ObjectiveTo systematically evaluate the relationship between the-2548G/A polymorphism in the leptin gene and antipsychotic-induced weight gain (AIWG). MethodsLiterature for the relationship between the-2548G/A polymorphism in the leptin gene and AIWG was retrieved in electronic databases including PubMed, EMbase, CNKI and WanFang Data from establishment dates to June, 2013. Two reviewers independently screened studies according to the inclusion and exclusion criteria, extracted data and evaluated the methodological quality of the included studies. Then meta-analysis was performed using RevMan 5.2 software. ResultsA total of 7 case-control studies were included, involving 404 AIWG cases and 508 controls (patients with no significant changes of weight after taking antipsychotic drugs). The results of meta-analysis showed that, regarding the total population, the-2548G/A polymorphism of the leptin gene was not associated with AIWG (OR=1.16, 95%CI 0.70 to 1.93, P=0.57). After stratification analysis, according to Chinese or non-Chinese origin, the results showed that significant association was found between the-2548G/A polymorphism of leptin gene and AIWG for Chinese (OR=2.15, 95%CI 1.41 to 3.26, P=0.000 4) but not for non-Chinese (OR=0.69, 95%CI 0.45 to 1.07, P=0.10). ConclusionThe current evidence suggests that the-2548G/A polymorphism in the leptin gene is associated with increased risk of AIWG for Chinese. Due to limited quantity of the included studies, the aforementioned conclusion needs to be further validate by more high-quality and large-scale studies.
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.
ObjectivesTo systematically review the clinical efficacy and safety of antipsychotics for delirium. MethodsDatabases including The Cochrane Library (Issue 5, 2015), PubMed, MEDLINE, EMbase, CNKI, VIP and WanFang Data were electronically searched for randomized controlled trials (RCTs) about antipsychotics compared with placebo/blank for delirium from inception to May 2015. We also hand-searched related conference proceedings and references of included studies for additional studies. Two reviewers independently screened literature, extracted data, and assessed the risk of bias of included studies. Then, meta-analysis was conducted by using RevMen 5.3 software. ResultsA total of 7 RCTs involving 712 patients were included. The results of meta-analysis showed that there were no significant differences between the antipsychotics group and the placebo/blank group in mortality (RR=1.00, 95%CI 0.90 to 1.10, P=0.99), duration of delirium (MD=-1.53, 95%CI -4.95 to 1.89, P=0.38), length of stay (MD=-0.89, 95%CI -7.69 to 5.90, P=0.80), and ICU stay time (MD=-3.70, 95%CI -15.83 to 8.43, P=0.55). Compared with the placebo/ blank group, the antipsychotics could reduce the severity of delirium (SMD=-1.62, 95%CI -2.32 to -0.93, P<0.000 01). ConclusionCurrent evidence shows that the efficacy of antipsychotics in the treatment of delirium is not clear. Due to the limited quantity and quality of the included studies, the above conclusion needs to be further verified by more high quality studies.
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.
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.