A predictive model for the recurrence of intracranial aneurysms following coil embolization

ObjectiveThis study aimed to identify risk factors for intracranial aneurysms (IAs) recurrence and establish a predictive model to aid evaluation.MethodsA total of 302 patients with 312 IAs undergoing coil embolization between September 2017 and October 2022 were divided into two groups based on dig...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Tao He [verfasserIn] Kun Chen [verfasserIn] Ru-Dong Chen [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	intracranial aneurysm coil embolization recurrence predictive model diameter maximum Raymond-Roy occlusion classification

Übergeordnetes Werk:	In: Frontiers in Neurology - Frontiers Media S.A., 2010, 14(2023)
Übergeordnetes Werk:	volume:14 ; year:2023

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3389/fneur.2023.1248603

Katalog-ID:	DOAJ091083788

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520			\|a ObjectiveThis study aimed to identify risk factors for intracranial aneurysms (IAs) recurrence and establish a predictive model to aid evaluation.MethodsA total of 302 patients with 312 IAs undergoing coil embolization between September 2017 and October 2022 were divided into two groups based on digital subtraction angiography follow-up. Clinical characteristics, operation-related factors, and morphologies were measured. Cox proportional hazard regression was used to identify the risk factors. Hazard ratios (HRs) were used to score points, and a predictive model was established. The test cohorts consisted of 51 IAs. Receiver operating characteristic curves were generated to determine the cutoff values and area under the curves (AUCs). A Delong test was performed to compare the AUCs.ResultsDiameter maximum (D max) (p < 0.001, HR = 1.221), Raymond-Roy occlusion classification (RROC) II or III (p = 0.004, HR = 2.852), and ruptured status (p < 0.001, HR = 7.782) were independent risk factors for the recurrence of IAs. A predictive model was established: D max + 2 * RROC (II or III; yes = 1, no = 0) + 6 * ruptured status (yes = 1; no = 0). The AUC of the predictive model (0.818) was significantly higher than those of D max (0.704), RROC (II or III) (0.645), and rupture status (0.683), respectively (Delong test, p < 0.05). The cutoff values of the predictive model and D max were 9.75 points and 6.65 mm, respectively.ConclusionThe D max, RROC (II or III), and ruptured status could independently predict the recurrence of IAs after coil embolization. Our model could aid in practical evaluations.
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allfields	10.3389/fneur.2023.1248603 doi (DE-627)DOAJ091083788 (DE-599)DOAJ29578280cc3e45bbad6bb989dfa816ae DE-627 ger DE-627 rakwb eng RC346-429 Tao He verfasserin aut A predictive model for the recurrence of intracranial aneurysms following coil embolization 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier ObjectiveThis study aimed to identify risk factors for intracranial aneurysms (IAs) recurrence and establish a predictive model to aid evaluation.MethodsA total of 302 patients with 312 IAs undergoing coil embolization between September 2017 and October 2022 were divided into two groups based on digital subtraction angiography follow-up. Clinical characteristics, operation-related factors, and morphologies were measured. Cox proportional hazard regression was used to identify the risk factors. Hazard ratios (HRs) were used to score points, and a predictive model was established. The test cohorts consisted of 51 IAs. Receiver operating characteristic curves were generated to determine the cutoff values and area under the curves (AUCs). A Delong test was performed to compare the AUCs.ResultsDiameter maximum (D max) (p < 0.001, HR = 1.221), Raymond-Roy occlusion classification (RROC) II or III (p = 0.004, HR = 2.852), and ruptured status (p < 0.001, HR = 7.782) were independent risk factors for the recurrence of IAs. A predictive model was established: D max + 2 * RROC (II or III; yes = 1, no = 0) + 6 * ruptured status (yes = 1; no = 0). The AUC of the predictive model (0.818) was significantly higher than those of D max (0.704), RROC (II or III) (0.645), and rupture status (0.683), respectively (Delong test, p < 0.05). The cutoff values of the predictive model and D max were 9.75 points and 6.65 mm, respectively.ConclusionThe