Journal of Medicine and Life最新文献

The most severe clinically recognized complication of venous thromboembolism (VTE), pulmonary embolism (PE), can be difficult to diagnose due to its nonspecific symptoms. The overlapping clinical symptoms of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection that causes Coronavirus 2019 (COVID-19) and PE can make it difficult to differentiate between one and the other. Therefore, PE diagnosis can be delayed or missed in patients with COVID-19, resulting in critical consequences for patient safety and outcomes. A 70-year-old woman presented to our Emergency Department with dyspnoea and chest pain. On admission, she had peripheral O2 saturation (SpO2) of 94% on 6 l/min O2, pain, and an increase in the volume of the right lower limb. Anamnesis revealed that she had been discharged two weeks earlier from the Infectious Diseases Department, where she was admitted for SARS-CoV-2 infection. Venous Doppler ultrasound of the right limb revealed complete thrombosis in the common femoral, popliteal, and small saphenous veins. The computed tomography angiography of the pulmonary artery revealed defects suggestive of pulmonary thromboembolism, visualized in the pulmonary artery trunk, bilateral pulmonary arteries, and various lobes. In patients with a recent history of COVID-19, pulmonary thromboembolism must always be considered as a critical differential diagnosis. Timely recognition and intervention are vital, as they can significantly influence the patient's prognosis and overall outcome through prompt diagnosis and appropriate treatment.

Up to 1 in 13 patients with apparent early-stage ovarian neoplasms harbor occult advanced disease, posing a diagnostic dilemma with major therapeutic implications that remains poorly characterized. We conducted a retrospective consecutive cohort study of 106 patients with apparent early-stage ovarian neoplasms at a tertiary gynecological oncology center (2014-2023) to determine the prevalence, consequences, and clinical correlates of staging discordance and develop the first descriptive risk stratification for surgical planning. Staging discordance occurred in 8/106 patients (7.5%), all of whom were upstaged to Stage III disease. All malignant cases (5/106, 4.7%) were discordant, demonstrating universally advanced disease requiring chemotherapy (100% vs. 1.0% concordant, P < 0.001). A five-year follow-up revealed nearly a five-fold higher recurrence rate, indicating a worse prognosis in discordant cases (37.5% vs 8.2%, P = 0.025). Two preoperative features-CA-125 ≥100 U/mL and ascites-were most strongly associated with discordance (both P < 0.01). Risk grouping by these factors showed clear stratification: 1.5% discordance with neither factor, 9.5% with one, and 83.3% with both. In this comprehensive consecutive cohort of apparent early-stage ovarian neoplasms, staging discordance was rare but clinically decisive, identifying patients with universally advanced disease, chemotherapy requirement, and worse prognosis. Two readily available preoperative features offer immediate, pragmatic risk stratification to guide surgical triage, particularly in community or resource-limited settings.

Self-control is essential for youth navigating today's technological and lifestyle challenges. Artificial intelligence (AI) offers scalable, personalized approaches to improve self-regulation through medical and educational interventions. This pilot research was conducted over a period of five months and structured into two studies, each comprising four phases. The first study included 180 adolescents, divided into two equal samples, to examine whether impulsivity varies according to high school profile. One group was drawn from Grigore Moisil Informatics College (theoretical high school), and the other from the National College of Arts Dinu Lipatti (vocational arts high school). Impulsivity was initially assessed using the Barratt Impulsiveness Scale (BIS). Drama students showed significantly higher levels of impulsivity, guiding the development of a targeted AI-driven (neural network-based) self-control intervention. The second study focused on the drama student cohort. Over the course of three months, the group participated in an online, AI-guided self-control education program. BIS was re-administered at the end of the intervention to measure changes. Pre-intervention data confirmed significantly higher impulsivity among drama students. Following the AI-based intervention, the group showed statistically significant improvements in self-control. The findings support the effectiveness of AI tools in fostering self-regulatory skills among adolescents and highlight their potential in health education and mental wellness, especially for anxiety, behavioral issues, and mild depression. The AI-guided, game-based cognitive training significantly reduced impulsivity in drama students, demonstrating its promise as a tool for improving adolescent self-control and psychological resilience.

