Prevalence and outcomes of upper gastrointestinal bleeding in COVID-19: A systematic review and meta-analysis.

Upper gastrointestinal bleeding (UGIB) in COVID-19 presents challenges in patient management. Existing studies lack comprehensive review due to varied designs, samples, and demographics. A meta-analysis can provide valuable insights into the incidence, features, and outcomes of UGIB in COVID-19. A comprehensive literature search was carried out using several databases. We considered all appropriate observational studies from all over the world. Mantel-Haenszel odds ratios and associated 95% confidence intervals (CIs) were produced to report the overall effect size using random effect models. Besides, Random effects models were used to calculate the overall pooled prevalence. Funnel plots, Egger regression tests, and Begg-Mazumdar's rank correlation test were used to appraise publication bias. Data from 21 articles consisting of 26,933 COVID-19 patients were considered. The pooled estimate of UGIB prevalence in patients admitted with COVID-19 across studies was 2.10% (95% CI, 1.23-3.13). Similarly, the overall pooled estimate for severity, mortality, and rebleeding in COVID-19 patients with UGIB was 55% (95% CI, 37.01-72.68), 29% (95% CI, 19.26-40.20) and 12.7% (95% CI, 7.88-18.42) respectively. Further, UGIB in COVID-19 patients was associated with increased odds of severity (OR = 3.52, 95% CI 1.80-6.88, P = 0.001) and mortality (OR = 2.16, 95% CI 1.33-3.51, P = 0.002) compared with patients without UGIB. No significant publication bias was evident in the meta-analysis. The results of our study indicate that UGIB in individuals with COVID-19 is linked to negative outcomes such as severe illness, higher mortality rates, and an increased risk of re-bleeding. These findings highlight the significance of identifying UGIB as a significant complication in COVID-19 cases and emphasise the importance of timely clinical assessment and proper treatment.

Ventricular Septal Rupture and Artificial Intelligence (AI)-Assisted Healthcare.

This case report highlights the use of point-of-care ultrasound (POCUS) for the diagnosis of ventricular septal rupture (VSR), a severe consequence of acute myocardial infarction (AMI). VSR has a broad spectrum of signs and inconspicuous symptoms, making the diagnosis difficult. POCUS offers non-invasive, real-time cardiac imaging and has an advantage over other methods due to its ability to identify VSR early. Here we present a 63-year-old female with a history of type 2 diabetes, hypothyroidism, hyperlipidemia, and a family history of cardiovascular disease, who came to the ED with chest pain for three days, palpitations, and dyspnea at rest. On examination, the patient was hypotensive, tachycardic, and had crackles with a harsh holosystolic murmur. An EKG and elevated troponin levels suggested acute on chronic anterior-lateral wall ST-elevation myocardial infarction (STEMI). Resuscitation efforts were initiated, followed by a lung ultrasound that revealed good lung sliding and multiple B lines without pleural thickening, indicating pulmonary edema. Echocardiography revealed ischemic heart disease with moderate left ventricle (LV) systolic dysfunction and a 14 mm apical ventricular septal rupture (hypokinetic thinning of the anterior wall, septum, apex, and anterolateral wall with a left ventricular ejection fraction (LVEF) of 39%). The presence of flow on color Doppler across the interventricular septum, showing left-to-right shunting, led to a definitive diagnosis of acute-on-chronic myocardial infarction (MI) with ventricular septal rupture. The case report also emphasizes how modern AI applications like ChatGPT (OpenAI, San Francisco, California, United States), aid in language and research, saving time and redefining the healthcare and research industry. As a result, we are confident that AI-assisted healthcare will be the next global breakthrough.