Predicting outcome in acute low back pain using different models of patient profiling

This is a non-final version of an article published in final form in Spine, 34(18), 1970 - 1975, 2009. Copyright © 2009 Lippincott Williams & Wilkins, Inc.Study Design. Prospective observational study of prognostic indicators, using data from a randomized, controlled trial of physiotherapy care of acute low back pain (ALBP) with follow-up at 6 weeks, 3 months, and 6 months. Objective. To evaluate which patient profile offers the most useful guide to long-term outcome in ALBP. Summary of Background Data. The evidence used to inform prognostic decision-making is derived largely from studies where baseline data are used to predict future status. Clinicians often see patients on multiple occasions so may profile patients in a variety of ways. It is worth considering if better prognostic decisions can be made from alternative profiles. Methods. Clinical, psychological, and demographic data were collected from a sample of 54 ALBP patients. Three clinical profiles were developed from information collected at baseline, information collected at 6 weeks, and the change in status between these 2 time points. A series of regression models were used to determine the independent and relative contributions of these profiles to the prediction of chronic pain and disability. Results. The baseline profile predicted long-term pain only. The 6-week profile predicted both long-term pain and disability. The change profile only predicted long-term disability (P 0.05). A similar result was obtained when the order of entry was reversed. When predicting long-term disability, after the 6-week profile was entered at the first step, the change profile was not significant when forced in at the second step. However, when the change profile was entered at the first step and the 6-week clinical profile was forced in at the second step, a significant contribution of the 6-week profile was found. Conclusion. The profile derived from information collected at 6 weeks provided the best guide to long-term pain and disability. The baseline profile and change in status offered less predictive value

Does age affect the relationship between pain and disability? : a descriptive study in individuals suffering from chronic low back pain

Abstract : Background: Previous studies have revealed a weak to moderate relationship between pain and disability in individuals suffering from low back pain (LBP). However, to our knowledge, no studies have evaluated if this relationship is different between young and older adults. Purpose: The objective of this descriptive, cross-sectional study, was to determine if the relationship between LBP intensity and physical disability is different between young and older adults. Methods: Pain intensity (measured with a visual analog scale) and physical disability scores (measured with the Oswestry Disability Index) were collected from the medical files of 164 patients with LBP. Separate Pearson correlation coefficients were calculated between these 2 variables for young (mean age 40 ± 6 years, n = 82) and older (62 ± 9 years, n = 82) individuals and a Fisher r-to-z transformation was used to test for group differences in the strength of the relationship. Linear regression analyses were also performed to determine if the slope of the association was different between the 2 groups. Results: There was a significant and positive association between pain intensity and disability for both young and older individuals. However, the correlation was stronger in the young group (r = 0.66; p < 0.01) compared to the older group (r = 0.44; p < 0.01) (Fisher Z = 2,03; p < 0.05). The linear regression model also revealed that the slope of the relationship was steeper in the young group (p < .05). Conclusion: Although both young and older individuals showed a significant association between pain intensity and disability, the relationship between these 2 variables was more tenuous in older individuals than in young patients. Future research is essential to identify the factors underlying this age-related difference

An experimental study investigating the effect of pain relief from oral analgesia on lumbar range of motion, velocity, acceleration and movement irregularity

Background Movement alterations are often reported in individuals with back pain. However the mechanisms behind these movement alterations are not well understood. A commonly cited mechanism is pain. The aim of this study was to investigate the effect of pain reduction, from oral analgesia, on lumbar kinematics in individuals with acute and chronic low back pain. Methods A prospective, cross-sectional, experimental repeated-measures design was used. Twenty acute and 20 chronic individuals with low back pain were recruited from General Practitioner and self-referrals to therapy departments for low back pain. Participants complained of movement evoked low back pain. Inertial sensors were attached to the sacrum and lumbar spine and used to measure kinematics. Kinematic variables measured were range of motion, angular velocity and angular acceleration as well as a determining movement irregularity (a measure of deviation from smooth motion). Kinematics were investigated before and after administration of oral analgesia to instigate pain reduction. Results Pain was significantly reduced following oral analgesia. There were no significant effects on the kinematic variables before and after pain reduction from oral analgesia. There was no interaction between the variables group (acute and chronic) and time (pre and post pain reduction). Conclusion The results demonstrate that pain reduction did not alter lumbar range of motion, angular velocity, angular acceleration or movement irregularity questioning the role of pain in lumbar kinematics