D max, RROC (II or III), and ruptured status could independently predict the recurrence of IAs after coil embolization. Our model could aid in practical evaluations. intracranial aneurysm coil embolization recurrence predictive model diameter maximum Raymond-Roy occlusion classification Neurology. Diseases of the nervous system Tao He verfasserin aut Kun Chen verfasserin aut Ru-Dong Chen verfasserin aut In Frontiers in Neurology Frontiers Media S.A., 2010 14(2023) (DE-627)631498753 (DE-600)2564214-5 16642295 nnns volume:14 year:2023 https://doi.org/10.3389/fneur.2023.1248603 kostenfrei https://doaj.org/article/29578280cc3e45bbad6bb989dfa816ae kostenfrei https://www.frontiersin.org/articles/10.3389/fneur.2023.1248603/full kostenfrei https://doaj.org/toc/1664-2295 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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_2014 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 14 2023
spelling	10.3389/fneur.2023.1248603 doi (DE-627)DOAJ091083788 (DE-599)DOAJ29578280cc3e45bbad6bb989dfa816ae DE-627 ger DE-627 rakwb eng RC346-429 Tao He verfasserin aut A predictive model for the recurrence of intracranial aneurysms following coil embolization 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier ObjectiveThis study aimed to identify risk factors for intracranial aneurysms (IAs) recurrence and establish a predictive model to aid evaluation.MethodsA total of 302 patients with 312 IAs undergoing coil embolization between September 2017 and October 2022 were divided into two groups based on digital subtraction angiography follow-up. Clinical characteristics, operation-related factors, and morphologies were measured. Cox proportional hazard regression was used to identify the risk factors. Hazard ratios (HRs) were used to score points, and a predictive model was established. The test cohorts consisted of 51 IAs. Receiver operating characteristic curves were generated to determine the cutoff values and area under the curves (AUCs). A Delong test was performed to compare the AUCs.ResultsDiameter maximum (D max) (p < 0.001, HR = 1.221), Raymond-Roy occlusion classification (RROC) II or III (p = 0.004, HR = 2.852), and ruptured status (p < 0.001, HR = 7.782) were independent risk factors for the recurrence of IAs. A predictive model was established: D max + 2 * RROC (II or III; yes = 1, no = 0) + 6 * ruptured status (yes = 1; no = 0). The AUC of the predictive model (0.818) was significantly higher than those of D max (0.704), RROC (II or III) (0.645), and rupture status (0.683), respectively (Delong test, p < 0.05). The cutoff values of the predictive model and D max were 9.75 points and 6.65 mm, respectively.ConclusionThe D max, RROC (II or III), and ruptured status could independently predict the recurrence of IAs after coil embolization. Our model could aid in practical evaluations. intracranial aneurysm coil embolization recurrence predictive model diameter maximum Raymond-Roy occlusion classification Neurology. Diseases of the nervous system Tao He verfasserin aut Kun Chen verfasserin aut Ru-Dong Chen verfasserin aut In Frontiers in Neurology Frontiers Media S.A., 2010 14(2023) (DE-627)631498753 (DE-600)2564214-5 16642295 nnns volume:14 year:2023 https://doi.org/10.3389/fneur.2023.1248603 kostenfrei https://doaj.org/article/29578280cc3e45bbad6bb989dfa816ae kostenfrei https://www.frontiersin.org/articles/10.3389/fneur.2023.1248603/full kostenfrei https://doaj.org/toc/1664-2295 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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_2014 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 14 2023
allfields_unstemmed	10.3389/fneur.2023.1248603 doi (DE-627)DOAJ091083788 (DE-599)DOAJ29578280cc3e45bbad6bb989dfa816ae DE-627 ger DE-627 rakwb eng RC346-429 Tao He verfasserin aut A predictive model for the recurrence of intracranial aneurysms following coil embolization 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier ObjectiveThis study aimed to identify risk factors for intracranial aneurysms (IAs) recurrence and establish a predictive model to aid evaluation.MethodsA total of 302 patients with 312 IAs undergoing coil embolization between September 2017 and October 2022 were divided into two groups based on digital subtraction angiography follow-up. Clinical characteristics, operation-related factors, and morphologies