Nodulos de Schmorls

International Journal of Osteoarchaeology Int. J. Osteoarchaeol. 18: 28–44 (2008) Published online 5 July 2007 in Wiley InterScience (www.interscience.wiley.com) DOI: 10.1002/oa.924

Schmorl’s Nodes: Clinical Significance and Implications for the Bioarchaeological Record K. J. FACCIA a* AND R. C. WILLIAMS b a

University of Calgary, Department of Archaeology, 2500 University Dr. NW, Calgary, AB T2N 1N4, Canada b Arizona State University, School of Human Evolution and Social Change, PO Box 872402, Tempe, AZ 85287-2402, USA

ABSTRACT

Back pain is one of the major contributors to disability and loss of productivity in modern populations. However, osteological correlates of back pain are often absent or, as yet, unidentified. As bioarchaeologists depend on osteological evidence to interpret quality of life in the past, back pain, with its profound effects on modern populations, is largely overlooked in archaeological samples. This study addresses this shortcoming in bioarchaeological analysis by exploring the relationship between a defined vertebral osteological lesion, the Schmorl’s node, and its effect on quality of life in a clinical population. Using patient insight, healthcare practitioner diagnoses and MR imaging analyses, this study investigates: (1) Schmorl’s nodes and sociodemographic factors; (2) the number, location and quantitative aspects (e.g. length, depth, area) of Schmorl’s nodes, and how these influence the reporting of pain; (3) the dynamic effects of Schmorl’s nodes, in combination with other variables, in the reporting of pain; and (4) the perception and impact of pain that patients attribute to Schmorl’s nodes with regard to quality-of-life issues. The results of this study indicate that Schmorl’s nodes located in the central portion of the vertebral body are significantly associated with patient reporting of pain, and that the presence of osteophytes, in the affected vertebral region, may increase the likelihood that an individual will report pain. This finding provides bioarchaeologists with an osteological correlate to begin interpreting the presence and impact of pain in archaeological populations, with implications for scoring Schmorl’s nodes. Copyright ß 2007 John Wiley & Sons, Ltd. Key words: Schmorl’s node; back pain; vertebra; lesion; scoring

Introduction Complementing bioarchaeological analyses with current medical research allows more informed interpretations of archaeological populations. The Schmorl’s node is a vertebral lesion that is regularly found in both present and past populations; however, the impact of the Schmorl’s node on quality of life (pain, mobility, etc.) is poorly * Correspondence to: University of Calgary, Department of Archaeology, 2500 University Dr. NW, Calgary, AB T2N 1N4, Canada. e-mail: [email protected]

Copyright # 2007 John Wiley & Sons, Ltd.

understood. Therefore it is important for studies to address the impact of this lesion on an extant population’s quality of life because, if Schmorl’s nodes do cause pain or disability, this lesion could have had profound effects on archaeological individuals and populations with regard to activity, productivity, social relationships and morbidity. This study investigates the presence and impact of Schmorl’s nodes in a clinical pain population, addressing: (1) Schmorl’s nodes and sociodemographic factors; (2) the number, location and quantitative aspects (e.g. length, depth, area) of Schmorl’s nodes, and how these influence the Received 25 June 2006 Revised 6 November 2006 Accepted 20 February 2007

Significance of Schmorl’s Nodes reporting of pain; (3) the dynamic effects of Schmorl’s nodes, in combination with other variables, in reporting pain; and (4) the perception and impact of pain attributed to Schmorl’s nodes by patients on their quality of life. This study tests whether Schmorl’s nodes are capable of causing back pain, and it is hypothesised that the degree of pain is related to the number, location and physical characteristics (e.g. length, depth, area) of the nodes. If a significant relationship between Schmorl’s nodes and pain is found, then this study will provide bioarchaeologists with an osteological correlate to begin interpreting the presence and impact of pain in archaeological populations.

Back pain The ability to work and be a productive member of society is important. In the US, health statistics indicate that back pain is one of the primary factors leading to a loss of productivity (Argoff & Wheeler, 1998). Approximately 27% of workplace injuries are related to the back, costing that nation an estimated 11 billion dollars in care (1994 statistic: National Institutes of Health, 1997) and between 50 and 100 billion dollars per year in lost work and disability payouts (1990 statistic: Centers for Disease Control and Prevention, 1998). It is estimated that 80% of the US population will at some point suffer from back pain (Kelsey & White, 1980), the highest rates occurring in middle-aged1 individuals (National Institutes of Health, 1997). As Argoff & Wheeler (1998) summarised, back pain is the leading cause of disability in the under-45 age group, the fifth leading cause of hospitalisation, and the third leading cause of surgery. Although back pain has such an adverse effect on populations and productivity, its causes are still under investigation, and corresponding osteological indicators continue to perplex and/or evade the medical community. As Argoff & Wheeler (1998) argued in their review of various studies, most acute pain is non-specific, and chronic pain is usually considered to be caused by degenerative changes, 1 Although ‘middle-aged’ is not defined in this publication (NIH, 1997), the author does note that back pain is the most frequent reason for activity limitation in individuals less than 45 years.

Copyright # 2007 John Wiley & Sons, Ltd.

29 although this is not often supported by radiological findings. This is problematic for bioarchaeology, as researchers in this field depend upon skeletal indicators to interpret life in the past. If back pain is so debilitating today, even with the advantage of modern medicine, its effects on populations in the past must have been profound as well. Therefore, if skeletal correlates of back pain are not understood, then a major issue of past life is largely being overlooked. The present study addresses this shortcoming in bioarchaeological analysis by exploring the relationship between a defined spinal osteological lesion and its effect on quality of life in a clinical population, using patient insight, healthcare practitioner diagnoses, and magnetic resonance imaging (MRI) analyses. The results of this study may then be used by bioarchaeologists to arrive at more holistic interpretations of life in archaeological populations.

