Conectar
Single studies support the presence of several post-COVID-19 symptoms; however, there is no evidence for the synthesis of symptoms.
We attempt to provide an overview of the persistent symptoms that post-COVID-19 patients encounter, as well as the duration of these symptoms to help them plan their rehabilitation.
Systematic review and meta-analysis.
A total of 16 studies involving 8756 patients post-COVID-19 were included.
The CINAHL, PubMed, EMBASE, Scopus, and Web of Science databases were searched from 2019 to August 2021. Observational studies that reported data on post-COVID-19 symptoms were included. The methodological quality of the studies was assessed using the Joanna Briggs Institute Critical Appraisal for Observational Studies. We included medium- to high-quality studies. We used a random-effects model for the meta-analytical pooled prevalence of each post-COVID-19 symptom, and I 2 statistics for heterogeneity.
From the 2481 studies identified, 16 met the inclusion criteria. The sample included 7623 hospitalised and 1133 non-hospitalised patients. We found the most prevalent symptoms were fatigue and dyspnea with a pooled prevalence ranging from 42% (27%–58%). Other post-COVID-19 symptoms included sleep disturbance 28% (14%–45%), cough 25% (10%–44%), anosmia/ageusia 24% (7%–47%), fever 21% (4%–47%), myalgia 17% (2%–41%), chest pain 11% (5%–20%), and headache 9% (2%–20%). In addition to physical symptoms, anxiety/depression was also prevalent 27% (8%–53%).
Fatigue and dyspnea were the most prevalent post-COVID-19 symptoms and experienced up to 12 months.
Multiple persistent symptoms are still experienced until 12 months of post-Covid 19. This meta-analysis should provide some awareness to nurses to highlights the unmet healthcare needs of post-COVID-19 patients. Long-term monitoring for the evaluation and treatment of symptoms and conditions and rehabilitation programs should be conducted.
by Tomasz Kulik, Tomasz Molcan, Katarzyna Bilska, Marco Beyer, Matias Pasquali, Anne van Diepeningen, Kamil Myszczynski
Fusarium graminearum is the main causal agent of Fusarium head blight (FHB) disease in wheat in Europe. To reveal population structure and to pinpoint genetic targets of selection we studied genomes of 96 strains of F. graminearum using population genomics. Bayesian and phylogenomic analyses indicated that the F. graminearum emergence in Europe could be linked to two independently evolving populations termed here as East European (EE) and West European (WE) population. The EE strains are primarily prevalent in Eastern Europe, but to a lesser extent also in western and southern areas. In contrast, the WE population appears to be endemic to Western Europe. Both populations evolved in response to population-specific selection forces, resulting in distinct localized adaptations that allowed them to migrate into their environmental niche. The detection of positive selection in genes with protein/zinc ion binding domains, transcription factors and in genes encoding proteins involved in transmembrane transport highlights their important role in driving evolutionary novelty that allow F. graminearum to increase adaptation to the host and/or environment. F. graminearum also maintained distinct sets of accessory genes showing population-specific conservation. Among them, genes involved in host invasion and virulence such as those encoding proteins with high homology to tannase/feruloyl esterase and genes encoding proteins with functions related to oxidation-reduction were mostly found in the WE population. Our findings shed light on genetic features related to microevolutionary divergence of F. graminearum and reveal relevant genes for further functional research aiming at better control of this pathogen.Early identification of lung cancer on chest radiographs improves patient outcomes. Artificial intelligence (AI) tools may increase diagnostic accuracy and streamline this pathway. This study evaluated the performance of commercially available AI-based software trained to identify cancerous lung nodules on chest radiographs.
This retrospective study included primary care chest radiographs acquired in a UK centre. The software evaluated each radiograph independently and outputs were compared with two reference standards: (1) the radiologist report and (2) the diagnosis of cancer by multidisciplinary team decision. Failure analysis was performed by interrogating the software marker locations on radiographs.
5722 consecutive chest radiographs were included from 5592 patients (median age 59 years, 53.8% women, 1.6% prevalence of cancer).
Compared with radiologist reports for nodule detection, the software demonstrated sensitivity 54.5% (95% CI 44.2% to 64.4%), specificity 83.2% (82.2% to 84.1%), positive predictive value (PPV) 5.5% (4.6% to 6.6%) and negative predictive value (NPV) 99.0% (98.8% to 99.2%). Compared with cancer diagnosis, the software demonstrated sensitivity 60.9% (50.1% to 70.9%), specificity 83.3% (82.3% to 84.2%), PPV 5.6% (4.8% to 6.6%) and NPV 99.2% (99.0% to 99.4%). Normal or variant anatomy was misidentified as an abnormality in 69.9% of the 943 false positive cases.
The software demonstrated considerable underperformance in this real-world patient cohort. Failure analysis suggested a lack of generalisability in the training and testing datasets as a potential factor. The low PPV carries the risk of over-investigation and limits the translation of the software to clinical practice. Our findings highlight the importance of training and testing software in representative datasets, with broader implications for the implementation of AI tools in imaging.
The aim of this study is to provide insight from maternal survivors of intimate partner violence (IPV) describing their experiences with their ex-partners' firearm ownership, access, storage and behaviours in the context of co-parenting and separation.
We conducted a qualitative descriptive study informed by the IPV and Coparenting Model.
The analytic sample consists of self-identified maternal survivors (n = 14) who completed semi-structured qualitative interviews between January and May 2023 describing experiences of post-separation abuse. Participants were recruited through social media and domestic violence advocacy and legal aid organizations. In the interview guide, participants were asked one item about firearm exposure: Have you or your children had any experiences with guns and your ex-partner that made you or your children feel scared? Interviews were audio-recorded and transcribed. Interview transcripts were managed and coded in ATLAS.ti using a codebook. Codes were applied using descriptive content analysis, discrepancies reconciled and themes related to firearm exposure in the context of post-separation abuse identified.
Six themes emerged related to firearm experiences and post-separation abuse: (1) gun ownership (2) gun access; (3) unsafe storage; (4) direct and symbolic threats; (5) involving the children; (6) survivors' protective actions.
This manuscript provides context on how abusive ex-partners' firearm ownership, access and threats cause terror and pervasive fear for mothers and children following separation. Analysis of qualitative data provides important insights into opportunities to address firearm injury prevention.
Findings add to the contextual understanding of how survivors of IPV experience non-fatal firearm abuse. Existing quantitative data may not capture the full extent of fear caused by perpetrators' gun ownership access and symbolic threats. Data from this study can help inform firearm injury prevention efforts.
The authors would like to acknowledge and thank the individuals who helped in cognitive testing of the interview guide prior to conducting interviews with participants, including (3) survivors of post-separation abuse. The authors would also like to acknowledge domestic violence advocates and those individuals who helped with recruitment and connected us with participants. Importantly, with deep gratitude, the authors would like to thank the participants who generously shared their time and stories with us.
FreshRSS 