Retrospective validation of G-ROP, CO-ROP, Alex-ROP, and ROPscore predictive algorithms in two Chinese medical centers
PurposeTo evaluate the sensitivity and specificity of four predictive algorithms (G-ROP, CO-ROP, Alex-ROP, and ROPscore) for retinopathy of prematurity and compare their performances in the Chinese population.MethodsA retrospective study was conducted at two medical centers in China of infants born...
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Frontiers Media S.A.
2023-02-01
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| Series: | Frontiers in Pediatrics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fped.2023.1079290/full |
| _version_ | 1797900596978647040 |
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| author | Yang Lu Yang Lu Zhe Lv Jiner Cen Jiner Cen Jiwei Tao Yun Zhang Yifan Zhang Jianbo Mao Jianbo Mao Yiqi Chen Yiqi Chen Mingyuan Wu Shujun Chen Lijun Shen Lijun Shen |
| author_facet | Yang Lu Yang Lu Zhe Lv Jiner Cen Jiner Cen Jiwei Tao Yun Zhang Yifan Zhang Jianbo Mao Jianbo Mao Yiqi Chen Yiqi Chen Mingyuan Wu Shujun Chen Lijun Shen Lijun Shen |
| author_sort | Yang Lu |
| collection | DOAJ |
| description | PurposeTo evaluate the sensitivity and specificity of four predictive algorithms (G-ROP, CO-ROP, Alex-ROP, and ROPscore) for retinopathy of prematurity and compare their performances in the Chinese population.MethodsA retrospective study was conducted at two medical centers in China of infants born at Women's Hospital School of Medicine Zhejiang University and Yiwu Maternal and Child Health Hospital. A total of 1,634 infants who met the criteria and who were GA < 32 weeks or BW < 2,000 g according to Chinese guidelines for ROP screening were included. The ROP group was further grouped into severe ROP and mild ROP. The sensitivity and specificity of G-ROP, two simplified G-ROPs, CO-ROP, Alex-ROP, and ROPscore were analyzed.ResultsSevere ROP and any ROP were identified in 25 and 399 of 1,634 infants, respectively. According to the criteria of different models, 844, 1,122, 1,122, and 587 infants were eligible in the G-ROP, CO-ROP, Alex-ROP, and ROPscore, respectively. G-ROP had 96.0% sensitivity and 35.0% specificity for severe ROP. For two simplified G-ROPs (180 g and 200 g models), similar sensitivity was showed with original G-ROP and they had specificity of 21.8% and 14.0%, respectively. The sensitivity and specificity of Co-ROP were 96% and 64.3% for severe ROP, while Alex-ROP only had sensitivity of 56.0% and specificity of 61.4% for severe ROP. ROPscore had a sensitivity of 91.3% and a specificity of 62.4% for severe ROP. In 546 infants who met all 4 models' inclusion criteria and included 23 infants with severe ROP, the validation outcomes showed the sensitivity of G-ROP, ROPscore, CO-ROP, and Alex-ROP for severe ROP was 95.6%, 91.3%, 100%, and 56.0%, and their specificity was 38.0%, 60.8%, 39.9%, and 52.9%, respectively.ConclusionG-ROP, ROPscore, and CO-ROP had high sensitivity for severe ROP in the Chinese population, but both the sensitivity and specificity of Alex-ROP were low. CO-ROP (not high-grade CO-ROP) provided the best performance for severe ROP in a fair comparison. For further application, ROP screening models need to be adjusted by local populations. |
| first_indexed | 2024-04-10T08:47:25Z |
| format | Article |
| id | doaj.art-e30e214e883743c1bf59b7a8bab145a8 |
| institution | Directory Open Access Journal |
| issn | 2296-2360 |
| language | English |
| last_indexed | 2024-04-10T08:47:25Z |
| publishDate | 2023-02-01 |
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| series | Frontiers in Pediatrics |
| spelling | doaj.art-e30e214e883743c1bf59b7a8bab145a82023-02-22T06:47:47ZengFrontiers Media S.A.Frontiers in Pediatrics2296-23602023-02-011110.3389/fped.2023.10792901079290Retrospective validation of G-ROP, CO-ROP, Alex-ROP, and ROPscore predictive algorithms in two Chinese medical centersYang Lu0Yang Lu1Zhe Lv2Jiner Cen3Jiner Cen4Jiwei Tao5Yun Zhang6Yifan Zhang7Jianbo Mao8Jianbo Mao9Yiqi Chen10Yiqi Chen11Mingyuan Wu12Shujun Chen13Lijun Shen14Lijun Shen15National Clinical Research Center for Ocular Diseases, Eye Hospital, Wenzhou Medical University, Wenzhou, ChinaDepartment of Ophthalmology, Lishui People’s Hospital, Lishui, ChinaNational Clinical Research Center for Ocular Diseases, Eye Hospital, Wenzhou Medical University, Wenzhou, ChinaNational Clinical Research Center for Ocular Diseases, Eye Hospital, Wenzhou Medical University, Wenzhou, ChinaDepartment of Ophthalmology, Jiaxing Second People's Hospital, Jiaxing, ChinaNational Clinical Research Center for Ocular Diseases, Eye Hospital, Wenzhou Medical University, Wenzhou, ChinaNational