ArticleHeliyon2023
Evaluation of patients treated by telemedicine in the beginning of the COVID-19 pandemic in São Paulo, Brazil: A non-randomized clinical trial preliminary study.
Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.
- A systematic review of methods used for COVID-19 telehealth systems evaluation: lessons from past experiences for future use.BMC health services research · 2025Pooled it
- Trade-offs between Accessibility and Practicality in Global Telemedicine: A Systematic Review.Iranian journal of public health · 2025Review
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors at 7 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We performed a pilot open-label, non-randomized controlled clinical trial in a clinic in São Paulo, Brazil in the beginning of the COVID-19 pandemic. "This medical pilot project was carried out during the pandemic of a new and unknown agent. It was necessary to find a new and safe therapeutic approach for pathogens with high potential for severity and contamination. The repositioning of safe and accessible pre-existing and approved medications and the telemedicine approach improved treated covid patients' symptoms and reduced the risk of disease transmission. The emergency application of a new medical technology was the major limitation of the study. This innovative care model is a low-cost safe strategy, and we understand that applicability can be expanded to other regions in emergency situations." The 187 patients of the study (mean age of 37.6 ± 15,6 years) were divided into four groups: (1) asymptomatic, (2) mild symptoms, (3) moderate symptoms and (4) severe symptoms and were followed up for five days. A drug intervention was performed in group 3 and the patients of Group 4 were oriented to seek hospital care. Of all the patients, 23.0% were asymptomatic, 29.4% reported mild symptoms, 43.9% moderate symptoms and 3.7% severe symptoms. Three patients were hospitalized and discharged after recovery. Our results indicate that the use of telemedicine with diagnosis and drug treatment is a safe and effective strategy to reduce overload of health services and the exposure of healthcare providers and the population. The patients that initiated the treatment in the early stages of the disease presented satisfactory clinical response, reducing the need of face-to-face consultations and hospitalizations. The patients who followed the protocol treatment for COVID-19 with hydroxychloroquine and azithromycin for five days presented statistically significant improvement of clinical symptoms when compared to moderate patients who opted for not following the protocol (p < 0.05) and to all no treatment patients (p < 0.001).
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.