ObjectAimed to describe the clinical characteristics of the patients with interictal schizophrenia-like psychoses of epilepsy (SLPE), so as to improve the identification, diagnosis and treatment.MethodsWe collected the cases from January 2017 to December 2019 that diagnosed as "epileptic psychosis/organic mental disorders/brain damage and functional disorders and somatic diseases caused by other mental disorders/organic delusions (schizophrenia-like) disorders" in the medical record system of the Sixth Hospital of Changchun. The discharge records were re-diagnosed by two experienced epilepsy specialists and psychiatrists respectively. Retrospective statistical analysis was performed on the cases identified as SLPE.ResultsA total of 45 patients were diagnosed as SLPE (male: female=1:1.4). The onset age of epilepsy and mental symptoms was (16.4±12.5) years and (35.3±13.4) years respectively. The duration of mental symptoms after first seizure was (18.9±13.4) years. 7 patients (15.6%) were not treated with AEDs, and 26 patients (57.8%) were treated with first generation AEDs. 8 patients (17.8%) had no seizures within 1 year before the onset of mental symptoms, and 28 patients (62.2%) had frequent seizures, even status epilepticus or clustered seizures. 2 patients (4.4%) had generalized tonic-clonic seizure, only 4 patients (8.9%) showed focal impaired awareness seizure, and 39 patients (86.7%) had focal to bilateral tonic-clonic seizure.The PANSS positive symptom score, PANSS negative symptom score and BPRS score were (15.1±4.4), (17.7±4.6) and (44.7±8.4) respectively.ConclusionThere were some features of epilepsy in SLPE, such as early onset age, frequent seizure (some patients were seizure-free), focal epilepsy, and poor AEDs treatment compliance. The onset age of mental symptoms in SLPE was later than Schizophrenia and long duration after first seizure. The PANSS scale showed that the mental symptoms of patients with SLPE were similar to those of patients with schizophrenia, and both positive and negative symptoms existed.
Objective To explore factors that affect the assessment of sexual self-defense capacity and to evaluate the effect of social functions on sexual self-defense capacity in patients with mental retardation. Methods A 1∶1 matched case-control study was carried out, which included 174 sexual assault cases, 87 with mental retardation and 87 without mental retardation. A record of forensic psychiatry assessment designed by ourselves was used to collect the general characteristics. Wechsler Adult Intelligence-Rerisedin China (WAIS-RC) was used to determine the intelligence quotient. Rating Scale of Intellectual Disability (RSID) and Global Assessment Function (GAF) were used to assess social functions. Results Besides factors such as culture, occupation, knowledge about sex and payment claim, the scores of GAF and RSID were also related to the assessment of sexual self-defense capacity. Moreover, the correct ratio of discrimination was 73.1% (yes), 66.9% (impaired) and 87.2% (no), respectively, and the general correct ratio of discrimination was 78.1%. Conclusion Not only social and legal factors but also the level of social functions should be considered in the assessment of sexual self-defense capacity. Therefore, it might be concluded that multiple discriminant analysis can be useful when assessing the sexual self-defense capacity of patients with mental retardation.
Objective To investigate whether antipsychotic drugs will increase the risk of venous thromboembolism (VTE) and pulmonary embolism (PE), and to provide evidence for the prevention of VTE and PE in patients with APs exposure. Methods Databases including PubMed, Web of Science, CNKI, VIP and Elsevier were searched from inception to July 2016 to collect case-control studies and cohort studies on the association between APs exposure and the risk of VTE and PE. The literature were screened according to the inclusion and exclusion criteria, the data were extracted and the bias risk of the included studies were evaluated by two reviewers independently. The Meta-analysis was performed by using Stata 12 software. Results Nineteen studies were included. The results of meta-analysis showed that APs exposure was associated with VTE (OR=1.50, 95%CI 1.30 to 1.74,P<0.001). Exposure to low-potency FGA (OR=2.28, 95%CI 1.02 to 5.10,P=0.045), high-potency FGA (OR=1.68, 95%CI 1.37 to 2.05,P<0.001) and SGA (OR=1.74, 95%CI 1.24 to 2.44,P=0.001) revealed an increased risk of VTE. Exposure to APs also signi?cantly increase the risk of PE (OR=3.69, 95%CI 1.23 to 11.07,P=0.02), especially exposure to FGA (OR=2.54, 95%CI 1.22 to 5.32,P=0.013), but exposure to SGA could not revealed an increased risk of PE. Conclusion FGA and SGA exposure maybe associated with an increase in the risk of developing VTE. And exposure to the FGA could increase the risk of PE. The occurrence of VTE and PE should be monitored when taking Aps.
