Relationships Between the Physical Work Environment, Postures and Musculoskeletal Pain During COVID-19: A Survey of Frequent Computer Users.

OBJECTIVE: To understand the flexible work practices during the COVID-19 pandemic and their impact on work-related musculoskeletal disorders (MSDs) and depression in frequent computer users. METHODS: An e-survey determined the extent of workplace changes and MSD, and the relationships between them using descriptive-statistics and chi-squared tests. RESULTS: Of 700 who commenced the survey, 511 were analyzed. Since the pandemic commenced, 80% of respondents reported they were working more from home; and 89% reported some musculoskeletal pain. Compared with prepandemic, more people worked in nonergonomic environments, computer configurations and body postures. Work location was associated with upper back pain ( P = 0.011); body posture with headache ( P = 0.027) and low back pain ( P = 0.003). CONCLUSION: Nonergonomic work environments of frequent computer users during COVID-19 are related to having upper back pain, whereas nonergonomic postures are related to having headache and low back pain.

Impact of the COVID-19 pandemic on suicidal attempts and death rates: a systematic review

The COVID-19 pandemic has exacerbated the risk factors associated with suicidal behavior and thus, prioritizing its prevention is recommended. This study systematically reviewed the global evidence on the incidence of suicide/suicidal attempts and the trend in suicidal rates during the COVID-19 pandemic. Cross-sectional and cohort studies investigating the outcomes of suicidal death and suicidal attempts at any setting during the COVID-19 pandemic were searched in Medline, Embase, and PsycINFO databases for papers published from December 2019 to May 2021. Out of 1052 studies18 studies with 12,746 suicidal attempts and 33,345 suicidal deaths were included in the final analysis. The mental health impact of social distancing, COVID-19 quarantine, and financial crises due to loss of employment were associated risk factors with suicide and/or suicidal attempts during the COVID-19 pandemic. Six common thematic recommendations for preventing suicidal deaths and suicidal attempts were identified. Unexpected behavior changes during the COVID-19 pandemic may have contributed to the increasing trend of suicidal attempts reported. Domestic conflicts and violence, financial loss, anxiety and depression, and pre-existing mental health condition/s should be considered in preventing suicidal attempts and deaths secondary to the COVID 19 pandemic. Early detection and timely intervention for individuals with suicidal behavior is crucial and collated recommendations in the current study can be utilized for those preventive interventions. More systematic suicide risk screening process should be introduced who are at risk, along with an evidence base prevention approach.

Adverse Perinatal Outcomes in COVID-19 Infected Pregnant Women: A Systematic Review and Meta-Analysis.

The impact of COVID-19 virus infection during pregnancy is still unclear. This systematic review and meta-analysis aimed to quantitatively pool the evidence on impact of COVID-19 infection on perinatal outcomes. Databases of Medline, Embase, and Cochrane library were searched using the keywords related to COVID-19 and perinatal outcomes from December 2019 to 30 June 2021. Observational studies comparing the perinatal outcomes of COVID-19 infection in pregnancy with a non-infected comparator were included. The screening process and quality assessment of the included studies were performed independently by two reviewers. Meta-analyses were used to pool the comparative dichotomous data on perinatal outcomes. The database search yielded 4049 results, 1254 of which were duplicates. We included a total of 21 observational studies that assessed the adverse perinatal outcomes with COVID-19 infection. The odds of maternal death (pooled OR: 7.05 [2.41-20.65]), preeclampsia (pooled OR: 1.39 [1.29-1.50]), cesarean delivery (pooled OR: 1.67 [1.29-2.15]), fetal distress (pooled OR: 1.66 [1.35-2.05]), preterm birth (pooled OR: 1.86 [1.34-2.58]), low birth weight (pooled OR: 1.69 [1.35-2.11]), stillbirth (pooled OR: 1.46 [1.16-1.85]), 5th minute Apgar score of less than 7 (pooled OR: 1.44 [1.11-1.86]) and admissions to neonatal intensive care unit (pooled OR: 2.12 [1.36-3.32]) were higher among COVID-19 infected pregnant women compared to non-infected pregnant women.

Factors Associated for Mortality of Older People With COVID 19: A Systematic Review and Meta-analysis.

BACKGROUND: Whilst people of all ages are affected in some way by COVID-19 virus, older people are at a high mortality risk. This study aimed to systematically review the numerous factors associated with mortality among COVID-19 infected older people. METHOD: PubMed and Science Direct were searched from inception to the April 15, 2021. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 statement and Joanna Briggs Institute critical appraisal tool to assess the methodological quality of the included studies. RESULTS: Of the 4957 studies identified, 20 were included in the qualitative analysis, while 10 were included in the quantitative analysis. Male sex (OR = 2.22, 95% CI = 1.23-3.99), age (over 75 years old) (OR = 3.36, 95% CI = 2.30-4.90), Dementia (OR = 3.69, 95% CI = 1.99-6.83) and Dyspnoea (OR = 3.16, 95% CI = 2.61-3.82), were found to be significantly associated with mortality. There is no significant association between Diabetes, or Hypertension. CONCLUSION: Older age, male gender, dyspnoea and dementia were associated with a greater risk of death of older people from COVID-19 infection. These findings may help health care professionals to identify high-risk groups, facilitate appropriate remedial measures, and control mortality among older people.

Novel Coronavirus Infection (COVID-19) in Humans: A Scoping Review and Meta-Analysis.

