Clinical characteristics of patients with mpox infection in the United Arab Emirates: a prospective cohort study.

OBJECTIVES: The study aims to explore the risk factors, clinical characteristics, and outcomes of mpox infection in Abu Dhabi, United Arab Emirates (UAE). METHODS: A prospective cohort study was conducted at two communicable disease centers in Abu Dhabi, UAE and patients admitted with confirmed mpox infections between May 01, 2022 and December 31, 2022 were included in our study. RESULTS: A total of 176 mpox patients were admitted, of which 93% (n = 164) were men and mean age was 30.4 ± 7 years. Individuals presented with mucocutaneous lesions, most commonly on the genital and anal regions (n = 157; 89%). Only 70 (39.8%) gave a history of sexual exposure. The most common systemic symptoms reported were fever (n = 91; 52%), exanthema (n = 92; 52%), and inguinal lymphadenopathy (n = 60; 34%). Median timeframe from systemic symptoms to appearance of lesions was 4 days (interquartile range 4-6 days). Complications were observed in seven (4%) participants; two (1.1%) individuals developed conjunctivitis, four (2.3%) patients developed penile edema, and one (0.6%) case of myocarditis was reported. In 60% (n = 106) of patients, a potential source of sexual exposure was not identified. CONCLUSION: The clinical characteristics of mpox cases in the UAE are similar to those in other countries. However, cultural and religious factors likely prevent patient disclosure of sexual exposure and symptoms, contributing to the limited information about the disease in the Middle East.

Improving Information Extraction from Pathology Reports using Named Entity Recognition.

Pathology reports are considered the gold standard in medical research due to their comprehensive and accurate diagnostic information. Natural language processing (NLP) techniques have been developed to automate information extraction from pathology reports. However, existing studies suffer from two significant limitations. First, they typically frame their tasks as report classification, which restricts the granularity of extracted information. Second, they often fail to generalize to unseen reports due to variations in language, negation, and human error. To overcome these challenges, we propose a BERT (bidirectional encoder representations from transformers) named entity recognition (NER) system to extract key diagnostic elements from pathology reports. We also introduce four data augmentation methods to improve the robustness of our model. Trained and evaluated on 1438 annotated breast pathology reports, acquired from a large medical center in the United States, our BERT model trained with data augmentation achieves an entity F1-score of 0.916 on an internal test set, surpassing the BERT baseline (0.843). We further assessed the model's generalizability using an external validation dataset from the United Arab Emirates, where our model maintained satisfactory performance (F1-score 0.860). Our findings demonstrate that our NER systems can effectively extract fine-grained information from widely diverse medical reports, offering the potential for large-scale information extraction in a wide range of medical and AI research. We publish our code at https://github.com/nyukat/pathology_extraction.

Clinical prediction system of complications among patients with COVID-19: A development and validation retrospective multicentre study during first wave of the pandemic.

Clinical evidence suggests that some patients diagnosed with coronavirus disease 2019 (COVID-19) experience a variety of complications associated with significant morbidity, especially in severe cases during the initial spread of the pandemic. To support early interventions, we propose a machine learning system that predicts the risk of developing multiple complications. We processed data collected from 3,352 patient encounters admitted to 18 facilities between April 1 and April 30, 2020, in Abu Dhabi (AD), United Arab Emirates. Using data collected during the first 24 h of admission, we trained machine learning models to predict the risk of developing any of three complications after 24 h of admission. The complications include Secondary Bacterial Infection (SBI), Acute Kidney Injury (AKI), and Acute Respiratory Distress Syndrome (ARDS). The hospitals were grouped based on geographical proximity to assess the proposed system's learning generalizability, AD Middle region and AD Western & Eastern regions, A and B, respectively. The overall system includes a data filtering criterion, hyperparameter tuning, and model selection. In test set A, consisting of 587 patient encounters (mean age: 45.5), the system achieved a good area under the receiver operating curve (AUROC) for the prediction of SBI (0.902 AUROC), AKI (0.906 AUROC), and ARDS (0.854 AUROC). Similarly, in test set B, consisting of 225 patient encounters (mean age: 42.7), the system performed well for the prediction of SBI (0.859 AUROC), AKI (0.891 AUROC), and ARDS (0.827 AUROC). The performance results and feature importance analysis highlight the system's generalizability and interpretability. The findings illustrate how machine learning models can achieve a strong performance even when using a limited set of routine input variables. Since our proposed system is data-driven, we believe it can be easily repurposed for different outcomes considering the changes in COVID-19 variants over time.

