Соображения, касающиеся менеджмента медицинских услуг больным сахарным диабетом

Chronic disease transformed the patient-doctor relationship into a long-term one ensuring the continuity of healthcare. The questionnaire PACIC (Patient Assessment of Chronic Illness Care) has the aim to measure the structuring of provided healthcare. We will present the Romanian version of PACIC, which is now in the phase of pre-testing and cognitive interviewing.Хроническое заболевание превратило отношение врач – пациент в долгосрочные отношения, обеспечивая непрерывность медицинской помощи. Целью анкеты PACIC (Patient Assessment of Chronic Illness Care – Оценка пациентом медицинских услуг при хроническом заболевании) является определение степени структурирования оказываемых медицинских услуг. В нашем исследовании мы представляем разработанный на румынском языке вариант, который в настоящее время находится на этапе предварительного испытания и когнитивного интервью

Lesser-Known Molecules in Ovarian Carcinogenesis

Currently, the deciphering of the signaling pathways brings about new advances in the understanding of the pathogenic mechanism of ovarian carcinogenesis, which is based on the interaction of several molecules with different biochemical structure that, consequently, intervene in cell metabolism, through their role as regulators in proliferation, differentiation, and cell death. Given that the ensemble of biomarkers in OC includes more than 50 molecules the interest of the researchers focuses on the possible validation of each one’s potential as prognosis markers and/or therapeutic targets. Within this framework, this review presents three protein molecules: ALCAM, c-FLIP, and caveolin, motivated by the perspectives provided through the current limited knowledge on their role in ovarian carcinogenesis and on their potential as prognosis factors. Their structural stability, once altered, triggers the initiation of the sequences characteristic for ovarian carcinogenesis, through their role as modulators for several signaling pathways, contributing to the disruption of cellular junctions, disturbance of pro-/antiapoptotic equilibrium, and alteration of transmission of the signals specific for the molecular pathways. For each molecule, the text is built as follows: (i) general remarks, (ii) structural details, and (iii) particularities in expression, from different tumors to landmarks in ovarian carcinoma

How the SARS-CoV-2 Pandemic Period Influenced the Health Status and Determined Changes in Professional Practice among Obstetrics and Gynecology Doctors in Romania

Background and Objectives: The beginning of the SARS-Cov-2 pandemic period has had a strong impact on patients’ life, but also on doctors. The main goal of this research is to identify the difficulties related to the professional activity and personal life of obstetrics and gynecology doctors. Material and Methods: In total, 94 physicians from a single university center answered to an online questionnaire. Socio-demographic, health, family, and job-related data were collected. Data were processed using SPSS (v.25). Results: 7.4% of the doctors were confirmed infected with SARS-Cov-2 during the first 6 months of the pandemic, and 48.94% treated infected patients. Due to the large number of patients, 10.64% of the doctors have had no days-off during the last 6 months, and 22.34% of them have had new medical problems that led them to see a specialist. Seventeen to nineteen percent mentioned an increasing number of working hours and shifts per month due to the pandemic period, more than 10% used pills to cope with work-stress, and 25% of them had sleep disorders along with appetite loss. Extra-protection rules and negative consequences of wearing special equipment were identified: thermal discomfort that caused decreasing resistance and concentration during the surgery (52%), reduced mobility and accuracy of surgical or medical gestures (40%), and intraoperative visibility (47%). Doctors who were working with confirmed pregnant women preferred caesarean section. Conclusions: Working under the stress of an infection with SARS-Cov-2 is causing a lot of pressure and determines changes in personal, familial, social, and professional life. Understanding the challenges that ob-gyn doctors are facing will help institutions to better provide support

Prediction of Intrauterine Growth Restriction and Preeclampsia Using Machine Learning-Based Algorithms: A Prospective Study

(1) Background: Prenatal care providers face a continuous challenge in screening for intrauterine growth restriction (IUGR) and preeclampsia (PE). In this study, we aimed to assess and compare the predictive accuracy of four machine learning algorithms in predicting the occurrence of PE, IUGR, and their associations in a group of singleton pregnancies; (2) Methods: This observational prospective study included 210 singleton pregnancies that underwent first trimester screenings at our institution. We computed the predictive performance of four machine learning-based methods, namely decision tree (DT), naïve Bayes (NB), support vector machine (SVM), and random forest (RF), by incorporating clinical and paraclinical data; (3) Results: The RF algorithm showed superior performance for the prediction of PE (accuracy: 96.3%), IUGR (accuracy: 95.9%), and its subtypes (early onset IUGR, accuracy: 96.2%, and late-onset IUGR, accuracy: 95.2%), as well as their association (accuracy: 95.1%). Both SVM and NB similarly predicted IUGR (accuracy: 95.3%), while SVM outperformed NB (accuracy: 95.8 vs. 94.7%) in predicting PE; (4) Conclusions: The integration of machine learning-based algorithms in the first-trimester screening of PE and IUGR could improve the overall detection rate of these disorders, but this hypothesis should be confirmed in larger cohorts of pregnant patients from various geographical areas