Clinical Features of COVID-19 Patients in the First Year of Pandemic: A Systematic Review and Meta-Analysis.

BACKGROUND: The new coronavirus disease (COVID-19) carries a high risk of infection and has spread rapidly around the world. However, there are limited data about the clinical symptoms globally. The purpose of this systematic review and meta-analysis is to identify the prevalence of the clinical symptoms of patient with COVID-19. METHODS: A systematic review and meta-analysis were carried out. The following databases were searched: PubMed, CINAHL, MEDLINE, EMBASE, PsycINFO, medRxiv, and Google Scholar, from December 1st, 2019 to January 1st, 2021. Prevalence rates were pooled with meta-analysis using a random-effects model. Heterogeneity was tested using I-squared (I2) statistics. RESULTS: A total of 215 studies, involving 132,647 COVID-19 patients, met the inclusion criteria. The pooled prevalence of the four most common symptoms were fever 76.2% (n = 214; 95% CI 73.9-78.5); coughing 60.4% (n = 215; 95% CI 58.6-62.1); fatigue 33.6% (n = 175; 95% CI 31.2-36.1); and dyspnea 26.2% (n = 195; 95% CI 24.1-28.5). Other symptoms from highest to lowest in terms of prevalence include expectorant (22.2%), anorexia (21.6%), myalgias (17.5%), chills (15%), sore throat (14.1%), headache (11.7%), nausea or vomiting (8.7%), rhinorrhea (8.2%), and hemoptysis (3.3%). In subgroup analyses by continent, it was found that four symptoms have a slight prevalence variation-fever, coughing, fatigue, and diarrhea. CONCLUSION: This meta-analysis found the most prevalent symptoms of COVID-19 patients were fever, coughing, fatigue, and dyspnea. This knowledge might be beneficial for the effective treatment and control of the COVID-19 outbreak. Additional studies are required to distinguish between symptoms during and after, in patients with COVID-19.

Prevalence of Fatigue in Patients With Cancer: A Systematic Review and Meta-Analysis.

CONTEXT: Fatigue is a particularly common and troubling symptom that has a negative impact on quality of life throughout all phases of treatment and stages of the illness among patients with cancer. OBJECTIVES: The objective of this meta-analysis is to examine the present status of fatigue prevalence in patients with cancer. METHODS: The following databases were searched: PubMed, MEDLINE, EMBASE, PsycINFO, Cochrane Library, from inception up to February 2020. Prevalence rates were pooled with meta-analysis using a random-effects model. Heterogeneity was tested using I-squared (I2) statistics. RESULTS: A total of 129 studies (N = 71,568) published between 1993 and 2020 met the inclusion criteria. The overall prevalence of fatigue was 49% (34,947 of 71,656 participants, 95% CI = 45-53) with significant heterogeneity between studies (P < 0.000; τ2 = 0.0000; I2 = 98.88%). Subgroup analyses show that the prevalence of fatigue related to type of cancer ranged from 26.2% in patients with gynecological cancer to 56.3% in studies that included mixed types of cancer. In advanced cancer stage patients, the highest prevalence of fatigue (60.6%) was reported. Fatigue prevalence rates were 62% during treatment and 51% during mixed treatment status. The prevalence of fatigue decreased from 64% in studies published from 1996 to 2000 to 43% in studies published from 2016 to 2020. Metaregression identified female gender as a significant moderator for higher prevalence of fatigue, whereas mean age is not associated with fatigue. CONCLUSION: This meta-analysis highlights the importance of developing optimal monitoring strategies to reduce fatigue and improve the quality of life of patients with cancer.

Discrete event simulation and pharmacy process re-engineering.

PURPOSE: The purpose of this paper is to describe a case study undertaken at Al Buraimi Hospital in Oman, which used computer simulation and the Delphi approach to improve efficiency by reducing prescription dispensing waiting times. DESIGN/METHODOLOGY/APPROACH: This study's framework was based on a discrete event simulation (DES) to identify the as-is pharmacy process and to create a to-be (future situation) to achieve an improvement in pharmacy workflow and service quality. Owing to healthcare environment complexity, and to gain a deeper understanding about Al Buraimi Hospital pharmacy problems, a Delphi technique was also used. FINDINGS: Based on Delphi, and according to the expert panel suggestions, two alternative scenarios were proposed to improve Al Buraimi Hospital pharmacy efficiency: fast-track and direct-dispensing, which should help to reduce the prescription dispensing waiting time process by 7.3 and 9.8 min, respectively. RESEARCH LIMITATIONS/IMPLICATIONS: The main limitation is the pharmacists' shortage, which may affect the prescription dispensing process's quality as insufficient manpower to check the prescriptions may increase the medication errors' risk. ORIGINALITY/VALUE: Based on this case study's real-world data, findings can be used to improve public healthcare sector pharmacy efficiency. The DES can be used in healthcare services to describe and test actual and proposed situations.