Schmorl’s nodes Schmorl’s nodes were extensively studied by and named after Georg Schmorl (Schmorl, 1926; Schmorl & Junghanns, 1959). Technically, the term ‘Schmorl’s node’ applies to prolapsed intervertebral disc material that enters into the vertebral body, superior or inferior to the disc (Schmorl & Junghanns, 1959: 133). However, this term has been adopted to apply to the end result of the prolapsed disc, or the lesion that eventually forms on the surface of the affected vertebral body. In this study, the term Schmorl’s node will refer to the osteological lesion (Figure 1). Defined as such, Schmorl’s nodes are quite commonly found in archaeological, cadaveric and extant populations (for examples, see Merbs, 1983; Malmivaara et al., 1987; Wagner et al., 2000). However, despite the prevalence of Schmorl’s nodes throughout time, and despite the fact that this type of lesion has been the focus of research for nearly a century, the link between Schmorl’s nodes and pain is still poorly understood. The process of Schmorl’s node formation (Schmorl & Junghanns, 1959) begins with an inferiorly or superiorly directed extrusion of nucleus pulposus material. Subsequently, the fluid travels through a break or fissure in the cartilaInt. J. Osteoarchaeol. 18: 28–44 (2008) DOI: 10.1002/oa

30

Figure 1. Arrow points to Schmorl’s node on thoracic vertebral body. From Shamanka II, Lake Baikal, 2004, V.I. Bazaliiskii (Director). Photograph by Mike Metcalf, Baikal Archaeology Project (SSHRC-MCRI No. 412-2000–28). This figure is available in colour online at www.interscience.wiley.com/journal/oa.

ginous endplate and erodes into the vertebral body. Here, degeneration of local trabeculae ensues, resulting in a small ‘cavitation’ in the surface of the vertebral body. In reaction to changes in pressure within the vertebral body, caused by intruding nucleus pulposus material, an osseous barrier is formed that ultimately prevents further progression of the extruded material into the vertebral body. Once the reaction is complete, the result is what is considered a completed Schmorl’s node, a smooth-walled lesion on the inferior or superior surface of the vertebral body. Currently, research indicates that Schmorl’s nodes result from: (1) congenital defects of the spine; (2) traumatic events; and (3) senescent processes (Resnick & Niwayama, 1978). Congenital defects include conditions such as Scheuermann’s kyphosis, which often results in a series of Schmorl’s nodes throughout the spinal column (Tribus, 1988). In Scheuermann’s kyphosis, classic vertebral symptoms include: contiguous vertebral wedging of 58 or more, narrowed disc space, and irregular endplates (Tribus, 1988). The combination of these factors, when coupled with the normal loading regime of the spine, predisposes an individual to disc rupture and, subsequently, Schmorl’s nodes. Likewise, in instances of trauma, Copyright # 2007 John Wiley & Sons, Ltd.

K. J. Faccia and R. C. Williams high axial loading (Wagner et al., 2000) fractures the cartilaginous endplate, causing deformation and rupturing of the intervertebral disc, which may ultimately result in the formation of Schmorl’s nodes. With regard to senescent processes, rupturing of the intervertebral disc, particularly around the edges of the structure, is attributed to disorganisation and weakening of the annulus fibrosus (Hansson & Roos, 1983). Schmorl’s nodes are relatively common in modern populations and, although they can appear at any level in the spine, the lesions tend to concentrate in the lower back, specifically the lower thoracic and lumbar regions (Resnick & Niwayama, 1978). The high frequency of Schmorl’s nodes in the lower back is attributed to the anatomy and biomechanics of the lower spine, as the amount of loading on the spine normally increases from the cervical to the lumbar regions (Argoff & Wheeler, 1998). However, back-related trauma is also dependent on posture and various loading factors (Smith, 1969; Chaffin & Park, 1973; Adams et al., 1993). Therefore, the frequency of Schmorl’s nodes in the spinal column can vary based on activity patterns and postures. In addition, other factors related to health and degenerative disease could differentially affect the strength and integrity of intervertebral discs and vertebral bodies throughout the spinal column.

Bioarchaeological context Schmorl’s nodes are frequently found in archaeological populations, regardless of the antiquity of the population, the subsistence strategy or the geographical location. For example, Schmorl’s nodes have been noted in skeletal samples that include (in basic chronological order, from ca. 7000 years BP to the 20th century), but are not limited to: mid-Holocene hunter-gatherers from Lake Baikal, Siberia (Faccia, n.d.); Neolithic and medieval populations in western Switzerland (Kramar et al., 1990); Middle Kingdom to Roman period Egyptians buried at Abydos (Baker, 1997); Iron Age Italians (Robb et al., 2001); Woodland period Native Americans living in Illinois (Buikstra & Cook, 1981); a Towton (English) battlefield population (Coughlan & Holst, 2000; Knu¨sel, 2000; Knu¨sel & Boylston, 2000); the Int. J. Osteoarchaeol. 18: 28–44 (2008) DOI: 10.1002/oa

Significance of Schmorl’s Nodes Sadlermiut of Hudson Bay, Canada (Merbs, 1983); and Colonial and slave era AfricanAmerican communities in the southern US (Angel et al., 1987; Kelley & Angel, 1987; Owsley et al., 1987; Rathbun, 1987; Parrington & Roberts, 1990). Together, these archaeological studies and observations indicate that Schmorl’s nodes are found cross-culturally, throughout various time periods, and in groups differing in subsistence and overall activity patterns. A few of the bioarchaeological studies above note the presence of Schmorl’s nodes, but do little else to interpret them (Buikstra & Cook, 1981; Merbs, 1983; Kramar et al., 1990). Others (Angel et al., 1987; Owsley et al., 1987; Kelley & Angel, 1987; Baker, 1997; Coughlan & Hoist, 2000; Knu¨sel, 2000; Knu¨sel & Boylston, 2000) use the presence of Schmorl’s nodes as indicators of demanding physical activity. Some authors go further by using Schmorl’s nodes to assess differences in activity patterns between the sexes (Rathbun, 1987; Parrington & Roberts, 1990) or between social classes (Robb et al., 2001). However, none of the researchers question how Schmorl’s nodes impacted the quality of life experienced by historic and prehistoric peoples. The lack of this sort of analysis is partly due to ambiguity in the medical literature as to whether Schmorl’s nodes cause pain. If the impact of Schmorl’s nodes in clinical samples were better understood, bioarchaeologists would be able to assess these lesions with regard to their impact on an individual’s and group’s quality of life, as well as social dynamics issues. For example, in past populations, back pain could have led to an individual’s dependence on others, and this could have led to a diminished status within the social group. Particularly if physical activity were constant and demanding, pain could have greatly affected the health and survival of an individual. On a larger scale, chronic back-pain issues could conceivably have compromised the overall strength, health and viability of a social group.

Modern context In the medical community, confusion exists as to whether Schmorl’s nodes cause pain. Researchers continue to study these lesions and, with the Copyright # 2007 John Wiley & Sons, Ltd.

