On December 31, 2019, the World Health Organization was informed of a cluster of cases of pneumonia of unknown cause detected in Wuhan City, Hubei Province, China. The pneumonia was caused by a virus called SARS-Cov-2 (severe acute respiratory syndrome coronavirus 2), which was later named coronavirus infectious disease 2019 (COVID-19). The symptoms most commonly reported by patients affected by COVID-19 include fever, dry cough, and shortness of breath. In this report, we present a case of a 57-year-old woman who presented to the clinic’s infectious department with swelling, pain, warmth, and redness in the left leg who was treated with therapeutic heparin. There were no typical and distinguished symptoms of COVID-19, and she had no risk factor for deep vein thrombosis. Then chest X-ray revealed bilateral patchy ground-glass opacity, and computed tomography angiography was performed to rule out pulmonary thromboembolism, which showed no evidence of thrombosis. Left lower limb venous color Doppler ultrasound revealed dilatation and thrombosis in the external iliac and left iliac veins up to the level of the bifurcation of the common iliac veins, as well as thrombosis to the superficial and small saphenous veins. Because of ground-glass opacity and lymphopenia, nasal swabs were used for sampling, and SARS-CoV-2 nucleic acid was detected by reverse transcription polymerase chain reaction (RT-PCR). This case aims to arouse the medical staff’s awareness of deep vein thrombosis as a clinical symptom of COVID-19 even if the patient has no typical symptoms of COVID-19.

Efficacious therapies are urgently required to tackle the coronavirus disease 2019 (COVID-19). This trial aims to evaluate the effects of atorvastatin in comparison with standard care for adults hospitalized with COVID-19. We conducted a randomized controlled clinical trial on adults hospitalized with COVID-19. Patients were randomized into a treatment group receiving atorvastatin + lopinavir/ritonavir or a control group receiving lopinavir/ritonavir alone. The primary outcome of the trial was the duration of hospitalization. The secondary outcomes were the need for interferon or immunoglobulin, receipt of invasive mechanical ventilation, and O2 saturation (O2sat), and level of C-reactive protein (CRP) which were assessed at the onset of admission and on the 6th day of treatment. Forty patients were allocated and enrolled in the study with a 1 to 1 ratio in atorvastatin + lopinavir/ritonavir and lopinavir/ritonavir groups. Clinical and demographic characteristics were similar between the two groups. CRP level was significantly decreased in the lopinavir/ritonavir + atorvastatin group (P < 0.0001, Cohen’s d = 0.865) so that there was a significant difference in CRP level on the 6th day between the two groups (P = 0.01). Nevertheless, there was no significant difference in O2sat on day 6. Although the duration of hospitalization in the lopinavir/ritonavir + atorvastatin group was significantly reduced compared to the control group (P = 0.012), there was no significant difference in the invasive mechanical ventilation reception and the need for interferon and immunoglobulin. Atorvastatin + lopinavir/ritonavir may be more effective than lopinavir/ritonavir in treating COVID-19 adult hospitalized patients.

The international outbreak of respiratory illness termed coronavirus disease 2019 (COVID-19) began in December 2019 that has affected >0.8 million individuals. Self-limiting respiratory tract involvement, severe pneumonia, multiorgan failure and death are the spectrum of COVID-19. To date, there are no especial therapeutic agents for COVID-19 infections. One such medication includes the antimalarial hydroxychloroquine (HCQ), which recently reported as a possible therapy for shortening the duration of COVID-19 symptoms, reducing inflammatory reactions to infection, impairing the exacerbation of pneumonia and boosting lung imaging findings. Like all medications, HCQ has side effects and may occur in COVID-19 patients. Here, we report on the case of a 42-year-old woman, presented with fever and dry cough, who had COVID-19 and 2 days later presented with a pruritic erythematous maculopapular rash, which started from the distal of upper extremities and rapidly, involved the entire body.

Background: This study aimed to compare the gut microbiome (GM) composition, serum inflammatory markers and faecal short‐chain fatty acids among individuals with type 1 and type 2 diabetes mellitus (DM) and healthy controls.Methods: This case–control study examined 49 subjects with type 2 DM, 21 with type 1 DM and 40 healthy controls. Blood and faecal samples were collected. Serum inflammatory markers, including CRP, IL‐1β, IL‐6, TNF‐α and IFN‐γ, were measured using enzyme‐linked immunosorbent assays (ELISA). Bacterial populations were quantified using RT‐qPCR and NGS. Faecal metabolites were analysed using gas chromatography.Results: Simpson's alpha diversity was higher among types 1 and 2 DM than in the control. The frequency of the bacterial genera Gemmiger, Dorea, Collinsella, Escherichia/Shigella, Dialister, Coprococcus, Achromobacter, Intestinimonas and Allisonella in type 2 DM was higher than in the control, and the frequency of the genera Romboutsia and Clostridium was decreased in type 2 DM. The frequency of the Prevotella, Bacteroides and Faecalibacterium genera in type 1 DM was lower than in the other groups. Acetate, propionate and butyrate levels were significantly higher in type 2 DM patients compared to the other groups. Participants with diabetes had significantly higher hs‐CRP, IL1‐β, TNF, IL‐6 and IFG levels compared to the controls. Compared to healthy controls, both T1DM and T2DM patients showed a significant increase in the abundance of the Lactobacillus genus (p = 0.01) and a decrease in Faecalibacterium (p = 0.02). Additionally, serum levels of IL‐6 and TNF‐α were significantly elevated in T2DM patients (p = 0.003 and p = 0.005, respectively). Faecal levels of butyrate were significantly reduced in both diabetic groups compared to the controls (p = 0.004).Conclusion: By determining the GM alterations in patients with diabetes, interventional strategies could be designed to modulate the GM composition as an adjunctive therapy in diabetes.

We evaluated the clinical applications of artificial intelligence models in diagnosing corneal diseases, highlighting their performance metrics and clinical potential. A systematic search was conducted for several disease categories: keratoconus (KC), Fuch’s endothelial corneal dystrophy (FECD), infectious keratitis (IK), corneal neuropathy, dry eye disease (DED), and conjunctival diseases. Metrics such as sensitivity, specificity, accuracy, and area under the curve (AUC) were extracted. Across the diseases, convolutional neural networks and other deep learning models frequently achieved or exceeded established diagnostic benchmarks (AUC > 0.90; sensitivity/specificity > 0.85–0.90), with a particularly strong performance for KC and FECD when trained on consistent imaging modalities such as anterior segment optical coherence tomography (AS-OCT). Models for IK and conjunctival diseases showed promise but faced challenges in heterogeneous image quality and limited objective training criteria. DED and tear film models benefited from multimodal data yet lacked direct comparisons with expert clinicians. Despite high diagnostic precision, challenges from heterogeneous data, a lack of standardization in disease definitions, imaging acquisition, and model training remain. The broad implementation of artificial intelligence must address these limitations to improve eye care equity.