scholarly journals Predicting pain recovery in patients with acute low back pain: a study protocol for a broad validation of a prognosis prediction model

BMJ Open ◽  
2020 ◽  
Vol 10 (10) ◽  
pp. e040785
Author(s):  
Fernanda Gonçalves Silva ◽  
Tatiane Mota da Silva ◽  
Gabriele Alves Palomo ◽  
Mark Jonathan Hancock ◽  
Lucíola da Cunha Menezes Costa ◽  
...  
Keyword(s):  
Low Back Pain ◽  
Back Pain ◽  
Prediction Model ◽  
Sao Paulo ◽  
Validation Dataset ◽  
Low Back ◽  
São Paulo ◽  
Clinical Prediction ◽  
Clinical Prediction Model ◽  
Acute Low Back Pain

BackgroundThe clinical course of acute low back pain (LBP) is generally favourable; however, there is significant variability in the prognosis of these patients. A clinical prediction model to predict the likelihood of pain recovery at three time points for patients with acute LBP has recently been developed. The aim of this study is to conduct a broad validation test of this clinical prediction model, by testing its performance in a new sample of patients and a different setting.MethodsThe validation study with a prospective cohort design will recruit 420 patients with recent onset non-specific acute LBP, with moderate pain intensity, seeking care in the emergency departments of hospitals in São Paulo, Brazil. The primary outcome measure will be days to recovery from pain. The predicted probability of pain recovery for each individual will be computed based on predictions of the development model and this will be used to test the performance (calibration and discrimination) in the validation dataset.DiscussionThe findings of this study will better inform about the performance of the clinical prediction model, helping both clinicians and patients. If the model’s performance is acceptable, then future research should evaluate the impact of the prediction model, assessing whether it produces a change in clinicians’ behaviour and/or an improvement in patient outcomes.Ethics and disseminationEthics were granted by the Research Ethics Committee of the Universidade Cidade de São Paulo, #20310419.4.0000.0064. Study findings will be disseminated widely through peer-reviewed publications and conference presentations.

Predicting recovery in patients with acute low back pain: A Clinical Prediction Model

2017 ◽  
Vol 21 (4) ◽  
pp. 716-726 ◽  
Author(s):  
T. da Silva ◽  
P. Macaskill ◽  
K. Mills ◽  
C. Maher ◽  
C. Williams ◽  
...  
Keyword(s):  
Low Back Pain ◽  
Back Pain ◽  
Prediction Model ◽  
Low Back ◽  
Clinical Prediction ◽  
Clinical Prediction Model ◽  
Acute Low Back Pain

Predicting pain recovery in patients with acute low back pain: Updating and validation of a clinical prediction model

2018 ◽  
Vol 23 (2) ◽  
pp. 341-353 ◽  
Author(s):  
Tatiane da Silva ◽  
Petra Macaskill ◽  
Alice Kongsted ◽  
Kathryn Mills ◽  
Chris G. Maher ◽  
...  
Keyword(s):  
Low Back Pain ◽  
Back Pain ◽  
Prediction Model ◽  
Low Back ◽  
Clinical Prediction ◽  
Clinical Prediction Model ◽  
Acute Low Back Pain

Can rate of recovery be predicted in patients with acute low back pain? Development of a clinical prediction rule

2009 ◽  
Vol 13 (1) ◽  
pp. 51-55 ◽  
Author(s):  
Mark J. Hancock ◽  
Christopher G. Maher ◽  
Jane Latimer ◽  
Rob D. Herbert ◽  
James H. McAuley
Keyword(s):  
Low Back Pain ◽  
Back Pain ◽  
Prediction Rule ◽  
Clinical Prediction Rule ◽  
Low Back ◽  
Clinical Prediction ◽  
Acute Low Back Pain ◽  
Rate Of Recovery

scholarly journals Study of the prevalence and risk factors for low back pain in truck drivers in the state of São Paulo, Brazil

Clinics ◽  
2006 ◽  
Vol 61 (6) ◽  
pp. 503-510 ◽  
Author(s):  
Silvia Ferreira Andrusaitis ◽  
Reginaldo Perilo Oliveira ◽  
Tarcísio Eloy P. Barros Filho
Keyword(s):  
Risk Factors ◽  
Low Back Pain ◽  
Back Pain ◽  
Sao Paulo ◽  
The State ◽  
Truck Drivers ◽  
Low Back ◽  
São Paulo

scholarly journals Low back pain prevalence in Sao Paulo, Brazil: A cross-sectional study

2021 ◽  
Author(s):  
Gabrielle Z. Gonzalez ◽  
Tatiane da Silva ◽  
Marina A. Avanzi ◽  
Gabriel T. Macedo ◽  
Shirley S. Alves ◽  
...  
Keyword(s):  
Low Back Pain ◽  
Back Pain ◽  
Cross Sectional Study ◽  
Sao Paulo ◽  
Low Back ◽  
São Paulo ◽  
Sectional Study ◽  
Cross Sectional ◽  
Pain Prevalence

scholarly journals Prognostic Prediction Models for Patients with Low Back Pain: Systematic Review Protocol

