RESUMO
OBJECTIVE: Aim: The aim of the study was to investigate the incidence of IBD in gastrointestinal surgery patients and record the disease's characteristics and treatment. PATIENTS AND METHODS: Materials and Methods: A search was carried out in the archives of the gastroenterology clinics of the University General Hospital of Ioannina and the General Hospital of Ioannina "G. Hatzikosta" in Greece. All cases of operated patients from 1980 to 2018 were examined. The duration of the study was 4 months. Data were analyzed with the SPSS program, v.28. RESULTS: Results: The total sample consisted of 1464 patients (n=1464). Most of them (915-62.5%) came from the University General Hospital of Ioannina, while the rest (549-37.5%) came from the GHI hospital "G. Hatzikosta". The mean age of the patients was 47 years (M=47.26, SD=17.34, Min=<1 month, Max=95 years). From the total sample, 58 patients (4%) suffered from IBD; most were men (42-72.41%). Their mean age was approximately 50 years (M=49.63, SD=16.48, Min=25 years, Max=77 years, range=52 years) and most belonged to the age groups of 31-40 years (11 patients- 19.6%) and 21-30 years and 61-70 years (10 patients-17.9%). The perianal disease was present in 43.1% (25 patients). The most frequent type of operation was fistula resection, ligation, curettage-biopsy (24.1%) and opening-drainage (22.4%-13 patients) and the most frequent type of anesthesia was general anesthesia (93.1%-54 patients). CONCLUSION: Conclusions: This long-term study of the patients' data followed up over time showed that the possibility of surgery in patients with IBD is mitigated through systematic monitoring and multifaceted therapeutic treatment.The perianal disease which appeared more often in men shows that it can be diagnosed early and at an early stage and with the new minimally invasive techniques the patient with IBD can be treated with a better quality of life.
Assuntos
Doença de Crohn , Doenças Inflamatórias Intestinais , Masculino , Humanos , Pessoa de Meia-Idade , Feminino , Doença de Crohn/diagnóstico , Doença de Crohn/tratamento farmacológico , Doença de Crohn/cirurgia , Qualidade de Vida , Doenças Inflamatórias Intestinais/epidemiologia , Doenças Inflamatórias Intestinais/cirurgiaRESUMO
Currently, researchers spend significant time manually searching through large volumes of data produced during scanning probe imaging to identify specific patterns and motifs formed via self-assembly and self-organization. Here, we use a combination of Monte Carlo simulations, general statistics, and machine learning to automatically distinguish several spatially correlated patterns in a mixed, highly varied data set of real AFM images of self-organized nanoparticles. We do this regardless of feature-scale and without the need for manually labeled training data. Provided that the structures of interest can be simulated, the strategy and protocols we describe can be easily adapted to other self-organized systems and data sets.