C 12 H 22 CdN4O14, triclinic, P¯ (no. 2), a = 7.188(2) Å, b = 8.895(3) Å, c = 9.771(3) Å, α = 63.148(3)°, β = 76.750(3)°, γ = 66.225(3)°, V = 509.2(3) Å 3 , Z = 1, Rgt(F) = 0.0253, wR ref (F 2 ) = 0.0676, T = 296(2) K. CCDC no.: 1484775The crystal structure is shown in the gure. Tables 1 and 2 contain details of the measurement method and a list of the atoms including atomic coordinates and displacement parameters. Source of materialThe title compound was synthesized by a hydrothermal method under autogenous pressure. A mixture of CdCl 2 ·H 2 O

Inflammatory bowel diseases (IBD) is a term referring to chronic and recurrent gastrointestinal disease. It includes Crohn’s disease (CD) and ulcerative colitis (UC). It is undeniable that presenting features may be unclear and do not enable differentiation between disease types. Therefore, additional information, obtained during the analysis, can definitely provide a potential way to differentiate between UC and CD. For that reason, finding the optimal logistic model for further analysis of collected medical data, is a main factor determining the further precisely defined decision class for each examined patient. In our study, 152 patients with CD or UC were included. The collected data concerned not only biochemical parameters of blood but also very subjective information, such as data from interviews. The built-in logistics model with very high precision was able to assign patients to the appropriate group (sensitivity = 0.84, specificity = 0.74, AUC = 0.93). This model indicates factors differentiating between CD and UC and indicated odds ratios calculated for significantly different variables in these two groups. All obtained parameters of the model were checked for statistically significant. The constructed model was able to be distinguish between ulcerative colitis and Crohn’s disease.

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The article presents the process of building a logistic regression model, which aims to support the decision-making process in medicine. Currently, there is no precise diagnosis for ulcerative colitis (UC) and Crohn's disease (CD). Specialist physicians must exclude many other diseases occurring in the colon. The first goal of this study is a retrospective analysis of medical data of patients hospitalized in the Department of Gastroenterology and Internal Diseases and finding the symptoms differentiating the two analyzed diseases. The second goal is to build a system that clearly points to UC or CD, which shortens the time of diagnosis and facilitates the treatment of patients. The work focuses on building a model that can be the basis for the construction of classifiers, which are one of the basic elements in the medical recommendation system. The developed logistic regression model will define the probability of the disease and will indicate the statistically significant changes that affect the onset of the disease. The value of probability will be one of the main reasons for the decision.

OBJECTIVE The Chicago Chiari Outcome Scale (CCOS) serves as a standardized clinical outcome evaluation tool among patients with Chiari malformation type I (CM-I). While the reliability of this scale has been proven for pediatric patients, the literature lacks CCOS validation when used solely in adults. Therefore, this study aimed to determine the validity of the CCOS in an external cohort of adult patients. METHODS The authors retrospectively analyzed the medical records of symptomatic patients with CM-I who underwent posterior fossa decompression between 2010 and 2018 in six neurosurgical departments. Each patient was clinically assessed at the latest available follow-up. Gestalt outcome was determined as improved, unchanged, or worsened compared with the preoperative clinical state. Additionally, the CCOS score was calculated for each patient based on the detailed clinical data. To verify the ability of the CCOS to determine clinical improvement, the area under the receiver operating characteristic (AUROC) curve was evaluated. A logistic regression analysis using all four components of the CCOS (pain symptoms, nonpain symptoms, functionality, and complications) was performed to establish predictors of the improved outcome. RESULTS Seventy-five individuals with a mean age of 42 ± 15.32 years were included in the study. The mean follow-up duration was 52 ± 33.83 months. Considering gestalt outcome evaluation, 41 patients (54.7%) were classified as improved, 24 (32%) as unchanged, and 10 (13.3%) as worsened. All patients with a CCOS score of 14 or higher improved, while all those with a CCOS score of 8 or lower worsened. The AUROC was 0.986, suggesting almost perfect accuracy of the CCOS in delineating clinical improvement. A CCOS score of 13 showed high sensitivity (0.93) and specificity (0.97) for identifying patients with clinical improvement. Additionally, a meaningful correlation was found between higher CCOS scores in each component and better outcomes. Patient stratification by total CCOS score showed that those categorized as improved, unchanged, and worsened scored prevalently between 13 and 16 points, 10 and 12 points, and 4 and 9 points, respectively. CONCLUSIONS In this adult cohort, the CCOS was found to be almost perfectly accurate in reflecting postoperative clinical improvement. Moreover, all four CCOS components (pain symptoms, nonpain symptoms, functionality, and complications) significantly correlated with patient clinical outcomes.