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Multicenter external validation of prediction models for clinical outcomes after spinal fusion for lumbar degenerative disease.
Grob, Alexandra; Rohr, Jonas; Stumpo, Vittorio; Vieli, Moira; Ciobanu-Caraus, Olga; Ricciardi, Luca; Maldaner, Nicolai; Raco, Antonino; Miscusi, Massimo; Perna, Andrea; Proietti, Luca; Lofrese, Giorgio; Dughiero, Michele; Cultrera, Francesco; D'Andrea, Marcello; An, Seong Bae; Ha, Yoon; Amelot, Aymeric; Bedia Cadelo, Jorge; Viñuela-Prieto, Jose M; Gandía-González, Maria L; Girod, Pierre-Pascal; Lener, Sara; Kögl, Nikolaus; Abramovic, Anto; Laux, Christoph J; Farshad, Mazda; O'Riordan, Dave; Loibl, Markus; Galbusera, Fabio; Mannion, Anne F; Scerrati, Alba; De Bonis, Pasquale; Molliqaj, Granit; Tessitore, Enrico; Schröder, Marc L; Stienen, Martin N; Regli, Luca; Serra, Carlo; Staartjes, Victor E.
Afiliación
  • Grob A; Machine Intelligence in Clinical Neuroscience and Microsurgical Neuroanatomy (MICN) Laboratory, Department of Neurosurgery, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
  • Rohr J; Machine Intelligence in Clinical Neuroscience and Microsurgical Neuroanatomy (MICN) Laboratory, Department of Neurosurgery, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
  • Stumpo V; Machine Intelligence in Clinical Neuroscience and Microsurgical Neuroanatomy (MICN) Laboratory, Department of Neurosurgery, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
  • Vieli M; Machine Intelligence in Clinical Neuroscience and Microsurgical Neuroanatomy (MICN) Laboratory, Department of Neurosurgery, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
  • Ciobanu-Caraus O; Machine Intelligence in Clinical Neuroscience and Microsurgical Neuroanatomy (MICN) Laboratory, Department of Neurosurgery, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
  • Ricciardi L; Department of NESMOS, Azienda Ospedaliera Universitaria Sant'Andrea, Sapienza University, Rome, Italy.
  • Maldaner N; Machine Intelligence in Clinical Neuroscience and Microsurgical Neuroanatomy (MICN) Laboratory, Department of Neurosurgery, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
  • Raco A; Department of NESMOS, Azienda Ospedaliera Universitaria Sant'Andrea, Sapienza University, Rome, Italy.
  • Miscusi M; Department of NESMOS, Azienda Ospedaliera Universitaria Sant'Andrea, Sapienza University, Rome, Italy.
  • Perna A; Department of Orthopedics, Foundation Casa Sollievo Della Sofferenza IRCCS, San Giovanni Rotondo, Italy.
  • Proietti L; Department of Aging, Neurological, Orthopedic and Head-Neck Sciences, IRCCS A. Gemelli University Polyclinic Foundation, Rome, Italy.
  • Lofrese G; Department of Geriatrics and Orthopedics, Sacred Heart Catholic University, Rome, Italy.
  • Dughiero M; Neurosurgery Division, Department of Neurosciences, "M.Bufalini" Hospital, Cesena, Italy.
  • Cultrera F; Neurosurgery Division, Department of Neurosciences, "M.Bufalini" Hospital, Cesena, Italy.
  • D'Andrea M; Neurosurgery Division, Department of Neurosciences, "M.Bufalini" Hospital, Cesena, Italy.
  • An SB; Neurosurgery Division, Department of Neurosciences, "M.Bufalini" Hospital, Cesena, Italy.
  • Ha Y; Department of Neurosurgery, Spine and Spinal Cord Institute, College of Medicine, Severance Hospital, Yonsei University, Seoul, Korea.
  • Amelot A; Department of Neurosurgery, Spine and Spinal Cord Institute, College of Medicine, Severance Hospital, Yonsei University, Seoul, Korea.
  • Bedia Cadelo J; Department of Neurosurgery, La Pitié Salpétrière Hospital, Paris, France.
  • Viñuela-Prieto JM; Neurosurgical Spine Department, University Hospital of Tours, Tours, France.
  • Gandía-González ML; Department of Neurosurgery, Hospital Universitario La Paz, Madrid, Spain.
  • Girod PP; Department of Neurosurgery, Hospital Universitario La Paz, Madrid, Spain.
  • Lener S; Department of Neurosurgery, Hospital Universitario La Paz, Madrid, Spain.
  • Kögl N; Department of Neurosurgery, Vienna Healthcare Network/ Municipial Hospital, Vienna, Austria.
  • Abramovic A; Department of Neurosurgery, Medical University of Innsbruck, Innsbruck, Austria.
  • Laux CJ; Department of Neurosurgery, Medical University of Innsbruck, Innsbruck, Austria.
  • Farshad M; Department of Neurosurgery, Medical University of Innsbruck, Innsbruck, Austria.
  • O'Riordan D; University Spine Center, Balgrist University Hospital, University of Zurich, Zurich, Switzerland.
  • Loibl M; University Spine Center, Balgrist University Hospital, University of Zurich, Zurich, Switzerland.
  • Galbusera F; Spine Center Division, Department of Teaching, Research and Development, Schulthess Klinik, Zurich, Switzerland.
  • Mannion AF; Department of Spine Surgery, Schulthess Klinik, Zurich, Switzerland.
  • Scerrati A; Spine Center Division, Department of Teaching, Research and Development, Schulthess Klinik, Zurich, Switzerland.
  • De Bonis P; Spine Center Division, Department of Teaching, Research and Development, Schulthess Klinik, Zurich, Switzerland.
  • Molliqaj G; Department of Neurosurgery, University Hospital Sant'Anna, Ferrara, Italy.
  • Tessitore E; Department of Neurosurgery, University Hospital Sant'Anna, Ferrara, Italy.
  • Schröder ML; Department of Neurosurgery, HUG Geneva University Hospital, Geneva, Switzerland.
  • Stienen MN; Department of Neurosurgery, HUG Geneva University Hospital, Geneva, Switzerland.
  • Regli L; Department of Neurosurgery, Bergman Clinics Amsterdam, Amsterdam, The Netherlands.
  • Serra C; Department of Neurosurgery and Spine Center of Eastern Switzerland, Cantonal Hospital St. Gallen and Medical School of St.Gallen, St. Gallen, Switzerland.
  • Staartjes VE; Machine Intelligence in Clinical Neuroscience and Microsurgical Neuroanatomy (MICN) Laboratory, Department of Neurosurgery, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Eur Spine J ; 2024 Jul 11.
Article en En | MEDLINE | ID: mdl-38987513
ABSTRACT