Clinical Research Center for Ocular Diseases, Eye Hospital, Wenzhou Medical University, Wenzhou, ChinaNational Clinical Research Center for Ocular Diseases, Eye Hospital, Wenzhou Medical University, Wenzhou, ChinaNational Clinical Research Center for Ocular Diseases, Eye Hospital, Wenzhou Medical University, Wenzhou, ChinaDepartment of Ophthalmology, Zhejiang Provincial People's Hospital, Hangzhou, ChinaNational Clinical Research Center for Ocular Diseases, Eye Hospital, Wenzhou Medical University, Wenzhou, ChinaDepartment of Ophthalmology, Zhejiang Provincial People's Hospital, Hangzhou, ChinaDepartment of Neonatology and Pediatrics, Women’s Hospital School of Medicine Zhejiang University, Hangzhou, ChinaDepartment of Neonatology and Pediatrics, Yiwu Maternity and Children Hospital, Yiwu, ChinaNational Clinical Research Center for Ocular Diseases, Eye Hospital, Wenzhou Medical University, Wenzhou, ChinaDepartment of Ophthalmology, Zhejiang Provincial People's Hospital, Hangzhou, ChinaPurposeTo evaluate the sensitivity and specificity of four predictive algorithms (G-ROP, CO-ROP, Alex-ROP, and ROPscore) for retinopathy of prematurity and compare their performances in the Chinese population.MethodsA retrospective study was conducted at two medical centers in China of infants born at Women's Hospital School of Medicine Zhejiang University and Yiwu Maternal and Child Health Hospital. A total of 1,634 infants who met the criteria and who were GA < 32 weeks or BW < 2,000 g according to Chinese guidelines for ROP screening were included. The ROP group was further grouped into severe ROP and mild ROP. The sensitivity and specificity of G-ROP, two simplified G-ROPs, CO-ROP, Alex-ROP, and ROPscore were analyzed.ResultsSevere ROP and any ROP were identified in 25 and 399 of 1,634 infants, respectively. According to the criteria of different models, 844, 1,122, 1,122, and 587 infants were eligible in the G-ROP, CO-ROP, Alex-ROP, and ROPscore, respectively. G-ROP had 96.0% sensitivity and 35.0% specificity for severe ROP. For two simplified G-ROPs (180 g and 200 g models), similar sensitivity was showed with original G-ROP and they had specificity of 21.8% and 14.0%, respectively. The sensitivity and specificity of Co-ROP were 96% and 64.3% for severe ROP, while Alex-ROP only had sensitivity of 56.0% and specificity of 61.4% for severe ROP. ROPscore had a sensitivity of 91.3% and a specificity of 62.4% for severe ROP. In 546 infants who met all 4 models' inclusion criteria and included 23 infants with severe ROP, the validation outcomes showed the sensitivity of G-ROP, ROPscore, CO-ROP, and Alex-ROP for severe ROP was 95.6%, 91.3%, 100%, and 56.0%, and their specificity was 38.0%, 60.8%, 39.9%, and 52.9%, respectively.ConclusionG-ROP, ROPscore, and CO-ROP had high sensitivity for severe ROP in the Chinese population, but both the sensitivity and specificity of Alex-ROP were low. CO-ROP (not high-grade CO-ROP) provided the best performance for severe ROP in a fair comparison. For further application, ROP screening models need to be adjusted by local populations.https://www.frontiersin.org/articles/10.3389/fped.2023.1079290/fullretinopathy of prematurityG-ROPCO-ROPprediction modelalgorithminfants |
| spellingShingle | Yang Lu Yang Lu Zhe Lv Jiner Cen Jiner Cen Jiwei Tao Yun Zhang Yifan Zhang Jianbo Mao Jianbo Mao Yiqi Chen Yiqi Chen Mingyuan Wu Shujun Chen Lijun Shen Lijun Shen Retrospective validation of G-ROP, CO-ROP, Alex-ROP, and ROPscore predictive algorithms in two Chinese medical centers Frontiers in Pediatrics retinopathy of prematurity G-ROP CO-ROP prediction model algorithm infants |
| title | Retrospective validation of G-ROP, CO-ROP, Alex-ROP, and ROPscore predictive algorithms in two Chinese medical centers |
| title_full | Retrospective validation of G-ROP, CO-ROP, Alex-ROP, and ROPscore predictive algorithms in two Chinese medical centers |
| title_fullStr | Retrospective validation of G-ROP, CO-ROP, Alex-ROP, and ROPscore predictive algorithms in two Chinese medical centers |
| title_full_unstemmed | Retrospective validation of G-ROP, CO-ROP, Alex-ROP, and ROPscore predictive algorithms in two Chinese medical centers |
| title_short | Retrospective validation of G-ROP, CO-ROP, Alex-ROP, and ROPscore predictive algorithms in two Chinese medical centers |
| title_sort | retrospective validation of g rop co rop alex rop and ropscore predictive algorithms in two chinese medical centers |
| topic | retinopathy of prematurity G-ROP CO-ROP prediction model algorithm infants |
| url | https://www.frontiersin.org/articles/10.3389/fped.2023.1079290/full |
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