were measured. Cox proportional hazard regression was used to identify the risk factors. Hazard ratios (HRs) were used to score points, and a predictive model was established. The test cohorts consisted of 51 IAs. Receiver operating characteristic curves were generated to determine the cutoff values and area under the curves (AUCs). A Delong test was performed to compare the AUCs.ResultsDiameter maximum (D max) (p < 0.001, HR = 1.221), Raymond-Roy occlusion classification (RROC) II or III (p = 0.004, HR = 2.852), and ruptured status (p < 0.001, HR = 7.782) were independent risk factors for the recurrence of IAs. A predictive model was established: D max + 2 * RROC (II or III; yes = 1, no = 0) + 6 * ruptured status (yes = 1; no = 0). The AUC of the predictive model (0.818) was significantly higher than those of D max (0.704), RROC (II or III) (0.645), and rupture status (0.683), respectively (Delong test, p < 0.05). The cutoff values of the predictive model and D max were 9.75 points and 6.65 mm, respectively.ConclusionThe D max, RROC (II or III), and ruptured status could independently predict the recurrence of IAs after coil embolization. Our model could aid in practical evaluations. intracranial aneurysm coil embolization recurrence predictive model diameter maximum Raymond-Roy occlusion classification Neurology. Diseases of the nervous system Tao He verfasserin aut Kun Chen verfasserin aut Ru-Dong Chen verfasserin aut In Frontiers in Neurology Frontiers Media S.A., 2010 14(2023) (DE-627)631498753 (DE-600)2564214-5 16642295 nnns volume:14 year:2023 https://doi.org/10.3389/fneur.2023.1248603 kostenfrei https://doaj.org/article/29578280cc3e45bbad6bb989dfa816ae kostenfrei https://www.frontiersin.org/articles/10.3389/fneur.2023.1248603/full kostenfrei https://doaj.org/toc/1664-2295 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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_2014 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 14 2023
allfieldsGer	10.3389/fneur.2023.1248603 doi (DE-627)DOAJ091083788 (DE-599)DOAJ29578280cc3e45bbad6bb989dfa816ae DE-627 ger DE-627 rakwb eng RC346-429 Tao He verfasserin aut A predictive model for the recurrence of intracranial aneurysms following coil embolization 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier ObjectiveThis study aimed to identify risk factors for intracranial aneurysms (IAs) recurrence and establish a predictive model to aid evaluation.MethodsA total of 302 patients with 312 IAs undergoing coil embolization between September 2017 and October 2022 were divided into two groups based on digital subtraction angiography follow-up. Clinical characteristics, operation-related factors, and morphologies were measured. Cox proportional hazard regression was used to identify the risk factors. Hazard ratios (HRs) were used to score points, and a predictive model was established. The test cohorts consisted of 51 IAs. Receiver operating characteristic curves were generated to determine the cutoff values and area under the curves (AUCs). A Delong test was performed to compare the AUCs.ResultsDiameter maximum (D max) (p < 0.001, HR = 1.221), Raymond-Roy occlusion classification (RROC) II or III (p = 0.004, HR = 2.852), and ruptured status (p < 0.001, HR = 7.782) were independent risk factors for the recurrence of IAs. A predictive model was established: D max + 2 * RROC (II or III; yes = 1, no = 0) + 6 * ruptured status (yes = 1; no = 0). The AUC of the predictive model (0.818) was significantly higher than those of D max (0.704), RROC (II or III) (0.645), and rupture status (0.683), respectively (Delong test, p < 0.05). The cutoff values of the predictive model and D max were 9.75 points and 6.65 mm, respectively.ConclusionThe D max, RROC (II or III), and ruptured status could independently predict the recurrence of IAs after coil embolization. Our model could aid in practical evaluations. intracranial aneurysm coil embolization recurrence predictive model diameter maximum Raymond-Roy occlusion classification Neurology. Diseases of the nervous system Tao He verfasserin aut Kun Chen verfasserin aut Ru-Dong Chen verfasserin aut In Frontiers in Neurology Frontiers Media S.A., 2010 14(2023) (DE-627)631498753 (DE-600)2564214-5 16642295 nnns volume:14 year:2023 https://doi.org/10.3389/fneur.2023.1248603 kostenfrei https://doaj.org/article/29578280cc3e45bbad6bb989dfa816ae kostenfrei https://www.frontiersin.org/articles/10.3389/fneur.2023.1248603/full kostenfrei https://doaj.org/toc/1664-2295 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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_2014 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 14 2023
