speech disturbance
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2021 ◽  
Vol 14 (12) ◽  
pp. e245484
Author(s):  
David Vaughan ◽  
Adrinda Affendi ◽  
Patrick Sheahan ◽  
Brian Sweeney

Acquired vocal cord paralysis (VCP) is caused by dysfunction or injury of one or both recurrent laryngeal nerves. Here we report a 41-year-old man with spinocerebellar atrophy, autosomal recessive type 10 (SCAR10) due to an autosomal recessive mutation in the ANO10 gene, with VCP as the presenting symptom. He later developed ataxia and speech disturbance.


2021 ◽  
Vol 8 (2) ◽  
pp. 54-61
Author(s):  
Anmar jumaa Ghali ◽  
Khalid Ayad Al-Majmae ◽  
Ahmed Adnan Nabat

Cerebral palsy was a primary neuromotor disorder that affects the development of movement, muscular tone and posture due to injury to the developing brain in prenatal, natal, or post-natal period. cp is non progressive disease but it is changeable features with period. The objective of this study is to identify clinical types of cerebral palsy and neuro-disabilities associated with cerebral palsy patient. Data (2019-2020) on 100 children of cerebral palsy in central teaching hospital in Baghdad analysis include clinical patterns of cerebral palsy and topographic classification of spastic cerebral palsy. also, the complication and neurological disabilities associated with cerebral palsy. In this analysis found most of cerebral palsy patients (84%) were spastic according to topographic classification, (47%) of spastic cerebral palsy was diplegic type. (29%) quadriplegic cerebral palsy and (8%) of hemiplegic cerebral palsy. About neurological complication and disabilities associated with cerebral palsy, (79%) of cerebral palsy patients had speech disturbance. (53%) had epilepsy, (43%) Micro acephaly, (32%) of patients had growth retardation, (29 %) had ocular problems, and (15%) of cerebral palsy patients had mental retardation. In conclusions; the most common type of cerebral palsy was spastic cerebral palsy & according to a topographic classification diplegic spastic cerebral palsy was the most common type of Spastic cerebral palsy. About neurodisabilities associated with cerebral palsy, the most common disabilities were speech disturbance and epilepsy.


2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Sunny X. Tang ◽  
Reno Kriz ◽  
Sunghye Cho ◽  
Suh Jung Park ◽  
Jenna Harowitz ◽  
...  

AbstractComputerized natural language processing (NLP) allows for objective and sensitive detection of speech disturbance, a hallmark of schizophrenia spectrum disorders (SSD). We explored several methods for characterizing speech changes in SSD (n = 20) compared to healthy control (HC) participants (n = 11) and approached linguistic phenotyping on three levels: individual words, parts-of-speech (POS), and sentence-level coherence. NLP features were compared with a clinical gold standard, the Scale for the Assessment of Thought, Language and Communication (TLC). We utilized Bidirectional Encoder Representations from Transformers (BERT), a state-of-the-art embedding algorithm incorporating bidirectional context. Through the POS approach, we found that SSD used more pronouns but fewer adverbs, adjectives, and determiners (e.g., “the,” “a,”). Analysis of individual word usage was notable for more frequent use of first-person singular pronouns among individuals with SSD and first-person plural pronouns among HC. There was a striking increase in incomplete words among SSD. Sentence-level analysis using BERT reflected increased tangentiality among SSD with greater sentence embedding distances. The SSD sample had low speech disturbance on average and there was no difference in group means for TLC scores. However, NLP measures of language disturbance appear to be sensitive to these subclinical differences and showed greater ability to discriminate between HC and SSD than a model based on clinical ratings alone. These intriguing exploratory results from a small sample prompt further inquiry into NLP methods for characterizing language disturbance in SSD and suggest that NLP measures may yield clinically relevant and informative biomarkers.


