Prognostic Impact of Malnutrition Evaluated via Bioelectrical Impedance Vector Analysis (BIVA) in Acute Ischemic Stroke: Findings from an Inverse Probability Weighting Analysis Article Swipe
Simone Dal Bello
,
Laura Ceccarelli
,
Yan Tereshko
,
Gian Luigi Gigli
,
Lucio D’Anna
,
Mariarosaria Valente
,
Giovanni Merlino
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/nu17050919
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/nu17050919
Background. The association between malnutrition and poor outcomes in stroke patients has, to date, been evaluated using composite scores derived from laboratory measurements. However, Bioelectrical Impedance Analysis (BIA) and its advanced application, Bioelectrical Impedance Vector Analysis (BIVA), offer a non-invasive, cost-efficient, and rapid alternative. These methods enable precise assessment of body composition, nutritional status, and hydration levels, making them valuable tools in the clinical evaluation of stroke patients. Objective. This study aimed to compare the ordinal distribution of modified Rankin Scale (mRS) scores at 90 days following an acute ischemic stroke, stratifying patients based on their nutritional status at the time of Stroke Unit admission, as determined by the Bioelectrical Impedance Vector Analysis (BIVA) malnutrition parameter. Methods. We conducted a single-centre prospective observational study on all consecutive patients admitted for acute ischemic stroke to our Stroke Unit between 1 April 2024, and 30 September 2024. We applied the IPW (Inverse Probability Weighting) statistical technique and ordinal logistic regression to compare mRS scores in malnourished and non-malnourished patients. Results. Overall, our study included 195 patients with ischemic stroke assessed using BIVA. Of these, 37 patients (19%) were malnourished. After IPW, we found that malnourished patients had significantly lower rates of favorable 90-day functional outcomes (cOR 3.34, 95% CI 1.74–6.41; p = 0.001). Even after accounting for relevant covariates, malnutrition remained an independent predictor of unfavorable outcomes (acOR 2.79, 95% CI 1.37–5.70; p = 0.005), along with NIHSS score at admission (acOR 1.19, 95% CI 1.11–1.28; p < 0.001), intravenous thrombolysis (acOR 0.28, 95% CI 0.15–0.52; p < 0.001), absolute lymphocyte count (cOR 1.01, 95% CI 1.00–1.02; p = 0.027), and albumin concentration (cOR 0.82, 95% CI 0.75–0.89; p < 0.001). Conclusions. Malnutrition, assessed through Bioelectrical Impedance Vector Analysis (BIVA) at the time of admission to the Stroke Unit, is associated with worse clinical outcomes at 90 days following the ischemic cerebrovascular event.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/nu17050919
- https://www.mdpi.com/2072-6643/17/5/919/pdf?version=1741250783
- OA Status
- gold
- Cited By
- 1
- References
- 39
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4408199021
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4408199021Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/nu17050919Digital Object Identifier
- Title
-
Prognostic Impact of Malnutrition Evaluated via Bioelectrical Impedance Vector Analysis (BIVA) in Acute Ischemic Stroke: Findings from an Inverse Probability Weighting AnalysisWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-03-06Full publication date if available
- Authors
-
Simone Dal Bello, Laura Ceccarelli, Yan Tereshko, Gian Luigi Gigli, Lucio D’Anna, Mariarosaria Valente, Giovanni MerlinoList of authors in order
- Landing page
-
https://doi.org/10.3390/nu17050919Publisher landing page
- PDF URL
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https://www.mdpi.com/2072-6643/17/5/919/pdf?version=1741250783Direct link to full text PDF
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YesWhether a free full text is available
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-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/2072-6643/17/5/919/pdf?version=1741250783Direct OA link when available
- Concepts
-
