Characteristics of retinal image associated with premature ovarian insufficiency: a case- control study

Purpose To establish an early clinical diagnosis model based on the retinal vascular features associated with POI, supplying a non-invasive way for accurately and early predicted the risk of POI. Methods A total of 78 women with spontaneous POI and 48 healthy women were recruited from the Affiliated...
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Autor*in:	Wu, Jiaman [verfasserIn] Tan, Liya Ning, Yan Yuan, Weiqu Lee, Zuowei Ma, Fei Wang, Erfeng Zhuo, Yuanyuan

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	Retinal characteristics Premature ovarian insufficiency Retinal image analysis Biostatistics method Early clinical diagnosis

Anmerkung:	© The Author(s) 2023

Übergeordnetes Werk:	Enthalten in: Journal of ovarian research - London : BioMed Central, 2008, 16(2023), 1 vom: 24. Juli
Übergeordnetes Werk:	volume:16 ; year:2023 ; number:1 ; day:24 ; month:07

Links:	Volltext

DOI / URN:	10.1186/s13048-023-01231-0

Katalog-ID:	SPR052362299

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520			\|a Purpose To establish an early clinical diagnosis model based on the retinal vascular features associated with POI, supplying a non-invasive way for accurately and early predicted the risk of POI. Methods A total of 78 women with spontaneous POI and 48 healthy women were recruited from the Affiliated Shenzhen Maternity & Child Healthcare Hospital in the study. Retinal characteristics were analyzed using an automated retinal image analysis system. Binary logistic regression was used to identify POI cases and develop predictive models. Results Compared to the normal group, the POI group had larger central retinal artery equivalent (CRAE) (P = 0.006), central retinal vein equivalent (CRVE) (P = 0.001), index of venules asymmetry (Vasym) (P = 0.000); larger bifurcation angles of arterioles (Aangle) (P = 0.001), bifurcation coefficient of venule (BCV) (P = 0.001) and more obvious arteriovenous nipping (Nipping) (P = 0.005), but lower arteriole-to-venule ratio (AVR) (P = 0.012). In the POI group, the odds ratio (OR) of Vasym was 6.72e-32 (95% C.I. 4.62e-49–9.79e-15, P = 0.000), the OR of BCV was 5.66e-20 (95% C.I. 1.93e-34–.0000, P = 5.66e-20) and the OR of Nipping was 6.65e-06 (95% C.I. 6.33e-10–.0698, P = 0.012). Moreover, the area under the ROC curve for the binary logistic regression with retinal characteristics was 0.8582, and the fitting degree of regression models was 60.48% (Prob > chi-square = 0.6048). Conclusion This study demonstrated that retinal image analysis can provide useful information for POI identification and certain characteristics may help with early clinical diagnosis of POI.
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650		4	\|a Premature ovarian insufficiency \|7 (dpeaa)DE-He213
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650		4	\|a Biostatistics method \|7 (dpeaa)DE-He213
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700	1		\|a Zhuo, Yuanyuan \|4 aut
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allfields	10.1186/s13048-023-01231-0 doi (DE-627)SPR052362299 (SPR)s13048-023-01231-0-e DE-627 ger DE-627 rakwb eng Wu, Jiaman verfasserin aut Characteristics of retinal image associated with premature ovarian insufficiency: a case- control study 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Purpose To establish an early clinical diagnosis model based on the retinal vascular features associated with POI, supplying a non-invasive way for accurately and early predicted the risk of POI. Methods A total of 78 women with spontaneous POI and 48 healthy women were recruited from the Affiliated Shenzhen Maternity & Child Healthcare Hospital in the study. Retinal characteristics were analyzed using an automated retinal image analysis system. Binary logistic regression was used to identify POI cases and develop predictive models. Results Compared to the normal group, the POI group had larger central retinal artery equivalent (CRAE) (P = 0.006), central retinal vein equivalent (CRVE) (P = 0.001), index of venules asymmetry (Vasym) (P = 0.000); larger