Letter to the Editor
Neural network and logistic regression predictive calculator for giant cell arteritis
Red neuronal y calculadora predictiva de regresión logística para la arteritis de células gigantes
E.B. Ing
Departamento de Oftalmología, University of Toronto, Toronto, Canada
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"apellidos" => "Alba García" ] ] ] ] ] "idiomaDefecto" => "en" "Traduccion" => array:1 [ "es" => array:9 [ "pii" => "S036566911930187X" "doi" => "10.1016/j.oftal.2019.05.016" "estado" => "S300" "subdocumento" => "" "abierto" => array:3 [ "ES" => false "ES2" => false "LATM" => false ] "gratuito" => false "lecturas" => array:1 [ "total" => 0 ] "idiomaDefecto" => "es" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S036566911930187X?idApp=UINPBA00004N" ] ] "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2173579419301318?idApp=UINPBA00004N" "url" => "/21735794/0000009400000012/v1_201912161902/S2173579419301318/v1_201912161902/en/main.assets" ] "en" => array:14 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Letter to the Editor</span>" "titulo" => "Neural network and logistic regression predictive calculator for giant cell arteritis" "tieneTextoCompleto" => true "saludo" => "Dear Editor:" "paginas" => array:1 [ 0 => array:1 [ "paginaInicial" => "622" ] ] "autores" => array:1 [ 0 => array:3 [ "autoresLista" => "E.B. Ing" "autores" => array:1 [ 0 => array:3 [ "nombre" => "E.B." "apellidos" => "Ing" "email" => array:1 [ 0 => "edingLidStrab@gmail.com" ] ] ] "afiliaciones" => array:1 [ 0 => array:2 [ "entidad" => "Departamento de Oftalmología, University of Toronto, Toronto, Canada" "identificador" => "aff0005" ] ] ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Red neuronal y calculadora predictiva de regresión logística para la arteritis de células gigantes" ] ] "textoCompleto" => "<span class="elsevierStyleSections"><p id="par0005" class="elsevierStylePara elsevierViewall">I read with interest the article by Moraña et al.<a class="elsevierStyleCrossRef" href="#bib0005"><span class="elsevierStyleSup">1</span></a></p><p id="par0010" class="elsevierStylePara elsevierViewall">An alternative giant cell arteritis (GCA) risk calculator employing both neural network and logistic regression models (NN-LR) was published in early 2019,<a class="elsevierStyleCrossRef" href="#bib0010"><span class="elsevierStyleSup">2</span></a> and is available online at <a href="https://goo.gl/THCnuU">https://goo.gl/THCnuU</a>. The prediction model was developed using retrospective data from 1201 consecutive patients undergoing temporal artery biopsy for suspected giant cell arteritis at 14 medical centers. The patients were referred by ophthalmologists and internal medicine specialists. The NN-LR calculator adheres to the guidelines for the Transparent Reporting of Multivariable Prediction Model for Individual Diagnosis or Prognosis,<a class="elsevierStyleCrossRef" href="#bib0015"><span class="elsevierStyleSup">3</span></a> and has geographic external validation and provides cut-points for 99% and 95% sensitivity.</p><p id="par0015" class="elsevierStylePara elsevierViewall">The NN-LR calculator used the ten predictor variables of: age, gender, new onset headache, temporal artery tenderness or pulselessness, jaw claudication, vision loss, diplopia, erythrocyte sedimentation rate, C-reactive protein and platelets. The age and the bloodwork predictors were maintained as continuous variables to preserve statistical power. There was no multicollinearity. Age, platelets, jaw claudication and vision loss were the strongest predictors of GCA.</p><p id="par0020" class="elsevierStylePara elsevierViewall">Unlike the González-López calculator,<a class="elsevierStyleCrossRef" href="#bib0020"><span class="elsevierStyleSup">4</span></a> the NN-LR calculator does not require data on temporal artery biopsy length. The NN-LR calculator did not include polymyalgia rheumatica (PMR) as a predictor variable as it can be a nonspecific clinical manifestation, with overlapping age and acute phase response characteristics with GCA. The distinction of PMR from osteoarthritis flare can be difficult. Reports of joint X-rays were not available in the NN-LR study. Also, rotator cuff injury and fibromyalgia may have overlapping clinical features with PMR.</p></span>" "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2019-07-16" "NotaPie" => array:1 [ 0 => array:2 [ "etiqueta" => "☆" "nota" => "<p class="elsevierStyleNotepara" id="npar0005">Please cite this article as: Ing EB. Red neuronal y calculadora predictiva de regresión logística para la arteritis de células gigantes. Arch Soc Esp Oftalmol. 2019;94:622.</p>" ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0005" "bibliografiaReferencia" => array:4 [ 0 => array:3 [ "identificador" => "bib0005" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Giant cell arteritis and usefulness of a predictive calculator [Article in English, Spanish]" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:4 [ 0 => "M.N. Moraña" 1 => "C. Sevillano" 2 => "S. Martínez" 3 => "M.L. Carral" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.oftal.2019.04.009" "Revista" => array:2 [ "tituloSerie" => "Arch Soc Esp Oftalmol" "fecha" => "2019" ] ] ] ] ] ] 1 => array:3 [ "identificador" => "bib0010" "etiqueta" => "2" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Neural network and logistic regression diagnostic prediction models for giant cell arteritis: development and validation" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "E.B. Ing" 1 => "N.R. Miller" 2 => "A. Nguyen" 3 => "W. Su" 4 => "L.L. Bursztyn" 5 => "M. Poole" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.2147/OPTH.S193460" "Revista" => array:6 [ "tituloSerie" => "Clin Ophthalmol" "fecha" => "2019" "volumen" => "13" "paginaInicial" => "421" "paginaFinal" => "430" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/30863010" "web" => "Medline" ] ] ] ] ] ] ] ] 2 => array:3 [ "identificador" => "bib0015" "etiqueta" => "3" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:4 [ 0 => "G.S. Collins" 1 => "J.B. Reitsma" 2 => "D.G. Altman" 3 => "K.G. Moons" ] ] ] ] ] "host" => array:1 [ 0 => array:1 [ "Revista" => array:5 [ "tituloSerie" => "BMJ" "fecha" => "2015" "volumen" => "162" "paginaInicial" => "55" "paginaFinal" => "63" ] ] ] ] ] ] 3 => array:3 [ "identificador" => "bib0020" "etiqueta" => "4" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "A calculator for temporal artery biopsy" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:3 [ 0 => "J.J. González-López" 1 => "J. González-Moraleja" 2 => "G. Rebolleda" ] ] ] ] ] "host" => array:1 [ 0 => array:1 [ "Revista" => array:5 [ "tituloSerie" => "Eur J Intern" "fecha" => "2014" "volumen" => "25" "paginaInicial" => "e98" "paginaFinal" => "100" ] ] ] ] ] ] ] ] ] ] ] "idiomaDefecto" => "en" "url" => "/21735794/0000009400000012/v1_201912161902/S2173579419301574/v1_201912161902/en/main.assets" "Apartado" => array:4 [ "identificador" => "5813" "tipo" => "SECCION" "en" => array:2 [ "titulo" => "Letter to the Editor" "idiomaDefecto" => true ] "idiomaDefecto" => "en" ] "PDF" => "https://static.elsevier.es/multimedia/21735794/0000009400000012/v1_201912161902/S2173579419301574/v1_201912161902/en/main.pdf?idApp=UINPBA00004N&text.app=https://www.elsevier.es/" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2173579419301574?idApp=UINPBA00004N" ]
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