Association between spatial neglect and impaired verticality perception after stroke: A systematic review
Bibliographic record
Abstract
Background: Although most research on spatial neglect (SN) has focused on spatial perception deficits with regard to the lateral (left-right) axis, deficits of spatial perception with regard to the vertical (up-down) axis, such as disturbances in the perception of verticality (e.g., judgement of vertical orientations), have also been suggested. Objective: We aimed to systematically analyse reported associations between SN and characteristics of verticality perception while considering the time post-stroke. Methods: PubMed, Web of Science, Scopus, PubPsych and PsycArticles databases were searched on May 24, 2022 for articles written in English that evaluated the association between SN and verticality perception (i.e., the subjective visual vertical [SVV], subjective postural vertical [SPV] and subjective haptic vertical [SHV]) in adults after stroke. Left and right SN were considered and had to be assessed using standardized methods. Data were manually extracted, and risk of bias was assessed with the Newcastle-Ottawa Scale. The tilt of the line/chair relative to the gravitational vector and its direction, together with uncertainty (i.e., variability across measurements), were evaluated. Results: Thirteen studies were included (431 participants after stroke); at least 191 participants exhibited SN. Mainly the first 3 to 6 months post-stroke were evaluated. SN was associated with SVV misperception, which resulted in larger SVV tilts (mostly in the contralesional direction) and uncertainty in participants with than without SN. SVV tilt magnitudes ranged from a mean/median of -8.9° to -2.3° in SN participants and from -1.6° to 0.6° in non-SN participants, the latter falling within normative ranges. For SPV and SHV measurements, the magnitude of tilt and the uncertainty were insufficiently assessed or results were inconclusive. Conclusions: SN was associated with larger SVV tilts and uncertainty, which suggests that SVV misperception is a key feature of SN. This observation highlights the importance of regular SVV assessment in people with SN in clinical practice.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".