bifurcation angles of arterioles (Aangle) (P = 0.001), bifurcation coefficient of venule (BCV) (P = 0.001) and more obvious arteriovenous nipping (Nipping) (P = 0.005), but lower arteriole-to-venule ratio (AVR) (P = 0.012). In the POI group, the odds ratio (OR) of Vasym was 6.72e-32 (95% C.I. 4.62e-49–9.79e-15, P = 0.000), the OR of BCV was 5.66e-20 (95% C.I. 1.93e-34–.0000, P = 5.66e-20) and the OR of Nipping was 6.65e-06 (95% C.I. 6.33e-10–.0698, P = 0.012). Moreover, the area under the ROC curve for the binary logistic regression with retinal characteristics was 0.8582, and the fitting degree of regression models was 60.48% (Prob > chi-square = 0.6048). Conclusion This study demonstrated that retinal image analysis can provide useful information for POI identification and certain characteristics may help with early clinical diagnosis of POI. Retinal characteristics (dpeaa)DE-He213 Premature ovarian insufficiency (dpeaa)DE-He213 Retinal image analysis (dpeaa)DE-He213 Biostatistics method (dpeaa)DE-He213 Early clinical diagnosis (dpeaa)DE-He213 Tan, Liya aut Ning, Yan aut Yuan, Weiqu aut Lee, Zuowei aut Ma, Fei aut Wang, Erfeng aut Zhuo, Yuanyuan aut Enthalten in Journal of ovarian research London : BioMed Central, 2008 16(2023), 1 vom: 24. Juli (DE-627)581041070 (DE-600)2455679-8 1757-2215 nnns volume:16 year:2023 number:1 day:24 month:07 https://dx.doi.org/10.1186/s13048-023-01231-0 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 16 2023 1 24 07
spelling	10.1186/s13048-023-01231-0 doi (DE-627)SPR052362299 (SPR)s13048-023-01231-0-e DE-627 ger DE-627 rakwb eng Wu, Jiaman verfasserin aut Characteristics of retinal image associated with premature ovarian insufficiency: a case- control study 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Purpose To establish an early clinical diagnosis model based on the retinal vascular features associated with POI, supplying a non-invasive way for accurately and early predicted the risk of POI. Methods A total of 78 women with spontaneous POI and 48 healthy women were recruited from the Affiliated Shenzhen Maternity & Child Healthcare Hospital in the study. Retinal characteristics were analyzed using an automated retinal image analysis system. Binary logistic regression was used to identify POI cases and develop predictive models. Results Compared to the normal group, the POI group had larger central retinal artery equivalent (CRAE) (P = 0.006), central retinal vein equivalent (CRVE) (P = 0.001), index of venules asymmetry (Vasym) (P = 0.000); larger bifurcation angles of arterioles (Aangle) (P = 0.001), bifurcation coefficient of venule (BCV) (P = 0.001) and more obvious arteriovenous nipping (Nipping) (P = 0.005), but lower arteriole-to-venule ratio (AVR) (P = 0.012). In the POI group, the odds ratio (OR) of Vasym was 6.72e-32 (95% C.I. 4.62e-49–9.79e-15, P = 0.000), the OR of BCV was 5.66e-20 (95% C.I. 1.93e-34–.0000, P = 5.66e-20) and the OR of Nipping was 6.65e-06 (95% C.I. 6.33e-10–.0698, P = 0.012). Moreover, the area under the ROC curve for the binary logistic regression with retinal characteristics was 0.8582, and the fitting degree of regression models was 60.48% (Prob > chi-square = 0.6048). Conclusion This study demonstrated that retinal image analysis can provide useful information for POI identification and certain characteristics may help with early clinical diagnosis of POI. Retinal characteristics (dpeaa)DE-He213 Premature ovarian insufficiency (dpeaa)DE-He213 Retinal image analysis (dpeaa)DE-He213 Biostatistics method (dpeaa)DE-He213 Early clinical diagnosis (dpeaa)DE-He213 Tan, Liya aut Ning, Yan aut Yuan, Weiqu aut Lee, Zuowei aut Ma, Fei aut Wang, Erfeng aut Zhuo, Yuanyuan aut Enthalten in Journal of ovarian research London : BioMed Central, 2008 16(2023), 1 vom: 24. Juli (DE-627)581041070 (DE-600)2455679-8 1757-2215 nnns volume:16 year:2023 number:1 day:24 month:07 https://dx.doi.org/10.1186/s13048-023-01231-0 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 16 2023 1 24 07
