Browsing by Subject "CURVE"

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  • Lappi, Otto; Lehtonen, Esko; Pekkanen, Jami; Itkonen, Teemu (2013)
  • Strganac, Christopher; Salminen, Johanna; Jacobs, Louis L.; Polcyn, Michael J.; Ferguson, Kurt M.; Mateus, Octavio; Schulp, Anne S.; Morais, Maria Luisa; Tavares, Tatiana da Silva; Goncalves, Antonio Olimpio (2014)
  • Jadhav, A. P.; Desai, S. M.; Panczykowski, D. M.; Rangaraju, S.; Campbell, D.; Ritvonen, J. K.; Schreiner, M.; Silvennoinen, H.; Gerber, J.; Puetz, Volker; Raza, S. A.; Haussen, D. C.; Nogueira, R. G.; Strbian, D.; Jovin, T. G.; Lindsberg, P. J. (2020)
    Background and purpose Basilar artery occlusion (BAO) leads to high rates of morbidity and mortality, despite successful recanalization. The discordance between flow restoration and long-term functional status clouds clinical decision-making regarding further aggressive care. We sought to develop and validate a practical, prognostic tool for the prediction of 3-month favorable outcome after acute reperfusion therapy for BAO. Methods This retrospective, multicenter, observational study was conducted at four high-volume stroke centers in the USA and Europe. Multivariate regression analysis was performed to identify predictors of favorable outcome (90-day modified Rankin scale scores 0-2) and derive a clinically applicable prognostic model (the Pittsburgh Outcomes after Stroke Thrombectomy-Vertebrobasilar (POST-VB) score). The POST-VB score was evaluated and internally validated with regard to calibration and discriminatory ability. External validity was assessed in patient cohorts at three separate centers. Results In the derivation cohort of 59 patients, independent predictors of favorable outcome included smaller brainstem infarct volume on post-procedure magnetic resonance imaging (P <0.01) and younger age (P = 0.01). POST-VB score was calculated as: age + (10 x brainstem infarct volume). POST-VB score demonstrated excellent discriminatory ability [area under the receiver-operating characteristic curve (AUC) = 0.91] and adequate calibration (P = 0.88) in the derivation cohort (Center A). It performed equally well across the three external validation cohorts (Center B, AUC = 0.89; Center C, AUC = 0.78; Center D, AUC = 0.80). Overall, a POST-VB score <49 was associated with an 88% likelihood of favorable outcome, as compared to 4% with a score >= 125. Conclusions The POST-VB score effectively predicts 3-month functional outcome following acute reperfusion therapy for BAO and may aid in guiding post-procedural care.
  • FINNAKI Study Grp; Törnblom, Sanna; Nisula, Sara; Petäjä, Liisa; Vaara, Suvi T.; Haapio, Mikko; Pesonen, Eero; Pettilä, Ville (2020)
    Background: Neutrophil gelatinase-associated lipocalin (NGAL) is released from kidney tubular cells under stress as well as from neutrophils during inflammation. It has been suggested as a biomarker for acute kidney injury (AKI) in critically ill patients with sepsis. To evaluate clinical usefulness of urine NGAL (uNGAL), we post-hoc applied recently introduced statistical methods to a sub-cohort of septic patients from the prospective observational Finnish Acute Kidney Injury (FINNAKI) study. Accordingly, in 484 adult intensive care unit patients with sepsis by Sepsis-3 criteria, we calculated areas under the receiver operating characteristic curves (AUCs) for the first available uNGAL to assess discrimination for four outcomes: AKI defined by Kidney Disease: Improving Global Outcomes (KDIGO) criteria, severe (KDIGO 2-3) AKI, and renal replacement therapy (RRT) during the first 3 days of intensive care, and mortality at day 90. We constructed clinical prediction models for the outcomes and used risk assessment plots and decision curve analysis with predefined threshold probabilities to test whether adding uNGAL to the models improved reclassification or decision making in clinical practice. Results: Incidences of AKI, severe AKI, RRT, and mortality were 44.8% (217/484), 27.7% (134/484), 9.5% (46/484), and 28.1% (136/484). Corresponding AUCs for uNGAL were 0.690, 0.728, 0.769, and 0.600. Adding uNGAL to the clinical prediction models improved discrimination of AKI, severe AKI, and RRT. However, the net benefits for the new models were only 1.4% (severe AKI and RRT) to 2.5% (AKI), and the number of patients needed to be tested per one extra true-positive varied from 40 (AKI) to 74 (RRT) at the predefined threshold probabilities. Conclusions: The results of the recommended new statistical methods do not support the use of uNGAL in critically ill septic patients to predict AKI or clinical outcomes.