Search strategy

We searched electronic databases PubMed and EMBASE (to May 2016) using controlled vocabulary and keyword variations of the concepts: emergency department, low back pain and prevalence (see Additional file 1 and Additional file 2). We conducted citation searches of seminal studies [9, 10, 12–15]. For studies with greater than 500 citations, we searched within citations for “emergency department” using Google Scholar. We reviewed reference lists of included studies to identify other potentially relevant studies. Additionally, our literature search incorporated all relevant literature that was identified in a broad scoping review mapping published research studies about back pain in the emergency department [7]. We searched for relevant subsequent publications for any abstracts identified.

We searched the grey literature guided by the ‘Grey Matters’ checklist [16]; we searched all websites listed in the checklist under the headings of health economics [e.g. Public Health Agency of Canada] or health statistics [e.g. Canadian Institute for Health Information and the CDC National Centre for Health Statistics], excluding pharmacological based websites (see Additional file 3). Websites that we reviewed collected data from Canada, the United States, Australia, Ireland, England, Scotland and five international databases (e.g. World Health Organization). We searched these websites 10 pages deep using the following search criteria, “low back pain” and “prevalence” and “emergency department”. We did not restrict searches by language or date. The grey literature search was conducted in May 2016.

Selection criteria

We included studies that investigated patients presenting to emergency settings. We defined ‘emergency setting’ as all pre-hospital, emergency, ambulatory, outpatient, accident, trauma, triage and urgent care services. Standard emergency settings provide initial treatment to patients with a broad spectrum of illnesses and injuries, some of which may be life threatening and require immediate action. For completeness, we included non-standard emergency settings, which provide care for a limited population and/or limited spectrum of illness and injuries (for example, orthopedic emergency settings). Additionally, we included studies from any year, written in any language.

We classified emergency settings by size. Emergency department settings with less than 10,000 annual visits were categorized as ‘rural’, those with more than 10 000 annual visits were categorized as ‘metropolitan’ and we separately considered studies that used nationally representative samples of emergency settings.

We categorized emergency settings by country level health care system funding. Studies were classified as being either using primarily a public funding system or a private funding system. If information was not provided in the publication, this data was collected from governmental websites and online encyclopedias identified using the search engine Google. We defined publicly funded healthcare systems as systems with no out of pocket costs associated with care in an emergency setting. We defined private funded healthcare systems as systems that require out of pocket payments for most visits to emergency settings and many procedures.

We included studies that measured adults presenting with low back pain. We defined adults as individuals over the age of 14, as this is an age where patients are likely to be diagnosed and treated as an adult [17]. If study selection criteria were mixed or unclear, we defined studies with an adequately ‘adult’ population as those with a minimum mean age of 30 years.

We included studies that used any definition of back pain. We used subgroups to explore the impact of study definitions of low back pain. We categorized studies that identified patients from presenting complaint codes and studies that captured their study population from diagnostic codes, and we collected information on the specific coding system used.

We categorized low back pain definitions as ‘broad’ or ‘narrow’. Studies were defined as ‘broad’ if they used a general definition of ‘back pain’ to define their prevalence estimate. These studies may have included some individuals with back pain in regions other than the low back (for example, thoracic spine). Studies were defined as ‘narrow’ if they used the definition of ‘low back pain’ or ‘non-specific low back pain’, or were limited to pain complaints in the lumbar region.

We included studies that presented data about the prevalence, including presentation of a prevalence rate (total number of adults presenting to an emergency setting with low back pain / total number of individuals presenting to the emergency setting over a specified period of time), or raw data to allow prevalence calculation.

Study selection and data collection

Two independent reviewers screened the titles and abstracts from the electronic database searches for studies meeting our selection criteria. In the case of disagreement, resolution was achieved by discussion with a third reviewer. The primary author screened the titles from the grey literature searches, reference lists (from included studies), results of the scoping review [7], and citation searches. Full articles were obtained for potentially relevant studies, or where relevance was unclear; two authors independently assessed the full text to determine eligibility prior to data extraction.

Two independent reviewers performed data extraction. In the case of disagreement, resolution was achieved by including a third reviewer. We used a data extraction form (see Additional file 4), to record information about the methods and results of each included study, including study objectives, location and type of emergency setting, study period, sample size, the definition of low back pain used by the study authors to calculate prevalence, population characteristics including age and sex, and the prevalence estimate. In studies using the same datasets, we extracted the prevalence data of the study that was conducted over the longest period of time and rated as having the lowest risk of bias. Finally, one reviewer collected information from an independent Google search to characterize each study’s country-level healthcare system funding system.

Critical appraisal

Two independent reviewers critically appraised each included study using a tool developed by Hoy et al., [3], to assess prevalence studies (see Additional file 5) [18]. In the case of disagreement or uncertainty, discussion was used to reach consensus with a third reviewer. The modified tool assesses each study according to nine domains: three external validity domains, and six internal validity domains, plus one item assessing overall risk of bias. The external validity domains assess the target population; sampling and non-response bias, while the internal risk of bias domains assess data collection, case definitions, assessment tools, prevalence period and an assessment of the numerator and denominator. We modified the tool by omitting an additional domain that assesses whether the study population represents the national population, which was not relevant to our review. The reviewers rated each of the nine domains as either high or low risk of bias; the overall risk of bias was rated as low, moderate or high risk of bias. We judged an overall low risk of bias if a study scored ‘low risk of bias’ on all domains. A moderate risk of bias study had one to two domains rated as a high risk of bias, and an overall high risk of bias study had three or more domains rated as a high risk of bias.

Analysis

Descriptive analyses were used to report study characteristics. We reported prevalence ranges, information on emergency settings, study methodology, and study populations.