Objective To compare the incidence of social function disorders in head injury patients with and without craniocerebral injury and to explore the value for mental identification. Methods SDSS (Social Disability Screening Schedule), GAF (Global Assessment Function) and GAS (Global Assessment Scale) instruments were used to test the social function of 56 patients without craniocerebral injury and 55 patients with craniocerebral injury. Results One hundred and eleven patients with head injury were included and identified as head injury with or without craniocerebral injury by CT or MRI. The incidence of social function deficit, tested by using SDSS instrument, was 33.9% (19/56) in patients without craniocerebral injury and 45.5% (25/55) in patients with craniocerebral injury respectively. There was no statistically significant difference between the two groups (χ2=1.544, P=0.214). This was also no statitical difference in both GAS group (t=0.021, P=0.983) and GAF group (t=0.391, P=0.697). Conclusions The limited evidence showed that the incidence of social function deficit of the head injury patients combined with craniocerebral injury is higher than those who without craniocerebral injury, but the difference between the two groups has no statistically significant difference.We could not detect a difference in the incidence of social deficit between those head injury patients with or without craniocerebral injury ones.
ObjectiveTo explore the effects of drug management skill training on lightening the family burden of schizophrenic patients in their recovery period. MethodsBetween December 2011 and December 2013, 101 patients with schizophrenia were randomly divided into experimental group (n=56) and control group (n=45). The experimental group was given drug management skill training, while the control group only received routine follow-up. The course of the research was six months. Both groups were assessed by the positive and negative syndrome scale on patients' psychological symptoms, and family burden scale of diseases was used to assess the burden of the family. ResultsCompared with the controls, patients in the experimental group improved more in their positive symptoms (t=2.692, P=0.008), negative symptoms (t=2.729, P=0.008), general psychopathology symptoms (t=3.231, P=0.002) and the whole psychiatric symptoms (t=3.870, P<0.001). Moreover, the degree of patients' symptom improvement was positively correlated with the degree of family burden lightening (r=0.44, P<0.001). ConclusionFor patients with schizophrenia, reasonable drug management skill training can effectively improve patients' medication compliance, promote treatment effect and lighten family burden.
Speech feature learning is the core and key of speech recognition method for mental illness. Deep feature learning can automatically extract speech features, but it is limited by the problem of small samples. Traditional feature extraction (original features) can avoid the impact of small samples, but it relies heavily on experience and is poorly adaptive. To solve this problem, this paper proposes a deep embedded hybrid feature sparse stack autoencoder manifold ensemble algorithm. Firstly, based on the prior knowledge, the psychotic speech features are extracted, and the original features are constructed. Secondly, the original features are embedded in the sparse stack autoencoder (deep network), and the output of the hidden layer is filtered to enhance the complementarity between the deep features and the original features. Third, the L1 regularization feature selection mechanism is designed to compress the dimensions of the mixed feature set composed of deep features and original features. Finally, a weighted local preserving projection algorithm and an ensemble learning mechanism are designed, and a manifold projection classifier ensemble model is constructed, which further improves the classification stability of feature fusion under small samples. In addition, this paper designs a medium-to-large-scale psychotic speech collection program for the first time, collects and constructs a large-scale Chinese psychotic speech database for the verification of psychotic speech recognition algorithms. The experimental results show that the main innovation of the algorithm is effective, and the classification accuracy is better than other representative algorithms, and the maximum improvement is 3.3%. In conclusion, this paper proposes a new method of psychotic speech recognition based on embedded mixed sparse stack autoencoder and manifold ensemble, which effectively improves the recognition rate of psychotic speech.