Bioelectrical impedance analysis, Medicine, Malnutrition, Acute stroke, Weighting, Stroke (engine), Internal medicine, Intensive care medicine, Cardiology, Body mass index, Radiology, Mechanical engineering, Engineering, Tissue plasminogen activatorTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
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2025: 1Per-year citation counts (last 5 years)
- References (count)
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39Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.CI | 206, 228, 242, 252, 263, 274 |
| abstract_inverted_index.Of | 180 |
| abstract_inverted_index.We | 117, 145 |
| abstract_inverted_index.an | 87, 219 |
| abstract_inverted_index.as | 105 |
| abstract_inverted_index.at | 83, 98, 237, 288, 303 |
| abstract_inverted_index.by | 107 |
| abstract_inverted_index.in | 8, 61, 162 |
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| abstract_inverted_index.of | 49, 65, 77, 101, 198, 222, 291 |
| abstract_inverted_index.on | 94, 124 |
| abstract_inverted_index.to | 12, 72, 133, 158, 293 |
| abstract_inverted_index.we | 189 |
| abstract_inverted_index.195 | 172 |
| abstract_inverted_index.95% | 205, 227, 241, 251, 262, 273 |
| abstract_inverted_index.IPW | 148 |
| abstract_inverted_index.The | 1 |
| abstract_inverted_index.all | 125 |
| abstract_inverted_index.and | 5, 28, 41, 54, 141, 154, 164, 268 |
| abstract_inverted_index.for | 129, 214 |
| abstract_inverted_index.had | 194 |
| abstract_inverted_index.its | 29 |
| abstract_inverted_index.mRS | 160 |
| abstract_inverted_index.our | 134, 169 |
| abstract_inverted_index.the | 62, 74, 99, 108, 147, 289, 294, 307 |
| abstract_inverted_index.< | 245, 255, 277 |
| abstract_inverted_index.(cOR | 203, 260, 271 |
| abstract_inverted_index.Even | 211 |
| abstract_inverted_index.IPW, | 188 |
| abstract_inverted_index.This | 69 |
| abstract_inverted_index.Unit | 103, 136 |
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| abstract_inverted_index.body | 50 |
| abstract_inverted_index.days | 85, 305 |
| abstract_inverted_index.from | 20 |
| abstract_inverted_index.has, | 11 |
| abstract_inverted_index.poor | 6 |
| abstract_inverted_index.that | 191 |
| abstract_inverted_index.them | 58 |
| abstract_inverted_index.time | 100, 290 |
| abstract_inverted_index.were | 185 |
| abstract_inverted_index.with | 174, 234, 299 |
| abstract_inverted_index.(19%) | 184 |
| abstract_inverted_index.(BIA) | 27 |
| abstract_inverted_index.(acOR | 225, 239, 249 |
| abstract_inverted_index.(mRS) | 81 |
| abstract_inverted_index.0.28, | 250 |
| abstract_inverted_index.0.82, | 272 |
| abstract_inverted_index.1.01, | 261 |
| abstract_inverted_index.1.19, | 240 |
| abstract_inverted_index.2.79, | 226 |
| abstract_inverted_index.2024, | 140 |
| abstract_inverted_index.2024. | 144 |
| abstract_inverted_index.3.34, | 204 |
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| abstract_inverted_index.April | 139 |
| abstract_inverted_index.BIVA. | 179 |
| abstract_inverted_index.NIHSS | 235 |
| abstract_inverted_index.Scale | 80 |
| abstract_inverted_index.These | 44 |
| abstract_inverted_index.Unit, | 296 |
| abstract_inverted_index.acute | 88, 130 |
| abstract_inverted_index.after | 212 |
| abstract_inverted_index.aimed | 71 |
| abstract_inverted_index.along | 233 |
| abstract_inverted_index.based | 93 |
| abstract_inverted_index.count | 259 |
| abstract_inverted_index.date, | 13 |
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| abstract_inverted_index.lower | 196 |
| abstract_inverted_index.offer | 37 |
| abstract_inverted_index.rapid | 42 |
| abstract_inverted_index.rates | 197 |
| abstract_inverted_index.score | 236 |
| abstract_inverted_index.study | 70, 123, 170 |
| abstract_inverted_index.their | 95 |
| abstract_inverted_index.tools | 60 |
| abstract_inverted_index.using | 16, 178 |
| abstract_inverted_index.worse | 300 |
| abstract_inverted_index.(BIVA) | 113, 287 |
| abstract_inverted_index.90-day | 200 |
| abstract_inverted_index.Rankin | 79 |
| abstract_inverted_index.Stroke | 102, 135, 295 |
| abstract_inverted_index.Vector | 34, 111, 285 |