BACKGROUND:

Clinical prediction models (CPM), such as the SCOAP-CERTAIN tool, can be utilized to enhance decision-making for lumbar spinal fusion surgery by providing quantitative estimates of outcomes, aiding surgeons in assessing potential benefits and risks for each individual patient. External validation is crucial in CPM to assess generalizability beyond the initial dataset. This ensures performance in diverse populations, reliability and real-world applicability of the results. Therefore, we externally validated the tool for predictability of improvement in oswestry disability index (ODI), back and leg pain (BP, LP).

METHODS:

Prospective and retrospective data from multicenter registry was obtained. As outcome measure minimum clinically important change was chosen for ODI with ≥ 15-point and ≥ 2-point reduction for numeric rating scales (NRS) for BP and LP 12 months after lumbar fusion for degenerative disease. We externally validate this tool by calculating discrimination and calibration metrics such as intercept, slope, Brier Score, expected/observed ratio, Hosmer-Lemeshow (HL), AUC, sensitivity and specificity.

RESULTS:

We included 1115 patients, average age 60.8 ± 12.5 years. For 12-month ODI, area-under-the-curve (AUC) was 0.70, the calibration intercept and slope were 1.01 and 0.84, respectively. For NRS BP, AUC was 0.72, with calibration intercept of 0.97 and slope of 0.87. For NRS LP, AUC was 0.70, with calibration intercept of 0.04 and slope of 0.72. Sensitivity ranged from 0.63 to 0.96, while specificity ranged from 0.15 to 0.68. Lack of fit was found for all three models based on HL testing.

CONCLUSIONS:

Utilizing data from a multinational registry, we externally validate the SCOAP-CERTAIN prediction tool. The model demonstrated fair discrimination and calibration of predicted probabilities, necessitating caution in applying it in clinical practice. We suggest that future CPMs focus on predicting longer-term prognosis for this patient population, emphasizing the significance of robust calibration and thorough reporting.
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Eur Spine J Asunto de la revista: ORTOPEDIA Año: 2024 Tipo del documento: Article País de afiliación: Suiza Pais de publicación: Alemania

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Eur Spine J Asunto de la revista: ORTOPEDIA Año: 2024 Tipo del documento: Article País de afiliación: Suiza Pais de publicación: Alemania