Prognostic value of cerebral infarction coefficient in patients with massive cerebral infarction
Objective: We proposed the concept of the cerebral infarction coefficient, which is cerebral infarction volume/brain volume. This study aimed to evaluate the prognostic value of the cerebral infarction coefficient in patients with massive cerebral infarction (MCI).Methods: According to the modified...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Du, Xiaoyan [verfasserIn] Liu, Qingjun [verfasserIn] Li, Qi [verfasserIn] Yang, Zhao [verfasserIn] Liao, Juan [verfasserIn] Gong, Hongmin [verfasserIn] Wu, Lin [verfasserIn] Wei, Jing [verfasserIn] Tan, Qing [verfasserIn] Du, Hongheng [verfasserIn] Zhao, Rui [verfasserIn] Zhao, Libo [verfasserIn] |
|---|
| Format: |
E-Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2020 |
|---|
| Schlagwörter: |
|---|
| Übergeordnetes Werk: |
Enthalten in: Clinical neurology and neurosurgery - Amsterdam [u.a.] : Elsevier Science, 1974, 196 |
|---|---|
| Übergeordnetes Werk: |
volume:196 |
| DOI / URN: |
10.1016/j.clineuro.2020.106009 |
|---|
| Katalog-ID: |
ELV00466891X |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | ELV00466891X | ||
| 003 | DE-627 | ||
| 005 | 20230524162122.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 230503s2020 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1016/j.clineuro.2020.106009 |2 doi | |
| 035 | |a (DE-627)ELV00466891X | ||
| 035 | |a (ELSEVIER)S0303-8467(20)30352-8 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rda | ||
| 041 | |a eng | ||
| 082 | 0 | 4 | |a 610 |q DE-600 |
| 084 | |a 44.90 |2 bkl | ||
| 084 | |a 44.65 |2 bkl | ||
| 100 | 1 | |a Du, Xiaoyan |e verfasserin |0 (orcid)0000-0002-8474-946X |4 aut | |
| 245 | 1 | 0 | |a Prognostic value of cerebral infarction coefficient in patients with massive cerebral infarction |
| 264 | 1 | |c 2020 | |
| 336 | |a nicht spezifiziert |b zzz |2 rdacontent | ||
| 337 | |a Computermedien |b c |2 rdamedia | ||
| 338 | |a Online-Ressource |b cr |2 rdacarrier | ||
| 520 | |a Objective: We proposed the concept of the cerebral infarction coefficient, which is cerebral infarction volume/brain volume. This study aimed to evaluate the prognostic value of the cerebral infarction coefficient in patients with massive cerebral infarction (MCI).Methods: According to the modified Rankin score, 71 patients with acute MCI were divided into good prognosis and poor prognosis groups. Clinical and imaging data of the two groups were collected and univariate analysis was carried out. If there were significant differences in the data between the two groups, binary logistic regression analysis was performed.Results: The poor prognosis group had a significantly higher cerebral infarction volume, cerebral infarction coefficient, and D-dimer levels, older age, the highest body temperature, a higher rate of a history of atrial fibrillation, and a lower rate of a history of hypertension compared with the good prognosis group (all P < 0.05). Binary logistic regression analysis showed that the cerebral infarction coefficient was an independent risk factor for a poor prognosis of patients with MCI (P < 0.05, 95 % confidence interval, 2.091, 42.562), and the odds ratio was 8.506. The area under the receiver operating characteristic curve for the cerebral infarction coefficient was 0.753. When the cut-off value was 7.8 %, the sensitivity of predicting a poor prognosis of patients with MCI was 92.5 %.Conclusion: The cerebral infarction coefficient may have predictive value in determining the prognosis of patients with MCI. | ||
| 650 | 4 | |a Massive cerebral infarction | |
| 650 | 4 | |a Cerebral infarction volume | |
| 650 | 4 | |a Cerebral infarction coefficient | |
| 650 | 4 | |a Outcome | |
| 650 | 4 | |a Predictive value | |
| 700 | 1 | |a Liu, Qingjun |e verfasserin |4 aut | |
| 700 | 1 | |a Li, Qi |e verfasserin |4 aut | |
| 700 | 1 | |a Yang, Zhao |e verfasserin |4 aut | |
| 700 | 1 | |a Liao, Juan |e verfasserin |4 aut | |
| 700 | 1 | |a Gong, Hongmin |e verfasserin |4 aut | |
| 700 | 1 | |a Wu, Lin |e verfasserin |4 aut | |
| 700 | 1 | |a Wei, Jing |e verfasserin |4 aut | |
| 700 | 1 | |a Tan, Qing |e verfasserin |4 aut | |
| 700 | 1 | |a Du, Hongheng |e verfasserin |4 aut | |
| 700 | 1 | |a Zhao, Rui |e verfasserin |4 aut | |
| 700 | 1 | |a Zhao, Libo |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Clinical neurology and neurosurgery |d Amsterdam [u.a.] : Elsevier Science, 1974 |g 196 |h Online-Ressource |w (DE-627)320438236 |w (DE-600)2004613-3 |w (DE-576)261862197 |x 1872-6968 |7 nnns |
| 773 | 1 | 8 | |g volume:196 |
| 912 | |a GBV_USEFLAG_U | ||
| 912 | |a SYSFLAG_U | ||
| 912 | |a GBV_ELV | ||
| 912 | |a SSG-OLC-PHA | ||
| 912 | |a GBV_ILN_20 | ||
| 912 | |a GBV_ILN_22 | ||
| 912 | |a GBV_ILN_23 | ||
| 912 | |a GBV_ILN_24 | ||
| 912 | |a GBV_ILN_31 | ||
| 912 | |a GBV_ILN_32 | ||
| 912 | |a GBV_ILN_40 | ||
| 912 | |a GBV_ILN_60 | ||
| 912 | |a GBV_ILN_62 | ||
| 912 | |a GBV_ILN_63 | ||
| 912 | |a GBV_ILN_65 | ||
| 912 | |a GBV_ILN_69 | ||
| 912 | |a GBV_ILN_70 | ||
| 912 | |a GBV_ILN_73 | ||
| 912 | |a GBV_ILN_74 | ||
| 912 | |a GBV_ILN_90 | ||
| 912 | |a GBV_ILN_95 | ||
| 912 | |a GBV_ILN_100 | ||
| 912 | |a GBV_ILN_101 | ||
| 912 | |a GBV_ILN_105 | ||
| 912 | |a GBV_ILN_110 | ||
| 912 | |a GBV_ILN_151 | ||
| 912 | |a GBV_ILN_224 | ||
| 912 | |a GBV_ILN_370 | ||
| 912 | |a GBV_ILN_602 | ||
| 912 | |a GBV_ILN_702 | ||
| 912 | |a GBV_ILN_2003 | ||
| 912 | |a GBV_ILN_2004 | ||
| 912 | |a GBV_ILN_2005 | ||
| 912 | |a GBV_ILN_2011 | ||
| 912 | |a GBV_ILN_2014 | ||
| 912 | |a GBV_ILN_2015 | ||
| 912 | |a GBV_ILN_2020 | ||
| 912 | |a GBV_ILN_2021 | ||