31 advent of MRI technology, Schmorl’s nodes are more quickly and frequently detected in extant populations (Walters et al., 1991; Hamanishi et al., 1994). Therefore, the process of node formation, and the prevalence of Schmorl’s nodes within living individuals and populations, is becoming clearer. Currently, studies in extant populations present reports of both symptomatic (Smith, 1976; Walters et al., 1991; Hamanishi et al., 1994; Takahashi & Takata, 1994; Takahashi et al., 1995; Wagner et al., 2000) and asymptomatic nodes (Hamanishi et al., 1994; Ogon et al., 2001). In general, researchers argue that Schmorl’s nodes may be an initial, post-traumatic source of pain, but they hesitate to attribute long-lasting painful effects to the lesions. Often, researchers report the presence of a painful Schmorl’s node, but that pain tends to subside within weeks (Smith, 1976; Walters et al., 1991; Takahashi et al., 1995; Wagner et al., 2000), often within the time-frame necessary for the healing of joint and soft tissue injuries (Argoff & Wheeler, 1998). However, the conclusions of these studies do not echo the experience of many patients, who insist that their Schmorl’s nodes are chronically painful. Although patients claim that their Schmorl’s nodes cause pain, the medical community still disputes whether these nodes are actually painful, or whether the pain is due to other factors, either physically or psychologically mediated (Argoff & Wheeler, 1998). Essentially, a disconnection exists between the pain that a patient attributes to the Schmorl’s node(s) and the conclusions of modern medical studies, which are unable to find a link between the lesion and pain. Therefore, particularly for bioarchaeological studies, it is important to continue analysing the relationships between qualitative and quantitative aspects of the Schmorl’s node, a defined osteological lesion, and perceived pain. Such analyses will then facilitate more informed interpretations of quality-of-life issues in the present and past. The hesitation of the medical and research communities to attribute pain to Schmorl’s nodes may be due to a long-standing lack of understanding as to the innervation of the vertebral body. Most research involving the innervation of the spinal complex focuses on soft-tissue anatomy rather than on the vertebrae themselves (AntoInt. J. Osteoarchaeol. 18: 28–44 (2008) DOI: 10.1002/oa

K. J. Faccia and R. C. Williams

32 nacci et al., 1998). However, recent studies indicate that nerves enter the vertebral body through basivertebral foramina and small apertures in the anterior cortex (Antonacci et al., 1998). Also, Fras et al. (2003) found that basivertebral nerves stain positive for substance P, a peptide neurotransmitter that is released in response to painful stimuli. Therefore, the authors postulate that basivertebral nerves are probably a part of the sympathetic nervous system, which strongly suggests that nerves within vertebral bodies are capable of transmitting painful signals (Fras et al., 2003). In addition to the findings indicating that vertebral bodies are heavily innervated, researchers have discovered that nerve bundles are frequently found in association with vertebral fractures, extruded bone marrow, and, in some instances, near-new endochondral bone formation (Antonacci et al., 2002). Therefore, Antonacci et al. (2002) postulate that these nerve bundles not only aid in the healing process, but may be a factor in generating back pain. Based on this information, it seems logical that spinal lesions, such as Schmorl’s nodes, would cause pain. It further follows that the acuity and longevity of pain caused by the Schmorl’s node could be related to the location and size of the lesion, or the degree to which it overlaps with or aggravates an innervated region. In support of this hypothesis, Ogon et al. (2001) did find that larger and more anteriorly located (non-Schmorl’s node) vertebral lesions were significantly correlated with pain. Therefore, the premise of this study is that Schmorl’s nodes are capable of causing pain, and it is hypothesised that the degree of pain is related to the number, location and physical characteristics (e.g. length, depth, area) of the nodes.

Materials and methods

Sample All patients were adult (
18 years) volunteers who were under the care of Spectrum Pain Clinics, Inc., a chronic pain management group with offices in Franklin, Clarksville and Cookeville, Tennessee, US. Health Insurance Portability and Copyright # 2007 John Wiley & Sons, Ltd.

Accountability Act2 (HIPAA) and adult consent forms were signed by all volunteers (291), and those patients with documented evidence of Schmorl’s nodes were chosen for inclusion in the study (33; 11.3%). In compliance with HIPAA regulations, all patient data were anonymised by assigning each individual an identification number, which was used for all subsequent data collection.

Data collection Data were collected from the following sources: the patient, the patient’s medical chart, diagnostic imaging reports, and patient MRIs. The questionnaire was based on a modified clinic form that patients were required to complete upon their initial visit to Spectrum Pain Clinic. Demographic and socioeconomic information was included, general questions addressing back pain were modified to address specifically the pain that patients attributed to their Schmorl’s nodes, and questions were added regarding the impact of Schmorl’s nodes on quality of life issues. Twenty-six (79%) patients completed and returned the questionnaire. Two forms were used to collect data from the patient’s chart. One form was used to collect additional demographic, family medical, and pain history information prior to clinic treatment. This form was collected for all patients (n ¼ 33). The second form was used to collect data based on healthcare practitioner forms that were completed upon each individual medical appointment. In addition to the patient’s age, weight and height, information was gathered on the spinal region where pain was presented, aggravating and relieving factors, the history of pain and pain treatment, and a diagnostic review of patient health. This form was collected for each patient (n ¼ 33), for monthly visits extending as far back as January 2002 (total n ¼ 328), but only for the visits after which a Schmorl’s node(s) was 2

HIPAA is a United States federal act that was enacted in 1996 and intended to (1) create standards and requirements for the electronic submission of healthcare information, (2) protect the continuity of patient healthcare coverage, and (3) protect the patient from the abuse of their personal healthcare information (Public Law 104–191).

Int. J. Osteoarchaeol. 18: 28–44 (2008) DOI: 10.1002/oa

Significance of Schmorl’s Nodes diagnosed. Based on these criteria, a total of 328 patient visits were included in this study. Two diagnostic imaging forms were used to collect data based on MRIs. One form was used to review those MRI reports that diagnosed the presence of Schmorl’s nodes in the patient, and this form was completed for all subjects (n ¼ 33). The collected information included the number and location of Schmorl’s nodes in the spinal column, the region of the Schmorl’s node(s) (e.g. cervical, thoracic, lumbar, sacral), and the hard and soft tissue pathological conditions in the back (e.g. discogenic, neurological, sclerotic, and jointrelated abnormalities). A second form was used to record qualitative and quantitative information gathered directly from the MRIs. Of the 33 patients, MRIs were obtained for 28 individuals, although one was excluded due to the extremely poor quality of the film. Five MRIs were requested but not provided by the diagnostic imaging centers. The general location3 (e.g. superior or inferior; anterior third, central third, and/or posterior third) of the Schmorl’s node on the vertebral body was noted, as were the number of Schmorl’s nodes per region, and the length, depth and area of the Schmorl’s node relative to the vertebral body. Quantitative information was gathered using two methods: (1) ArcMap 8.2, a GIS program that obtains length and area measurements for irregular shapes based on a system of polygons and polylines (see Figures 2–7); and (2) computer program rulers and a manual intercept-count method (Russ, 1986), the latter of which uses the intersections of graph lines to determine percentage area (Figure 8). The following measurements were obtained and used in this study: area of the Schmorl’s node relative to the vertebral body; depth of the Schmorl’s node relative to the vertebral body; and surface length of the Schmorl’s node relative to the vertebral body. 3 The location of a Schmorl’s node is dependent on several factors, including the structural integrity of the intervertebral disc and cartilaginous endplate, the shape of the vertebral body, and the direction of loading on the spine. All but one of the Schmorl’s nodes in this study are considered central (versus peripheral) Schmorl’s nodes, as defined by Hansson & Roos (1983), meaning that the lesion is found directly under the intervertebral disc. However, in this study, the terms ‘anterior’, ‘central’ and ‘posterior’ are used to describe the location of the Schmorl’s node on the vertebral body in order to analyse how location on the sagittal plane influences the reporting of pain.