2021 ◽  
Vol 27 (3) ◽  
pp. 267-269
Author(s):  
Renyu Liu ◽  
Marc Fisher ◽  
Anthony Rudd ◽  
Jing Zhao

2020 ◽  
Author(s):  
Melike Ersoy ◽  
Semra Yılmaz ◽  
Serdar Ceylaner

Abstract Background: Hyperprolinemia type 1 (HPI) is an autosomal recessive inborn disease caused by mutations/deletions of PRODH gene, which is located on chromosome 22q11. The clinic spectrum involves mainly delayed psychomotor development, mild-to-severe mental retardation, neuropsychiatric symptoms and epilepsy. Although HPI can easily be diagnosed in patients undergoing metabolic screening tests, there is no effective therapy protocol in use. There are studies showing that it does most of its clinical findings by disrupting mitochondria function. Case report: We present a long-term follow-up of a four-year-old girl with mild neuromotor retardation and speech disturbance, diagnosed with HPI and treated with antioxidant therapy (vitamin C, CoenzymeQ10, vitamin B complex and L-carnitine) for six years. It has been shown that antioxidant therapy decreases proline levels properly and provides clinical improvement.


2020 ◽  
Vol 2 (25(52)) ◽  
pp. 24-27
Author(s):  
Veronika Nikolaevna Perevalova ◽  
Elena Anatolyevna Larina

This article substantiates the importance of neuropsychological examination in speech therapy practice. The article analyzes and summarizes the results of a neuropsychological and speech therapy examination of preschool children with an erased form of dysarthria.


2019 ◽  
Vol 16 (9-10) ◽  
pp. 330-6
Author(s):  
Soelatin Winarno ◽  
Oemar Wirjohatmodjo ◽  
Harijono Harijono ◽  
Siti Alfinah ◽  
Wirawan Wirawan

Thirty-five cases of cerebral palsy patients admitted to the Institution for Crippled Children, Semarang, have been discussed. Diagnosis was made by a team comprising an orthopedic surgeon, a neurologist, a paediatrician, and a psychologist. Treatment performed consisted of muscle relaxant, physiotherapy, and also surgery. Introduction, material arid method of observation, treatment, sex distribution; classification, speech disturbance, mental status, results of treatment, and comparison with the cases in Bombay, form the sequence of this report.


2019 ◽  
Vol 14 (4) ◽  
pp. 409-416
Author(s):  
Olli S Mattila ◽  
Tuukka Puolakka ◽  
Juhani Ritvonen ◽  
Saana Pihlasviita ◽  
Heini Harve ◽  
...  

Background Accurate identification of acute stroke by Emergency Medical Dispatchers (EMD) is essential for timely and purposeful deployment of Emergency Medical Services (EMS), and a prerequisite for operating mobile stroke units. However, precision of EMD stroke recognition is currently modest. Aims We sought to identify targets for improving dispatcher stroke identification. Methods Dispatch codes and EMS patient records were cross-linked to investigate factors associated with an incorrect dispatch code in a prospective observational cohort of 625 patients with a final diagnosis of acute stroke or transient ischemic attack (TIA), transported to our stroke center as candidates for recanalization therapies. Call recordings were analyzed in a subgroup that received an incorrect low-priority dispatch code indicating a fall or unknown acute illness ( n = 46). Results Out of 625 acute stroke/TIA patients, 450 received a high-priority stroke dispatch code (sensitivity 72.0%; 95% CI, 68.5–75.5). Independent predictors of dispatcher missed acute stroke included a bystander caller (aOR, 3.72; 1.48–9.34), confusion (aOR, 2.62; 1.59–4.31), fall at onset (aOR, 1.86; 1.24–2.78), and older age (aOR [per year], 1.02; 1.01–1.04). Of the analyzed call recordings, 71.7% revealed targets for improvement, including failure to recognize a Face Arm Speech Time (FAST) test symptom (21/46 cases, 18 with speech disturbance), or failure to thoroughly evaluate symptoms (12/46 cases). Conclusions Based on our findings, efforts to improve dispatcher stroke identification should primarily focus on improving recognition of acute speech disturbance, and implementing screening of FAST-symptoms in emergency phone calls revealing a fall or confusion. Clinical Trial Registration URL: http://www.clinicaltrials.gov . Unique identifier: NCT02145663.


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