COVID-19-associated lung weakness (CALW): Systematic review and meta-analysis

Redruello-Guerrero, Pablo; Ruiz-del-Pino, Marta; Jiménez-Gutiérrez, Carmen; Jiménez-Gutiérrez, Paula; Carrascos-Cáliz, Ana; Romero-Linares, Alejandro; Ramos‐Bossini, Antonio Jesús Láinez; Rivera-Izquierdo, Mario; Cárdenas-Cruz, Antonio

doi:10.1016/j.medine.2023.06.001

Cited by 3 publications

(4 citation statements)

References 32 publications

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“…Severe lung damage, secondary to a COVID-19 inflammatory response and barotrauma triggered by positive pressure ventilation, may lead to lung injury. A recent review showed that mortality among COVID-19 patients was higher among those who developed PNX/PNMD [23]. Similarly, in our study, as presented in Table 2, the in-hospital mortality rate in patients that developed barotrauma exceeded ten times the overall mortality rate (61.42%; OR = 25.1).…”

Section: Pneumothorax/pneumomediastinumsupporting

confidence: 84%

Evolving Clinical Manifestations and Outcomes in COVID-19 Patients: A Comparative Analysis of SARS-CoV-2 Variant Waves in a Romanian Hospital Setting

Briciu,

Leucuta,

Muntean

et al. 2023

Pathogens

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The aim of this study was to evaluate differences in the clinical manifestations and outcomes in hospitalized patients with COVID-19 in a single Romanian center during four pandemic waves determined by different SARS-CoV-2 variants of concern (VOCs). A retrospective study on 9049 consecutive hospitalized adult patients was performed between 27 February 2020 and 31 March 2023. The study interval was divided into waves based on national data on SARS-CoV-2 VOCs’ circulation. Multivariate logistic regression models were built, predicting death and complications as functions of comorbidities, therapy, wave, severity form, and vaccination status, and adjusted for ages ≥65 years. Pulmonary (pneumothorax/pneumomediastinum, pulmonary embolism) and extrapulmonary complications (liver injury, acute kidney injury, ischemic/hemorrhagic stroke, myocardial infarction, and gastrointestinal bleeding) were present, more frequently in ICU hospitalized patients and with differences between waves. The highest in-hospital mortality was found in patients presenting pneumothorax/pneumomediastinum. All of the evaluated risk factors were significantly associated with death, except for obesity and the Omicron wave. Our study highlights the changing nature of COVID-19 and acknowledges the impacts of viral mutations on disease outcomes. For all four waves, COVID-19 was a severe disease with a high risk of poor outcomes.

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Section: Pneumothorax/pneumomediastinumsupporting

confidence: 84%

Evolving Clinical Manifestations and Outcomes in COVID-19 Patients: A Comparative Analysis of SARS-CoV-2 Variant Waves in a Romanian Hospital Setting

Briciu,

Leucuta,

Muntean

et al. 2023

Pathogens

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“…There was also a review and analysis of existing scientific data on the use of artificial intelligence to identify and diagnose Frailty in the elderly [42]. Most of the reviews were done to diagnose fragility in various diseases [43][44][45].…”

Section: Discussionmentioning

confidence: 99%

Diagnostic Methods of Frailty Syndrome Used in 2018-2023: Scoping Review Pubmed

OMAROVA,

YESHMANOVA,

GABDULINA

2024

Farmaciâ Kazahstana

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Background: Frailty syndrome is a pathological, reversible aging process where frailty and comorbidity have a bidirectional relationship. It is characterized by having three of more of the following components: weight loss, exhaustion, slowness, low activity level, and weakness. Methods: We searched PubMed from January 1, 2018 to November 1, 2023. The dates of publication, language of publication, methodological characteristics and the key findings were analyzed separately. Results: We found 550 unfinished studies on the use of diagnostic methods for the Frailty syndrome. Only 26 suitable articles were found. 19 randomised controlled trials, 2 cohort study, 2 cross-sectional study, 1 case study,1 longitudinal study, 1 report. Conclusion: We conducted this evaluation review in order to identify clinical examples of the use of diagnostic methods of fragility syndrome in the period from 2018 to 2023. Only 26 suitable articles were found. This suggests that this topic has been little studied. There is not enough evidence. It is necessary to conduct more original research on this topic.