allfields_unstemmed	10.1186/s13048-023-01231-0 doi (DE-627)SPR052362299 (SPR)s13048-023-01231-0-e DE-627 ger DE-627 rakwb eng Wu, Jiaman verfasserin aut Characteristics of retinal image associated with premature ovarian insufficiency: a case- control study 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Purpose To establish an early clinical diagnosis model based on the retinal vascular features associated with POI, supplying a non-invasive way for accurately and early predicted the risk of POI. Methods A total of 78 women with spontaneous POI and 48 healthy women were recruited from the Affiliated Shenzhen Maternity & Child Healthcare Hospital in the study. Retinal characteristics were analyzed using an automated retinal image analysis system. Binary logistic regression was used to identify POI cases and develop predictive models. Results Compared to the normal group, the POI group had larger central retinal artery equivalent (CRAE) (P = 0.006), central retinal vein equivalent (CRVE) (P = 0.001), index of venules asymmetry (Vasym) (P = 0.000); larger bifurcation angles of arterioles (Aangle) (P = 0.001), bifurcation coefficient of venule (BCV) (P = 0.001) and more obvious arteriovenous nipping (Nipping) (P = 0.005), but lower arteriole-to-venule ratio (AVR) (P = 0.012). In the POI group, the odds ratio (OR) of Vasym was 6.72e-32 (95% C.I. 4.62e-49–9.79e-15, P = 0.000), the OR of BCV was 5.66e-20 (95% C.I. 1.93e-34–.0000, P = 5.66e-20) and the OR of Nipping was 6.65e-06 (95% C.I. 6.33e-10–.0698, P = 0.012). Moreover, the area under the ROC curve for the binary logistic regression with retinal characteristics was 0.8582, and the fitting degree of regression models was 60.48% (Prob > chi-square = 0.6048). Conclusion This study demonstrated that retinal image analysis can provide useful information for POI identification and certain characteristics may help with early clinical diagnosis of POI. Retinal characteristics (dpeaa)DE-He213 Premature ovarian insufficiency (dpeaa)DE-He213 Retinal image analysis (dpeaa)DE-He213 Biostatistics method (dpeaa)DE-He213 Early clinical diagnosis (dpeaa)DE-He213 Tan, Liya aut Ning, Yan aut Yuan, Weiqu aut Lee, Zuowei aut Ma, Fei aut Wang, Erfeng aut Zhuo, Yuanyuan aut Enthalten in Journal of ovarian research London : BioMed Central, 2008 16(2023), 1 vom: 24. Juli (DE-627)581041070 (DE-600)2455679-8 1757-2215 nnns volume:16 year:2023 number:1 day:24 month:07 https://dx.doi.org/10.1186/s13048-023-01231-0 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 16 2023 1 24 07
allfieldsGer	10.1186/s13048-023-01231-0 doi (DE-627)SPR052362299 (SPR)s13048-023-01231-0-e DE-627 ger DE-627 rakwb eng Wu, Jiaman verfasserin aut Characteristics of retinal image associated with premature ovarian insufficiency: a case- control study 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Purpose To establish an early clinical diagnosis model based on the retinal vascular features associated with POI, supplying a non-invasive way for accurately and early predicted the risk of POI. Methods A total of 78 women with spontaneous POI and 48 healthy women were recruited from the Affiliated Shenzhen Maternity & Child Healthcare Hospital in the study. Retinal characteristics were analyzed using an automated retinal image analysis system. Binary logistic regression was used to identify POI cases and develop predictive models. Results Compared to the normal group, the POI group had larger central retinal artery equivalent (CRAE) (P = 0.006), central retinal vein equivalent (CRVE) (P = 0.001), index of venules asymmetry (Vasym) (P = 0.000); larger bifurcation angles of arterioles (Aangle) (P = 0.001), bifurcation coefficient of venule (BCV) (P = 0.001) and more obvious arteriovenous nipping (Nipping) (P = 0.005), but lower arteriole-to-venule ratio (AVR) (P = 0.012). In the POI group, the odds ratio (OR) of Vasym was 6.72e-32 (95% C.I. 4.62e-49–9.79e-15, P = 0.000), the OR of BCV was 5.66e-20 (95% C.I. 1.93e-34–.0000, P = 5.66e-20) and the OR of Nipping was 6.65e-06 (95% C.I. 6.33e-10–.0698, P = 0.012). Moreover, the area under the ROC curve for the binary logistic regression with retinal characteristics was 0.8582, and the fitting degree of regression models was 60.48% (Prob > chi-square = 0.6048). Conclusion This study demonstrated that retinal image