allfieldsSound	10.3389/fneur.2023.1248603 doi (DE-627)DOAJ091083788 (DE-599)DOAJ29578280cc3e45bbad6bb989dfa816ae DE-627 ger DE-627 rakwb eng RC346-429 Tao He verfasserin aut A predictive model for the recurrence of intracranial aneurysms following coil embolization 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier ObjectiveThis study aimed to identify risk factors for intracranial aneurysms (IAs) recurrence and establish a predictive model to aid evaluation.MethodsA total of 302 patients with 312 IAs undergoing coil embolization between September 2017 and October 2022 were divided into two groups based on digital subtraction angiography follow-up. Clinical characteristics, operation-related factors, and morphologies were measured. Cox proportional hazard regression was used to identify the risk factors. Hazard ratios (HRs) were used to score points, and a predictive model was established. The test cohorts consisted of 51 IAs. Receiver operating characteristic curves were generated to determine the cutoff values and area under the curves (AUCs). A Delong test was performed to compare the AUCs.ResultsDiameter maximum (D max) (p < 0.001, HR = 1.221), Raymond-Roy occlusion classification (RROC) II or III (p = 0.004, HR = 2.852), and ruptured status (p < 0.001, HR = 7.782) were independent risk factors for the recurrence of IAs. A predictive model was established: D max + 2 * RROC (II or III; yes = 1, no = 0) + 6 * ruptured status (yes = 1; no = 0). The AUC of the predictive model (0.818) was significantly higher than those of D max (0.704), RROC (II or III) (0.645), and rupture status (0.683), respectively (Delong test, p < 0.05). The cutoff values of the predictive model and D max were 9.75 points and 6.65 mm, respectively.ConclusionThe D max, RROC (II or III), and ruptured status could independently predict the recurrence of IAs after coil embolization. Our model could aid in practical evaluations. intracranial aneurysm coil embolization recurrence predictive model diameter maximum Raymond-Roy occlusion classification Neurology. Diseases of the nervous system Tao He verfasserin aut Kun Chen verfasserin aut Ru-Dong Chen verfasserin aut In Frontiers in Neurology Frontiers Media S.A., 2010 14(2023) (DE-627)631498753 (DE-600)2564214-5 16642295 nnns volume:14 year:2023 https://doi.org/10.3389/fneur.2023.1248603 kostenfrei https://doaj.org/article/29578280cc3e45bbad6bb989dfa816ae kostenfrei https://www.frontiersin.org/articles/10.3389/fneur.2023.1248603/full kostenfrei https://doaj.org/toc/1664-2295 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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_2014 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 14 2023
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Clinical characteristics, operation-related factors, and morphologies were measured. Cox proportional hazard regression was used to identify the risk factors. Hazard ratios (HRs) were used to score points, and a predictive model was established. The test cohorts consisted of 51 IAs. Receiver operating characteristic curves were generated to determine the cutoff values and area under the curves (AUCs). A Delong test was performed to compare the AUCs.ResultsDiameter maximum (D max) (p &lt; 0.001, HR = 1.221), Raymond-Roy occlusion classification (RROC) II or III (p = 0.004, HR = 2.852), and ruptured status (p &lt; 0.001, HR = 7.782) were independent risk factors for the recurrence of IAs. A predictive model was established: D max + 2 * RROC (II or III; yes = 1, no = 0) + 6 * ruptured status (yes = 1; no = 0). The AUC of the predictive model (0.818) was significantly higher than those of D max (0.704), RROC (II or III) (0.645), and rupture status (0.683), respectively (Delong test, p &lt; 0.05). The cutoff values of the predictive model and D max were 9.75 points and 6.65 mm, respectively.ConclusionThe D max, RROC (II or III), and ruptured status could independently predict the recurrence of IAs after coil embolization. Our model could aid in practical evaluations.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">intracranial aneurysm</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">coil embolization</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">recurrence</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">predictive model</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">diameter maximum</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Raymond-Roy occlusion classification</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Neurology. 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callnumber-first	R - Medicine