Copyright # 2007 John Wiley & Sons, Ltd.

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Figure 2. Schmorl’s node length calculated by polyline in ArcMap 8.2. This figure is available in colour online at www.interscience.wiley.com/journal/oa.

Data analysis This study employs both descriptive and statistical analyses. Descriptive analyses were performed on two levels: (1) the individual; and (2) the Schmorl’s node. Descriptive information on the level of the individual includes: sociodemographic information, patient answers regarding the impact of Schmorl’s nodes on quality of life, and the number and region of Schmorl’s nodes in the vertebral columns analysed. Descriptive information on the level of the Schmorl’s node includes: the position of Schmorl’s nodes on the vertebral body and the number of Schmorl’s nodes found in each segment of the vertebral column. Statistical analyses are also performed on two levels: (1) the Schmorl’s node; and (2) the region

Figure 3. Vertebral body length calculated by polylines in ArcMap 8.2. This figure is available in colour online at www.interscience.wiley.com/journal/oa.

Int. J. Osteoarchaeol. 18: 28–44 (2008) DOI: 10.1002/oa

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Figure 4. Schmorl’s node depth calculated by polyline in ArcMap 8.2. This figure is available in colour online at www.interscience.wiley.com/journal/oa.

K. J. Faccia and R. C. Williams

Figure 6. Schmorl’s node area calculated by polygons in ArcMap 8.2. This figure is available in colour online at www.interscience.wiley.com/journal/oa.

of the Schmorl’s node. Logistic regression models were used to test whether there was any relationship between the reporting of pain and the characteristics of Schmorl’s nodes, as well as whether or not a Schmorl’s node(s), in combination with other variables, is more likely to predispose a person to report pain. For all analyses, the explained (dependent) variable was reported pain. The Schmorl’s node is the level of analysis for the physical characteristics of the lesions. In exploring the relationship of Schmorl’s node physical characteristics and pain, the explanatory (independent) variables were: (1) the inferior or

superior location of the Schmorl’s node; (2) the total number of Schmorl’s nodes in the region in question; (3–5) the anterior, central or posterior positioning of the Schmorl’s node on the vertebral body; (6) the maximum length percentage of the Schmorl’s node relative to the vertebral body; (7) the maximum depth percentage of the Schmorl’s node relative to the vertebral body; and (8) the maximum area of the vertebral body occupied by the Schmorl’s node(s). Maximum percentage values, as recorded in the MRI slices, were used because one of the hypotheses tested in this study is that it is the size of the Schmorl’s node that influences

Figure 5. Vertebral body height calculated by polyline in ArcMap 8.2. This figure is available in colour online at www.interscience.wiley.com/journal/oa.

Figure 7. Vertebral body area calculated by polygons in ArcMap 8.2. This figure is available in colour online at www.interscience.wiley.com/journal/oa.

Copyright # 2007 John Wiley & Sons, Ltd.

Int. J. Osteoarchaeol. 18: 28–44 (2008) DOI: 10.1002/oa

Significance of Schmorl’s Nodes

Figure 8. Example of the intercept-count method. Graph interceptions in the area of the Schmorl’s node (n ¼ 2) are divided by the number of graph intersections in the Schmorl’s node plus vertebral body (n ¼ 93) and multiplied by 100 to calculate the percentage area of the Schmorl’s node relative to the vertebral body: (2/ 93)  100 ¼ 2.2%. This figure is available in colour online at www.interscience.wiley.com/journal/oa.

the reporting of pain, and that a larger Schmorl’s node is more likely to predispose a patient to report pain than a smaller Schmorl’s node, based on the assumption that a larger node would overlap with more nerve bundles and hence cause more pain. Seventy-nine Schmorl’s nodes were noted. Nine Schmorl’s nodes were not included in the analysis because their images were located at the edges of the film, and certain measurements were not attainable. However, for the other 70 Schmorl’s nodes, each was examined in relation to the reporting of pain in the region of the Schmorl’s node per office visit. Therefore, with 70 Schmorl’s nodes included in the analysis, and a total of 327 office visits during which a patient with at least one Schmorl’s node reported pain or no pain in the region of the lesion, the sample size for this analysis was n ¼ 583,4 with n ¼ 218 Schmorl’s nodes allocated to the pain group, and 4 The sample size of 583 Schmorl’s nodes is not perfectly divisible by the number of Schmorl’s nodes (70) multiplied by the number of office visits (327) because patients had varying numbers of Schmorl’s nodes and were treated over different periods of time. For example, one patient with two Schmorl’s nodes might present with pain for both lesions over the course of ten office visits (n ¼ 20 to pain), whereas another patient with three Schmorl’s nodes might present without pain over the course of four office visits (n ¼ 12). Therefore, the number of total office visits (14) multiplied by the total number of Schmorl’s nodes (5) is not equal to the sample size of Schmorl’s nodes included in the analysis (14 visits  5 lesions ¼ 70, but the sample size of Schmorl’s nodes is 20 þ 12, or n ¼ 32).

Copyright # 2007 John Wiley & Sons, Ltd.

35 365 Schmorl’s nodes allocated to the no-pain group. The region of the Schmorl’s node (e.g. cervical, thoracic, lumbar, sacral) is the unit of analysis in testing whether or not dynamic relationships exist between Schmorl’s nodes and 12 variables in the reporting of pain. The explanatory (independent) variables used in this analysis included the following: (1) age; (2) sex; (3) body mass index; (4) the region of Schmorl’s node (e.g. cervical, thoracic, lumbar or sacral); (5) a history of trauma to the region; (6) the presence of discogenic conditions (e.g. degenerative disc disease; desiccated discs; and protruding, bulging or ruptured discs); (7) failed back syndrome;5 (8) joint abnormalities; (9) compression fractures; (10) stenosis; (11) osteophytes; and (12) spinal cord abnormalities. Here, each region per patient with a Schmorl’s node is accounted for in the analysis, and each region is analysed with regard to pain or no pain reported per office visit. Therefore, the sample size for this analysis was n ¼ 327, with 125 regions allocated to the pain group and 202 regions allocated to the no pain group.

