| Literature DB >> 28435573 |
A S Deepak1, J Y Ong2, Dsk Choon2, C K Lee2, C K Chiu2, Cyw Chan2, M K Kwan2.
Abstract
INTRODUCTION: There is no large population size study on school screening for scoliosis in Malaysia. This study is aimed to determine the prevalence rate and positive predictive value (PPV) of screening programme for adolescent idiopathic scoliosis.Entities:
Keywords: adolescent idiopathic scoliosis; positive predictive value; prevalence; school screening
Year: 2017 PMID: 28435573 PMCID: PMC5393113 DOI: 10.5704/MOJ.1703.018
Source DB: PubMed Journal: Malays Orthop J ISSN: 1985-2533
Fig. 1Screening protocol of Adolescent Idiopathic Scoliosis in Kuala Langat, Malaysia.
Referral rate for radiographs using a scoliometer screening
| Age | 13 | 14 | 15 | 13-15 | Total | ||||
|---|---|---|---|---|---|---|---|---|---|
| Gender | M | F | M | F | M | F | M | F | |
| Population screened | 1636 | 1644 | 1469 | 1477 | 1276 | 1464 | 4381 | 4585 | 8966 |
| Positive subjects | 57 | 82 | 59 | 73 | 66 | 73 | 182 | 228 | 410 |
| Referral rate (%) | 3.5 | 5.0 | 4.0 | 4.9 | 5.2 | 5.0 | 4.2 | 5.0 | 4.6 |
M = Male, F = Female
Prevalence rate and positive predictive value
| Cobb angle | Prevalence | PPV | |||
|---|---|---|---|---|---|
| Rate (%) | 95% CI | Rate (%) | 95% CI | ||
| >10° | 87/8966 (0.97) | 0.0079, 0.0120 | 2.55 | 87/156 (55.8) | 0.635, 0.477 |
| >20° | 20/8966 (0.22) | 0.0014, 0.0034 | 0.59 | 20/156 (12.8) | 0.154, 0.101 |
| >40° | 4/8966 (0.04) | 0.0002, 0.0011 | 0.12 | 4/156 (2.6) | 0.0382, 0.0129 |
PPV = Positive predictive value
Adjusted prevalence rate = prevalence rate/turn-up rate x 100%; turn-up rate=38%
Literature reviews of school scoliosis screening in Asian countries
| Year Published | Country | Programme | Cobb angle (degrees) | Sample size | Age (years) | Gender | PR (%) | PPV (%) |
|---|---|---|---|---|---|---|---|---|
| 2005 | Singapore | Wong | >10 | 72,699 | 6 - 7 | Male | 0.02 | 17.6 |
| Female | 0.05 | 23.7 | ||||||
| 9 - 10 | Male | 0.15 | 24.5 | |||||
| Female | 0.24 | 24.1 | ||||||
| 11 - 12 | Male | 0.21 | 23.8 | |||||
| Female | 1.37 | 50.1 | ||||||
| 13 - 14 | Male | 0.66 | 27.5 | |||||
| Female | 2.22 | 47.7 | ||||||
| 2009 | Singapore | Yong | >10 | 93626 | 9 | Female | 0.27 | - |
| 10 | 0.64 | |||||||
| 11 | 1.58 | |||||||
| 12 | 2.22 | |||||||
| 13 | 2.49 | |||||||
| 2010 | Hong Kong | Luk | >10 | 157,444 | 10 - 19 | - | 2.49 | 76.5 |
| >20 | 1.39 | 36.5 | ||||||
| >40 | 0.23 | 8.1 | ||||||
| 2011 | Korea | Suh | >10 | 1,134,890 | 10 - 14 | Male | 1.97 | 41.0 |
| Female | 4.65 | 51.0 | ||||||
| 2011 | Japan | Ueno | >10 | 255,875 | 11 - 12 | Male | 0.04 | - |
| Female | 0.78 | |||||||
| 13 | Male | 0.25 | ||||||
| Female | 2.51 | |||||||
| 2013 | Malaysia | Htwe | >10 | 832 | 12 | - | 0.6 | 35.7 |
| 2014 | Korea | Lee | >10 | 37,856 | 11 | Male | 0.05 | - |
| Female | 0.35 | |||||||
| 2015 | Hong Kong | Fong | >10 | 306,144 | 5th G - 19 | Male | 2.2 | 81.0 |
| Female | 4.8 | |||||||
| 2015 | Japan | Yamamoto | 195,149 | 5th G | Male | 0.06 | 33.3 | |
| Female | 0.34 | |||||||
| 6th G | Male | 0.01 | ||||||
| Female | 0.37 | |||||||
| 7th G | Male | 0.06 | ||||||
| Female | 0.73 | |||||||
| 2016 | China | Du | >10 | 6,824 | 6 - 17 | Male | 1.96 | 33.8 |
| Female | 3.11 | 43.2 | ||||||
| 2016 | China | Hengwei | >10 | 99,695 | 10 - 19 | - | 5.14 | - |
| 2016 | China | Zheng | >10 | 11,024 | 10 - 11 | Male | 0.17 | - |
| Female | 0.08 | |||||||
| 12 - 13 | Male | 0.52 | ||||||
| Female | 0.88 | |||||||
| - | Malaysia | Present Study | >10 | 8,966 | 13 - 15 | - | 2.55 | 55.8 |
| >20 | 0.59 | 12.8 | ||||||
| >40 | 0.12 | 2.6 |
PR = Prevalence rate, PPV = Positive predictive value, G = Grade