| 912 | |a GBV_ILN_2025 | ||
| 912 | |a GBV_ILN_2027 | ||
| 912 | |a GBV_ILN_2034 | ||
| 912 | |a GBV_ILN_2038 | ||
| 912 | |a GBV_ILN_2044 | ||
| 912 | |a GBV_ILN_2048 | ||
| 912 | |a GBV_ILN_2049 | ||
| 912 | |a GBV_ILN_2050 | ||
| 912 | |a GBV_ILN_2056 | ||
| 912 | |a GBV_ILN_2059 | ||
| 912 | |a GBV_ILN_2061 | ||
| 912 | |a GBV_ILN_2064 | ||
| 912 | |a GBV_ILN_2065 | ||
| 912 | |a GBV_ILN_2068 | ||
| 912 | |a GBV_ILN_2111 | ||
| 912 | |a GBV_ILN_2112 | ||
| 912 | |a GBV_ILN_2113 | ||
| 912 | |a GBV_ILN_2118 | ||
| 912 | |a GBV_ILN_2122 | ||
| 912 | |a GBV_ILN_2129 | ||
| 912 | |a GBV_ILN_2143 | ||
| 912 | |a GBV_ILN_2147 | ||
| 912 | |a GBV_ILN_2148 | ||
| 912 | |a GBV_ILN_2152 | ||
| 912 | |a GBV_ILN_2153 | ||
| 912 | |a GBV_ILN_2190 | ||
| 912 | |a GBV_ILN_2336 | ||
| 912 | |a GBV_ILN_2507 | ||
| 912 | |a GBV_ILN_2522 | ||
| 912 | |a GBV_ILN_4035 | ||
| 912 | |a GBV_ILN_4037 | ||
| 912 | |a GBV_ILN_4112 | ||
| 912 | |a GBV_ILN_4125 | ||
| 912 | |a GBV_ILN_4126 | ||
| 912 | |a GBV_ILN_4242 | ||
| 912 | |a GBV_ILN_4251 | ||
| 912 | |a GBV_ILN_4305 | ||
| 912 | |a GBV_ILN_4313 | ||
| 912 | |a GBV_ILN_4323 | ||
| 912 | |a GBV_ILN_4324 | ||
| 912 | |a GBV_ILN_4325 | ||
| 912 | |a GBV_ILN_4326 | ||
| 912 | |a GBV_ILN_4333 | ||
| 912 | |a GBV_ILN_4334 | ||
| 912 | |a GBV_ILN_4335 | ||
| 912 | |a GBV_ILN_4338 | ||
| 912 | |a GBV_ILN_4393 | ||
| 936 | b | k | |a 44.90 |j Neurologie |
| 936 | b | k | |a 44.65 |j Chirurgie |
| 951 | |a AR | ||
| 952 | |d 196 | ||
| author_variant |
x d xd q l ql q l ql z y zy j l jl h g hg l w lw j w jw q t qt h d hd r z rz l z lz |
|---|---|
| matchkey_str |
article:18726968:2020----::rgotcauocrbaifrtocefcetnainsiha |
| hierarchy_sort_str |
2020 |
| bklnumber |
44.90 44.65 |
| publishDate |
2020 |
| allfields |
10.1016/j.clineuro.2020.106009 doi (DE-627)ELV00466891X (ELSEVIER)S0303-8467(20)30352-8 DE-627 ger DE-627 rda eng 610 DE-600 44.90 bkl 44.65 bkl Du, Xiaoyan verfasserin (orcid)0000-0002-8474-946X aut Prognostic value of cerebral infarction coefficient in patients with massive cerebral infarction 2020 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Objective: We proposed the concept of the cerebral infarction coefficient, which is cerebral infarction volume/brain volume. This study aimed to evaluate the prognostic value of the cerebral infarction coefficient in patients with massive cerebral infarction (MCI).Methods: According to the modified Rankin score, 71 patients with acute MCI were divided into good prognosis and poor prognosis groups. Clinical and imaging data of the two groups were collected and univariate analysis was carried out. If there were significant differences in the data between the two groups, binary logistic regression analysis was performed.Results: The poor prognosis group had a significantly higher cerebral infarction volume, cerebral infarction coefficient, and D-dimer levels, older age, the highest body temperature, a higher rate of a history of atrial fibrillation, and a lower rate of a history of hypertension compared with the good prognosis group (all P < 0.05). Binary logistic regression analysis showed that the cerebral infarction coefficient was an independent risk factor for a poor prognosis of patients with MCI (P < 0.05, 95 % confidence interval, 2.091, 42.562), and the odds ratio was 8.506. The area under the receiver operating characteristic curve for the cerebral infarction coefficient was 0.753. When the cut-off value was 7.8 %, the sensitivity of predicting a poor prognosis of patients with MCI was 92.5 %.Conclusion: The cerebral infarction coefficient may have predictive value in determining the prognosis of patients with MCI. Massive cerebral infarction Cerebral infarction volume Cerebral infarction coefficient Outcome Predictive value Liu, Qingjun verfasserin aut Li, Qi verfasserin aut Yang, Zhao verfasserin aut Liao, Juan verfasserin aut Gong, Hongmin verfasserin aut Wu, Lin verfasserin aut Wei, Jing verfasserin aut Tan, Qing verfasserin aut Du, Hongheng verfasserin aut Zhao, Rui verfasserin aut Zhao, Libo verfasserin aut Enthalten in Clinical neurology and neurosurgery Amsterdam [u.a.] : Elsevier Science, 1974 196 Online-Ressource (DE-627)320438236 (DE-600)2004613-3 (DE-576)261862197 1872-6968 nnns volume:196 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 44.90 Neurologie 44.65 Chirurgie AR 196 |
| spelling |
10.1016/j.clineuro.2020.106009 doi (DE-627)ELV00466891X (ELSEVIER)S0303-8467(20)30352-8 DE-627 ger DE-627 rda eng 610 DE-600 44.90 bkl 44.65 bkl Du, Xiaoyan verfasserin (orcid)0000-0002-8474-946X aut Prognostic value of cerebral infarction coefficient in patients with massive cerebral infarction 2020 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Objective: We proposed the concept of the cerebral infarction coefficient, which is cerebral infarction volume/brain volume. This study aimed to evaluate the prognostic value of the cerebral infarction coefficient in patients with massive cerebral infarction (MCI).Methods: According to the modified Rankin score, 71 patients with acute MCI were divided into good prognosis and poor prognosis groups. Clinical and imaging data of the two groups were collected and univariate analysis was carried out. If there were significant differences in the data between the two groups, binary logistic regression analysis was performed.Results: The poor prognosis group had a significantly higher cerebral infarction volume, cerebral infarction coefficient, and D-dimer levels, older age, the highest body temperature, a higher rate of a history of atrial fibrillation, and a lower rate of a history of hypertension compared with the good prognosis group (all P < 0.05). Binary