analysis can provide useful information for POI identification and certain characteristics may help with early clinical diagnosis of POI. Retinal characteristics (dpeaa)DE-He213 Premature ovarian insufficiency (dpeaa)DE-He213 Retinal image analysis (dpeaa)DE-He213 Biostatistics method (dpeaa)DE-He213 Early clinical diagnosis (dpeaa)DE-He213 Tan, Liya aut Ning, Yan aut Yuan, Weiqu aut Lee, Zuowei aut Ma, Fei aut Wang, Erfeng aut Zhuo, Yuanyuan aut Enthalten in Journal of ovarian research London : BioMed Central, 2008 16(2023), 1 vom: 24. Juli (DE-627)581041070 (DE-600)2455679-8 1757-2215 nnns volume:16 year:2023 number:1 day:24 month:07 https://dx.doi.org/10.1186/s13048-023-01231-0 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 16 2023 1 24 07
allfieldsSound	10.1186/s13048-023-01231-0 doi (DE-627)SPR052362299 (SPR)s13048-023-01231-0-e DE-627 ger DE-627 rakwb eng Wu, Jiaman verfasserin aut Characteristics of retinal image associated with premature ovarian insufficiency: a case- control study 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Purpose To establish an early clinical diagnosis model based on the retinal vascular features associated with POI, supplying a non-invasive way for accurately and early predicted the risk of POI. Methods A total of 78 women with spontaneous POI and 48 healthy women were recruited from the Affiliated Shenzhen Maternity & Child Healthcare Hospital in the study. Retinal characteristics were analyzed using an automated retinal image analysis system. Binary logistic regression was used to identify POI cases and develop predictive models. Results Compared to the normal group, the POI group had larger central retinal artery equivalent (CRAE) (P = 0.006), central retinal vein equivalent (CRVE) (P = 0.001), index of venules asymmetry (Vasym) (P = 0.000); larger bifurcation angles of arterioles (Aangle) (P = 0.001), bifurcation coefficient of venule (BCV) (P = 0.001) and more obvious arteriovenous nipping (Nipping) (P = 0.005), but lower arteriole-to-venule ratio (AVR) (P = 0.012). In the POI group, the odds ratio (OR) of Vasym was 6.72e-32 (95% C.I. 4.62e-49–9.79e-15, P = 0.000), the OR of BCV was 5.66e-20 (95% C.I. 1.93e-34–.0000, P = 5.66e-20) and the OR of Nipping was 6.65e-06 (95% C.I. 6.33e-10–.0698, P = 0.012). Moreover, the area under the ROC curve for the binary logistic regression with retinal characteristics was 0.8582, and the fitting degree of regression models was 60.48% (Prob > chi-square = 0.6048). Conclusion This study demonstrated that retinal image analysis can provide useful information for POI identification and certain characteristics may help with early clinical diagnosis of POI. Retinal characteristics (dpeaa)DE-He213 Premature ovarian insufficiency (dpeaa)DE-He213 Retinal image analysis (dpeaa)DE-He213 Biostatistics method (dpeaa)DE-He213 Early clinical diagnosis (dpeaa)DE-He213 Tan, Liya aut Ning, Yan aut Yuan, Weiqu aut Lee, Zuowei aut Ma, Fei aut Wang, Erfeng aut Zhuo, Yuanyuan aut Enthalten in Journal of ovarian research London : BioMed Central, 2008 16(2023), 1 vom: 24. Juli (DE-627)581041070 (DE-600)2455679-8 1757-2215 nnns volume:16 year:2023 number:1 day:24 month:07 https://dx.doi.org/10.1186/s13048-023-01231-0 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 16 2023 1 24 07
language	English
source	Enthalten in Journal of ovarian research 16(2023), 1 vom: 24. Juli volume:16 year:2023 number:1 day:24 month:07
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spellingShingle	Wu, Jiaman misc Retinal characteristics misc Premature ovarian insufficiency misc Retinal image analysis misc Biostatistics method misc Early clinical diagnosis Characteristics of retinal image associated with premature ovarian insufficiency: a case- control study
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topic_title	Characteristics of retinal image associated with premature ovarian insufficiency: a case- control study Retinal characteristics (dpeaa)DE-He213 Premature ovarian insufficiency (dpeaa)DE-He213 Retinal image analysis (dpeaa)DE-He213 Biostatistics method (dpeaa)DE-He213 Early clinical diagnosis (dpeaa)DE-He213