Diabetic foot complications are a major cause of morbidity and mortality, particularly in Saudi Arabia. Understanding how knowledge influences preventive practices is critical for designing effective interventions. A cross-sectional study was conducted among 647 diabetic patients in Al-Qassim, utilizing self-administered questionnaires to assess their knowledge, attitudes, and practices regarding diabetic foot care. Confirmatory factor analysis identified three knowledge domains (physiological, complication, preventive), two attitude constructs, and four practice domains. Structural equation modeling was employed to compare direct, full, and partial mediation models, with multi-group analysis used to assess demographic moderators. Among participants, 74.2% demonstrated good knowledge and 93.4% reported positive attitudes, but only 63.7% had adequate practices. The partial mediation model showed the best fit (CFI = 0.938, RMSEA = 0.049), with 59.8% of knowledge effects on practices mediated through attitudes. Preventive knowledge exerted the strongest effects on attitudes (β = 0.497, P < 0.001) and practices (β = 0.482, P < 0.001), while physiological knowledge had no direct impact. Knowledge-practice pathways were significantly stronger in patients with higher education, longer diabetes duration, and greater exposure to formal education. Attitudes primarily mediate the link between knowledge and practice. Effective interventions should emphasize preventive knowledge, address attitudinal barriers, and be tailored to demographic profiles. Achieving at least 70% knowledge mastery appears essential for improving preventive behaviors.

Frailty in older adults is a syndrome associated with increased morbidity and mortality. The Zulfiqar Frailty Scale (ZFS) was developed to facilitate the assessment of frailty in general practice. This study aimed to assess the predictive capacity of the ZFS over 12 months for events such as falls, hospitalizations, changes in treatment, and mortality. A prospective study was conducted in a general practice over a 12-month period. Patients aged 65 and over were included and assessed using the ZFS at T0 months, followed by assessment at T12 months. Data collected included demographic information, medical history, hemoglobin level over the last 3 months, and hemoglobin level at 12 months, as well as the occurrence of adverse events (falls, fractures, hospitalizations, and death). Statistical analyses were performed using ROC curves to determine the performance of the ZFS scale. Of the 135 patients included, 24% were considered frail at T0, and this figure rose to 28% at T12 months. The ZFS showed good predictive capacity for the occurrence of falls (AUC = 0.75) and hospitalizations (AUC = 0.64). Frail patients, according to the ZFS, had a significantly higher risk of falling (P < 0.05) and were hospitalized more frequently (P < 0.001) than non-frail patients. Concerning mortality, although the number of deaths was low (3 deaths), the ZFS showed an AUC of 0.87, indicating a good predictive capacity. On the other hand, the prediction of fractures (AUC = 0.62) and new comorbidities (AUC = 0.51) performed less well. The ZFS is a promising tool for screening for frailty and predicting certain clinical events such as falls and hospitalizations. However, for more comprehensive predictions (fractures, comorbidities), association with other assessment tools is recommended.

The simulated patient methodology (SPM), a form of participant observation, is generally recommended in the international literature. SPM studies investigating community pharmacy (CP) practice have been conducted in at least 52 countries from all regions of the world, with the number of publications per year increasing. Not only 'traditional' visits, but also calls are used in SPM studies. Accordingly, in addition to reviews of visits, reviews of calls are planned. The interest in the SPM is already so great that not only worldwide reviews, but also reviews on specific regions and individual countries, have been published. Finally, a checklist called CRiSPHe is available to help researchers report their studies using the simulated patient method. It was developed through a Delphi study focused on pharmacy and has since been refined. SPM is now considered the 'gold standard' in the international literature for investigating CP practice.

Urinary tract infections (UTIs) are a significant global public health issue, with Escherichia coli (E. coli), specifically uropathogenic E. coli (UPEC), being the predominant causative agent. UTIs affect millions of people annually, with a particularly high prevalence among women, children, the elderly, and individuals with compromised immunity or structural abnormalities of the urinary tract. UPEC has evolved a suite of specialized virulence factors like adhesins, flagella, capsular polysaccharides, lipopolysaccharide (LPS), outer membrane vesicles (OMVs), toxins, iron acquisition systems, autotransporters (ATs), and unique proteins such as TcpC and OmpT, that facilitate colonization, immune evasion, and disease progression. These factors enable the pathogen to cause both uncomplicated infections, such as cystitis, and more severe outcomes, including pyelonephritis and, in some cases, renal failure. The host defends against infection through mechanisms such as urine flow, urothelial shedding, cytokine release, antimicrobial peptides, and adaptive immunity. Despite advancements in medical care, the burden of UTIs remains high, underscoring the need for continued research into their pathogenesis and prevention.