logistic regression analysis showed that the cerebral infarction coefficient was an independent risk factor for a poor prognosis of patients with MCI (P < 0.05, 95 % confidence interval, 2.091, 42.562), and the odds ratio was 8.506. The area under the receiver operating characteristic curve for the cerebral infarction coefficient was 0.753. When the cut-off value was 7.8 %, the sensitivity of predicting a poor prognosis of patients with MCI was 92.5 %.Conclusion: The cerebral infarction coefficient may have predictive value in determining the prognosis of patients with MCI. Massive cerebral infarction Cerebral infarction volume Cerebral infarction coefficient Outcome Predictive value Liu, Qingjun verfasserin aut Li, Qi verfasserin aut Yang, Zhao verfasserin aut Liao, Juan verfasserin aut Gong, Hongmin verfasserin aut Wu, Lin verfasserin aut Wei, Jing verfasserin aut Tan, Qing verfasserin aut Du, Hongheng verfasserin aut Zhao, Rui verfasserin aut Zhao, Libo verfasserin aut Enthalten in Clinical neurology and neurosurgery Amsterdam [u.a.] : Elsevier Science, 1974 196 Online-Ressource (DE-627)320438236 (DE-600)2004613-3 (DE-576)261862197 1872-6968 nnns volume:196 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 44.90 Neurologie 44.65 Chirurgie AR 196 |
| allfields_unstemmed |
10.1016/j.clineuro.2020.106009 doi (DE-627)ELV00466891X (ELSEVIER)S0303-8467(20)30352-8 DE-627 ger DE-627 rda eng 610 DE-600 44.90 bkl 44.65 bkl Du, Xiaoyan verfasserin (orcid)0000-0002-8474-946X aut Prognostic value of cerebral infarction coefficient in patients with massive cerebral infarction 2020 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Objective: We proposed the concept of the cerebral infarction coefficient, which is cerebral infarction volume/brain volume. This study aimed to evaluate the prognostic value of the cerebral infarction coefficient in patients with massive cerebral infarction (MCI).Methods: According to the modified Rankin score, 71 patients with acute MCI were divided into good prognosis and poor prognosis groups. Clinical and imaging data of the two groups were collected and univariate analysis was carried out. If there were significant differences in the data between the two groups, binary logistic regression analysis was performed.Results: The poor prognosis group had a significantly higher cerebral infarction volume, cerebral infarction coefficient, and D-dimer levels, older age, the highest body temperature, a higher rate of a history of atrial fibrillation, and a lower rate of a history of hypertension compared with the good prognosis group (all P < 0.05). Binary logistic regression analysis showed that the cerebral infarction coefficient was an independent risk factor for a poor prognosis of patients with MCI (P < 0.05, 95 % confidence interval, 2.091, 42.562), and the odds ratio was 8.506. The area under the receiver operating characteristic curve for the cerebral infarction coefficient was 0.753. When the cut-off value was 7.8 %, the sensitivity of predicting a poor prognosis of patients with MCI was 92.5 %.Conclusion: The cerebral infarction coefficient may have predictive value in determining the prognosis of patients with MCI. Massive cerebral infarction Cerebral infarction volume Cerebral infarction coefficient Outcome Predictive value Liu, Qingjun verfasserin aut Li, Qi verfasserin aut Yang, Zhao verfasserin aut Liao, Juan verfasserin aut Gong, Hongmin verfasserin aut Wu, Lin verfasserin aut Wei, Jing verfasserin aut Tan, Qing verfasserin aut Du, Hongheng verfasserin aut Zhao, Rui verfasserin aut Zhao, Libo verfasserin aut Enthalten in Clinical neurology and neurosurgery Amsterdam [u.a.] : Elsevier Science, 1974 196 Online-Ressource (DE-627)320438236 (DE-600)2004613-3 (DE-576)261862197 1872-6968 nnns volume:196 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 44.90 Neurologie 44.65 Chirurgie AR 196 |
| allfieldsGer |
10.1016/j.clineuro.2020.106009 doi (DE-627)ELV00466891X (ELSEVIER)S0303-8467(20)30352-8 DE-627 ger DE-627 rda eng 610 DE-600 44.90 bkl 44.65 bkl Du, Xiaoyan verfasserin (orcid)0000-0002-8474-946X aut Prognostic value of cerebral infarction coefficient in patients with massive cerebral infarction 2020 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Objective: We proposed the concept of the cerebral infarction coefficient, which is cerebral infarction volume/brain volume. This study aimed to evaluate the prognostic value of the cerebral infarction coefficient in patients with massive cerebral infarction (MCI).Methods: According to the modified Rankin score, 71 patients with acute MCI were divided into good prognosis and poor prognosis groups. Clinical and imaging data of the two groups were collected and univariate analysis was carried out. If there were significant differences in the data between the two groups, binary logistic regression analysis was performed.Results: The poor prognosis group had a significantly higher cerebral infarction volume, cerebral infarction coefficient, and D-dimer levels, older age, the highest body temperature, a higher rate of a history of atrial fibrillation, and a lower rate of a history of hypertension compared with the good prognosis group (all P < 0.05). Binary logistic regression analysis showed that the cerebral infarction coefficient was an independent risk factor for a poor prognosis of patients with MCI (P < 0.05, 95 % confidence interval, 2.091, 42.562), and the odds ratio was 8.506. The area under the receiver operating characteristic curve for the cerebral infarction coefficient was 0.753. When the cut-off value was 7.8 %, the sensitivity of predicting a poor prognosis of patients with MCI was 92.5 %.Conclusion: The cerebral infarction coefficient may have predictive value in determining the prognosis of patients with MCI. Massive cerebral infarction Cerebral infarction volume Cerebral infarction coefficient Outcome Predictive value Liu, Qingjun verfasserin aut Li, Qi verfasserin aut Yang, Zhao verfasserin aut Liao, Juan verfasserin aut Gong, Hongmin verfasserin aut Wu, Lin verfasserin aut Wei, Jing verfasserin aut Tan, Qing verfasserin aut Du, Hongheng verfasserin aut Zhao, Rui verfasserin aut Zhao, Libo verfasserin aut Enthalten in Clinical neurology and neurosurgery Amsterdam [u.a.] : Elsevier Science, 1974 196 Online-Ressource (DE-627)320438236 (DE-600)2004613-3 (DE-576)261862197 1872-6968 nnns volume:196 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 44.90 Neurologie 44.65 Chirurgie AR 196 |
