TY - JOUR
T1 - A scoring tool to predict mortality and dependency after cerebral venous thrombosis
AU - Lindgren, Erik
AU - Krzywicka, Katarzyna
AU - de Winter, Maria A.
AU - Sánchez van Kammen, Mayte
AU - Heldner, Mirjam R.
AU - Hiltunen, Sini
AU - Aguiar de Sousa, Diana
AU - Mansour, Maryam
AU - Canhão, Patrícia
AU - Ekizoğlu, Esme
AU - Rodrigues, Miguel
AU - Martins Silva, Elisa
AU - Garcia-Esperon, Carlos
AU - Arnao, Valentina
AU - Aridon, Paolo
AU - Simaan, Naaem Moin
AU - Silvis, Suzanne M.
AU - Zuurbier, Susanna M.
AU - Scutelnic, Adrian
AU - Sezgin, Mine
AU - Alasheev, Andrey Marisovich
AU - Smolkin, Andrey
AU - Guisado-Alonso, Daniel
AU - Yesilot, Nilufer
AU - Barboza, Miguel
AU - Ghiasian, Masoud
AU - Leker, Ronen R.
AU - Arauz, Antonio
AU - Arnold, Marcel
AU - Putaala, Jukka
AU - Tatlisumak, Turgut
AU - Coutinho, Jonathan M.
AU - Jood, Katarina
N1 - Funding Information: EL has received academic grants from the Swedish state under the agreement between the Swedish government and the county councils, the ALF agreement (ALFGBG 942851), the Swedish Neurological Society, Elsa and Gustav Lindh's Foundation, P‐O Ahl's Foundation and Rune and Ulla Amlöv's Foundation for research on CVT. TT and KJ received academic grants from the Swedish state under the agreement between the Swedish government and the county councils, the ALF agreement (ALFGBG 726821 and ALFGBG‐965417). JP has received funding from the Hospital District of Helsinki and Uusimaa (TYH2022223). Publisher Copyright: © 2023 The Authors. European Journal of Neurology published by John Wiley & Sons Ltd on behalf of European Academy of Neurology.
PY - 2023/8
Y1 - 2023/8
N2 - Background and purpose: A prognostic score was developed to predict dependency and death after cerebral venous thrombosis (CVT) to identify patients for targeted therapy in future clinical trials. Methods: Data from the International CVT Consortium were used. Patients with pre-existent functional dependency were excluded. Logistic regression was used to predict poor outcome (modified Rankin Scale score 3–6) at 6 months and Cox regression to predict 30-day and 1-year all-cause mortality. Potential predictors derived from previous studies were selected with backward stepwise selection. Coefficients were shrunk using ridge regression to adjust for optimism in internal validation. Results: Of 1454 patients with CVT, the cumulative number of deaths was 44 (3%) and 70 (5%) for 30 days and 1 year, respectively. Of 1126 patients evaluated regarding functional outcome, 137 (12%) were dependent or dead at 6 months. From the retained predictors for both models, the SI2NCAL2C score was derived utilizing the following components: absence of female-sex-specific risk factor, intracerebral hemorrhage, infection of the central nervous system, neurological focal deficits, coma, age, lower level of hemoglobin (g/l), higher level of glucose (mmol/l) at admission, and cancer. C-statistics were 0.80 (95% confidence interval [CI] 0.75–0.84), 0.84 (95% CI 0.80–0.88) and 0.84 (95% CI 0.80–0.88) for the poor outcome, 30-day and 1-year mortality model, respectively. Calibration plots indicated a good model fit between predicted and observed values. The SI2NCAL2C score calculator is freely available at www.cerebralvenousthrombosis.com. Conclusions: The SI2NCAL2C score shows adequate performance for estimating individual risk of mortality and dependency after CVT but external validation of the score is warranted.
AB - Background and purpose: A prognostic score was developed to predict dependency and death after cerebral venous thrombosis (CVT) to identify patients for targeted therapy in future clinical trials. Methods: Data from the International CVT Consortium were used. Patients with pre-existent functional dependency were excluded. Logistic regression was used to predict poor outcome (modified Rankin Scale score 3–6) at 6 months and Cox regression to predict 30-day and 1-year all-cause mortality. Potential predictors derived from previous studies were selected with backward stepwise selection. Coefficients were shrunk using ridge regression to adjust for optimism in internal validation. Results: Of 1454 patients with CVT, the cumulative number of deaths was 44 (3%) and 70 (5%) for 30 days and 1 year, respectively. Of 1126 patients evaluated regarding functional outcome, 137 (12%) were dependent or dead at 6 months. From the retained predictors for both models, the SI2NCAL2C score was derived utilizing the following components: absence of female-sex-specific risk factor, intracerebral hemorrhage, infection of the central nervous system, neurological focal deficits, coma, age, lower level of hemoglobin (g/l), higher level of glucose (mmol/l) at admission, and cancer. C-statistics were 0.80 (95% confidence interval [CI] 0.75–0.84), 0.84 (95% CI 0.80–0.88) and 0.84 (95% CI 0.80–0.88) for the poor outcome, 30-day and 1-year mortality model, respectively. Calibration plots indicated a good model fit between predicted and observed values. The SI2NCAL2C score calculator is freely available at www.cerebralvenousthrombosis.com. Conclusions: The SI2NCAL2C score shows adequate performance for estimating individual risk of mortality and dependency after CVT but external validation of the score is warranted.
KW - cerebral venous thrombosis
KW - dependency
KW - follow-up
KW - mortality
KW - outcome
KW - prognosis
KW - risk score
KW - stroke
UR - http://www.scopus.com/inward/record.url?scp=85160937323&partnerID=8YFLogxK
U2 - https://doi.org/10.1111/ene.15844
DO - https://doi.org/10.1111/ene.15844
M3 - Article
C2 - 37165521
SN - 1351-5101
VL - 30
SP - 2305
EP - 2314
JO - European journal of neurology
JF - European journal of neurology
IS - 8
ER -