Results The results of this study are discussed in the following order: (1) sociodemographic factors; (2) Schmorl’s nodes as related to sex and age; (3) a descriptive analysis of the number and location of Schmorl’s nodes; (4) a statistical analysis of the location and quantitative characteristics of Schmorl’s nodes and their relationships with pain; (5) a statistical analysis of whether a patient is more predisposed to report pain in the region of a Schmorl’s node(s) based on age, sex, body mass index, or other pathological spinal conditions; (6) perceived pain that patients attribute to their Schmorl’s nodes; and (7) the effects of pain on patient quality of life.

5 ‘Failed back syndrome’ refers to chronic back pain after ‘unspecific treatment’ (Oaklander & North, 2001: 1540). At Spectrum Pain Clinics, Inc., this term is normally used in place of ‘failed back surgery syndrome’, which refers to chronic pain following at least one surgery (Oaklander & North, 2001: 1540).

Int. J. Osteoarchaeol. 18: 28–44 (2008) DOI: 10.1002/oa

K. J. Faccia and R. C. Williams

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Sociodemographic factors The following information is derived from patient questionnaires and, when possible, charts. If similar information was gathered from both sources, the patient questionnaire was used because (1) the information in the questionnaire was more current; and (2) the answers were directed toward the impact of Schmorl’s node(s) on pain, and not back pain in general. Sixteen of the 33 individuals in this study were female (51.6%). The average age of the patient was 42.7 years, and ages ranged from 23 to 62 years old. Twenty-six patients completed the questionnaire. Of those, the average income (US dollars) of the patients (22 responding, 4 failing to respond) was $19,253, with incomes ranging from $0 to $98,000 and a median income of $13,000. At least 12 (55%) of these patients are considered to be living below the poverty level (Office of the Federal Register, 2002). Occupations of the questionnaire sample were as follows: 21% (7) unemployed; 54% (14) disability; 15% (4) employed; and 4% (1) failed to respond to this question. Their relationship statuses were as follows: 15% (5) single; 45% (15) married; 24% (8) separated or divorced; and 15% (5) widowed. The average household size for the questionnaire sample was 2.08 individuals, with the mode being 1, and the range being 0 to 5 additional people in the household.

Schmorl’s nodes, age and sex MRIs were reviewed (27), and 79 Schmorl’s nodes were identified (see Table 1 for totals and stratification by sex). The number of Schmorl’s nodes per patient ranged from one to nine, with

the average number of Schmorl’s nodes per patient being 2.54. Overall, a greater percentage of Schmorl’s nodes was detected in the thoracic region (59.5%) than any other area of the spine, with the lumbar region (38.0%) being the second most numerous area; the sacrum and cervical regions had one lesion (1.3%) each. When stratified by sex, women had 35 Schmorl’s nodes, or 44.4% of the total, and each woman had an average of 2.19 lesions. Men had 44 Schmorl’s nodes, or 55.7% of the total, with an average of 2.93 lesions. Schmorl’s nodes in women were only found in the thoracic (16) and lumbar (19) regions, with the greatest concentration in the lumbar region. In contrast, men had Schmorl’s nodes in the cervical (1), thoracic (31), lumbar (11) and sacral (1) regions of the spine, with the greatest concentration in the thoracic region. Two contingency table analyses and Fisher’s exact test were performed to assess the significance in Schmorl’s node distribution by sex. Results show that there is a significant difference in the lesion’s distribution by sex when all Schmorl’s nodes are considered (n ¼ 79; x2 ¼ 7.991, df ¼ 3, P ¼ 0.0025, Fisher’s exact test), as well as when the cervical and sacral lesions are removed from consideration (n ¼ 77; x2 ¼ 6.3366, df ¼ 1, P ¼ 0.0082, Fisher’s exact test).

Descriptive analysis of Schmorl’s node location, size and number Seventy Schmorl’s nodes were included in the statistical analysis that tested the significance of the relationship between physical characteristics of Schmorl’s nodes and pain. Of these, 38 (53.3%) were inferior nodes and 32 (45.7%) were superior nodes (Table 2 for inferior and

Table 1. Schmorl’s nodes by spinal region and by sex Spinal region Cervical Thoracic Lumbar Sacral Total

Females (n)

% Schmorl’s nodes: female only

% Schmorl’s nodes (female/total)

Males (n)

% Schmorl’s nodes: males only

% Schmorl’s nodes (males/total)

0 16 19 0 35

0% 35.6% 63.3% 0% 100%

0% 20.3% 24.1% 0% 44.4%

1 31 11 1 44

2.3% 70.5% 25.0% 2.3% 100%

1.3% 39.2% 13.9% 1.3% 55.7%

Copyright # 2007 John Wiley & Sons, Ltd.

% Per spinal region 1.3% 59.5% 38.0% 1.3% 100%

Total

1 47 30 1 79

Int. J. Osteoarchaeol. 18: 28–44 (2008) DOI: 10.1002/oa

Significance of Schmorl’s Nodes

37

Table 2. Inferior and superior Schmorl’s nodes by spinal region Spinal region Cervical Thoracic Lumbar Sacral

Inferior node

Superior node

1 24 13 0

0 17 14 1

superior nodes by region). According to each MRI slice per individual, the total percentage area that Schmorl’s nodes occupied within a vertebral body ranged from 0.10% to 21.1%. Schmorl’s nodes ranged in length from 7.5% to 57.3% of the vertebral body length, and in depth from 2.8% to 52.9% of the vertebral body depth at the location of maximum node depth. Spinal regions had between one and nine Schmorl’s nodes, with the mode being one lesion per spinal region. Six vertebrae had both superior and inferior nodes. Schmorl’s nodes on the vertebral body were: 31 (44.3%) on the anterior third; 60 (85.7%) on the central third; and 27 (38.6%) on the posterior third of the vertebral body. These positional categories were not mutually exclusive.

Statistical analysis of Schmorl’s nodes and pain A full logistic regression model (n ¼ 583) was performed to assess whether the length, depth, area, location or number of Schmorl’s nodes per column was more likely to predispose a patient to report pain (Table 3). The only variable that

proved significantly associated with a patient reporting pain in the region of the Schmorl’s node was a centrally-located lesion, and this was a positively significant relationship (OR ¼ 2.781, 95% CI ¼ 1.471, 5.256, P ¼ 0.0016). Centrallylocated Schmorl’s nodes remained positively and significantly (OR ¼ 1.912, 95% CI ¼ 1.057, 3.458, P ¼ 0.0321) associated with the reporting of pain in a reduced logistic regression model, where only age, sex and body mass index were included as explanatory (independent) variables.

