Neural Correlates of Urinary Retention in Lateral Medullary Infarction
Bibliographic record
Abstract
PURPOSE: The brainstem plays an important role in the control of micturition, and brainstem strokes are known to present with micturition dysfunction. Micturition dysfunction in cases of lateral medullary infarction (LMI) is uncommon, but often manifests as urinary retention. In this study, we investigated the neuro-anatomical correlates of urinary retention in patients with LMI. METHODS: This was a hospital-based retrospective study conducted in the neurology unit of a quaternary-level teaching hospital. Inpatient records from January 2008 to May 2018 were searched using a computerized database. Cases of isolated LMI were identified and those with micturition dysfunction were reviewed. MRI brain images of all patients were viewed, and individual lesions were mapped onto the Montreal Neurological Institute (MNI) space manually using MRIcron. Nonparametric mapping toolbox software was used for voxel-based lesion-symptom analysis. The Liebermeister test was used for statistical analysis, and the resultant statistical map was displayed on the MNI template using MRIcron. RESULTS: During the study period, 31 patients with isolated LMI were identified. Their mean age was 48 years and 28 (90%) were male. Six of these patients (19%) developed micturition dysfunction. All 6 patients had urinary retention and 1 patient each had urge incontinence and overflow incontinence. In patients with LMI, the lateral tegmentum of the medulla showed a significant association with urinary retention. CONCLUSION: In patients with isolated LMI, we postulate that disruption of the descending pathway from the pontine micturition centre to the sacral spinal cord at the level of the lateral tegmentum results in urinary retention.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".