Study characteristics

Analyses

The pooled prevalence estimate for standard emergency settings was 4.39% (3.67%-5.18%). There is significant heterogeneity in the results of this analysis, as assessed by the Q statistic (5.9e + 05, p = 0.00) and the I² index (100.0%) (Fig. 2).

Subgroup analysis results are presented in (Table 3, Fig. 3). We found that studies using presenting complaints to measure prevalence had a higher pooled prevalence estimate 5.5% (3.5%-7.8%) than studies using diagnosis coding 3.4% (3.1%-3.8%), with significant inter-group heterogeneity p = 0.046. None of the covariates investigated in our meta-regression analyses were significantly associated with prevalence estimates (Table 4).

Subgroup	Category	Arcsine prevalence, 95% CI	Inter-group heterogeneity	Sensitivity analysis, 95% CI (Arcsine Excluding High ROB),	Inter-group heterogeneity
Back Pain Definition	Broad	4.9% (3.1-7.1)	p = 0.1850	3.9% (1.9-6.4)	p = 0.8574
	Narrow	3.6% (3.2-4.0)		3.6% (3.2-4.1)
Coding	Complaint	5.5% (3.5-7.8)	p = 0.0459	5.0% (2.6-8.2)	p = 0.2289
	Diagnosis	3.4% (3.1-3.8)		3.4% (3.1-3.8)
Health System	Private	4.3% (3.4-5.3)	p = 0.9464	4.1% (3.2-5.2)	p = 0.2106
	Public	4.4% (3.4-5.3)		3.3% (2.6-4.1)
Emergency Setting	Standard	4.4% (3.7-5.2)	p = 0.7734	4.0% (3.2-4.9)	p = 0.7149
	Non-Standard	6.1% (0.0-2.3)		6.1% (0.00-23.2)

Notes: Back Pain Definition; “Narrow” indicates studies using narrow definitions of low back pain. They used a definition of ‘low back pain’ or ‘non-specific low back pain’, or were limited to pain complaints in the lumbar region, while “Broad” indicates studies using broad definitions of low back pain. They used a general definition of ‘back pain’ to define their prevalence estimate, which may have included some individuals with back pain in regions other than the low back pain (for example, thoracic spine). Coding System; “Complaint” indicates studies using presenting complaints for their definitions of low back pain while “Diagnosis” indicates studies using diagnosis codes for their definition. Health System; “Private” indicates studies conducted in regions with private healthcare funding and “Public” indicates studies conducted in regions with public healthcare funding. Emergency Setting; “Standard” indicates studies provide initial treatment to patients with a broad spectrum of illness and injuries, while “Non-Standard” indicates settings, which provide care for a limited population and/or limited spectrum of illness and injuries

Covariate	Coefficient	95% Confidence interval		P-value
Coding	-0.01989	-0.04472	0.00493	0.106
ROB	0.01032	-0.02085	0.04149	0.485
Health System	0.00309	-0.02580	0.03199	0.819

Notes: “Coding” includes studies grouped by coding system used for the definition of low back pain. In our analysis 1 was given to studies using diagnosis codes for their definition, while 0 was given to studies using presenting complaints for their definition. “ROB” includes studies grouped by risk of bias. In our analysis 1 was given to studies judged to have a moderate to high risk of bias and 0 was given to studies judged to have a low risk of bias. “Health System” includes studies grouped by healthcare system funding. In our analysis 1 was given to studies conducted in regions with private healthcare funding and 0 was given to studies conducted in regions with public healthcare funding

When studies with a high risk of bias were eliminated from our analysis of standard emergency settings, the pooled prevalence estimate was 4% (3.2%-4.9%). Additionally, there was no longer significant inter-group heterogeneity in studies using presenting complaints and studies using diagnosis codes (p = 0.229). Other results from our sensitivity analysis can be found in (Table 3).

Quality of the evidence – GRADE

We judged the overall quality of the evidence available to be moderate and judged that further research could modify our estimate of low back pain in emergency settings. Our judgment was downgraded as we included four studies with high risk of bias and additionally 11 studies with moderate risk of bias. There was a large amount of variability in the prevalence estimates of included studies, and there was a lack of prevalence estimates from some important settings, including rural and from developing nations.

Strengths and limitations of our review

A strength of the review was our approach to analysis, which included a meta-analysis, meta-regression, subgroup analysis and sensitivity analyses. These analyses allowed us to explore the effects of study level characteristics on prevalence estimates and test the robustness of our analysis.

Another strength of the study was our use of alternative search strategies, such as the results from a scoping review of back pain in emergency settings. This was important as only 43% of included studies came from our electronic search. We believe this is a result of the poor indexing of prevalence studies in electronic databases rather than an issue with publication bias. We believe future research would benefit if studies were properly indexed with “prevalence” in electronic databases PubMed and EMBASE.

Our study should be considered in the context of the limitations of the evidence available. There are limitations in the generalizability of our results. In our search, we found no studies analyzing the prevalence of low back pain primarily in rural emergency settings. Also, we found no results from developing nations, though these and rural settings may represent unique populations and distinct prevalence rates. Furthermore, our results may not be generalizable to older populations of individuals, as included studies had relatively young mean ages between 30 and 53.

Our exploratory analyses require cautious interpretation. Our pooled estimates are useful to provide context and compare study level characteristics, however, they must be carefully interpreted. Decision makers and clinicians should consider individually relevant emergency settings and applicable study methodologies.

Researchers in the field should concentrate on improving the quality of prevalence estimates for low back pain in emergency settings. This could be achieved by conducting studies that use well defined, transparent, definitions of low back pain e.g. studies using specific triage codes or specific diagnosis codes. Also, there should be an increase in prevalence estimates from rural emergency settings and estimates from developing nations as they may represent unique populations with various low back pain needs.