Real world data in mechanical thrombectomy: who are we losing to follow-up? Article Swipe
Marianne Hahn
,
Sonja Gröschel
,
Ahmed E. Othman
,
Lavinia Brockstedt
,
Arda Civelek
,
Marc A. Brockmann
,
Klaus Gröschel
,
Timo Uphaus
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1136/jnis-2023-020435
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1136/jnis-2023-020435
Background Missing outcome data (MOD) is a common problem in clinical trials and registries, and a potential bias when drawing conclusions from these data. Identifying factors associated with MOD may help to increase follow-up rates and assess the need for imputation strategies. We investigated MOD in a multicenter, prospective registry study of mechanical thrombectomy (MT) in large vessel occlusion ischemic stroke. Methods 13 082 patients enrolled in the German Stroke Registry-Endovascular Treatment from May 2015 to December 2021 were analyzed with regard to MOD (90 day modified Rankin Scale, mRS). Univariate logistic regression analyses identified factors unbalanced between patients with and without MOD. Subgroup analyses were performed to identify patients for whom increased efforts to perform clinical follow-up after hospital discharge are needed. Results We identified 19.7% (2580/13 082) of patients with MOD at the 90 day follow-up. MOD was more common with higher pre-stroke disability (mRS 3–5, 32.2% vs mRS 0–2, 13.7%; P<0.001), absence of bridging intravenous thrombolysis, longer time to treatment, and in patients with high post-stroke disability at discharge (mRS 3–5 vs 0–2: OR 1.234 (95% CI 1.107 to 1.375); P<0.001). In contrast, MOD was less common with futile recanalization (thrombolysis in cerebral infarction (TICI) score of 0–2a, 12.4% vs TICI 2b–3, 15.0%; P=0.001). In patients discharged alive with well documented baseline characteristics, shorter hospital stay (OR 0.992 (95% CI 0.985 to 0.998); P=0.010) and discharge to institutional care or hospital (OR 1.754 (95% CI 1.558 to 1.976); P<0.001) were associated with MOD. Conclusion MOD in routine care MT registry data was not random. Increased efforts to perform clinical follow-up are needed, especially in the case of higher pre-stroke and post-stroke disability and discharge to hospital or institutional care. Trial registration NCT03356392 .
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1136/jnis-2023-020435
- https://jnis.bmj.com/content/neurintsurg/early/2023/07/17/jnis-2023-020435.full.pdf
- OA Status
- hybrid
- Cited By
- 6
- References
- 32
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4384521800
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4384521800Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1136/jnis-2023-020435Digital Object Identifier
- Title
-
Real world data in mechanical thrombectomy: who are we losing to follow-up?Work title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-07-17Full publication date if available
- Authors
-
Marianne Hahn, Sonja Gröschel, Ahmed E. Othman, Lavinia Brockstedt, Arda Civelek, Marc A. Brockmann, Klaus Gröschel, Timo UphausList of authors in order
- Landing page
-
https://doi.org/10.1136/jnis-2023-020435Publisher landing page
- PDF URL
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https://jnis.bmj.com/content/neurintsurg/early/2023/07/17/jnis-2023-020435.full.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
- OA URL
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https://jnis.bmj.com/content/neurintsurg/early/2023/07/17/jnis-2023-020435.full.pdfDirect OA link when available
- Concepts
-
Medicine, Stroke (engine), Surgery, Engineering, Mechanical engineeringTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
6Total citation count in OpenAlex
- Citations by year (recent)
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2025: 4, 2024: 2Per-year citation counts (last 5 years)
- References (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.factors | 25, 95 |
| abstract_inverted_index.needed, | 264 |
| abstract_inverted_index.needed. | 122 |