| allfieldsSound |
10.1016/j.clineuro.2020.106009 doi (DE-627)ELV00466891X (ELSEVIER)S0303-8467(20)30352-8 DE-627 ger DE-627 rda eng 610 DE-600 44.90 bkl 44.65 bkl Du, Xiaoyan verfasserin (orcid)0000-0002-8474-946X aut Prognostic value of cerebral infarction coefficient in patients with massive cerebral infarction 2020 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Objective: We proposed the concept of the cerebral infarction coefficient, which is cerebral infarction volume/brain volume. This study aimed to evaluate the prognostic value of the cerebral infarction coefficient in patients with massive cerebral infarction (MCI).Methods: According to the modified Rankin score, 71 patients with acute MCI were divided into good prognosis and poor prognosis groups. Clinical and imaging data of the two groups were collected and univariate analysis was carried out. If there were significant differences in the data between the two groups, binary logistic regression analysis was performed.Results: The poor prognosis group had a significantly higher cerebral infarction volume, cerebral infarction coefficient, and D-dimer levels, older age, the highest body temperature, a higher rate of a history of atrial fibrillation, and a lower rate of a history of hypertension compared with the good prognosis group (all P < 0.05). Binary logistic regression analysis showed that the cerebral infarction coefficient was an independent risk factor for a poor prognosis of patients with MCI (P < 0.05, 95 % confidence interval, 2.091, 42.562), and the odds ratio was 8.506. The area under the receiver operating characteristic curve for the cerebral infarction coefficient was 0.753. When the cut-off value was 7.8 %, the sensitivity of predicting a poor prognosis of patients with MCI was 92.5 %.Conclusion: The cerebral infarction coefficient may have predictive value in determining the prognosis of patients with MCI. Massive cerebral infarction Cerebral infarction volume Cerebral infarction coefficient Outcome Predictive value Liu, Qingjun verfasserin aut Li, Qi verfasserin aut Yang, Zhao verfasserin aut Liao, Juan verfasserin aut Gong, Hongmin verfasserin aut Wu, Lin verfasserin aut Wei, Jing verfasserin aut Tan, Qing verfasserin aut Du, Hongheng verfasserin aut Zhao, Rui verfasserin aut Zhao, Libo verfasserin aut Enthalten in Clinical neurology and neurosurgery Amsterdam [u.a.] : Elsevier Science, 1974 196 Online-Ressource (DE-627)320438236 (DE-600)2004613-3 (DE-576)261862197 1872-6968 nnns volume:196 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 44.90 Neurologie 44.65 Chirurgie AR 196 |
| language |
English |
| source |
Enthalten in Clinical neurology and neurosurgery 196 volume:196 |
| sourceStr |
Enthalten in Clinical neurology and neurosurgery 196 volume:196 |
| format_phy_str_mv |
Article |
| bklname |
Neurologie Chirurgie |
| institution |
findex.gbv.de |
| topic_facet |
Massive cerebral infarction Cerebral infarction volume Cerebral infarction coefficient Outcome Predictive value |
| dewey-raw |
610 |
| isfreeaccess_bool |
false |
| container_title |
Clinical neurology and neurosurgery |
| authorswithroles_txt_mv |
Du, Xiaoyan @@aut@@ Liu, Qingjun @@aut@@ Li, Qi @@aut@@ Yang, Zhao @@aut@@ Liao, Juan @@aut@@ Gong, Hongmin @@aut@@ Wu, Lin @@aut@@ Wei, Jing @@aut@@ Tan, Qing @@aut@@ Du, Hongheng @@aut@@ Zhao, Rui @@aut@@ Zhao, Libo @@aut@@ |
| publishDateDaySort_date |
2020-01-01T00:00:00Z |
| hierarchy_top_id |
320438236 |
| dewey-sort |
3610 |
| id |
ELV00466891X |
| language_de |
englisch |
| fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV00466891X</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230524162122.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230503s2020 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.clineuro.2020.106009</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV00466891X</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0303-8467(20)30352-8</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">rda</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">610</subfield><subfield code="q">DE-600</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">44.90</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">44.65</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Du, Xiaoyan</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(orcid)0000-0002-8474-946X</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Prognostic value of cerebral infarction coefficient in patients with massive cerebral infarction</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2020</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</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="520" ind1=" " ind2=" "><subfield code="a">Objective: We proposed the concept of the cerebral infarction coefficient, which is cerebral infarction volume/brain