Skin cancer is one of the most aggressive types of neoplasms, with high morbidity and mortality. Numerous factors are associated with the development of melanoma, including exposure to UV radiation and the use of exogenous hormones. Some studies suggest that oral contraceptives can influence the development of skin cancer, but the evidence is insufficient and contradictory. Our study aimed to initially evaluate the safety profile of the combination of levonorgestrel and 17β-ethinylestradiol on healthy cell lines (HaCaT and JB6 Cl 41-5a) and to further determine the possible association with skin cancer by investigating the effect of the combination on the murine melanoma tumor line (B164A5). The data obtained showed that levonorgestrel-ethinylestradiol (LG-EE) did not have a toxic effect on healthy cells (HaCaT and JB6 Cl 41-5a) but exhibited a slight proliferative effect on murine skin tumor cells at increasing concentrations. LG-EE on healthy lines did not significantly decrease viability and did not induce a cytotoxic effect. On the B164A5 tumor line, the hormonal combination at a concentration of 5 µM slightly decreased viability and degraded the cell membrane, observing a decrease in confluence and number of cells, as well as the presence of apoptotic bodies, while at the highest dose tested of 15 µM, an opposite effect was recorded with a slight stimulation of murine tumor cells. The results suggest that LG-EE may influence the development of melanoma; however, the evidence is insufficient, and further studies are necessary.

Artificial intelligence (AI) and machine learning (ML) are increasingly pivotal in advancing postoperative imaging for thoracic surgery, presenting transformative potentials in clinical practice. This comprehensive review investigates the current applications and future directions of AI and ML by comparing them with traditional imaging methods. It highlights how these technologies assist in the early detection of postoperative complications such as infections, anastomotic leaks, and pleural effusions through sophisticated image analysis algorithms. The discussion extends to the automation of routine imaging tasks, which not only improves efficiency but also allows radiologists to focus on more complex cases. Looking ahead, the article considers the implications of emerging technologies such as deep learning and neural networks. This further enhances the capabilities of AI in medical imaging. By providing a thorough overview of the current landscape and anticipating future advancements, this article highlights the profound impact of AI and ML on improving patient care and outcomes in thoracic surgery.

Empty Sella Syndrome (ESS) is characterized by a herniation of cerebrospinal fluid into the pituitary fossa, frequently causing pituitary dysfunction. Although ESS is generally asymptomatic, it can lead to progressive hormonal deficiencies. Long-term studies of pituitary function in patients with ESS are lacking. This study aimed to evaluate pituitary function in ESS patients, monitor the progression of hormone deficiencies, and explore the impact of gender, age, and body mass index (BMI). This is a descriptive and analytical study involving 41 patients diagnosed with ESS and treated at our university hospital between 2014 and 2024. All patients underwent MRI and endocrine testing for cortisol, thyrotropin, free thyroxine, prolactin, growth hormone, gonadal hormones, and testosterone. The median duration of follow-up was 5 years, with a range of 6 months to 10 years. Data was collected and analyzed using SPSS version 21. At diagnosis, 82.9% of patients had at least one pituitary hormone deficiency, primarily in the adrenal, gonadal, and growth hormone axes. Women were more likely to develop gonadal dysfunction (34.1%) than men (21.9%). A positive correlation between age and adrenal/gonadal insufficiency was observed. Additionally, a significant association was found between higher BMI and gonadal insufficiency, highlighting the role of obesity in exacerbating pituitary dysfunction. ESS is commonly linked to pituitary dysfunction, particularly in the adrenal and gonadal axes. Gender, age, and BMI influence the development and progression of hormonal deficiencies, underscoring the need for regular endocrine evaluation and long-term follow-up in these patients.