27 research outputs found

    The role of liquid based cytology and ancillary techniques in the peritoneal washing analysis: our institutional experience

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    Background The cytological analysis of peritoneal effusions serves as a diagnostic and prognostic aid for either primary or metastatic diseases. Among the different cytological preparations, liquid based cytology (LBC) represents a feasible and reliable method ensuring also the application of ancillary techniques (i.e immunocytochemistry-ICC and molecular testing). Methods We recorded 10348 LBC peritoneal effusions between January 2000 and December 2014. They were classified as non-diagnostic (ND), negative for malignancy-NM, atypical-suspicious for malignancy-SM and positive for malignancy-PM. Results The cytological diagnosis included 218 ND, 9.035 NM, 213 SM and 882 PM. A total of 8048 (7228 NM, 115SM, 705 PM) cases with histological follow-up were included. Our NM included 21 malignant and 7207 benign histological diagnoses. Our 820 SMs+PMs were diagnosed as 107 unknown malignancies (30SM and 77PM), 691 metastatic lesions (81SM and 610PM), 9 lymphomas (2SM and 7PM), 9 mesotheliomas (1SM and 8SM), 4 sarcomas (1SM and 3PM). Primary gynecological cancers contributed with 64% of the cases. We documented 97.4% sensitivity, 99.9% specificity, 98% diagnostic accuracy, 99.7% negative predictive value (NPV) and 99.7% positive predictive value (PPV). Furthermore, the morphological diagnoses were supported by either 173 conclusive ICC results or 50 molecular analyses. Specifically the molecular testing was performed for the EGFR and KRAS mutational analysis based on the previous or contemporary diagnoses of Non Small Cell Lung Cancer (NSCLC) and colon carcinomas. We identified 10 EGFR in NSCCL and 7 KRAS mutations on LBC stored material. Conclusions Peritoneal cytology is an adjunctive tool in the surgical management of tumors mostly gynecological cancers. LBC maximizes the application of ancillary techniques such as ICC and molecular analysis with feasible diagnostic and predictive yields also in controversial cases.info:eu-repo/semantics/publishedVersio

    Maternal and offspring intelligence in relation to BMI across childhood and adolescence

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    Objective: The present study tested the association between both mothers’ and offspring’s intelligence and offspring’s body mass index (BMI) in youth. Method: Participants were members of the National Longitudinal Survey of Youth 1979 (NLSY-79) Children and Young Adults cohort (n = 11,512) and their biological mothers who were members of the NLSY-79 (n = 4932). Offspring’s IQ was measured with the Peabody Individual Achievement Test (PIAT). Mothers’ IQ was measured with the Armed Forces Qualification Test (AFQT). A series of regression analyses tested the association between IQ and offspring’s BMI by age group, while adjusting for pre-pregnancy BMI and family SES. The analyses were stratified by sex and ethnicity (non-Black and non-Hispanic, Black, and Hispanic). Results: The following associations were observed in the fully adjusted analyses. For the non-Blacks and non-Hispanics, a SD increment in mothers’ IQ was negatively associated with daughters’ BMI across all age-groups, ranging from β = −0.12 (95% CI −0.22 to −0.02, p = 0.021) in late childhood, to β = −0.17 (95% C.I. −0.27 to −0.07, p = 0001), in early adolescence and a SD increment in boys’ IQ was positively associated with their BMI in early adolescence β = 0.09 (95% CI 0.01–0.18, p = 0.031). For Blacks, there was a non-linear relationship between mothers’ IQ and daughters’ BMI across childhood and between girls’ IQ and BMI across adolescence. There was a positive association between mothers’ IQ and sons’ BMI in early adolescence (β = 0.17, 95% CI 0.02–0.32, p = 0.030). For Hispanic boys, there was a positive IQ-BMI association in late childhood (β = 0.19, 95% CI 0.05–0.33, p = 0.008) and early adolescence (β = 0.17, 95% CI 0.04–0.31, p = 0.014). Conclusion: Mothers’ IQ and offspring’s IQ were associated with offspring’s BMI. The relationships varied in direction and strength across ethnicity, age group and sex. Obesity interventions may benefit from acknowledging the heterogeneous influence that intelligence has on childhood BMI
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