Clinical and laboratory characteristics of patients hospitalised with COVID-19: clinical outcomes in Abu Dhabi, United Arab Emirates.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first reported in December 2019. The severity of coronavirus disease 2019 (COVID-19) ranges from asymptomatic to severe and potentially fatal. We aimed to describe the clinical and laboratory features and outcomes of hospitalised patients with COVID-19 within the Abu Dhabi Healthcare Services Facilities (SEHA). METHODS: Our retrospective analysis of patient data collected from electronic health records (EHRs) available from the SEHA health information system included all patients admitted from 1 March to 31 May 2020 with a laboratory-confirmed PCR diagnosis of SARS-CoV-2 infection. Data of clinical features, co-morbidities, laboratory markers, length of hospital stay, treatment received and mortality were analysed according to severe versus non-severe disease. RESULTS: The study included 9390 patients. Patients were divided into severe and non-severe groups. Seven hundred twenty-one (7.68%) patients required intensive care, whereas the remaining patients (92.32%) had mild or moderate disease. The mean patient age of our cohort (41.8 years) was lower than the global average. Our population had male predominance, and it included various nationalities. The major co-morbidities were hypertension, diabetes mellitus and chronic kidney disease. Laboratory tests revealed significant differences in lactate dehydrogenase, ferritin, C-reactive protein, interleukin-6 and creatinine levels and the neutrophil count between the severe and non-severe groups. The most common anti-viral therapy was the combination of Hydroxychloroquine and Favipiravir. The overall in-hospital mortality rate was 1.63%, although the rate was 19.56% in the severe group. The mortality rate was higher in adults younger than 30 years than in those older than 60 years (2.3% vs. 0.95%). CONCLUSIONS: Our analysis suggested that Abu Dhabi had lower COVID-19 morbidity and mortalities rates were less than the reported rates then in China, Italy and the US. The affected population was relatively young, and it had an international representation. Globally, Abu Dhabi had one of the highest testing rates in relation to the population volume. We believe the early identification of patients and their younger age resulted in more favourable outcomes.

Protein C Deficiency Caused by a Novel Mutation in the PROC Gene in an Infant with Delayed Onset Purpura Fulminans.

Protein C is an anticoagulant that is encoded by the PROC gene. Protein C deficiency (PCD) is inherited in an autosomal dominant or recessive pattern. Autosomal dominant PCD is caused by monoallelic mutations in PROC and often presents with venous thromboembolism. On the other hand, biallelic PROC mutations lead to autosomal recessive PCD which is a more severe disease that typically presents in neonates as purpura fulminans. In this report, we describe an 8-month-old infant with autosomal recessive PCD who presented with multiple lumps on his lower extremities at the age of 2 months and later developed purpura fulminans after obtaining a muscle biopsy from the thigh at the age of 5 months. Protein C level was less than 10% and PROC gene sequencing identified a novel homozygous missense mutation, c.1198G>A (p.Gly400Ser). Autosomal recessive PCD typically presents with neonatal purpura fulminans which is often fatal if not recognized and treated early. Therefore, early recognition is critical in preventing morbidity and mortality associated with autosomal recessive PCD.

Significance of platelet count in children admitted with bronchiolitis.

AIM: To determine the true prevalence of thrombocytosis in children less than 2 years of age with bronchiolitis, its association with risk factors, disease severity and thromboembolic complications. METHODS: A retrospective observational medical chart review of 305 infants aged two years or less hospitalized for bronchiolitis. Clinical outcomes included disease severity, duration of hospital stay, admission to pediatric intensive care unit, or death. They also included complications of thrombocytosis, including thromboembolic complications such as cerebrovascular accident, acute coronary syndrome, deep venous thrombosis, pulmonary embolus, mesenteric thrombosis and arterial thrombosis and also hemorrhagic complications such as bleeding (spontaneous hemorrhage in the skin, mucous membranes, gastrointestinal, respiratory, or genitourinary tracts). RESULTS: The median age was 4.7 mo and 179 were males (59%). Respiratory syncytial virus was isolated in 268 (84%), adenovirus in 23 (7%) and influenza virus A or B in 13 (4%). Thrombocytosis (platelet count > 500 × 109/L) occurred in 88 (29%; 95%CI: 24%-34%), more commonly in younger infants with the platelet count declining with age. There was no significant association with the duration of illness, temperature on admission, white blood cell count, serum C-reactive protein concentration, length of hospital stay or admission to the intensive care unit. No death, thrombotic or hemorrhagic events occurred. CONCLUSION: Thrombocytosis is common in children under two years of age admitted with bronchiolitis. It is not associated with disease severity or thromboembolic complications.

Hyponatraemia and neurological complications in children admitted with bronchiolitis.

BACKGROUND: Hyponatraemia occurs during bronchiolitis, sometimes with neurological manifestations. The prevalence of the latter differs widely and little is known about the time of occurrence and associated factors. This study was undertaken to investigate these complications. METHODS: This was a retrospective observational chart review of a cohort of 233 infants under 2 years of age admitted with bronchiolitis to a teaching hospital in the United Arab Emirates. RESULTS: Hyponatraemia (serum sodium <135 mmol/L) occurred in 105 infants (45%, 95% CI 38-51). Hyponatraemia was present on admission in 84 infants (80%) with 90% of cases occurring within 6 days of the onset of illness. It was mild (130-135) in 100 infants (95%) and severe (<130) in five (5%). It was not significantly associated with age, duration of illness before admission, viral aetiology, white cell count or serum C-reactive protein concentrations, or the volume of administered intravenous fluid or use of 0.18% sodium chloride (NaCl). Neurological manifestations occurred in a 29-day-old child with a serum sodium level of 123 mmol/L while receiving two-thirds intravenous maintenance fluids (0.18% NaCl). His developmental milestones remained normal on follow-up to the age of 5 years. CONCLUSION: Hyponatraemia is common in infants with bronchiolitis and occurs in the majority within 6 days of onset of symptoms. There was a significant association between the presence of fever (>38°C) on admission and the duration of hospitalisation.