Pomeranian Medical University (PMU) was established in 1948 in Szczecin, Poland. It is referred to as Pomorski Uniwersytet Medyczny in Polish.
Artificial intelligence (AI) is increasingly utilized in orthodontics to automate cephalometric analysis. Despite promising results for AI-based landmark detection on 2D cephalograms, the reliability of AI analyses performed on 3D CBCT data by commercial systems remains unclear. The aim of this study was to evaluate the interchangeability between the results of AI-driven cephalometric analyses using two commercial software platforms (CephX and Invivo) on CBCT datasets and reference 2D cephalometric analysis following manual landmark identification. This retrospective study included 135 patients (mean age: 26.8 ± 10.1 years) who underwent concurrent CBCT and lateral cephalometric imaging. Analyses (Steiner and Ricketts methods) based on manual landmark identification served as the reference standard. For each variable, the mean difference (AI – reference) with 95
AIMS:Loneliness is a global public health concern that has been widely associated with a variety of mental health impairments. Two dimensions of loneliness have been differentiated, that is, social loneliness (the perceived absence or inadequacy of a broader social network) and emotional loneliness (the perceived absence of a close, intimate relationship or emotional support from a significant person). The present study aimed to test the hypothesis that both dimensions of loneliness are differentially associated with mental health outcomes. METHODS:Altogether, 3275 individuals (aged 45.2 ± 15.7 years, 47.9% men), enrolled from the general population, were assessed at two waves spanning 6 to 7 months. Social and emotional loneliness were quantified using the 11-item De Jong Gierveld Loneliness Scale. Social isolation was assessed with the six-item Lubben Social Network Scale, depressive symptoms with the Patient Health Questionnaire-9, generalised anxiety with the Generalised Anxiety Disorder-7, social anxiety with the Social Interaction Anxiety Scale, and paranoid ideation with the Revised Green et al. Paranoid Thoughts Scale. The data were analysed using a cross-lagged panel network model. Covariates included age, gender, education, employment status, place of residence, monthly income, the history of psychiatric treatment and substance use. RESULTS:Both dimensions of loneliness were bidirectionally associated and were found to have the highest overall weight of outcoming network connections. Emotional loneliness was bidirectionally and positively associated with all measures of mental health. In turn, social loneliness predicted higher levels of social anxiety but was not associated with other mental health outcomes. It was bidirectionally associated with social isolation. CONCLUSIONS:The findings imply the relevance of differentiating social and emotional dimensions of loneliness in the assessment of its underlying mechanisms and consequences for mental health. Emotional loneliness might show a greater importance in the development of psychopathological symptoms compared to its social dimension.
Recent studies have reported higher frequencies of overactive bladder (OAB) symptoms in both male and female patients diagnosed with obstructive sleep apnea (OSA) in sleep medicine centers. However, there is a paucity of data on the prevalence of OSA in female urogynecological patients with a primary diagnosis of OAB. The aims of the present study were: (i) to evaluate the prevalence of OSA among urogynecological patients diagnosed with OAB compared with a control group (non-OAB gynecological patients), (ii) to assess the correlation between the severity of OSA and OAB symptoms. All patients underwent the home sleep apnea test based on peripheral arterial tonometry (PAT). The analysis included the PAT Apnea Hypopnea Index (pAHI), PAT Respiratory Disturbance Index (pRDI), sleep time with desaturations < 90
BACKGROUND:People with mental disorders have an increased risk of diabetes, yet conflicting evidence exists regarding the quality of diabetes care they receive. To address this evidence gap, we conducted a systematic review and meta-analysis to assess and compare diabetes quality of care in people with diabetes with mental disorders versus people with diabetes without mental disorders. METHODS:In this systematic review and random-effects meta-analysis, we searched Scopus, Embase, MEDLINE, and PsycINFO for cohort and case-control studies published between database inception and Feb 8, 2025. We estimated summary odds ratios (ORs) for diabetes quality of care indicators in individuals with any mental disorder versus without mental disorders to investigate the association between the presence of a mental disorder and diabetes quality of care indicators, including overall diabetes monitoring and treatment. Studies were excluded if it was not possible to generate pooled quantitative data. The primary outcome was a binary composite measure of diabetes quality of care, meaning the percentage of people receiving any diabetes monitoring and treatment (ie, urine albumin-creatinine ratio test, HbA1c test, blood pressure measured, foot surveillance, serum creatinine test, serum cholesterol test, BMI recorded, smoking status recorded, retinal monitoring). Secondary outcomes were study-specific diabetes quality of care individual indicators matched to the nine NICE diabetes monitoring indicators and specific diabetes interventions and anti-diabetes medications. We analysed primary and secondary outcomes according to any mental disorder and to specific diagnostic subgroups. Study quality was evaluated using the Newcastle-Ottawa Scale (NOS). FINDINGS:Data from 49 studies (42 cohort and seven case-control) were included, comprising 5 503 712 individuals with diabetes, of whom 838 366 (15·2%) had a diagnosed mental disorder (defined using ICD-9 or ICD-10 criteria in 40 studies). Sex was reported in 35 of 49 studies, comprising 4 250 666 individuals, 1 956 506 (46·0%) of whom were female and 2 294 160 (54·0%) were male. The mean age was 61·4 years (SD 8·7; range 47-82 years). 38 studies reported on various mental disorders, 21 on mood disorders spectrum, 21 on major depressive disorder, 20 on schizophrenia, 11 on bipolar disorder, 11 on substance use disorder spectrum, including alcohol use disorder, six on dementia, five on anxiety disorder spectrum, and one on personality disorder spectrum. Most studies were high quality and spanned Asia, North America, Europe, and Australasia. Significant negative associations were observed between having any mental disorder and the likelihood of receiving any recommended diabetes monitoring (29 studies, OR=0·81 [95% CI 0·70-0·94], p=0·0049). Negative associations were also observed for HbA1c measurement (24 studies, 0·81 [0·68-0·97], p=0·024), retinal screening (21 studies, 0·77 [0·63-0·95], p=0·013), lipid and cholesterol measurement (20 studies, 0·83 [0·69-0·99], p=0·043), foot examination (11 studies, 0·85 [0·76-0·95], p=0·0044), and renal investigation (16 studies, 0·78 [0·63-0·96], p=0·022). A significant positive association was found between any mental disorder and recorded smoking status (two studies, 1·09 [1·02-1·17]; p=0·0076). Any mental disorder was significantly associated with higher odds of receiving insulin (ten studies, 1·52 [95% CI 1·16-1·99]; p=0·0022), but negatively associated with treatment with a GLP-1 receptor agonist (two studies, 0·26 [0·13-0·49]; p<0·0001). There was no evidence of publication bias. INTERPRETATION:Mental disorders are negatively associated with receiving adequate diabetes monitoring and GLP-1 agonist therapy. Addressing these disparities has the potential to address the increased mortality associated with mental disorders. FUNDING:None.
PVT1 is a non-coding RNA (ncRNA) playing an important role in various biological processes, including cell survival, differentiation, proliferation, and chromatin regulation. Overexpression of PVT1 improve a proliferation rate even for 30