2020 ◽  
Author(s):  
Fernanda Gonçalves Silva ◽  
Leonardo Oliveira Pena Costa ◽  
Mark J Hancock ◽  
Gabriele Alves Palomo ◽  
Luciola da Cunha Menezes Costa ◽  
...  
Keyword(s):  
Systematic Review ◽  
Low Back Pain ◽  
Back Pain ◽  
Prediction Model ◽  
Prediction Models ◽  
External Validation ◽  
Risk Of Bias ◽  
Low Back ◽  
Clinical Prediction ◽  
Clinical Prediction Models

Abstract Background: The prognosis of acute low back pain is generally favourable in terms of pain and disability; however, outcomes vary substantially between individual patients. Clinical prediction models help in estimating the likelihood of an outcome at a certain time point. There are existing clinical prediction models focused on prognosis for patients with low back pain. To date, there is only one previous systematic review summarising the discrimination of validated clinical prediction models to identify the prognosis in patients with low back pain of less than 3 months duration. The aim of this systematic review is to identify existing developed and/or validated clinical prediction models on prognosis of patients with low back pain of less than 3 months duration, and to summarise their performance in terms of discrimination and calibration. Methods: MEDLINE, Embase and CINAHL databases will be searched, from the inception of these databases until January 2020. Eligibility criteria will be: (1) prognostic model development studies with or without external validation, or prognostic external validation studies with or without model updating; (2) with adults aged 18 or over, with ‘recent onset’ low back pain (i.e. less than 3 months duration), with or without leg pain; (3) outcomes of pain, disability, sick leave or days absent from work or return to work status, and self-reported recovery; and (4) study with a follow-up of at least 12 weeks duration. The risk of bias of the included studies will be assessed by the Prediction model Risk Of Bias ASsessment Tool, and the overall quality of evidence will be rated using the Hierarchy of Evidence for Clinical Prediction Rules. Discussion: This systematic review will identify, appraise, and summarize evidence on the performance of existing prediction models for prognosis of low back pain, and may help clinicians to choose the best option of prediction model to better inform patients about their likely prognosis. Systematic review registration: PROSPERO reference number CRD42020160988

scholarly journals Investigation of low back pain in a non-hospital population of the coastline of the State of São Paulo

Revista Dor ◽  
2011 ◽  
Vol 12 (1) ◽  
pp. 19-22
Author(s):  
Janaína Macedo Malateaux ◽  
Flávia Rother Ricci ◽  
Yára Dadalti Fragoso
Keyword(s):  
Low Back Pain ◽  
Back Pain ◽  
Sao Paulo ◽  
The State ◽  
Low Back ◽  
São Paulo ◽  
Hospital Population

scholarly journals Prevalence and factors associated with low back pain in elderly registered in the Family Health Strategy

2017 ◽  
Vol 30 (2) ◽  
pp. 367-377 ◽  
Author(s):  
Natasha Mendonça Quintino ◽  
Marta Helena Souza De Conti ◽  
Roger Palma ◽  
Márcia Aparecida Nuevo Gatti ◽  
Sandra Fiorelli Almeida Penteado Simeão ◽  
...  
Keyword(s):  
Low Back Pain ◽  
Back Pain ◽  
Family Health ◽  
The Elderly ◽  
Sao Paulo ◽  
Low Back ◽  
São Paulo ◽  
Health Strategy ◽  
The Family ◽  
Family Health Strategy

Abstract Introduction: Low back pain has varied etiology and complex discussed and can be triggered by various factors. Objective: Was to assess the prevalence of low back pain in individuals 60 years or more of the areas of the Family Health Strategy “Vila Sao Paulo” in the city of Bauru, São Paulo, and its association with demographic and socioeconomic variables, relating to work, lifestyle and morbidity. Methods: We conducted a cross-sectional study with 363 elderly sampled by the technique of two-stage cluster, which were interviewed at home using a multidimensional instrument (demographic, socio-economic, featuring work; lifestyle; morbidity) and the Nordic questionnaire. Conducted descriptive analysis, bivariate and Poisson regression. Results: It was noted more frequently in the elderly age group between 60 and 69 years old, married, with low education and income from two to five. The prevalence of low back pain was 55.8% of elderly patients studied, 52.2% in men and 47.8% women and, the variables load and carry weight (p = 0.001) and the number of diseases referred to (p = 0.04) showed association with the presence of low back pain. Conclusion: The elderly respondents show a high prevalence of low back pain associated with the loading and transport weight and the number of diseases referred.

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