topic	misc Retinal characteristics misc Premature ovarian insufficiency misc Retinal image analysis misc Biostatistics method misc Early clinical diagnosis
topic_unstemmed	misc Retinal characteristics misc Premature ovarian insufficiency misc Retinal image analysis misc Biostatistics method misc Early clinical diagnosis
topic_browse	misc Retinal characteristics misc Premature ovarian insufficiency misc Retinal image analysis misc Biostatistics method misc Early clinical diagnosis
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title_sort	characteristics of retinal image associated with premature ovarian insufficiency: a case- control study
title_auth	Characteristics of retinal image associated with premature ovarian insufficiency: a case- control study
abstract	Purpose To establish an early clinical diagnosis model based on the retinal vascular features associated with POI, supplying a non-invasive way for accurately and early predicted the risk of POI. Methods A total of 78 women with spontaneous POI and 48 healthy women were recruited from the Affiliated Shenzhen Maternity & Child Healthcare Hospital in the study. Retinal characteristics were analyzed using an automated retinal image analysis system. Binary logistic regression was used to identify POI cases and develop predictive models. Results Compared to the normal group, the POI group had larger central retinal artery equivalent (CRAE) (P = 0.006), central retinal vein equivalent (CRVE) (P = 0.001), index of venules asymmetry (Vasym) (P = 0.000); larger bifurcation angles of arterioles (Aangle) (P = 0.001), bifurcation coefficient of venule (BCV) (P = 0.001) and more obvious arteriovenous nipping (Nipping) (P = 0.005), but lower arteriole-to-venule ratio (AVR) (P = 0.012). In the POI group, the odds ratio (OR) of Vasym was 6.72e-32 (95% C.I. 4.62e-49–9.79e-15, P = 0.000), the OR of BCV was 5.66e-20 (95% C.I. 1.93e-34–.0000, P = 5.66e-20) and the OR of Nipping was 6.65e-06 (95% C.I. 6.33e-10–.0698, P = 0.012). Moreover, the area under the ROC curve for the binary logistic regression with retinal characteristics was 0.8582, and the fitting degree of regression models was 60.48% (Prob > chi-square = 0.6048). Conclusion This study demonstrated that retinal image analysis can provide useful information for POI identification and certain characteristics may help with early clinical diagnosis of POI. © The Author(s) 2023
abstractGer	Purpose To establish an early clinical diagnosis model based on the retinal vascular features associated with POI, supplying a non-invasive way for accurately and early predicted the risk of POI. Methods A total of 78 women with spontaneous POI and 48 healthy women were recruited from the Affiliated Shenzhen Maternity & Child Healthcare Hospital in the study. Retinal characteristics were analyzed using an automated retinal image analysis system. Binary logistic regression was used to identify POI cases and develop predictive models. Results Compared to the normal group, the POI group had larger central retinal artery equivalent (CRAE) (P = 0.006), central retinal vein equivalent (CRVE) (P = 0.001), index of venules asymmetry (Vasym) (P = 0.000); larger bifurcation angles of arterioles (Aangle) (P = 0.001), bifurcation coefficient of venule (BCV) (P = 0.001) and more obvious arteriovenous nipping (Nipping) (P = 0.005), but lower arteriole-to-venule ratio (AVR) (P = 0.012). In the POI group, the odds ratio (OR) of Vasym was 6.72e-32 (95% C.I. 4.62e-49–9.79e-15, P = 0.000), the OR of BCV was 5.66e-20 (95% C.I. 1.93e-34–.0000, P = 5.66e-20) and the OR of Nipping was 6.65e-06 (95% C.I. 6.33e-10–.0698, P = 0.012). Moreover, the area under the ROC curve for the binary logistic regression with retinal characteristics was 0.8582, and the fitting degree of regression models was 60.48% (Prob > chi-square = 0.6048). Conclusion This study demonstrated that retinal image analysis can provide useful information for POI identification and certain characteristics may help with early clinical diagnosis of POI. © The Author(s) 2023