author	Tao He
spellingShingle	Tao He misc RC346-429 misc intracranial aneurysm misc coil embolization misc recurrence misc predictive model misc diameter maximum misc Raymond-Roy occlusion classification misc Neurology. Diseases of the nervous system A predictive model for the recurrence of intracranial aneurysms following coil embolization
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topic_title	RC346-429 A predictive model for the recurrence of intracranial aneurysms following coil embolization intracranial aneurysm coil embolization recurrence predictive model diameter maximum Raymond-Roy occlusion classification
topic	misc RC346-429 misc intracranial aneurysm misc coil embolization misc recurrence misc predictive model misc diameter maximum misc Raymond-Roy occlusion classification misc Neurology. Diseases of the nervous system
topic_unstemmed	misc RC346-429 misc intracranial aneurysm misc coil embolization misc recurrence misc predictive model misc diameter maximum misc Raymond-Roy occlusion classification misc Neurology. Diseases of the nervous system
topic_browse	misc RC346-429 misc intracranial aneurysm misc coil embolization misc recurrence misc predictive model misc diameter maximum misc Raymond-Roy occlusion classification misc Neurology. Diseases of the nervous system
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title	A predictive model for the recurrence of intracranial aneurysms following coil embolization
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title_full	A predictive model for the recurrence of intracranial aneurysms following coil embolization
author_sort	Tao He
journal	Frontiers in Neurology
journalStr	Frontiers in Neurology
callnumber-first-code	R
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author_browse	Tao He Kun Chen Ru-Dong Chen
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class	RC346-429
format_se	Elektronische Aufsätze
author-letter	Tao He
doi_str_mv	10.3389/fneur.2023.1248603
author2-role	verfasserin
title_sort	predictive model for the recurrence of intracranial aneurysms following coil embolization
callnumber	RC346-429
title_auth	A predictive model for the recurrence of intracranial aneurysms following coil embolization
abstract	ObjectiveThis study aimed to identify risk factors for intracranial aneurysms (IAs) recurrence and establish a predictive model to aid evaluation.MethodsA total of 302 patients with 312 IAs undergoing coil embolization between September 2017 and October 2022 were divided into two groups based on digital subtraction angiography follow-up. Clinical characteristics, operation-related factors, and morphologies were measured. Cox proportional hazard regression was used to identify the risk factors. Hazard ratios (HRs) were used to score points, and a predictive model was established. The test cohorts consisted of 51 IAs. Receiver operating characteristic curves were generated to determine the cutoff values and area under the curves (AUCs). A Delong test was performed to compare the AUCs.ResultsDiameter maximum (D max) (p < 0.001, HR = 1.221), Raymond-Roy occlusion classification (RROC) II or III (p = 0.004, HR = 2.852), and ruptured status (p < 0.001, HR = 7.782) were independent risk factors for the recurrence of IAs. A predictive model was established: D max + 2 * RROC (II or III; yes = 1, no = 0) + 6 * ruptured status (yes = 1; no = 0). The AUC of the predictive model (0.818) was significantly higher than those of D max (0.704), RROC (II or III) (0.645), and rupture status (0.683), respectively (Delong test, p < 0.05). The cutoff values of the predictive model and D max were 9.75 points and 6.65 mm, respectively.ConclusionThe D max, RROC (II or III), and ruptured status could independently predict the recurrence of IAs after coil embolization. Our model could aid in practical evaluations.