Impact of Schmorl’s nodes and variables on pain Two additional logistic regression analyses were performed to assess whether synergistic effects existed between Schmorl’s nodes and the other independent variables, thereby predisposing an individual to report pain. The full logistic regression model included 16 explanatory (independent) variables. Subsequently, a second, reduced logistic regression model included five explanatory variables: age, sex, BMI, and the two variables (i.e. failed back syndrome and osteophyte presence) that were found to be significantly associated with patient reporting of pain in the full regression model. Both models tested whether these independent variables predisposed a person to report pain in the region of the Schmorl’s node. The first logistic regression included the following explanatory (independent) variables: age, sex, body mass index, spinal region of the

Table 3. Odds ratio (OR) values for explanatory variables used in the full and reduced regression models to test whether Schmorl’s nodes and other variables are more likely to predispose an individual to report pain Explanatory variable Inferior or superior Total number in region Maximum surface % of node Maximum depth % of node Maximum area % of node Anterior on vertebral body Central on vertebral body Posterior on vertebral body 

OR value, full model (explanatory variables n ¼ 8) 0.797 0.920 0.985 0.995 0.944 1.238 2.781 0.712

(95% (95% (95% (95% (95% (95% (95% (95%

CI ¼ 0.523, CI ¼ 0.823, CI ¼ 0.967, CI ¼ 0.967, CI ¼ 0.878, CI ¼ 0.775, CI ¼ 1.471, CI ¼ 0.422,

1.214; 1.029; 1.003; 1.024; 1.016; 1.997; 5.256; 1.202;

OR value, reduced model (explanatory variables n ¼ 1)

P ¼ 0.2901) P ¼ 0.1437) P ¼ 0.1090) P ¼ 0.7202) P ¼ 0.1227) P ¼ 0.3725) P ¼ 0.0016) 1.912 (95% CI ¼ 1.057,3.458; P ¼ 0.0321) P ¼ 0.2030)

Statistically significant results.

Copyright # 2007 John Wiley & Sons, Ltd.

Int. J. Osteoarchaeol. 18: 28–44 (2008) DOI: 10.1002/oa

K. J. Faccia and R. C. Williams

38

Table 4. Odds ratio (OR) values for explanatory variables used in full and reduced regression models to test whether Schmorl’s nodes and other variables are more likely to predispose an individual to report pain Explanatory variable Age Sex Body mass index Lumbar column Thoracic column History of trauma Degenerative disc disease Disk bulge/extrusion Desiccated disc Failed back syndrome Joint abnormalities Stenosis Compression fracture Osteophytes Spinal cord abnormalities Cervical column 

OR value, full model (explanatory variables n ¼ 16) 0.987 (95% CI ¼ 0.960, 0.889 (95% CI ¼ 0.412, 0.999 (95% CI ¼ 0.937, 3.065 (95% CI ¼ 0.287, 0.631 (95% CI ¼ 0.058, 1.088 (95% CI ¼ 0.489, 1.423 (95% CI ¼ 0.702, 1.790 (95% CI ¼ 0.693, 1.085 (95% CI ¼ 0.512, 0.191 (95% CI ¼ 0.053, 1.237 (95% CI ¼ 0.492, 2.930 (95% CI ¼ 0.911, 0.961 (95% CI ¼ 0.329, 3.346 (95% CI ¼ 1.244, 1.084 (95% CI ¼ 0.310, Discarded by analysis

1.016; P ¼ 0.3756) 1.921; P ¼ 0.7652) 1.066; P ¼ 0.9858) 32.697; P ¼ 0.3538) 6.835; P ¼ 0.7050) 2.420; P ¼ 0.8361) 2.886; P ¼ 0.3277) 4.625; P ¼ 0.2293) 2.297; P ¼ 0.8319) 0.689; P ¼ 0.0115) 3.298; P ¼ 0.6186) 9.428; P ¼ 0.0714) 2.811; P ¼ 0.9421) 9.002; P ¼ 0.0168) 3.794; P ¼ 0.8993)

OR value, reduced model (explanatory variables n ¼ 4) 0.987 (95% CI ¼ 0.968, 1.007; P ¼ 0.1997) 1.111 (95% CI ¼ 0.677, 1.822; P ¼ 0.6767) 0.993 (95% CI ¼ 0.956, 1.031; P ¼ 0.7042)

1.266(95% CI ¼ 0.474,3.381; P ¼ 0.6378)

0.943 (95% CI ¼ 0.448,1.986; P ¼ 0.8770)

Statistically significant results.

Schmorl’s node (e.g. lumbar, thoracic, cervical), whether a history of trauma was associated with reported back pain, intervertebral disc abnormalities (e.g. degenerative disc disease, desiccated disc, and ruptured/bulging disc), failed back syndrome, joint abnormalities, stenosis, compression fractures, osteophytes, and spinal cord abnormalities. For the pathological conditions in the spine that were used as explanatory variables, each variable was recorded as present only if the pathological condition was reported in the same spinal region (e.g. lumbar, thoracic, cervical) as the Schmorl’s node. Results (Table 4) indicate that, when all of the aforementioned variables were used in the model, only osteophytes (OR ¼ 3.346, 95% CI ¼ 1.244, 9.002, P ¼ 0.0168; positive relationship) and failed back syndrome (OR ¼ 0.191, 95% CI ¼ 0.053, 0.689, P ¼ 0.0115; negative relationship) were significantly associated with Schmorl’s nodes and the reporting of pain. Results indicate that the presence of osteophytes, in association with Schmorl’s nodes, is more likely to predispose a person to report pain than a person without osteophytes in the region of a Schmorl’s node(s). However, the presence of failed back syndrome, in the region of a Schmorl’s node(s), is less likely to predispose a person to report back pain. The second (reduced) logistic regression tested the synergistic impact of Schmorl’s nodes and Copyright # 2007 John Wiley & Sons, Ltd.

osteophytes and failed back syndrome when only age, sex and body mass index were controlled in the model. In this analysis, neither osteophytes (OR ¼ 0.943, 95% CI ¼ 0.448, 1.986, P ¼ 0.8770), nor failed back syndrome (OR ¼ 1.266, 95% CI ¼ 0.474, 3.381, P ¼ 0.6378), appeared to predispose a person with Schmorl’s nodes to be more or less likely to report pain at a level of statistical significance (see Table 4).

Perceived pain attributed to Schmorl’s nodes Twenty-six patients returned the patient questionnaire which addressed issues of pain that patients perceived to be related to their Schmorl’s nodes.6 6

It is important to know that this section deals with perceptions of pain. According to the staff at Spectrum Pain Clinics, Inc., after diagnostic imaging, patients are usually told about the presence of Schmorl’s nodes, but that the lesions do not have a significant impact on their condition. Before answering the questionnaire, patients were again reminded of their lesion(s). Because this could have affected the way in which they answered the questions (i.e. this could have influenced patients to perceive pain to degrees or in locations that might not have seemed significant before learning about their lesions), the link between Schmorl’s nodes and the reporting of pain was primarily drawn from past routine clinical examinations, during which healthcare practitioners noted the specific regions of the spine where pain was reported, and during which time patients probably considered their Schmorl’s nodes insignificant.