abstract_unstemmed	Purpose To establish an early clinical diagnosis model based on the retinal vascular features associated with POI, supplying a non-invasive way for accurately and early predicted the risk of POI. Methods A total of 78 women with spontaneous POI and 48 healthy women were recruited from the Affiliated Shenzhen Maternity & Child Healthcare Hospital in the study. Retinal characteristics were analyzed using an automated retinal image analysis system. Binary logistic regression was used to identify POI cases and develop predictive models. Results Compared to the normal group, the POI group had larger central retinal artery equivalent (CRAE) (P = 0.006), central retinal vein equivalent (CRVE) (P = 0.001), index of venules asymmetry (Vasym) (P = 0.000); larger bifurcation angles of arterioles (Aangle) (P = 0.001), bifurcation coefficient of venule (BCV) (P = 0.001) and more obvious arteriovenous nipping (Nipping) (P = 0.005), but lower arteriole-to-venule ratio (AVR) (P = 0.012). In the POI group, the odds ratio (OR) of Vasym was 6.72e-32 (95% C.I. 4.62e-49–9.79e-15, P = 0.000), the OR of BCV was 5.66e-20 (95% C.I. 1.93e-34–.0000, P = 5.66e-20) and the OR of Nipping was 6.65e-06 (95% C.I. 6.33e-10–.0698, P = 0.012). Moreover, the area under the ROC curve for the binary logistic regression with retinal characteristics was 0.8582, and the fitting degree of regression models was 60.48% (Prob > chi-square = 0.6048). Conclusion This study demonstrated that retinal image analysis can provide useful information for POI identification and certain characteristics may help with early clinical diagnosis of POI. © The Author(s) 2023
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doi_str	10.1186/s13048-023-01231-0
up_date	2024-07-04T02:30:44.139Z
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fullrecord_marcxml	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">SPR052362299</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230725064747.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230725s2023 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1186/s13048-023-01231-0</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR052362299</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s13048-023-01231-0-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Wu, Jiaman</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Characteristics of retinal image associated with premature ovarian insufficiency: a case- control study</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2023</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© The Author(s) 2023</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Purpose To establish an early clinical diagnosis model based on the retinal vascular features associated with POI, supplying a non-invasive way for accurately and early predicted the risk of POI. Methods A total of 78 women with spontaneous POI and 48 healthy women were recruited from the Affiliated Shenzhen Maternity & Child Healthcare Hospital in the study. Retinal characteristics were analyzed using an automated retinal image analysis system. Binary logistic regression was used to identify POI cases and develop predictive models. Results Compared to the normal group, the POI group had larger central retinal artery equivalent (CRAE) (P = 0.006), central retinal vein equivalent (CRVE) (P = 0.001), index of venules asymmetry (Vasym) (P = 0.000); larger bifurcation angles of arterioles (Aangle) (P = 0.001), bifurcation coefficient of venule (BCV) (P = 0.001) and more obvious arteriovenous nipping (Nipping) (P = 0.005), but lower arteriole-to-venule ratio (AVR) (P = 0.012). In the POI group, the odds ratio (OR) of Vasym was 6.72e-32 (95% C.I. 4.62e-49–9.79e-15, P = 0.000), the OR of BCV was 5.66e-20 (95% C.I. 1.93e-34–.0000, P = 5.66e-20) and the OR of Nipping was 6.65e-06 (95% C.I. 6.33e-10–.0698, P = 0.012). Moreover, the area under the ROC curve for the binary logistic regression with retinal characteristics was 0.8582, and the fitting degree of regression models was 60.48% (Prob > chi-square = 0.6048). 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Characteristics of retinal image associated with premature ovarian insufficiency: a case- control study

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