volume. This study aimed to evaluate the prognostic value of the cerebral infarction coefficient in patients with massive cerebral infarction (MCI).Methods: According to the modified Rankin score, 71 patients with acute MCI were divided into good prognosis and poor prognosis groups. Clinical and imaging data of the two groups were collected and univariate analysis was carried out. If there were significant differences in the data between the two groups, binary logistic regression analysis was performed.Results: The poor prognosis group had a significantly higher cerebral infarction volume, cerebral infarction coefficient, and D-dimer levels, older age, the highest body temperature, a higher rate of a history of atrial fibrillation, and a lower rate of a history of hypertension compared with the good prognosis group (all P < 0.05). Binary logistic regression analysis showed that the cerebral infarction coefficient was an independent risk factor for a poor prognosis of patients with MCI (P < 0.05, 95 % confidence interval, 2.091, 42.562), and the odds ratio was 8.506. The area under the receiver operating characteristic curve for the cerebral infarction coefficient was 0.753. When the cut-off value was 7.8 %, the sensitivity of predicting a poor prognosis of patients with MCI was 92.5 %.Conclusion: The cerebral infarction coefficient may have predictive value in determining the prognosis of patients with MCI.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Massive cerebral infarction</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Cerebral infarction volume</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Cerebral infarction coefficient</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Outcome</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Predictive value</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Liu, Qingjun</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Li, Qi</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Yang, Zhao</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Liao, Juan</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Gong, Hongmin</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Wu, Lin</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Wei, Jing</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Tan, Qing</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Du, Hongheng</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Zhao, Rui</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Zhao, Libo</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Clinical neurology and neurosurgery</subfield><subfield code="d">Amsterdam [u.a.] : Elsevier Science, 1974</subfield><subfield code="g">196</subfield><subfield code="h">Online-Ressource</subfield><subfield code="w">(DE-627)320438236</subfield><subfield code="w">(DE-600)2004613-3</subfield><subfield code="w">(DE-576)261862197</subfield><subfield code="x">1872-6968</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:196</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_31</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_32</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_74</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_90</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_100</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_101</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_224</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_370</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_702</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2003</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2004</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2005</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2011</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2015</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2020</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2021</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2025</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2027</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2034</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2038</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2044</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2048</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2049</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2050</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2056</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2059</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2061</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2064</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2065</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2068</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2111</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2113</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2118</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2122</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2129</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2143</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2147</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2148</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2152</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2153</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2190</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2336</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2507</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2522</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4035</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4242</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4251</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4326</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4333</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4334</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4335</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4393</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">44.90</subfield><subfield code="j">Neurologie</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">44.65</subfield><subfield code="j">Chirurgie</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">196</subfield></datafield></record></collection>