Int. J. Osteoarchaeol. 18: 28–44 (2008) DOI: 10.1002/oa

Significance of Schmorl’s Nodes When asked if the pain that the patients attribute to their Schmorl’s nodes began with rupturing of a disc, 76.9% (20) of respondents answered yes, 14.4% (4) answered no, 3.9% (1) said that he or she didn’t know, and 3.9% (1) did not answer the question. Patients were also asked to state what movements were involved in injuring their backs. Lifting (13; 50%) was identified as the most common activity leading to back pain, with the other most identifiable activity being pulling (8; 31%). Patients were also asked about the duration and severity of their pain, with patients being allowed to mark as many categories as applied. The majority of patients, 69.2% (18), said that the pain had been constant since the ruptured disc was diagnosed, with the remaining patients, 30.8% (8), responding that the pain has been frequent. Half (13) of the patients ranked the severity of pain as moderate to severe, and over 50% (17) ranked their pain as severe and/or very severe. No patients reported that they experienced an absence of long-term pain related to their Schmorl’s nodes. In the questionnaire, patients addressed the sensations and types of pain that they attributed to their Schmorl’s nodes. These symptoms were based directly on Spectrum Pain Clinics, Inc. admittance forms. The sensations most frequently attributed to Schmorl’s nodes were tingling (9; 73%), numbness (18; 69%) and pins and needles (18; 69%). No patients reported an absence of sensations attributed to Schmorl’s nodes. The most common types of pain that the patients attributed to the lesions were sharp shooting (14; 54%), stabbing (13; 50%), burning (12; 46%), throbbing (12; 46%) and aching (11; 42%). No patients reported an absence of pain attributed to their Schmorl’s nodes. Patients were asked what aggravates and relieves their pain. The aggravating factors most frequently cited included standing (20; 77%), repetitive movements (18; 69%), stooping (15; 58%), sleeping (13; 50%), sneezing (13; 50%), bowel movements (12; 46%), and emotional upsets (11; 42%). No patients reported an absence of aggravating factors. Patients reported that the following methods best helped to relieve their pain: prescription pain pills (24; 92%); applying heat (20; 77%); other Copyright # 2007 John Wiley & Sons, Ltd.

39 (12; 46%) [the most common answers included hot baths (5) and lying on one’s side (4)]; and applying cold (11; 42%). One patient reported that nothing relieves his or her pain (i.e. the pain is constant).

Effects of pain When patients were asked if the pain that they attribute to their Schmorl’s nodes limits their activities, 92% (24) responded yes, and 8% (4) failed to answer this question. When asked if this pain had caused the individual to miss work, of the four patients still working, three (75%) answered yes. Of the total sample, including those now unemployed or on disability benefits, answers to the same question (missed work) were: 69% (18) yes, 15% (4) no, and 15% (4) failed to respond to this question. Of the 33 patients included in the study, 15% (5) of individuals have employed the use of mobility aids when visiting the clinic. Also, 39% (13) were diagnosed, in at least one visit, of having an irregular gait. When healthcare practitioners diagnosed patient range of motion, 58% (19) of patients were assessed as having a reduced range of motion in the region of the Schmorl’s node in at least one office visit. However, in at least one office visit, 70% (23) of patients were diagnosed with normal range of motion in areas affected by Schmorl’s nodes, and the same percentage of patients were diagnosed with a reduced range of motion in an area not diagnosed as having a Schmorl’s node(s). Notably, for those patients who had visited the clinic three or more times, 19 (66%) reported pain in the region of the Schmorl’s node at least three times, or over the course of three months. This is important, because chronic pain is considered to be pain that lasts for three or more months (Borenstein, 2002). Hence, it is possible that Schmorl’s nodes are a source of chronic back pain, although more detailed analysis is necessary. Also noteworthy is the fact that a third (11) of patients in this study were diagnosed with depression during at least one visit, with 27% (9) being diagnosed with depression during multiple visits. Int. J. Osteoarchaeol. 18: 28–44 (2008) DOI: 10.1002/oa

40

Discussion The present study provides information regarding the relationship between Schmorl’s nodes and sociodemographic factors, as well as the impact of pain in an extant patient population. Because the influence of Schmorl’s nodes on patient quality of life has remained somewhat ambiguous, this study also attempts to clarify the relationship that exists between a defined osteological lesion, the Schmorl’s node, and pain. Schmorl’s nodes in the clinical population are concentrated primarily in the thoracic region, a similar pattern to that noted in archaeological samples (Merbs, 1983; Owsley et al., 1987; Kramar et al., 1990; Coughlan & Holst, 2000). Also, as in the archaeological samples (Rathbun, 1987; Parrington & Roberts, 1990), the number of Schmorl’s nodes in males and females differs, with males exhibiting a greater percentage of lesions. Additionally, in the modern sample, the distribution of Schmorl’s nodes by spinal region and by sex is significantly different. The latter two trends suggest that there still exists a sexual division of labour that results in differentially distributed back trauma. Unfortunately, a comparison of social status and biological status, as per Baker (1997) and Robb et al. (2001), could not be performed, as the clinical sample lacked an adequate range of income levels needed for meaningful analysis. Complete and reduced logistic regression analyses were performed to assess whether the location, number, and/or quantitative aspects of Schmorl’s nodes predisposed an individual to report pain in the region of the Schmorl’s node(s). In each of the models, no significant relationship was found between a patient reporting pain and: (1) whether the Schmorl’s node was located on the inferior or superior surface of the vertebral body; (2) the total number of Schmorl’s nodes per region; (3) the maximum percentage surface area of the lesion; (4) the maximum percentage depth of the lesion; (5) the maximum percentage area occupied by the lesion(s); or (6) whether the Schmorl’s node was anteriorly or posteriorly located on the surface of the vertebral body. In both models, only centrally located Schmorl’s nodes were significantly associated with the reporting of pain in the region of the Schmorl’s Copyright # 2007 John Wiley & Sons, Ltd.

