Our data suggests that the majority of patients referred for an ED assessment have incomplete growth curves. Despite a mean age of 15.5 yrs at assessment, the majority of patients presented with 2 or less growth curve weight plots prior to ED onset, suggesting either a low number of medical doctor (MD) visits during the childhood and adolescent years and/or incomplete data collection at the time of the MD visit. Literature reviewing how often patient growth charts are kept up-to-date is sparse. Two studies performed in the pediatric inpatient setting found that rates of documentation of growth parameters in the hospital were suboptimal [18, 19]. In the outpatient primary care setting, it has been shown that many practitioners report not measuring children at every health visit and when measured, the data is often not plotted or analyzed on growth curves [20, 21]. This is concerning because of the potential delay in the diagnosis of a variety of illnesses that impair growth. Moreover, our observation that patient weights were only documented, on average, approximately one year after self-reported ED onset further highlights the importance of annual health screenings.
Although the sample of patients with sufficient growth curve data deemed necessary to calculate an estimated target weight was very small in our study (35%), we were able to demonstrate good utility when completed and up-to-date growth curves were available for patients with AN/restrictive EDNOS. Although we cannot comment definitively based upon our low sample size, it makes clinical sense that the sensitivity of such predictions would only improve when growth curves contain more data points for height and weight and are completed on an annual basis.
Unfortunately, there is no current consensus among providers regarding an ideal method of HBW calculation in patients with EDs [11]. Research into this area, while limited, has explored the utility of the BMI, McLaren, and Moore methods of HBW calculation, as well as other methods such as pelvic ultrasound grading, in both ED and non-ED adolescent and adult populations [3, 4, 12, 15]. While no clear consensus has been established, the BMI method (i.e. the use of BMI growth curves) is starting to emerge as a primary choice among researchers for HBW calculations in clinical and non-clinical children and adolescents [4, 12]. In this study, we used ROM as an objective indicator of weight restoration, although many would argue that this alone may be insufficient. Of the studies that have been completed as a means of addressing this question, most have shown that menses returns at an average weight around 90% of an estimated HBW [22–25]. It is important to note, however, that the means by which the HBW was calculated in these studies varied, although authors typically did so using the median weight for height and/or age as the reference point for calculation. Given the number of confounders associated with this issue, it is not surprising that the level of individual variation is considerable. For example, several authors have shown that anywhere from 5% to over 30% of patients remain amenorrheic once they reach 90% of their estimated “normal” body weight [22–25]. In one study, 48% of patients who resumed menses did so at a weight less than 90% of the “standard body weight” (range 75 to 115%) [23]. Another study showed that ROM occurred at a weight above the population average in 31% of patients [16]. Clearly, further research into this area is required. To our knowledge, there are no other publications using historical growth curve data as a means of estimating HBW, nor comparing it to HBW based on ROM. We were also unable to find any published reference on how calculation differences (i.e. using growth curves alone vs. standardized calculation of percentile of BMI) influence rates at which ROM is demonstrated. It is also important to note that it is unclear how close the correlation between BMI and ROM is expected to be. There is a complex relationship between leptin, adiponectin, inhibin B, ghrelin and a disrupted hypothalamic regulation of menstruation that likely effects the direct correlation between BMI and ROM [26].
We believe that our data, despite its limitations, shows obvious merit in the argument that growth curves should be used as a first line to predict HBW whenever sufficient data is available and allows for accurate prediction. We have shown in our small sample that using historical growth curve data to predict HBW goals is more accurate than using the BMI method of calculation. Although a small sample, the implications for the individual patients are note-worthy. For example, the HBW prediction done by the BMI method for one of our patients was 7.2 kg lower than the weight required for ROM, and 0.7 kg lower when done by the growth curve method. Another patient’s predicted HBW goal done by the BMI method was 8.1 kg below the weight required for ROM, as compared to 2 kg above the target when done by growth curve method. Clinically, overshooting and undershooting these weight goals for patients can lead to distrust of the treatment team and plan, as well as unneeded patient anxiety. As such, we recommend that ED clinicians make every possible effort to gather prior growth information at the time a first assessment is completed. Our own program has made it mandatory for all referred patients to have a completed growth curve sent in at the time of referral, although it is clear, based upon this study, that the majority of providers are not collecting such data longitudinally. We also recommend clinicians use any other means available, such as reviewing old hospital charts, triage visit records from emergency department visits, as well as having the family provide data whenever possible. Only after this method has been exhausted and/or deemed not applicable should we look at other methods of calculating HBWs. It is important to note that in growing and developing youth, HBW goals need to be continually adjusted as height increases, to maintain the same goal BMI percentile. Using historical growth curve data is of course limited to having data available, and our study has shown that growth curves in this population are often not complete. In those cases, the BMI method of HBW calculation can be used. Another noted limitation to our method involves HBW predictions for patients who were overweight prior to ED onset. We removed 2 patients from analysis because their pre-ED BMIs were greater than the 95 percentile for age. In those cases, weight trajectory as seen on growth curves are of limited use with our method of HBW goal prediction. In those cases as well, perhaps the BMI method of calculation is most appropriate. Further research is required exploring accurate methods of estimating HBW for those who were overweight prior to ED onset, as well as for males and pre-menarchal females.
It should be stated that, as is typically the case with pediatric ED populations [27], the observed proportion of EDNOS patients in this study is much greater than that of both the AN and BN patients, although this does not limit the representativeness of the findings. A diagnosis of EDNOS is given to patients who do not exactly meet the strict criteria set forth by the DSM-IV for a diagnosis of either AN or BN, and it is this diagnostic category that predominates the treatment-seeking adolescent ED population [27]. Additionally, for the purposes of this study, the population of interest consisted of patients with AN and those with restrictive EDNOS, as the determination of a “healthy weight” is most relevant for these patients at the time of assessment.
Limitations of our study include the fact that it was retrospective in nature and relied upon chart review. As noted above, the use of ROM as the primary indicator of heath is limited for a variety of different reasons, although this alone would suggest that patients have regained sufficient fat stores and hormone levels to allow menstrual functioning to resume. Although used as a marker of health in ED patients in this study, ROM should be regarded as the first step required for maintenance of medical health, as one of the primary goals of treatment is to re-establish regular ovulatory menstrual cycles [16]. We were also limited in our analysis of the reliability of our predictions due to the low number of growth curves completed with sufficient data points. Non-significant results may also have been found due to the small sample size available for this study.
