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Biln NK, Bansback N, Shojania K, Puil L, Harrison M. A scoping review of triage approaches for the referral of patients with suspected inflammatory arthritis, from primary to rheumatology care. Rheumatol Int 2024:10.1007/s00296-024-05575-8. [PMID: 38530455 DOI: 10.1007/s00296-024-05575-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Accepted: 02/29/2024] [Indexed: 03/28/2024]
Abstract
We aimed to (1) identify existing triage approaches for referral of patients with suspected inflammatory arthritis (IA) from primary care physicians (PCP) to rheumatologists, (2) describe their characteristics and methodologies for clinical use, and (3) report their level of validation for use in a publicly funded healthcare system. The comprehensive search strategy of multiple databases up to October 2023 identified relevant literature and focussed on approaches applied at the PCP-Rheumatologist referral stage. Primary, quantitative studies, reported in English were included. Triage approaches were grouped into patient conditions as defined by the authors of the reports, including IA, its subtypes and combinations. 13952 records were identified, 425 full text reviewed and 55 reports of 53 unique studies were included. Heterogeneity in disease nomenclature and study sample pretest probability was found. The number of published studies rapidly increased after 2012. Studies were mostly from Europe and North America, in IA and Axial Spondyloarthritis (AxSpa). We found tools ranging the continuum of development with those best performing, indicated by the area under the receiver operating curve (AUC) >0.8), requiring only patient-reported questions. There were AUCs for some tools reported from multiple studies, these were in the outstanding to excellent range for the Early IA Questionnaire (EIAQ) (0.88 to 0.92), acceptable for the Case Finding AxSpa (CaFaSpa) (0.70 to 0.75), and poor to outstanding for the Psoriasis Epidemiology Screening Tool (PEST) (0.61 to 0.91). Given the clinical urgency to improve rheumatology referrals and considering the good.
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Affiliation(s)
- Norma K Biln
- Faculty of Medicine, School of Population and Public Health, University of British Columbia, Vancouver, Canada
| | - Nick Bansback
- Faculty of Medicine, School of Population and Public Health, University of British Columbia, Vancouver, Canada
- Arthritis Research Canada, Vancouver, BC, Canada
- Centre for Advancing Health Outcomes, St. Paul's Hospital, Vancouver, BC, Canada
| | - Kam Shojania
- Faculty of Medicine, Department of Rheumatology, University of British Columbia, Vancouver, Canada
- Arthritis Research Canada, Vancouver, BC, Canada
- Centre for Advancing Health Outcomes, St. Paul's Hospital, Vancouver, BC, Canada
| | - Lorri Puil
- Faculty of Medicine, School of Population and Public Health, University of British Columbia, Vancouver, Canada
- Faculty of Medicine, Therapeutics Initiative, Department of Anaesthesiology, Pharmacology and Therapeutics, University of British Columbia, Vancouver, Canada
| | - Mark Harrison
- Faculty of Medicine, School of Population and Public Health, University of British Columbia, Vancouver, Canada.
- Faculty of Pharmaceutical Sciences, University of British Columbia, 4625-2405 Wesbrook Mall, Vancouver, BC, V6T 1Z3, Canada.
- Arthritis Research Canada, Vancouver, BC, Canada.
- Centre for Advancing Health Outcomes, St. Paul's Hospital, Vancouver, BC, Canada.
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Huang M, Guo Y, Zhou Z, Xu C, Liu K, Wang Y, Guo Z. Development and validation of a risk prediction model for arthritis in community-dwelling middle-aged and older adults in China. Heliyon 2024; 10:e24526. [PMID: 38298731 PMCID: PMC10828688 DOI: 10.1016/j.heliyon.2024.e24526] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 01/05/2024] [Accepted: 01/10/2024] [Indexed: 02/02/2024] Open
Abstract
Background Considering its high prevalence, estimating the risk of arthritis in middle-aged and older Chinese adults is of particular interest. This study was conducted to develop a risk prediction model for arthritis in community-dwelling middle-aged and older adults in China. Methods Our study included a total of 9599 participants utilising data from the China Health and Retirement Longitudinal Study (CHARLS). Participants were randomly assigned to training and validation groups at a 7:3 ratio. Univariate and multivariate binary logistic regression analyses were used to identify the potential predictors of arthritis. Based on the results of the multivariate binary logistic regression, a nomogram was constructed, and its predictive performance was evaluated using the receiver operating characteristic (ROC) curve. The accuracy and discrimination ability were assessed using calibration curve analysis, while decision curve analysis (DCA) was performed to evaluate the net clinical benefit rate. Results A total of 9599 participants were included in the study, of which 6716 and 2883 were assigned to the training and validation groups, respectively. A nomogram was constructed to include age, hypertension, heart diseases, gender, sleep time, body mass index (BMI), residence address, the parts of joint pain, and trouble with body pains. The results of the ROC curve suggested that the prediction model had a moderate discrimination ability (AUC >0.7). The calibration curve of the prediction model demonstrated a good predictive accuracy. The DCA curves revealed a favourable net benefit for the prediction model. Conclusions The predictive model demonstrated good discrimination, calibration, and clinical validity, and can help community physicians and clinicians to preliminarily assess the risk of arthritis in middle-aged and older community-dwelling adults.
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Affiliation(s)
- Mina Huang
- Department of Orthopedics, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, China
- School of Nursing, Jinzhou Medical University, Jinzhou, China
| | - Yue Guo
- Department of Orthopedics, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, China
| | - Zipeng Zhou
- Department of Orthopedics, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, China
| | - Chang Xu
- Department of Orthopedics, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, China
| | - Kun Liu
- School of Medical College, Jinzhou Medical University, Jinzhou, China
| | - Yongzhu Wang
- Department of Orthopedics, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, China
| | - Zhanpeng Guo
- Department of Orthopedics, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, China
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