abstractGer	ObjectiveThis study aimed to identify risk factors for intracranial aneurysms (IAs) recurrence and establish a predictive model to aid evaluation.MethodsA total of 302 patients with 312 IAs undergoing coil embolization between September 2017 and October 2022 were divided into two groups based on digital subtraction angiography follow-up. Clinical characteristics, operation-related factors, and morphologies were measured. Cox proportional hazard regression was used to identify the risk factors. Hazard ratios (HRs) were used to score points, and a predictive model was established. The test cohorts consisted of 51 IAs. Receiver operating characteristic curves were generated to determine the cutoff values and area under the curves (AUCs). A Delong test was performed to compare the AUCs.ResultsDiameter maximum (D max) (p < 0.001, HR = 1.221), Raymond-Roy occlusion classification (RROC) II or III (p = 0.004, HR = 2.852), and ruptured status (p < 0.001, HR = 7.782) were independent risk factors for the recurrence of IAs. A predictive model was established: D max + 2 * RROC (II or III; yes = 1, no = 0) + 6 * ruptured status (yes = 1; no = 0). The AUC of the predictive model (0.818) was significantly higher than those of D max (0.704), RROC (II or III) (0.645), and rupture status (0.683), respectively (Delong test, p < 0.05). The cutoff values of the predictive model and D max were 9.75 points and 6.65 mm, respectively.ConclusionThe D max, RROC (II or III), and ruptured status could independently predict the recurrence of IAs after coil embolization. Our model could aid in practical evaluations.
abstract_unstemmed	ObjectiveThis study aimed to identify risk factors for intracranial aneurysms (IAs) recurrence and establish a predictive model to aid evaluation.MethodsA total of 302 patients with 312 IAs undergoing coil embolization between September 2017 and October 2022 were divided into two groups based on digital subtraction angiography follow-up. Clinical characteristics, operation-related factors, and morphologies were measured. Cox proportional hazard regression was used to identify the risk factors. Hazard ratios (HRs) were used to score points, and a predictive model was established. The test cohorts consisted of 51 IAs. Receiver operating characteristic curves were generated to determine the cutoff values and area under the curves (AUCs). A Delong test was performed to compare the AUCs.ResultsDiameter maximum (D max) (p < 0.001, HR = 1.221), Raymond-Roy occlusion classification (RROC) II or III (p = 0.004, HR = 2.852), and ruptured status (p < 0.001, HR = 7.782) were independent risk factors for the recurrence of IAs. A predictive model was established: D max + 2 * RROC (II or III; yes = 1, no = 0) + 6 * ruptured status (yes = 1; no = 0). The AUC of the predictive model (0.818) was significantly higher than those of D max (0.704), RROC (II or III) (0.645), and rupture status (0.683), respectively (Delong test, p < 0.05). The cutoff values of the predictive model and D max were 9.75 points and 6.65 mm, respectively.ConclusionThe D max, RROC (II or III), and ruptured status could independently predict the recurrence of IAs after coil embolization. Our model could aid in practical evaluations.
collection_details	GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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_2014 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
title_short	A predictive model for the recurrence of intracranial aneurysms following coil embolization
url	https://doi.org/10.3389/fneur.2023.1248603 https://doaj.org/article/29578280cc3e45bbad6bb989dfa816ae https://www.frontiersin.org/articles/10.3389/fneur.2023.1248603/full https://doaj.org/toc/1664-2295
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author2	Tao He Kun Chen Ru-Dong Chen
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doi_str	10.3389/fneur.2023.1248603
callnumber-a	RC346-429
up_date	2024-07-03T18:20:31.526Z
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The AUC of the predictive model (0.818) was significantly higher than those of D max (0.704), RROC (II or III) (0.645), and rupture status (0.683), respectively (Delong test, p &lt; 0.05). The cutoff values of the predictive model and D max were 9.75 points and 6.65 mm, respectively.ConclusionThe D max, RROC (II or III), and ruptured status could independently predict the recurrence of IAs after coil embolization. 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A predictive model for the recurrence of intracranial aneurysms following coil embolization

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