Several factors were found to be associated with disability at follow-up for at least two different pain symptoms .
However , owing to insufficient studies , no generic risk factors for sick leave were identified .
Conclusions Multiple site pain , high pain severity , older age , baseline disability and longer pain duration were identified as potential prognostic factors for disability across pain sites .
There was limited evidence that anxiety and depression were associated with disability in patients with subacute pain , indicating that these factors may not play as large a role as expected in developing disability due to a pain condition .
Objective This systematic review aims to identify generic prognostic factors for disability and sick leave in subacute pain patients .
A Clinical Prediction Rule To Identify Patients with Low Back Pain Most Likely To Benefit from Spinal Manipulation: A Validation Study
Context In this r and omized , controlled trial , spinal manipulation plus exercise produced outcomes for low back pain  similar to those produced by exercise alone . Yet , some patients did respond to spinal manipulation , and it would be helpful for doctors to be able to identify such patients . Contribution Patients were most likely to benefit from  spinal manipulation  if they met 4 of 5 of the following criteria : symptom duration less than 16 days , no symptoms distal to knee , score less than 19 on a fear-avoidance measure , at least 1 hypomobile lumbar segment , and at least 1 hip with more than 35 degrees of internal rotation . Implication s Clinicians may be able to use these criteria to identify patients with low back pain who are good c and i date s for  spinal manipulation . The Editors Next to the common cold , low back pain is the most common reason that individuals visit a physician 's office ( 1 ) . Billions of dollars in medical expenditures and lost labor costs for this condition are incurred each year ( 2 , 3 ) . Attempts to identify effective interventions for individuals with low back pain have been largely unsuccessful ( 4 ) . In particular , conflicting evidence exists about the effectiveness of spinal manipulation ; some r and omized trials have shown a benefit , while other trials have not ( 5 - 7 ) . These conflicting conclusions are reflected in the various recommendations in national clinical practice guidelines , with some recommending manipulation and others not ( 8) . The variety of conclusions in trials of manipulation may be attributable to the failure of research ers to adequately consider the importance of classification . Using broad inclusion criteria results in a heterogeneous sample that may include many patients for whom no benefit is expected , thus masking the intervention 's true value ( 9 , 10 ) . Consequently , developing methods for matching patients with low back pain to treatments that are most likely to benefit them has become an important research priority ( 11 ) . Clinical prediction rules are tools design ed to assist clinicians in decision making when caring for patients ( 12 ) . Several clinical prediction rules have been developed and vali date d to improve clinical decision making for the use of imaging in patients with ankle , knee , cervical spine , or minor head injuries ( 13 - 16 ) . Few studies have attempted to develop rules that establish prognosis on the basis of outcome from a specific intervention , such as spinal manipulation . Recently , Flynn and colleagues ( 17 ) developed a clinical prediction rule for identifying patients with low back pain who are likely to benefit from  manipulation .  They examined a series of patients with low back pain who received a manipulation intervention .  Five factors formed the most parsimonious set of predictors for identifying patients who achieved at least 50 % improvement in disability within 1 week with a maximum of 2 manipulation interventions ( Table 1 ) ( 17 ) . The positive likelihood ratio among patients who met at least 4 of 5 of the criteria was 24.4 ( 95 % CI , 4.6 to 139.4 ) . Table 1 . Five Criteria in the Spinal Manipulation Clinical Prediction Rule Clinical prediction rules must be vali date d in separate population s before being recommended for widespread implementation ( 18 ) . A clinical prediction rule for identifying which patients with low back pain are most likely to respond to manipulation could improve clinical efficiency and re source utilization . Thus , we aim ed to vali date the spinal manipulation clinical prediction rule in a multicenter trial . Methods We considered consecutive patients with a primary symptom of low back pain who were referred to physical therapy for participation . We used 14 physical therapists at 8 clinics in various U.S. regions and setting s ( 2 academic medical centers and smaller outpatient practice setting s ) . Most participating sites were health care facilities within the U.S. Air Force . Each site 's institutional review board approved the study before we began recruitment and data collection . Inclusion criteria were age 18 to 60 years ; a primary symptom of low back pain , with or without referral into the lower extremity ; and an Oswestry Disability Question naire ( ODQ ) score of at least 30 % . We excluded patients who had red flags for a serious spinal condition ( for example , tumor , compression fracture , or infection ) , those who had signs consistent with nerve root compression ( that is , positive straight-leg increase < 45 degrees or diminished reflexes , sensation , or lower-extremity strength ) , those who were pregnant , or those who had previous surgery to the lumbar spine or buttock . These criteria are consistent with those used in Flynn and colleagues ' study ( 17 ) and were design ed to include patients without a contraindication to manipulation . Once patients were admitted to the study , we used intention-to-treat principles , and no patient was removed for nonadherence . History and Physical