Neurogenic speech sequelae following suicide attempt by hanging: a case report
Bibliographic record
Abstract
BACKGROUND: Attempting suicide by hanging has become one of the most preferred means among adolescents. Individuals who survive a suicide attempt by hanging have a range of deficits, including neuropsychological, neuropsychiatric, pulmonary and even speech and language deficits. Literature regarding speech and language deficits in cases of near hanging is especially limited. OBJECTIVE: This study aimed to demonstrate the sequelae of neurogenic speech deficits following a suicide attempt by hanging, the treatment strategies, and prognostic issues in one such case. METHODS: We report of Patient X who attempted suicide by hanging. The patient was admitted and a detailed speech and language evaluation was completed. RESULTS: Patient X was diagnosed with hypoxic-ischemic encephalopathy with organic amnesic syndrome. Consequent to the neurogenic insult, the patient demonstrated speech deficits that were characterized by moderate flaccid dysarthria and neurogenic stuttering. Patient X underwent a week of treatment, subsequent to which there was an improvement in certain speech subsystems. However, the neurogenic stuttering symptoms did not resolve completely even post therapy. CONCLUSION: Individuals who survive a suicide attempt by hanging have a range of deficits, including speech deficits that need to be addressed by a speech language pathologist. This case report is an eye opener for speech language pathologists regarding their role in such cases.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".