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“…An analysis of 70 PROSPERO protocols was conducted as part of this systematic review, with five being centered on COVID-19. Three studies demonstrated the effectiveness of AI algorithms in tasks such as COVID-19 detection from highresolution CT images [22], patient triaging based on medical imaging [23], and conducting systematic reviews [24]. However, these studies also highlighted considerable limitations related to data heterogeneity and the limited quantity of available data for AI training, indicating a requirement for enhanced future research [23].…”

Section: Covid-19mentioning

confidence: 99%

“…Three studies demonstrated the effectiveness of AI algorithms in tasks such as COVID-19 detection from highresolution CT images [22], patient triaging based on medical imaging [23], and conducting systematic reviews [24]. However, these studies also highlighted considerable limitations related to data heterogeneity and the limited quantity of available data for AI training, indicating a requirement for enhanced future research [23]. A fourth study [25] reinforced the need for high-quality datasets, reproducible studies with thorough documentation, and external validation to increase the likelihood of these models being integrated into future clinical trials.…”

Section: Covid-19mentioning

confidence: 99%

Artificial Intelligence in Biomedicine: Systematic Review

Gabashvili¹

2023

Preprint

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Artificial Intelligence (AI) is a rapidly progressing technology with its applications expanding exponentially over the past decade. While initial breakthroughs predominantly focused on deep learning and computer vision, recent advancements have facilitated a shift towards natural language processing and beyond. This includes generative models, like ChatGPT, capable of understanding the 'grammar' of software code, analog signals, and molecular structures. This research undertakes a comprehensive examination of AI trends within the biomedical domain, including the impact of ChatGPT. We explore scientific literature, clinical trials, and FDA-approval data, utilizing a thematic synthesis approach and bibliometric mapping of keywords to examine numerous subsets from over a hundred thousand unique records found in prominent public repositories up to mid- July 2023. Our analysis reveals a higher prevalence of general health-related publications compared to more specialized papers using or evaluating ChatGPT. However, the growth in specialized papers suggests a convergence with the trend observed for other AI tools. Our findings also imply a greater prevalence of publications using ChatGPT across multiple medical specialties compared to other AI tools, indicating its rising influence in complex fields requiring interdisciplinary collaboration. Leading topics in AI literature include radiology, ethics, drug discovery, COVID-19, robotics, brain research, stroke, and laparoscopy, indicating a shift from laboratory to emergency medicine and deep-learning-based image processing. Publications involving ChatGPT predominantly address current themes such as COVID-19, practical applications, interdisciplinary collaboration, and risk mitigation. Radiology retains dominance across all stages of biomedical R&D, spanning preprints, peer-reviewed papers, clinical trials, patents, and FDA approvals. Meanwhile, surgery-focused papers appear more frequently within ChatGPT preprints and case reports. Traditionally less represented areas, such as Pediatrics, Otolaryngology, and Internal Medicine, are starting to realize the benefits of ChatGPT, hinting at its potential to spark innovation within new medical sectors. AI application in geriatrics is notably underrepresented in publications. However, ongoing clinical trials are already exploring the use of ChatGPT for managing age-related conditions. The higher frequency of general health-related publications compared to specialized papers employing or evaluating ChatGPT showcases its broad applicability across multiple fields. AI, particularly ChatGPT, possesses significant potential to reshape the future of medicine. With millions of papers published annually across various disciplines, efficiently navigating the information deluge to pinpoint valuable studies has become increasingly challenging. Consequently, AI methods, gaining in popularity, are poised to redefine the future of scientific publishing and its educational reach. Despite challenges like quality of training data and ethical concerns, prevalent in preceding AI tools, the wider applicability of ChatGPT across diverse fields is manifest. This review employed the PRISMA tool and numerous overlapping data sources to minimize bias risks.

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COVID-19-associated lung weakness (CALW): Systematic review and meta-analysis

Cited by 3 publications

References 32 publications

Evolving Clinical Manifestations and Outcomes in COVID-19 Patients: A Comparative Analysis of SARS-CoV-2 Variant Waves in a Romanian Hospital Setting

Evolving Clinical Manifestations and Outcomes in COVID-19 Patients: A Comparative Analysis of SARS-CoV-2 Variant Waves in a Romanian Hospital Setting

Diagnostic Methods of Frailty Syndrome Used in 2018-2023: Scoping Review Pubmed

Artificial Intelligence in Biomedicine: Systematic Review

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