Objective To estimate the one year prognosis and identify prognostic factors in cases of recent onset low back pain managed in primary care. Design Cohort study with one year follow-up. Setting Primary care clinics in Sydney, Australia. Participants An inception cohort of 973 consecutive primary care patients (mean age 43.3, 54.8% men) with non-specific low back pain of less than two weeks' duration recruited from the clinics of 170 general practitioners, physiotherapists, and chiropractors. Main outcome measures Participants completed a baseline questionnaire and were contacted six weeks, three months, and 12 months after the initial consultation. Recovery was assessed in terms of return to work, return to function, and resolution of pain. The association between potential prognostic factors and time to recovery was modelled with Cox regression. Results The follow-up rate over the 12 months was more than 97%. Half of those who reduced their work status at baseline had returned to previous work status within 14 days (95% confidence interval 11 to 17 days) and 83% had returned to previous work status by three months. Disability (median recovery time 31 days, 25 to 37 days) and pain (median 58 days, 52 to 63 days) took much longer to resolve. Only 72% of participants had completely recovered 12 months after the baseline consultation. Older age, compensation cases, higher pain intensity, longer duration of low back pain before consultation, more days of reduced activity because of lower back pain before consultation, feelings of depression, and a perceived risk of persistence were each associated with a longer time to recovery. Conclusions In this cohort of patients with acute low back pain in primary care, prognosis was not as favourable as claimed in clinical practice guidelines. Recovery was slow for most patients. Nearly a third of patients did not recover from the presenting episode within a year.

Objective. To determine the prevalence of serious pathology in patients presenting to primary care settings with acute low back pain, and to evaluate the diagnostic accuracy of recommended "red flag" screening questions.Methods. An inception cohort of 1,172 consecutive patients receiving primary care for acute low back pain was recruited from primary care clinics in Sydney, Australia. At the initial consultation, clinicians recorded responses to 25 red flag questions and then provided an initial diagnosis. The reference standard was a 12-month followup supplemented with a specialist review of a random subsample of participants.Results. There were 11 cases (0.9%) of serious pathology, including 8 cases of fracture. Despite the low prevalence of serious pathology, most patients (80.4%) had at least 1 red flag (median 2, interquartile range 1-3). Only 3 of the red flags for fracture recommended for use in clinical guidelines were informative: prolonged use of corticosteroids, age >70 years, and significant trauma. Clinicians identified 5 of the 11 cases of serious pathology at the initial consultation and made 6 false-positive diagnoses. The status of a diagnostic prediction rule containing 4 features (female sex, age >70 years, significant trauma, and prolonged use of corticosteroids) was moderately associated with the presence of fracture (the area under the curve for the rule score was 0.834 [95% confidence interval 0.654-1.014]; P ‫؍‬ 0.001).Conclusion. In patients presenting to a primary care provider with back pain, previously undiagnosed serious pathology is rare. The most common serious pathology observed was vertebral fracture. Approximately half of the cases of serious pathology were identified at the initial consultation. Some red flags have very high false-positive rates, indicating that, when used in isolation, they have little diagnostic value in the primary care setting.

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Accurate estimation of food portion size is critical in dietary studies. Hands are potentially useful as portion size estimation aids; however, their accuracy has not been tested. The aim of the present study was to test the accuracy of a novel portion size estimation method using the width of the fingers as a ‘ruler’ to measure the dimensions of foods (‘finger width method’), as well as fists and thumb or finger tips. These hand measures were also compared with household measures (cups and spoons). A total of sixty-seven participants (70 % female; age 32·7 (sd 13·7) years; BMI 23·2 (sd  3·5) kg/m2) attended a 1·5 h session in which they estimated the portion sizes of forty-two pre-weighed foods and liquids. Hand measurements were used in conjunction with geometric formulas to convert estimations to volumes. Volumes determined with hand and household methods were converted to estimated weights using density factors. Estimated weights were compared with true weights, and the percentage difference from the true weight was used to compare accuracy between the hand and household methods. Of geometrically shaped foods and liquids estimated with the finger width method, 80 % were within ±25 % of the true weight of the food, and 13 % were within ±10 %, in contrast to 29 % of those estimated with the household method being within ±25 % of the true weight of the food, and 8 % being within ±10 %. For foods that closely resemble a geometric shape, the finger width method provides a novel and acceptably accurate method of estimating portion size.