|
| author |
Du, Xiaoyan |
| spellingShingle |
Du, Xiaoyan ddc 610 bkl 44.90 bkl 44.65 misc Massive cerebral infarction misc Cerebral infarction volume misc Cerebral infarction coefficient misc Outcome misc Predictive value Prognostic value of cerebral infarction coefficient in patients with massive cerebral infarction |
| authorStr |
Du, Xiaoyan |
| ppnlink_with_tag_str_mv |
@@773@@(DE-627)320438236 |
| format |
electronic Article |
| dewey-ones |
610 - Medicine & health |
| delete_txt_mv |
keep |
| author_role |
aut aut aut aut aut aut aut aut aut aut aut aut |
| collection |
elsevier |
| remote_str |
true |
| illustrated |
Not Illustrated |
| issn |
1872-6968 |
| topic_title |
610 DE-600 44.90 bkl 44.65 bkl Prognostic value of cerebral infarction coefficient in patients with massive cerebral infarction Massive cerebral infarction Cerebral infarction volume Cerebral infarction coefficient Outcome Predictive value |
| topic |
ddc 610 bkl 44.90 bkl 44.65 misc Massive cerebral infarction misc Cerebral infarction volume misc Cerebral infarction coefficient misc Outcome misc Predictive value |
| topic_unstemmed |
ddc 610 bkl 44.90 bkl 44.65 misc Massive cerebral infarction misc Cerebral infarction volume misc Cerebral infarction coefficient misc Outcome misc Predictive value |
| topic_browse |
ddc 610 bkl 44.90 bkl 44.65 misc Massive cerebral infarction misc Cerebral infarction volume misc Cerebral infarction coefficient misc Outcome misc Predictive value |
| format_facet |
Elektronische Aufsätze Aufsätze Elektronische Ressource |
| format_main_str_mv |
Text Zeitschrift/Artikel |
| carriertype_str_mv |
cr |
| hierarchy_parent_title |
Clinical neurology and neurosurgery |
| hierarchy_parent_id |
320438236 |
| dewey-tens |
610 - Medicine & health |
| hierarchy_top_title |
Clinical neurology and neurosurgery |
| isfreeaccess_txt |
false |
| familylinks_str_mv |
(DE-627)320438236 (DE-600)2004613-3 (DE-576)261862197 |
| title |
Prognostic value of cerebral infarction coefficient in patients with massive cerebral infarction |
| ctrlnum |
(DE-627)ELV00466891X (ELSEVIER)S0303-8467(20)30352-8 |
| title_full |
Prognostic value of cerebral infarction coefficient in patients with massive cerebral infarction |
| author_sort |
Du, Xiaoyan |
| journal |
Clinical neurology and neurosurgery |
| journalStr |
Clinical neurology and neurosurgery |
| lang_code |
eng |
| isOA_bool |
false |
| dewey-hundreds |
600 - Technology |
| recordtype |
marc |
| publishDateSort |
2020 |
| contenttype_str_mv |
zzz |
| author_browse |
Du, Xiaoyan Liu, Qingjun Li, Qi Yang, Zhao Liao, Juan Gong, Hongmin Wu, Lin Wei, Jing Tan, Qing Du, Hongheng Zhao, Rui Zhao, Libo |
| container_volume |
196 |
| class |
610 DE-600 44.90 bkl 44.65 bkl |
| format_se |
Elektronische Aufsätze |
| author-letter |
Du, Xiaoyan |
| doi_str_mv |
10.1016/j.clineuro.2020.106009 |
| normlink |
(ORCID)0000-0002-8474-946X |
| normlink_prefix_str_mv |
(orcid)0000-0002-8474-946X |
| dewey-full |
610 |
| author2-role |
verfasserin |
| title_sort |
prognostic value of cerebral infarction coefficient in patients with massive cerebral infarction |
| title_auth |
Prognostic value of cerebral infarction coefficient in patients with massive cerebral infarction |
| abstract |
Objective: We proposed the concept of the cerebral infarction coefficient, which is cerebral infarction volume/brain volume. This study aimed to evaluate the prognostic value of the cerebral infarction coefficient in patients with massive cerebral infarction (MCI).Methods: According to the modified Rankin score, 71 patients with acute MCI were divided into good prognosis and poor prognosis groups. Clinical and imaging data of the two groups were collected and univariate analysis was carried out. If there were significant differences in the data between the two groups, binary logistic regression analysis was performed.Results: The poor prognosis group had a significantly higher cerebral infarction volume, cerebral infarction coefficient, and D-dimer levels, older age, the highest body temperature, a higher rate of a history of atrial fibrillation, and a lower rate of a history of hypertension compared with the good prognosis group (all P < 0.05). Binary logistic regression analysis showed that the cerebral infarction coefficient was an independent risk factor for a poor prognosis of patients with MCI (P < 0.05, 95 % confidence interval, 2.091, 42.562), and the odds ratio was 8.506. The area under the receiver operating characteristic curve for the cerebral infarction coefficient was 0.753. When the cut-off value was 7.8 %, the sensitivity of predicting a poor prognosis of patients with MCI was 92.5 %.Conclusion: The cerebral infarction coefficient may have predictive value in determining the prognosis of patients with MCI. |
| abstractGer |