Examination Before r and omization , patients completed several self-report measures and then received a st and ardized history and physical examination . We collected demographic information , including age and sex ; medical history ; and location and nature of symptoms . Self-report measures included a body diagram to assess the symptom distribution ( 19 ) . We used an 11-point pain-rating scale ranging from 0 ( no pain ) to 10 ( worst imaginable pain ) to assess current pain intensity and the best and worst level of pain during the last 24 hours ( 20 ) . We used the average of the 3 ratings . We used the Fear-Avoidance Beliefs Question naire ( FABQ ) to quantify the patient 's fear of pain and beliefs about avoiding activity ( 21 ) . Previous studies have found a high level of testretest reliability for both the FABQ physical activity and work subscales ( 22 ) . Fearavoidance beliefs have been associated with current and future disability and work loss in patients with acute ( 23 ) and chronic ( 24 ) low back pain . The modified ODQ is a region-specific disability scale for patients with low back pain ( 25 ) that has high levels of reliability , validity , and responsiveness ( 26 ) . Physical examination measures included lumbar active range of motion ( 27 ) and various tests purported to identify dysfunction in the lumbopelvic region ( 28 ) . Complete details of the physical examination are described elsewhere ( 26 ) . Specific components pertinent to validation of the rule were assessment s of segmental mobility and hip internal rotation range of motion , the performance of which is described in Appendix 1 and Appendix 3 video . Each physical therapist received a detailed manual that operationally defined each examination and treatment procedure and was trained in the study procedures by an investigator before data collection began . Supplement . Appendix 3 video : A Clinical Prediction Rule To Identify Patients with Low Back Pain Most Likely To Benefit from Spinal Manipulation Determining Status on the Clinical Prediction Rule A physical therapist who was blinded to the patients ' treatment group assignment assessed the 5 criteria in the rule ( Table 1 , Appendix 1 , and Appendix 3 video ) . To further minimize bias , examiners were not instructed in the rule 's criteria and were unaware of the patient 's status on the rule . After completion of the study , an examiner who was blinded to the patient 's treatment assignment determined the patient 's status on the rule by using the results of the baseline examination . As was done in the initial study ( 17 ) , we classified patients as positive if they met at least 4 of 5 criteria and were therefore likely to respond to manipulation . We classified patients with 3 or fewer criteria as negative . An examiner who was blinded to the patient 's status on the rule repeated the history and physical examination 1 and 4 weeks after r and omization . Patients also completed a 6-month follow-up postal question naire to assess disability , work status , and health care utilization . Treatment Groups We used a r and om-number generator to generate a r and omization list before the study began . We prepared individual , sequentially numbered index cards with the r and omization assignments . We folded the cards and placed them in sealed envelopes . After the baseline examination , the physical therapist who conducted the examination opened the next envelope , indicating the treatment group assignment . We r and omly assigned patients to 1 of 2 groups : 1 ) spinal manipulation plus an exercise program ( manipulation group ) or 2 ) an exervideocise program alone ( exercise group ) . Patients in both groups attended physical therapy twice during the first week and then once a week for the next 3 weeks , for a total of 5 sessions . We initiated treatment immediately after completion of the baseline examination , unless prohibited by time constraints ; in that case the first treatment session took place 24 to 48 hours after the baseline examination . All patients received an exercise instruction booklet that outlined the proper performance and frequency of each exercise and were instructed to perform their assigned exercise program once daily on the days that they did not attend therapy . On the basis of the benefits associated with remaining active ( 29 ) , patients in both groups were given advice to maintain usual activity within the limits of pain . Manipulation Group The treatment received by the manipulation group differed from that of the exercise group during the first 2 physical therapy sessions . During these 2 sessions , patients received high-velocity thrust spinal manipulation  and a  range-of-motion exercise only . First , the physical therapist performed the manipulation by using the same technique used by Flynn and colleagues ( 17 ) . Appendix 2 describes and Figure 1 and Appendix 3 video illustrate the procedures used to perform the manipulation technique . Figure 1 . Manipulative intervention used in developing and validating the spinal manipulation clinical prediction rule .  Exercise Group We treated patients in the exercise group with a low-stress
Several factors were found to be associated with disability at follow-up for at least two different pain symptoms .
However , owing to insufficient studies , no generic risk factors for sick leave were identified .
Conclusions Multiple site pain , high pain severity , older age , baseline disability and longer pain duration were identified as potential prognostic factors for disability across pain sites .
There was limited evidence that anxiety and depression were associated with disability in patients with subacute pain , indicating that these factors may not play as large a role as expected in developing disability due to a pain condition .
Objective This systematic review aims to identify generic prognostic factors for disability and sick leave in subacute pain patients .