Purpose/background: To add to limited evidence on the Abnormal Involuntary Movement Scale (AIMS) as a measure of tardive dyskinesia (TD) in clinical practice settings, the characteristics and correlates of AIMS scores were assessed.
Methods/procedures: Veterans with schizophrenia/schizoaffective, bipolar, or major depressive disorders receiving antipsychotics and at least 1 AIMS score during October 1, 2014, to September 30, 2015, were identified. Tardive dyskinesia was determined by the International Classification of Diseases, Ninth Revision, Clinical Modification, codes. Correlates of AIMS scores were examined using χ or t tests. Odds ratios and β parameters with 95% confidence intervals for categorical and continuous variables associated with AIMS scores were derived from a multivariate logistic and linear regression, respectively.
Findings/results: Among 7985 veterans receiving antipsychotics, only 4706 (58.9%) had at least 1 AIMS examination. Of these, 229 (4.9%) were diagnosed with possible TD. The mean total AIMS scores and AIMS awareness/incapacitation scores were significantly higher for patients with TD (both P < 0.0001). Comparing diagnostic threshold criteria of AIMS ratings, only 17.5% to 37.1% of veterans with TD were successfully identified. Among TD patients, 21.4% had a total score of moderate-severe and 15.3% had ratings of at least mild movements in 2 or more body regions. In the regression analyses, being older, African-American, having schizophrenia/schizoaffective disorder, and receiving antipsychotics or benztropine significantly increased the severity of AIMS scores. Higher AIMS scores were not predictive of outcomes other than marital status in socioeconomic or healthcare domains.
Implications/conclusions: Although the AIMS is essential for TD research, its value in clinical practice without training and oversight remains unclear. Efforts to adapt screening procedures to clinical needs may be worthwhile.
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http://dx.doi.org/10.1097/JCP.0000000000001229 | DOI Listing |
Sci Rep
December 2024
Nehme and Therese Tohme Multiple Sclerosis Center, American University of Beirut Medical Center, Riad El-Solh, PO Box 11-0236, 1107 2020, Beirut, Lebanon.
Fatigue is one of the most prevalent and disabling symptoms among patients with MS, but there is limited research investigating the longitudinal determinants of fatigue progression. This study aims to identify the sociodemographic, behavioral and clinical characteristics, and therapeutic regimens that are correlated with worsening fatigue over time in patients diagnosed with MS. This is a retrospective chart review of 483 patients.
View Article and Find Full Text PDFEur Heart J Cardiovasc Imaging
December 2024
Division of Radiology, Severance Cardiovascular Hospital, Yonsei University College of Medicine, Seoul, South Korea.
Aims: This study compared echocardiography (echo) and cardiac computed tomography (CT) in measuring the Wilkins score and evaluated the potential added benefit of CT in predicting immediate percutaneous mitral valvuloplasty (PMV) outcomes in rheumatic mitral stenosis (MS) patients deemed eligible for PMV by echo.
Methods And Results: From a multicentre registry of 3,140 patients with at least moderate MS, we included 96 patients (age 56.4±11.
Neuro Endocrinol Lett
December 2024
SC&C marketing and sociology research agency, 110 00 Prague, Czech Republic.
The quality of prenatal care for women during pregnancy, in terms of monitoring somatic development, is generally high. The study aims to evaluate the psychosocial situation (well being) of pregnant women during a physiological pregnancy. The care of psychosocial issues of pregnant women is not systematic and often does not occur at all.
View Article and Find Full Text PDFFront Comput Neurosci
December 2024
School of Health Sciences and Engineering, University of Shanghai for Science and Technology, Shanghai, China.
This study aims to enhance the classification accuracy of adverse events associated with the da Vinci surgical robot through advanced natural language processing techniques, thereby ensuring medical device safety and protecting patient health. Addressing the issues of incomplete and inconsistent adverse event records, we employed a deep learning model that combines BERT and BiLSTM to predict whether adverse event reports resulted in patient harm. We developed the Bert-BiLSTM-Att_dropout model specifically for text classification tasks with small datasets, optimizing the model's generalization ability and key information capture through the integration of dropout and attention mechanisms.
View Article and Find Full Text PDFInt J Womens Health
December 2024
Department of Infection Control, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, 210029, People's Republic of China.
Purpose: This study aims to examine the risk factors for catheter-associated urinary tract infection (CAUTI) following radical hysterectomy for cervical cancer (CC). Furthermore, the study seeks to develop a visual model that can effectively assist physicians in improving their proficiency in diagnosing, treating, and preventing CAUTIs.
Patients And Methods: 48 subjects who developed CAUTI postoperatively were assigned to the infection group.
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