Variable selection under multiple imputation using the bootstrap in a prognostic study

Background: Missing data is a challenging problem in many prognostic studies. Multiple imputation (MI) accounts for imputation uncertainty that allows for adequate statistical testing. We developed and tested a methodology combining MI with bootstrapping techniques for studying prognostic variable selection. Method: In our prospective cohort study we merged data from three different randomized controlled trials (RCTs) to assess prognostic variables for chronicity of low back pain. Among the outcome and prognostic variables data were missing in the range of 0 and 48.1%. We used four methods to investigate the influence of respectively sampling and imputation variation: MI only, bootstrap only, and two methods that combine MI and bootstrapping. Variables were selected based on the inclusion frequency of each prognostic variable, i.e. the proportion of times that the variable appeared in the model. The discriminative and calibrative abilities of prognostic models developed by the four methods were assessed at different inclusion levels. Results: We found that the effect of imputation variation on the inclusion frequency was larger than the effect of sampling variation. When MI and bootstrapping were combined at the range of 0% (full model) to 90% of variable selection, bootstrap corrected c-index values of 0.70 to 0.71 and slope values of 0.64 to 0.86 were found. Conclusion: We recommend to account for both imputation and sampling variation in sets of missing data. The new procedure of combining MI with bootstrapping for variable selection, results in multivariable prognostic models with good performance and is therefore attractive to apply on data sets with missing values

Knee disorders in primary care: design and patient selection of the HONEUR knee cohort.

BACKGROUND: Knee complaints are a frequent reason for consultation in general practice. These patients constitute a specific population compared to secondary care patients. However, information to base treatment decisions on is generally derived from specialistic settings. Our cohort study is aimed at collecting knowledge about prognosis and prognostic factors of knee complaints presented in a primary care setting. This paper describes the methods used for data collection, and discusses potential selectiveness of patient recruitment. METHODS: This is a descriptive prospective cohort study with one-year follow-up. 40 Dutch GPs recruited consecutive patients with incident knee complaints aged 12 years and above from October 2001 to October 2003. Patients were assessed with questionnaires and standardised physical examinations. Additional measurements of subgroups included MRI for recent knee traumas and device assessed function measurements for non-traumatic patients. After the inclusion period we retrospectively searched the computerized medical files of participating GPs to obtain a sample to determine possible selective recruitment. We assessed differences in proportions of gender, traumatic onset of injury and age groups between participants and non-participants using Odds Ratios (OR) and 95% confidence intervals. RESULTS: We recruited 1068 patients. In a sample of 310 patients visiting the GP, we detected some selective recruitment, indicating an underrepresentation of patients aged 12 to 35 years (OR 1.70; 1.15-2.77), especially among men (OR 2.16; 1.12-4.18). The underrepresentation of patients with traumatic onset of injury was not statistically significant. CONCLUSION: This cohort is unique in its size, setting, and its range of both age and type of knee complaints. We believe the detected selective recruitment is unlikely to introduce significant bias, as the cohort will be divided into subgroups according to age group or traumatic onset of injury for future analyses. However, the underrepresentation of men in the age group of 12 to 35 years of age warrants caution. Based on the available data, we believe our cohort is an acceptable representation of patients with new knee complaints consulting the GP, and we expect no problems with extrapolation of the results to the general Dutch population

Methodological quality of 100 recent systematic reviews of health-related outcome measurement instruments:an overview of reviews

Purpose: Systematic reviews evaluating and comparing the measurement properties of outcome measurement instruments (OMIs) play an important role in OMI selection. Earlier overviews of review quality (2007, 2014) evidenced substantial concerns with regards to alignment to scientific standards. This overview aimed to investigate whether the quality of recent systematic reviews of OMIs lives up to the current scientific standards.Methods: One hundred systematic reviews of OMIs published from June 1, 2021 onwards were randomly selected through a systematic literature search performed on March 17, 2022 in MEDLINE and EMBASE. The quality of systematic reviews was appraised by two independent reviewers. An updated data extraction form was informed by the earlier studies, and results were compared to these earlier studies’ findings.Results: A quarter of the reviews had an unclear research question or aim, and in 22% of the reviews the search strategy did not match the aim. Half of the reviews had an incomprehensive search strategy, because relevant search terms were not included. In 63% of the reviews (compared to 41% in 2014 and 30% in 2007) a risk of bias assessment was conducted. In 73% of the reviews (some) measurement properties were evaluated (58% in 2014 and 55% in 2007). In 60% of the reviews the data were (partly) synthesized (42% in 2014 and 7% in 2007); evaluation of measurement properties and data syntheses was not conducted separately for subscales in the majority. Certainty assessments of the quality of the total body of evidence were conducted in only 33% of reviews (not assessed in 2014 and 2007). The majority (58%) did not make any recommendations on which OMI (not) to use.Conclusion: Despite clear improvements in risk of bias assessments, measurement property evaluation and data synthesis, specifying the research question, conducting the search strategy and performing a certainty assessment remain poor. To ensure that systematic reviews of OMIs meet current scientific standards, more consistent conduct and reporting of systematic reviews of OMIs is needed