K. J. Faccia and R. C. Williams node. Therefore, the hypothesis that variation in the percentage node length, depth and area occupied by the Schmorl’s node, in relation to the vertebral body (e.g. the amount of trabecular and cortical destruction caused by the Schmorl’s node formation process), will affect the likelihood that a patient will report pain is not supported. However, these results do not nullify the aspect of the hypothesis that predicts that Schmorl’s nodes cause pain because they overlap with, or aggravate, nerves within the vertebral body. To the contrary, the fact that centrally located Schmorl’s nodes are significantly related to patients reporting pain supports this hypothesis. According to Antonnaci et al. (1998: 528), basivertebral nerves, capable of transmitting painful signals (Fras et al., 2003), enter the vertebral body posteriorly and run towards ‘more central areas’. Additionally, according to preliminary observations by Antonnaci et al. (1998), it appears that the concentration of nerve bundles in the vertebral body varies according to location. Therefore, it follows that the important factor in predisposing a person with a Schmorl’s node to report pain is that the Schmorl’s node is located in an area with a concentration of nerve fibres. Hence, the pain or lack of pain attributed to Schmorl’s nodes appears equally dependent on neurological factors (i.e. distribution, level below surface, etc.) as characteristics of the Schmorl’s node itself. Because it seems that centrally located Schmorl’s nodes are significantly related to patients reporting pain, the next step in the analysis is to assess whether or not Schmorl’s nodes, in combination with other spinal conditions, would be likely to predispose a person to report pain. The full and reduced logistic regression analyses that examined the dynamic effects of Schmorl’s nodes and other variables produced interesting and seemingly contradictory results. With multiple variables in the model, the combination of Schmorl’s nodes and osteophytes appears to increase the chances that a person will report pain, while the combination of Schmorl’s nodes and failed back syndrome reduces the likelihood that someone will report pain. However, in the second, reduced model, when only age, sex and body mass index were included, neither osteophytes nor failed back syndrome seemed to significantly increase or Int. J. Osteoarchaeol. 18: 28–44 (2008) DOI: 10.1002/oa

Significance of Schmorl’s Nodes decrease the chances that a person with Schmorl’s nodes would report pain. There are several possible reasons for these ‘contradictory’ results. Firstly, it is possible that there is no real relationship between osteophytes or failed back syndrome and Schmorl’s nodes and pain. Perhaps the seemingly significant results of the first analysis were only artefacts of the data, or they reflect other variables that were not included, but are either (1) related to osteophytes and/or failed back syndrome, or (2) their effects only become observable when other factors are included. Alternatively, perhaps these relationships, between Schmorl’s nodes and osteophytes and failed back syndrome, really do exist. Osteophytes are known to cause pain in some instances (Lanyon et al., 1998; Lamer, 1999), and, in conjunction with Schmorl’s nodes, perhaps the pain becomes significant enough for a patient to report it to his or her healthcare practitioner. With regard to failed back syndrome, the answer for the counterintuitive relationship, that it appears to reduce the likelihood of pain reported, might be an indirect benefit of the failed back surgery or another course of back treatment. As Antonacci et al. (1998) discussed, nerves enter the vertebral body though various foramina. Because of the partially exterior nature of the nerves, impingement of the nerve fibres outside of the vertebral body could result in a diffused pain that is felt within the vertebral body. Thus it could follow that, in conditions in which externally located nerve fibres were impinged upon prior to surgery or other form of treatment, the procedure could have successfully relieved the aggravating factor(s); this, in turn, would lead to relief in the vertebral body with the Schmorl’s node. Therefore, in instances where failed back syndrome reduces the likelihood that a person with a Schmorl’s node will report pain, the pain may actually be a result of nerve aggravation at an external location and not the node itself. In this case, the Schmorl’s node(s) may only coincidentally be located on the aggravated vertebral body in question.

Implications for bioarchaeological research The importance of this research for bioarchaeology is that it offers a beginning point for Copyright # 2007 John Wiley & Sons, Ltd.

41 researchers to address the impact of back pain in past populations by providing a link between a defined osteological lesion, the Schmorl’s node, and the presence of reported back pain. Additionally, this study presents tentative evidence that other pathological conditions, notably osteophytes, in combination with Schmorl’s nodes, increase the likelihood that a person had experienced back pain. Therefore, it is suggested that the bioarchaeologist score the location of the Schmorl’s node (i.e. anterior 1/3, central 1/3, posterior 1/3) and note the presence of osteophytes in the affected vertebral region. It should be noted that this study does not demonstrate that the productivity of individuals affected by Schmorl’s nodes was equally compromised in past and modern groups; but it does provide evidence that Schmorl’s nodes could have caused back pain, and that productivity could have been affected. With this information, the bioarchaeologist may begin to explore the impact of pain in archaeological populations by combining the results of this study with other forms of evidence for pain, disability and social dependence in the bioarchaeological record.

Conclusions Analysing the impact of Schmorl’s nodes on pain in a clinical sample, this study determined that the only physical characteristic of Schmorl’s nodes that is significantly correlated with pain is a centrally located Schmorl’s node. In addition, the presence of osteophytes, in combination with Schmorl’s nodes, could significantly increase the reporting of back pain. Ultimately, this study provides evidence that a defined osteological lesion, whose impact has perplexed the medical community, is a likely contributor to chronic back pain. These results allow for the bioarchaeologist to begin addressing a symptom that probably had as profound implications for past populations as it does for modern populations. The evidence for back pain and its social implications should be used in conjunction with other bioarchaeological evidence for pain, disability and social dependence, in order to arrive at more informed and insightful interpretations of Int. J. Osteoarchaeol. 18: 28–44 (2008) DOI: 10.1002/oa

K. J. Faccia and R. C. Williams

42 quality-of-life issues in archaeological populations.

Future directions This study provides a beginning for more informed analyses of Schmorl’s nodes in past populations. However, the results should be strengthened by future analyses that include: (1) a non-Schmorl’s node population with back pain; (2) a Schmorl’s node population that has never presented for pain; and (3) a larger sample size, so that the statistical and descriptive analyses will encompass a much broader range of experiences, leading to more comprehensive analyses. Additionally, future studies should address the long-term impact of Schmorl’s nodes. Now that it has been shown that a significant relationship exists between centrally located Schmorl’s nodes and an increased predisposition to report pain, it would be interesting to test the statistical relationship between Schmorl’s nodes and chronic pain, or pain lasting at least three months. According to Valkenburg & Haanen (1982), approximately 85% of people who report lower back pain experience a recurrence in this pain. The data collected for this study incorporated long-term healthcare information; therefore, with a larger sample size based on the suggestions listed above, a longitudinal study investigating the long-term impact of Schmorl’s nodes would greatly benefit the interpretation of Schmorl’s nodes and pain in archaeological populations.

Acknowledgements Kathleen Faccia would like to thank Dr Charles F. Merbs, Dr Brenda J. Baker and Dr Katherine A. Spielmann for their assistance with this manuscript. I am also indebted to the staff and patients of Spectrum Pain Clinics, Inc. for agreeing to participate in this project, as well as the various diagnostic imaging centres for providing images for this study. Thanks to Mr Vladimir I. Bazaliiskii (Irkutsk State University), the Baikal Archaeology Project (SSHRC MCRI No. 412-2000-28), and Mike Metcalf for use of the thoracic vertebra Copyright # 2007 John Wiley & Sons, Ltd.

photograph. The authors would also like to thank Dr M. Anne Katzenberg and the three anonymous reviewers for their time, comments and suggestions.

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Int. J. Osteoarchaeol. 18: 28–44 (2008) DOI: 10.1002/oa