Objective: We proposed the concept of the cerebral infarction coefficient, which is cerebral infarction volume/brain volume. This study aimed to evaluate the prognostic value of the cerebral infarction coefficient in patients with massive cerebral infarction (MCI).Methods: According to the modified Rankin score, 71 patients with acute MCI were divided into good prognosis and poor prognosis groups. Clinical and imaging data of the two groups were collected and univariate analysis was carried out. If there were significant differences in the data between the two groups, binary logistic regression analysis was performed.Results: The poor prognosis group had a significantly higher cerebral infarction volume, cerebral infarction coefficient, and D-dimer levels, older age, the highest body temperature, a higher rate of a history of atrial fibrillation, and a lower rate of a history of hypertension compared with the good prognosis group (all P < 0.05). Binary logistic regression analysis showed that the cerebral infarction coefficient was an independent risk factor for a poor prognosis of patients with MCI (P < 0.05, 95 % confidence interval, 2.091, 42.562), and the odds ratio was 8.506. The area under the receiver operating characteristic curve for the cerebral infarction coefficient was 0.753. When the cut-off value was 7.8 %, the sensitivity of predicting a poor prognosis of patients with MCI was 92.5 %.Conclusion: The cerebral infarction coefficient may have predictive value in determining the prognosis of patients with MCI. |
| abstract_unstemmed |
Objective: We proposed the concept of the cerebral infarction coefficient, which is cerebral infarction volume/brain volume. This study aimed to evaluate the prognostic value of the cerebral infarction coefficient in patients with massive cerebral infarction (MCI).Methods: According to the modified Rankin score, 71 patients with acute MCI were divided into good prognosis and poor prognosis groups. Clinical and imaging data of the two groups were collected and univariate analysis was carried out. If there were significant differences in the data between the two groups, binary logistic regression analysis was performed.Results: The poor prognosis group had a significantly higher cerebral infarction volume, cerebral infarction coefficient, and D-dimer levels, older age, the highest body temperature, a higher rate of a history of atrial fibrillation, and a lower rate of a history of hypertension compared with the good prognosis group (all P < 0.05). Binary logistic regression analysis showed that the cerebral infarction coefficient was an independent risk factor for a poor prognosis of patients with MCI (P < 0.05, 95 % confidence interval, 2.091, 42.562), and the odds ratio was 8.506. The area under the receiver operating characteristic curve for the cerebral infarction coefficient was 0.753. When the cut-off value was 7.8 %, the sensitivity of predicting a poor prognosis of patients with MCI was 92.5 %.Conclusion: The cerebral infarction coefficient may have predictive value in determining the prognosis of patients with MCI. |
| collection_details |
GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 |
| title_short |
Prognostic value of cerebral infarction coefficient in patients with massive cerebral infarction |
| remote_bool |
true |
| author2 |
Liu, Qingjun Li, Qi Yang, Zhao Liao, Juan Gong, Hongmin Wu, Lin Wei, Jing Tan, Qing Du, Hongheng Zhao, Rui Zhao, Libo |
| author2Str |
Liu, Qingjun Li, Qi Yang, Zhao Liao, Juan Gong, Hongmin Wu, Lin Wei, Jing Tan, Qing Du, Hongheng Zhao, Rui Zhao, Libo |
| ppnlink |
320438236 |
| mediatype_str_mv |
c |
| isOA_txt |
false |
| hochschulschrift_bool |
false |
| doi_str |
10.1016/j.clineuro.2020.106009 |
| up_date |
2024-07-06T23:45:57.288Z |
| _version_ |
1803875314345967616 |
| fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV00466891X</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230524162122.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230503s2020 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.clineuro.2020.106009</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV00466891X</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0303-8467(20)30352-8</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">rda</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">610</subfield><subfield code="q">DE-600</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">44.90</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">44.65</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Du, Xiaoyan</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(orcid)0000-0002-8474-946X</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Prognostic value of cerebral infarction coefficient in patients with massive cerebral infarction</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2020</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</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="520" ind1=" " ind2=" "><subfield code="a">Objective: We proposed the concept of the cerebral infarction coefficient, which is cerebral infarction volume/brain volume. This study aimed to evaluate the prognostic value of the cerebral infarction coefficient in patients with massive cerebral infarction (MCI).Methods: According to the modified Rankin score, 71 patients with acute MCI were divided into good prognosis and poor prognosis groups. Clinical and imaging data of the two groups were collected and univariate analysis was carried out. If there were significant differences in the data between the two groups, binary logistic regression analysis was performed.Results: The poor prognosis group had a significantly higher cerebral infarction volume, cerebral infarction coefficient, and D-dimer levels, older age, the highest body temperature, a higher rate of a history of atrial fibrillation, and a lower rate of a history of hypertension compared with the good prognosis group (all P < 0.05). Binary logistic regression analysis showed that the cerebral infarction coefficient was an independent risk factor for a poor prognosis of patients with MCI (P < 0.05, 95 % confidence interval, 2.091, 42.562), and the odds ratio was 8.506. The area under the receiver operating characteristic curve for the cerebral infarction coefficient was 0.753. When the cut-off value was 7.8 %, the sensitivity of predicting a poor prognosis of patients with MCI was 92.5 %.Conclusion: The cerebral infarction coefficient may have predictive value in determining the prognosis of patients with MCI.