Surgical site infection after caesarean section. Space for post-discharge surveillance improvements and reliable comparisons

Surgical site infections (SSI) after caesarean section (CS) represent a substantial health system concern. Surveying SSI has been associated with a reduction in SSI incidence. We report the findings of three (2008, 2011 and 2013) regional active SSI surveillances after CS in community hospital of the Latium region determining the incidence of SSI. Each CS was surveyed for SSI occurrence by trained staff up to 30 post-operative days, and association of SSI with relevant characteristics was assessed using binomial logistic regression. A total of 3,685 CS were included in the study. A complete 30 day post-operation follow-up was achieved in over 94% of procedures. Overall 145 SSI were observed (3.9% cumulative incidence) of which 131 (90.3%) were superficial and 14 (9.7%) complex (deep or organ/space) SSI; overall 129 SSI (of which 89.9% superficial) were diagnosed post-discharge. Only higher NNIS score was significantly associated with SSI occurrence in the regression analysis. Our work provides the first regional data on CS-associated SSI incidence, highlighting the need for a post-discharge surveillance which should assure 30 days post-operation to not miss data on complex SSI, as well as being less labour intensive

Familial aggregation of MATRICS Consensus Cognitive Battery scores in a large sample of outpatients with schizophrenia and their unaffected relatives

Background The increased use of the MATRICS Consensus Cognitive Battery (MCCB) to investigate cognitive dysfunctions in schizophrenia fostered interest in its sensitivity in the context of family studies. As various measures of the same cognitive domains may have different power to distinguish between unaffected relatives of patients and controls, the relative sensitivity of MCCB tests for relative-control differences has to be established. We compared MCCB scores of 852 outpatients with schizophrenia (SCZ) with those of 342 unaffected relatives (REL) and a normative Italian sample of 774 healthy subjects (HCS). We examined familial aggregation of cognitive impairment by investigating within-family prediction of MCCB scores based on probands' scores.Methods Multivariate analysis of variance was used to analyze group differences in adjusted MCCB scores. Weighted least-squares analysis was used to investigate whether probands' MCCB scores predicted REL neurocognitive performance.Results SCZ were significantly impaired on all MCCB domains. REL had intermediate scores between SCZ and HCS, showing a similar pattern of impairment, except for social cognition. Proband's scores significantly predicted REL MCCB scores on all domains except for visual learning.Conclusions In a large sample of stable patients with schizophrenia, living in the community, and in their unaffected relatives, MCCB demonstrated sensitivity to cognitive deficits in both groups. Our findings of significant within-family prediction of MCCB scores might reflect disease-related genetic or environmental factors

The association between insight and depressive symptoms in schizophrenia: Undirected and Bayesian network analyses

Background. Greater levels of insight may be linked with depressive symptoms among patients with schizophrenia, however, it would be useful to characterize this association at symptom-level, in order to inform research on interventions. Methods. Data on depressive symptoms (Calgary Depression Scale for Schizophrenia) and insight (G12 item from the Positive and Negative Syndrome Scale) were obtained from 921 community-dwelling, clinically-stable individuals with a DSM-IV diagnosis of schizophrenia, recruited in a nationwide multicenter study. Network analysis was used to explore the most relevant connections between insight and depressive symptoms, including potential confounders in the model (neurocognitive and social-cognitive functioning, positive, negative and disorganization symptoms, extrapyramidal symptoms, hostility, internalized stigma, and perceived discrimination). Bayesian network analysis was used to estimate a directed acyclic graph (DAG) while investigating the most likely direction of the putative causal association between insight and depression. Results. After adjusting for confounders, better levels of insight were associated with greater self-depreciation, pathological guilt, morning depression and suicidal ideation. No difference in global network structure was detected for socioeconomic status, service engagement or illness severity. The DAG confirmed the presence of an association between greater insight and self-depreciation, suggesting the more probable causal direction was from insight to depressive symptoms. Conclusions. In schizophrenia, better levels of insight may cause self-depreciation and, possibly, other depressive symptoms. Person-centered and narrative psychotherapeutic approaches may be particularly fit to improve patient insight without dampening self-esteem

On the Implementation of Computerized Adaptive Observations for Psychological Assessment

The use of observational tools in psychological assessment has decreased in recent years, mainly due to its personnel and time costs, and researchers have not explored methodological innovations like adaptive algorithms in observational assessment. In the present study, we introduce the behavior-driven observation procedure to develop, test, and implement observational adaptive instruments. In Study 1, we use a preexisting observational checklist to evaluate nonverbal behaviors related to psychotic symptoms and to specify the adaptive algorithm\u2019s model. We fit the model to observational data collected from 114 participants. The results support the model\u2019s goodness of fit. In Study 2, we use the estimated model parameters to calibrate the adaptive procedure and test the algorithm for accuracy and efficiency in adaptively reconstructing 58 nonadaptively collected response patterns. The results show the algorithm\u2019s good accuracy and efficiency, with a 40% average reduction in the number of administered items. In Study 3, we used real raters to test the adaptive checklist built with behavior-driven observation. The results indicate adequate intrarater agreement and good consistency of the observed response patterns. In conclusion, the results support the possibility of using behavior-driven observation to create accurate and affordable (in terms of resources) observational assessment tools