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Original research
Visualisation of the non-linear correlation between age and poor outcome in patients with aneurysmal subarachnoid haemorrhage
  1. Fusao Ikawa1,2,
  2. Nao Ichihara3,
  3. Masaaki Uno4,
  4. Yoshiaki Shiokawa5,
  5. Kazunori Toyoda6,
  6. Kazuo Minematsu6,7,
  7. Shotai Kobayashi8,
  8. Shuhei Yamaguchi8,9,
  9. Kaoru Kurisu1,10
  10. On behalf of The Japanese Standard Stroke Registry Study Group
  1. 1Department of Neurosurgery, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
  2. 2Department of Neurosurgery, Shimane Prefectural Central Hospital, Izumo, Shimane, Japan
  3. 3Department of Healthcare Quality Assessment, University of Tokyo, Tokyo, Japan
  4. 4Department of Neurosurgery, Kawasaki Medical school, Kurashiki, Okayama, Japan
  5. 5Department of Neurosurgery, Kyorin University School of Medicine, Tokyo, Japan
  6. 6Department of Cerebrovascular Medicine, National Cerebral and Cardiovascular Center, Suita, Osaka, Japan
  7. 7Department of Neurology, Iseikai Medical Corporation, Osaka, Japan
  8. 8Department of Neurology, Shimane University School of Medicine, Izumo, Shimane, Japan
  9. 9Department of Neurology, Shimane Prefectural Central Hospital, Izumo, Shimane, Japan
  10. 10Department of Neurosurgery, Chugoku Rosai Hospital, Kure, Hiroshima, Japan
  1. Correspondence to Dr Fusao Ikawa, Department of Neurosurgery, Shimane Prefectural Central Hospital, Izumo, Japan; fikawa-nsu{at}umin.ac.jp

Abstract

Objective To visualise the non-linear correlation between age and poor outcome at discharge in patients with aneurysmal subarachnoid haemorrhage (SAH) while adjusting for covariates, and to address the heterogeneity of this correlation depending on disease severity by a registry-based design.

Methods We extracted data from the Japanese Stroke Databank registry for patients with SAH treated via surgical clipping or endovascular coiling within 3 days of SAH onset between 2000 and 2017. Poor outcome was defined as a modified Rankin Scale Score ≥3 at discharge. Variable importance was calculated using machine learning (random forest) model. Correlations between age and poor outcome while adjusting for covariates were determined using generalised additive models in which spline-transformed age was fit to each neurological grade of World Federation of Neurological Societies (WFNS) and treatment.

Results In total, 4149 patients were included in the analysis. WFNS grade and age had the largest and second largest variable importance in predicting the outcome. The non-linear correlation between age and poor outcome was visualised after adjusting for other covariates. For grades I–III, the risk slope for unit age was relatively smaller at younger ages and larger at older ages; for grade IV, the slope was steep even in younger ages; while for grade V, it was relatively smooth, but with high risk even at younger ages.

Conclusions The clear visualisation of the non-linear correlation between age and poor outcome in this study can aid clinical decision making and help inform patients with aneurysmal SAH and their families better.

Data availability statement

Data are available upon reasonable request. The anonymised data for this study were shared to the corresponding author by any qualified investigator after request. Primary data from the Japanese Stroke Databank (JSDB) were made available after reasonable request, in accordance with the review board of the JSDB.

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Data availability statement

Data are available upon reasonable request. The anonymised data for this study were shared to the corresponding author by any qualified investigator after request. Primary data from the Japanese Stroke Databank (JSDB) were made available after reasonable request, in accordance with the review board of the JSDB.

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Footnotes

  • Collaborators The Japanese Standard Stroke Registry Study Group.

  • Contributors All authors have made substantial contributions to the intellectual content of the paper, contributed to data interpretation, approved the final manuscript and agree with submission to this journal. Specific contributions are as follows. FI conceived and designed the study; acquired funding; conducted the research; collected, curated, managed and analysed the data; ensured quality control; and drafted the manuscript. NI conceived and designed the study; ensured quality control; performed the statistical analysis; and drafted the manuscript. MU and YS helped conceive and oversee the study and revise the manuscript. KT, KM and SK helped conceive and oversee the study; collected data; generated the database; and revised the manuscript. SY and KK helped conceive and oversee the study and revise the manuscript.

  • Funding This study was funded by the Pfizer Health Research Foundation Japan 2019 (19-E-01) and the Japan Society for the Promotion of Science Grant-in-Aid for Scientific Research (C) 17K10829.

  • Competing interests None declared.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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