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Massive cerebral infarction</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Cerebral infarction volume</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Cerebral infarction coefficient</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Outcome</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Predictive value</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Liu, Qingjun</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Li, Qi</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Yang, Zhao</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Liao, Juan</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Gong, Hongmin</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Wu, Lin</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Wei, Jing</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Tan, Qing</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Du, Hongheng</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Zhao, Rui</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Zhao, Libo</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Clinical neurology and neurosurgery</subfield><subfield code="d">Amsterdam [u.a.] : Elsevier Science, 1974</subfield><subfield code="g">196</subfield><subfield code="h">Online-Ressource</subfield><subfield code="w">(DE-627)320438236</subfield><subfield code="w">(DE-600)2004613-3</subfield><subfield code="w">(DE-576)261862197</subfield><subfield code="x">1872-6968</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:196</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_31</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_32</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_74</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_90</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_100</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_101</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_224</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_370</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_702</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2003</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2004</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2005</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2011</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2015</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2020</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2021</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2025</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2027</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2034</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2038</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2044</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2048</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2049</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2050</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2056</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2059</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2061</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2064</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2065</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2068</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2111</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2113</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2118</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2122</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2129</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2143</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2147</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2148</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2152</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2153</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2190</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2336</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2507</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2522</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4035</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4242</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4251</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4326</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4333</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4334</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4335</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4393</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">44.90</subfield><subfield code="j">Neurologie</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">44.65</subfield><subfield code="j">Chirurgie</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">196</subfield></datafield></record></collection>
|
| score |
7.399868 |