| abstract_inverted_index.enable | 46 |
| abstract_inverted_index.event. | 310 |
| abstract_inverted_index.making | 57 |
| abstract_inverted_index.scores | 18, 82, 161 |
| abstract_inverted_index.status | 97 |
| abstract_inverted_index.stroke | 9, 66, 132, 176 |
| abstract_inverted_index.these, | 181 |
| abstract_inverted_index.(BIVA), | 36 |
| abstract_inverted_index.0.001), | 246, 256 |
| abstract_inverted_index.0.001). | 210, 278 |
| abstract_inverted_index.0.005), | 232 |
| abstract_inverted_index.0.027), | 267 |
| abstract_inverted_index.albumin | 269 |
| abstract_inverted_index.applied | 146 |
| abstract_inverted_index.between | 3, 137 |
| abstract_inverted_index.compare | 73, 159 |
| abstract_inverted_index.derived | 19 |
| abstract_inverted_index.levels, | 56 |
| abstract_inverted_index.methods | 45 |
| abstract_inverted_index.ordinal | 75, 155 |
| abstract_inverted_index.precise | 47 |
| abstract_inverted_index.status, | 53 |
| abstract_inverted_index.stroke, | 90 |
| abstract_inverted_index.through | 282 |
| abstract_inverted_index.(Inverse | 149 |
| abstract_inverted_index.Analysis | 26, 35, 112, 286 |
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| abstract_inverted_index.Methods. | 116 |
| abstract_inverted_index.Overall, | 168 |
| abstract_inverted_index.Results. | 167 |
| abstract_inverted_index.absolute | 257 |
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| abstract_inverted_index.advanced | 30 |
| abstract_inverted_index.assessed | 177, 281 |
| abstract_inverted_index.clinical | 63, 301 |
| abstract_inverted_index.included | 171 |
| abstract_inverted_index.ischemic | 89, 131, 175, 308 |
| abstract_inverted_index.logistic | 156 |
| abstract_inverted_index.modified | 78 |
| abstract_inverted_index.outcomes | 7, 202, 224, 302 |
| abstract_inverted_index.patients | 10, 92, 127, 173, 183, 193 |
| abstract_inverted_index.relevant | 215 |
| abstract_inverted_index.remained | 218 |
| abstract_inverted_index.valuable | 59 |
| abstract_inverted_index.Impedance | 25, 33, 110, 284 |
| abstract_inverted_index.September | 143 |
| abstract_inverted_index.admission | 238, 292 |
| abstract_inverted_index.composite | 17 |
| abstract_inverted_index.conducted | 118 |
| abstract_inverted_index.evaluated | 15 |
| abstract_inverted_index.favorable | 199 |
| abstract_inverted_index.following | 86, 306 |
| abstract_inverted_index.hydration | 55 |
| abstract_inverted_index.patients. | 67, 166 |
| abstract_inverted_index.predictor | 221 |
| abstract_inverted_index.technique | 153 |
| abstract_inverted_index.Objective. | 68 |
| abstract_inverted_index.Weighting) | 151 |
| abstract_inverted_index.accounting | 213 |
| abstract_inverted_index.admission, | 104 |
| abstract_inverted_index.assessment | 48 |
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| abstract_inverted_index.determined | 106 |
| abstract_inverted_index.evaluation | 64 |
| abstract_inverted_index.functional | 201 |
| abstract_inverted_index.laboratory | 21 |
| abstract_inverted_index.lymphocyte | 258 |
| abstract_inverted_index.parameter. | 115 |
| abstract_inverted_index.regression | 157 |
| abstract_inverted_index.Background. | 0 |
| abstract_inverted_index.Probability | 150 |
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| abstract_inverted_index.consecutive | 126 |
| abstract_inverted_index.covariates, | 216 |
| abstract_inverted_index.independent | 220 |
| abstract_inverted_index.intravenous | 247 |
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| abstract_inverted_index.prospective | 121 |
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| abstract_inverted_index.non-malnourished | 165 |
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| corresponding_author_ids | https://openalex.org/A5015813814 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 7 |
| corresponding_institution_ids | https://openalex.org/I129043915, https://openalex.org/I4210126152 |
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| citation_normalized_percentile.is_in_top_10_percent | True |