| abstract_inverted_index.outcome | 2 |
| abstract_inverted_index.perform | 115, 260 |
| abstract_inverted_index.problem | 8 |
| abstract_inverted_index.random. | 256 |
| abstract_inverted_index.routine | 249 |
| abstract_inverted_index.shorter | 216 |
| abstract_inverted_index.stroke. | 60 |
| abstract_inverted_index.without | 101 |
| abstract_inverted_index.(2580/13 | 127 |
| abstract_inverted_index.December | 76 |
| abstract_inverted_index.P=0.010) | 226 |
| abstract_inverted_index.Subgroup | 103 |
| abstract_inverted_index.analyses | 93, 104 |
| abstract_inverted_index.analyzed | 79 |
| abstract_inverted_index.baseline | 214 |
| abstract_inverted_index.bridging | 156 |
| abstract_inverted_index.cerebral | 195 |
| abstract_inverted_index.clinical | 10, 116, 261 |
| abstract_inverted_index.enrolled | 65 |
| abstract_inverted_index.hospital | 119, 217, 233, 278 |
| abstract_inverted_index.identify | 108 |
| abstract_inverted_index.increase | 32 |
| abstract_inverted_index.ischemic | 59 |
| abstract_inverted_index.logistic | 91 |
| abstract_inverted_index.modified | 86 |
| abstract_inverted_index.patients | 64, 98, 109, 130, 165, 208 |
| abstract_inverted_index.registry | 49, 252 |
| abstract_inverted_index.Increased | 257 |
| abstract_inverted_index.P=0.001). | 206 |
| abstract_inverted_index.Treatment | 71 |
| abstract_inverted_index.contrast, | 185 |
| abstract_inverted_index.discharge | 120, 171, 228, 276 |
| abstract_inverted_index.follow-up | 33, 117, 262 |
| abstract_inverted_index.increased | 112 |
| abstract_inverted_index.occlusion | 58 |
| abstract_inverted_index.performed | 106 |
| abstract_inverted_index.potential | 16 |
| abstract_inverted_index.Background | 0 |
| abstract_inverted_index.Conclusion | 246 |
| abstract_inverted_index.Univariate | 90 |
| abstract_inverted_index.associated | 26, 243 |
| abstract_inverted_index.disability | 145, 169, 274 |
| abstract_inverted_index.discharged | 209 |
| abstract_inverted_index.documented | 213 |
| abstract_inverted_index.especially | 265 |
| abstract_inverted_index.follow-up. | 137 |
| abstract_inverted_index.identified | 94, 125 |
| abstract_inverted_index.imputation | 40 |
| abstract_inverted_index.infarction | 196 |
| abstract_inverted_index.mechanical | 52 |
| abstract_inverted_index.pre-stroke | 144, 271 |
| abstract_inverted_index.regression | 92 |
| abstract_inverted_index.treatment, | 162 |
| abstract_inverted_index.unbalanced | 96 |
| abstract_inverted_index.Identifying | 24 |
| abstract_inverted_index.NCT03356392 | 284 |
| abstract_inverted_index.P<0.001) | 241 |
| abstract_inverted_index.conclusions | 20 |
| abstract_inverted_index.intravenous | 157 |
| abstract_inverted_index.post-stroke | 168, 273 |
| abstract_inverted_index.prospective | 48 |
| abstract_inverted_index.registries, | 13 |
| abstract_inverted_index.strategies. | 41 |
| abstract_inverted_index.P<0.001), | 153 |
| abstract_inverted_index.P<0.001). | 183 |
| abstract_inverted_index.investigated | 43 |
| abstract_inverted_index.multicenter, | 47 |
| abstract_inverted_index.registration | 283 |
| abstract_inverted_index.thrombectomy | 53 |
| abstract_inverted_index.(thrombolysis | 193 |
| abstract_inverted_index.institutional | 230, 280 |
| abstract_inverted_index.thrombolysis, | 158 |
| abstract_inverted_index.recanalization | 192 |
| abstract_inverted_index.characteristics, | 215 |
| abstract_inverted_index.Registry-Endovascular | 70 |
| cited_by_percentile_year.max | 98 |
| cited_by_percentile_year.min | 94 |
| corresponding_author_ids | https://openalex.org/A5060520647 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 8 |
| corresponding_institution_ids | https://openalex.org/I197323543, https://openalex.org/I4210094062 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/3 |
| sustainable_development_goals[0].score | 0.5299999713897705 |
| sustainable_development_goals[0].display_name | Good health and well-being |
| citation_normalized_percentile.value | 0.83552308 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |