"Oxygen :" An innovative model for SARS-CoV-2 screening in resource-limited settings.

Indian J Public Health

Professor and Head, Department of Neurology, Institute of Medical Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh, India.

Published: July 2022

The second wave of SARS-CoV-2 infection came as a hypoxic emergency and situation became worse in rural India, where undiagnosed COVID-19 patients died without any diagnosis or intervention. The primary aim of this innovative model was the early diagnosis of suspected SARS-CoV-2 cases, providing empirical treatment and timely referral to appropriate COVID care facilities. Fever was measured with infrared thermometer and oxygen saturation level with pulse oximeter. A total of 8203 people were screened, of which 274 persons were febrile and 69 (25%) were hypoxic too. Sixty-four out of 69 (93%) patients turned COVID-19 positive on reverse transcription-polymerase chain reaction. At the end of 3 weeks, 48/64 (75%) patients were successfully discharged. This model can be easily implemented in resource-limited regions to identify and prioritize the patients not only in this pandemic but also in outbreak of other communicable diseases.

Download full-text PDF

Source
http://dx.doi.org/10.4103/ijph.ijph_1553_21DOI Listing

Publication Analysis

Top Keywords

innovative model
8
"oxygen innovative
4
model sars-cov-2
4
sars-cov-2 screening
4
screening resource-limited
4
resource-limited settings
4
settings second
4
second wave
4
wave sars-cov-2
4
sars-cov-2 infection
4

Similar Publications

Mesenchymal stromal cells promote the formation of lung cancer organoids via Kindlin-2.

Stem Cell Res Ther

January 2025

Shenzhen Key Laboratory of Epigenetics and Precision Medicine for Cancers, Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, 518116, China.

Background: Patient-derived lung cancer organoids (PD-LCOs) demonstrate exceptional potential in preclinical testing and serve as a promising model for the multimodal management of lung cancer. However, certain lung cancer cells derived from patients exhibit limited capacity to generate organoids due to inter-tumor or intra-tumor variability. To overcome this limitation, we have created an in vitro system that employs mesenchymal stromal cells (MSCs) or fibroblasts to serve as a supportive scaffold for lung cancer cells that do not form organoids.

View Article and Find Full Text PDF

Apricot trees, serving as critical agricultural resources, hold a significant role within the agricultural domain. Conventional methods for detecting pests and diseases in these trees are notably labor-intensive. Many conditions affecting apricot trees manifest distinct visual symptoms that are ideally suited for precise identification and classification via deep learning techniques.

View Article and Find Full Text PDF

Background: Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by joint inflammation, tissue damage, and fibrosis, significantly affecting the quality of life. While there are currently some effective treatments available, they often come with side effects. There is an urgent need to find new treatments that can further improve therapeutic outcomes and reduce side effects.

View Article and Find Full Text PDF

A machine learning model accurately identifies glycogen storage disease Ia patients based on plasma acylcarnitine profiles.

Orphanet J Rare Dis

January 2025

Laboratory of Metabolic Diseases, Department of Laboratory Medicine, University Medical Center Groningen, University of Groningen, Hanzeplein 1, Postbus, Groningen, 30001 - 9700 RB, the Netherlands.

Background: Glycogen storage disease (GSD) Ia is an ultra-rare inherited disorder of carbohydrate metabolism. Patients often present in the first months of life with fasting hypoketotic hypoglycemia and hepatomegaly. The diagnosis of GSD Ia relies on a combination of different biomarkers, mostly routine clinical chemical markers and subsequent genetic confirmation.

View Article and Find Full Text PDF

Background: Adolescent idiopathic scoliosis, a complex three-dimensional spine deformity, presents a formidable challenge for orthopedic residents in understanding its anatomy and surgical strategies. The aim of this study is to investigate the impact of three-dimensional printing (3DP) models in enhancing the comprehension of adolescent idiopathic scoliosis among orthopedic residents.

Methods: Forty orthopedic residents were randomly divided into two groups, the first group received lectures that were augmented with 3DP models illustrating five cases of adolescent idiopathic scoliosis, along with corresponding X-ray and CT images.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!