research, with authors’ invariably describing selection bias within their sample as a limitation of their study [5]–[11]. However, the impact of this bias is rarely described [12]. It is important to understand this research limitation in applying results to clinical practice and to better design future studies.

From the current study, one hospital was unable to identify the relevant files because of changes in their database. This hospital was excluded and subsequently, one patient from this hospital who had been referred to the PP study was excluded.

Thirty nine (27%) of a possible 146 patients were referred during the first full year of the study (table 1). The referred population had a median age 8 years younger (p<0.001) and were less likely to have had amputation because of a vascular condition, diabetes or infection (p=0.003) than those who were not referred. More non-referred patients had bilateral amputation while more referred patients had a knee disarticulation (p=0.049). No differences in the number or type of major co-morbidities were seen, although referred patients were more likely to have had undergone a previous vascular intervention (p=0.042) such as a peripheral bypass procedure or angioplasty. Referred patients were more frequently discharged home or to a rehabilitation centre with non-referred patients more often discharged to a care centre (p=0.020).

There was a significant difference in one year survival between the groups; 67% of referred patients survived compared with 40% of non-referred patients (p=0.004). Overall survival time after amputation also differed significantly (figure 1): median (standard error) survival for referred group=41.1 (7.9) months, non-referred=13.6 (6.6) months, χ²(1df)=5.6; p=0.018.

To verify whether or not the differences in the groups were linked to the significantly poorer survival of the non-referred population, characteristics of patients who survived to 12 months are presented in table 2. There remained a significantly younger median (p=0.016) and mean (p=0.007) age difference between the referred and non-referred group. Again, the referred group were more likely to have had a knee disarticulation, less likely to have had a transtibial amputation (p=0.041), and more frequently had amputation because of non-vascular causes (0.012). There were no other significant differences between the referred and non-referred groups in 12 month survivors. Overall survival differed by 9 months (median (standard error) survival for referred group=64.1 (14.7) months, non-referred=55.6 (11.5) months, χ²(1df)=1.8; p=0.177) and non-referred patients were more frequently discharged to a care center while referred patients were more often discharged to a rehabilitation center (p=0.130).

The PP study described a prevalence rate for phantom pain of 32% measured 6 months after amputation [5]. Other literature measuring occurrence at 6 months has reported more than double this amount, with 65–79% of people having phantom pain [13], [14]. Occurrence rates at 6 months in trials to treat phantom pain range from 0–38% (0/10 in intervention; 5/13 in control group) [15] to 9–73% (1/11 in intervention; 8/11 in control) [16]. The PP study has a lower rate of phantom pain than expected which raises some uncertainty in generalisation and clinical application of the protective factors identified. These protective factors should be considered within the context of the biased population.

Three protective factors against the development of phantom pain were described: being male, having a lower limb amputation (versus an upper limb amputation) and time since amputation [5]. In the current study, there were no differences in sex between referred and non-referred patients (upper limb amputations were not included and only one year of the PP study was analysed). Other factors in the PP study were also investigated but not found to be significant, including level of amputation, cause of amputation and age at time of amputation. None of these factors were accurately represented by the sample referred to the PP study and it is not possible to draw a valid conclusion over their influence based only on this data.

The factors identified in the PP study were largely in disagreement to other literature. In addition to prevalence rates being much higher than the PP study, sex is reported as being unrelated to occurrence of phantom pain [13], [17] although males and females may deal with the pain differently [18]. Increasing age is shown as having a higher risk of phantom pain [19] while others have reported no relation [17] or not included age in their analysis [13]. More proximal amputation levels, and having bilateral amputation, may increase a person’s risk of phantom pain [19] although again others have found no association between the two [13], [20].

The contradictory findings surrounding phantom pain in these different populations are, at least in part, also partly attributable to differences in definitions and study design. Cut-off points for what constitutes phantom pain can include people with almost constant pain or people who experience only occasional pain [5]. Most previous studies of phantom pain are cross sectional and direct cause and effect cannot be stated. Studies include people with differing lengths of time since amputation, from a few months to many years [18], [19], [21], yet time since amputation is another factor potentially linked to phantom pain. Poor physical condition from co-morbidities and cognitive deficit leads to difficulties in patient inclusion and sample sizes are generally small. As amputation research is also characterised by a high mortality rate, follow up rates are often low. In this study almost 50% of the total population had died within 12 months of their first major amputation, including 33% of the referred group. The PP study is the largest longitudinal study of phantom pain performed (total included at first follow up was 85 from 120 included) and followed patients for up to 3.5 years [5]. Unfortunately, the substantial bias seen in the population presents a major limitation and there remains limited evidence around risk factors associated with phantom pain. Reviews looking at mechanisms and treatment of phantom limb pain reveal similar shortcomings in methodology [22]–[26].

A major difficulty with amputation outcome research is obtaining large and representative samples. The reasons for having an amputation make it difficult for many cases to be included in research as elderly people with systemic disease tend not to be considered for participation and have a higher rate of drop out or death [1]. This appeared to be a key element of (non)recruitment to the PP study, with patients who were older and with amputation due to vascular disease least likely to be referred. Data, or at least their estimates, on non-participants (including people who did not give consent, patients who are excluded, deaths and drop outs) should be communicated by authors. In the PP study, all referral sources were requested to provide this information, but unfortunately it did not occur. Minimal data presented in amputation research should include the number of participants and non-participants, age, sex, level of amputation and cause of amputation.

Our data were split to look at 12 month ‘non-survivors’ compared to ‘survivors’. With outcomes of interest for the ‘frailer’ group likely differing from the survivors, it is reasonable that they are not included in longitudinal outcome research. Unfortunately, our results showed that a substantial number of this healthier group, the 12-month survivors, also failed to be included in the PP study. In designing any study, gaining strong interest and support from relevant stakeholders and referral sources is vital. In the case of the PP study, referral sources (surgeons and staff) were informed of the aims and methodology at a regional meeting, with verbal agreements given for participation (referral of patients). The high referral rate (>85% of all within hospital, contributing >69% of all referred) from the study’s operating/base hospital, suggests either the physical presence of the investigator and/or simply being the study’s main location are the most effective strategies for recruitment. Across the entire regional network of hospitals, a physical presence was not possible. Attempts to counter this limitation through regular phone and newsletter contact were unsuccessful, with 6 hospitals not referring patients in the first year despite their agreement. Improving recruitment via clinicians is a difficult task; even large randomised controlled trials have great difficulty identifying successful strategies [27]. Adding to this are strict timeframes of the inclusion criteria of the PP study with referral set for within 5 days. This meant that surgeons (and their staff) were primarily responsible for identifying cases, at a time when other factors, such as pre-operative assessment, can naturally be of a greater priority. It is not routine practice for the rehabilitation physician to be involved pre-surgically so this additional referral source was not utilised. Other alternatives were not considered as clinically relevant options, such as extending the inclusion period to >5 days, as this would have introduced problems with recall.