Literature DB >> 28577068

Intensive care medicine in 2050: statistical tools for development of prognostic models (why clinicians should not be ignored).

Daniele Poole1, Greta Carrara2, Guido Bertolini2.   

Abstract

Mesh：

Year:  2017        PMID： 28577068     DOI： 10.1007/s00134-017-4825-x

Source DB:  PubMed          Journal:  Intensive Care Med        ISSN： 0342-4642            Impact factor:   17.440


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  9 in total

1.  A new test and graphical tool to assess the goodness of fit of logistic regression models.

Authors:  Giovanni Nattino; Stefano Finazzi; Guido Bertolini
Journal:  Stat Med       Date:  2015-10-05       Impact factor: 2.373

2.  Recalibration of risk prediction models in a large multicenter cohort of admissions to adult, general critical care units in the United Kingdom.

Authors:  David A Harrison; Anthony R Brady; Gareth J Parry; James R Carpenter; Kathy Rowan
Journal:  Crit Care Med       Date:  2006-05       Impact factor: 7.598

3.  A new calibration test and a reappraisal of the calibration belt for the assessment of prediction models based on dichotomous outcomes.

Authors:  Giovanni Nattino; Stefano Finazzi; Guido Bertolini
Journal:  Stat Med       Date:  2014-02-04       Impact factor: 2.373

4.  A review of goodness of fit statistics for use in the development of logistic regression models.

Authors:  S Lemeshow; D W Hosmer
Journal:  Am J Epidemiol       Date:  1982-01       Impact factor: 4.897

5.  Effect of mortality rate on the performance of the Acute Physiology and Chronic Health Evaluation II: a simulation study.

Authors:  L G Glance; T M Osler; P Papadakos
Journal:  Crit Care Med       Date:  2000-10       Impact factor: 7.598

6.  Evaluation of the uniformity of fit of general outcome prediction models.

Authors:  R Moreno; G Apolone; D R Miranda
Journal:  Intensive Care Med       Date:  1998-01       Impact factor: 17.440

Review 7.  Outcome prediction in critical care: the Simplified Acute Physiology Score models.

Authors:  Maurizia Capuzzo; Rui P Moreno; Jean-Roger Le Gall
Journal:  Curr Opin Crit Care       Date:  2008-10       Impact factor: 3.687

8.  External validation of the Simplified Acute Physiology Score (SAPS) 3 in a cohort of 28,357 patients from 147 Italian intensive care units.

Authors:  Daniele Poole; Carlotta Rossi; Abramo Anghileri; Michele Giardino; Nicola Latronico; Danilo Radrizzani; Martin Langer; Guido Bertolini
Journal:  Intensive Care Med       Date:  2009-08-14       Impact factor: 17.440

9.  Calibration belt for quality-of-care assessment based on dichotomous outcomes.

Authors:  Stefano Finazzi; Daniele Poole; Davide Luciani; Paola E Cogo; Guido Bertolini
Journal:  PLoS One       Date:  2011-02-23       Impact factor: 3.240
  9 in total
  2 in total

Review 1.  Changes in critically ill cancer patients' short-term outcome over the last decades: results of systematic review with meta-analysis on individual data.

Authors:  Michaël Darmon; Aurélie Bourmaud; Quentin Georges; Marcio Soares; Kyeongman Jeon; Sandra Oeyen; Chin Kook Rhee; Pascale Gruber; Marlies Ostermann; Quentin A Hill; Pieter Depuydt; Christelle Ferra; Anne-Claire Toffart; Peter Schellongowski; Alice Müller; Virginie Lemiale; Djamel Mokart; Elie Azoulay
Journal:  Intensive Care Med       Date:  2019-05-29       Impact factor: 17.440

2.  Validation of the ICH score in patients with spontaneous intracerebral haemorrhage admitted to the intensive care unit in Southern Spain.

Authors:  Sonia Rodríguez-Fernández; Encarnación Castillo-Lorente; Francisco Guerrero-Lopez; David Rodríguez-Rubio; Eduardo Aguilar-Alonso; Jesús Lafuente-Baraza; Francisco Javier Gómez-Jiménez; Juan Mora-Ordóñez; Ricardo Rivera-López; María Dolores Arias-Verdú; Guillermo Quesada-García; Miguel Ángel Arráez-Sánchez; Ricardo Rivera-Fernández
Journal:  BMJ Open       Date:  2018-08-13       Impact factor: 2.692
  2 in total

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