Methodological quality of 100 recent systematic reviews of health-related outcome measurement instruments:an overview of reviews

Purpose: Systematic reviews evaluating and comparing the measurement properties of outcome measurement instruments (OMIs) play an important role in OMI selection. Earlier overviews of review quality (2007, 2014) evidenced substantial concerns with regards to alignment to scientific standards. This overview aimed to investigate whether the quality of recent systematic reviews of OMIs lives up to the current scientific standards.Methods: One hundred systematic reviews of OMIs published from June 1, 2021 onwards were randomly selected through a systematic literature search performed on March 17, 2022 in MEDLINE and EMBASE. The quality of systematic reviews was appraised by two independent reviewers. An updated data extraction form was informed by the earlier studies, and results were compared to these earlier studies’ findings.Results: A quarter of the reviews had an unclear research question or aim, and in 22% of the reviews the search strategy did not match the aim. Half of the reviews had an incomprehensive search strategy, because relevant search terms were not included. In 63% of the reviews (compared to 41% in 2014 and 30% in 2007) a risk of bias assessment was conducted. In 73% of the reviews (some) measurement properties were evaluated (58% in 2014 and 55% in 2007). In 60% of the reviews the data were (partly) synthesized (42% in 2014 and 7% in 2007); evaluation of measurement properties and data syntheses was not conducted separately for subscales in the majority. Certainty assessments of the quality of the total body of evidence were conducted in only 33% of reviews (not assessed in 2014 and 2007). The majority (58%) did not make any recommendations on which OMI (not) to use.Conclusion: Despite clear improvements in risk of bias assessments, measurement property evaluation and data synthesis, specifying the research question, conducting the search strategy and performing a certainty assessment remain poor. To ensure that systematic reviews of OMIs meet current scientific standards, more consistent conduct and reporting of systematic reviews of OMIs is needed

Methodological quality of 100 recent systematic reviews of health-related outcome measurement instruments:an overview of reviews

PURPOSE: Systematic reviews evaluating and comparing the measurement properties of outcome measurement instruments (OMIs) play an important role in OMI selection. Earlier overviews of review quality (2007, 2014) evidenced substantial concerns with regards to alignment to scientific standards. This overview aimed to investigate whether the quality of recent systematic reviews of OMIs lives up to the current scientific standards.METHODS: One hundred systematic reviews of OMIs published from June 1, 2021 onwards were randomly selected through a systematic literature search performed on March 17, 2022 in MEDLINE and EMBASE. The quality of systematic reviews was appraised by two independent reviewers. An updated data extraction form was informed by the earlier studies, and results were compared to these earlier studies' findings.RESULTS: A quarter of the reviews had an unclear research question or aim, and in 22% of the reviews the search strategy did not match the aim. Half of the reviews had an incomprehensive search strategy, because relevant search terms were not included. In 63% of the reviews (compared to 41% in 2014 and 30% in 2007) a risk of bias assessment was conducted. In 73% of the reviews (some) measurement properties were evaluated (58% in 2014 and 55% in 2007). In 60% of the reviews the data were (partly) synthesized (42% in 2014 and 7% in 2007); evaluation of measurement properties and data syntheses was not conducted separately for subscales in the majority. Certainty assessments of the quality of the total body of evidence were conducted in only 33% of reviews (not assessed in 2014 and 2007). The majority (58%) did not make any recommendations on which OMI (not) to use.CONCLUSION: Despite clear improvements in risk of bias assessments, measurement property evaluation and data synthesis, specifying the research question, conducting the search strategy and performing a certainty assessment remain poor. To ensure that systematic reviews of OMIs meet current scientific standards, more consistent conduct and reporting of systematic reviews of OMIs is needed.</p