Respiratory and functional status of inpatients with stroke: a cross-sectional study
Bibliographic record
Abstract
Background Respiratory function and functional status are often impaired after stroke, yet respiratory assessment before rehabilitation is frequently overlooked. Few studies explore these parameters in the acute and subacute phases, which are critical for recovery. Understandingtheir relationship may guide more effective rehabilitation.Objectives To characterize respiratory function and functional status in stroke inpatients at rehabilitation admission. Secondary objectives were to examine correlations between them, and to assess the influence of sex, age, comorbidities, body mass index, stroke type, and time since stroke on these correlations.Methods A cross-sectional study included stroke inpatients admitted to rehabilitation between 2023 and 2024. Demographics, Maximal Inspiratory Pressure (MIP), Maximal Expiratory Pressure (MEP), Peak Cough Flow (PCF), Trunk Impairment Scale (TIS), and Functional Independence Measure (FIM) were collected.Results Eighty-four participants (67% male; 49% aged 60–69; 48% > 25 kg/m2; 70% ischemic stroke; 38 median days post-stroke) were included. Respiratory function was: MIP (median: 48.5 cmH2O; interquartile range [IQR]: 28.5;66), MEP (mean: 65.1 cmH2O; standard deviation [SD]: 26.1) and PCF (mean: 218.5 L/min; SD: 142.1), which were majorly below reference values, except for PCF. Functional status was as follows: FIM (median: 84; IQR: 70.75;93) and TIS (median: 14; IQR: 10.75;18). Correlation analysis showed weak correlation between PCF and FIM (R = 0.35) and TIS (R = 0.30), and moderate correlations between FIM and MIP (R = 0.47) and MEP (R = 0.42). Demographics and stroke subtypes did not significantly impact these correlations.Conclusions Respiratory and functional impairments are common early after stroke. Their significant correlation supports routine respiratory assessment at rehabilitation admission to guide individualized interventions, regardless of demographics or stroke subtypes.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".