A growing body of literature on the 2019 novel coronavirus (SARS-CoV-2) is becoming available, but a synthesis of available data has not been conducted. We performed a scoping review of currently available clinical, epidemiological, laboratory, and chest imaging data related to the SARS-CoV-2 infection. We searched MEDLINE, Cochrane CENTRAL, EMBASE, Scopus and LILACS from 01 January 2019 to 24 February 2020. Study selection, data extraction and risk of bias assessment were performed by two independent reviewers. Qualitative synthesis and meta-analysis were conducted using the clinical and laboratory data, and random-effects models were applied to estimate pooled results. A total of 61 studies were included (59,254 patients). The most common disease-related symptoms were fever (82%, 95% confidence interval (CI) 56%-99%; n = 4410), cough (61%, 95% CI 39%-81%; n = 3985), muscle aches and/or fatigue (36%, 95% CI 18%-55%; n = 3778), dyspnea (26%, 95% CI 12%-41%; n = 3700), headache in 12% (95% CI 4%-23%, n = 3598 patients), sore throat in 10% (95% CI 5%-17%, n = 1387) and gastrointestinal symptoms in 9% (95% CI 3%-17%, n = 1744). Laboratory findings were described in a lower number of patients and revealed lymphopenia (0.93 × 109/L, 95% CI 0.83-1.03 × 109/L, n = 464) and abnormal C-reactive protein (33.72 mg/dL, 95% CI 21.54-45.91 mg/dL; n = 1637). Radiological findings varied, but mostly described ground-glass opacities and consolidation. Data on treatment options were limited. All-cause mortality was 0.3% (95% CI 0.0%-1.0%; n = 53,631). Epidemiological studies showed that mortality was higher in males and elderly patients. The majority of reported clinical symptoms and laboratory findings related to SARS-CoV-2 infection are non-specific. Clinical suspicion, accompanied by a relevant epidemiological history, should be followed by early imaging and virological assay.

Coronavirus disease (COVID-19) pandemic: an overview of systematic reviews.

BACKGROUND: Navigating the rapidly growing body of scientific literature on the SARS-CoV-2 pandemic is challenging, and ongoing critical appraisal of this output is essential. We aimed to summarize and critically appraise systematic reviews of coronavirus disease (COVID-19) in humans that were available at the beginning of the pandemic. METHODS: Nine databases (Medline, EMBASE, Cochrane Library, CINAHL, Web of Sciences, PDQ-Evidence, WHO's Global Research, LILACS, and Epistemonikos) were searched from December 1, 2019, to March 24, 2020. Systematic reviews analyzing primary studies of COVID-19 were included. Two authors independently undertook screening, selection, extraction (data on clinical symptoms, prevalence, pharmacological and non-pharmacological interventions, diagnostic test assessment, laboratory, and radiological findings), and quality assessment (AMSTAR 2). A meta-analysis was performed of the prevalence of clinical outcomes. RESULTS: Eighteen systematic reviews were included; one was empty (did not identify any relevant study). Using AMSTAR 2, confidence in the results of all 18 reviews was rated as "critically low". Identified symptoms of COVID-19 were (range values of point estimates): fever (82-95%), cough with or without sputum (58-72%), dyspnea (26-59%), myalgia or muscle fatigue (29-51%), sore throat (10-13%), headache (8-12%) and gastrointestinal complaints (5-9%). Severe symptoms were more common in men. Elevated C-reactive protein and lactate dehydrogenase, and slightly elevated aspartate and alanine aminotransferase, were commonly described. Thrombocytopenia and elevated levels of procalcitonin and cardiac troponin I were associated with severe disease. A frequent finding on chest imaging was uni- or bilateral multilobar ground-glass opacity. A single review investigated the impact of medication (chloroquine) but found no verifiable clinical data. All-cause mortality ranged from 0.3 to 13.9%. CONCLUSIONS: In this overview of systematic reviews, we analyzed evidence from the first 18 systematic reviews that were published after the emergence of COVID-19. However, confidence in the results of all reviews was "critically low". Thus, systematic reviews that were published early on in the pandemic were of questionable usefulness. Even during public health emergencies, studies and systematic reviews should adhere to established methodological standards.

Impact of Big Data Analytics on People's Health: Overview of Systematic Reviews and Recommendations for Future Studies.

BACKGROUND: Although the potential of big data analytics for health care is well recognized, evidence is lacking on its effects on public health. OBJECTIVE: The aim of this study was to assess the impact of the use of big data analytics on people's health based on the health indicators and core priorities in the World Health Organization (WHO) General Programme of Work 2019/2023 and the European Programme of Work (EPW), approved and adopted by its Member States, in addition to SARS-CoV-2-related studies. Furthermore, we sought to identify the most relevant challenges and opportunities of these tools with respect to people's health. METHODS: Six databases (MEDLINE, Embase, Cochrane Database of Systematic Reviews via Cochrane Library, Web of Science, Scopus, and Epistemonikos) were searched from the inception date to September 21, 2020. Systematic reviews assessing the effects of big data analytics on health indicators were included. Two authors independently performed screening, selection, data extraction, and quality assessment using the AMSTAR-2 (A Measurement Tool to Assess Systematic Reviews 2) checklist. RESULTS: The literature search initially yielded 185 records, 35 of which met the inclusion criteria, involving more than 5,000,000 patients. Most of the included studies used patient data collected from electronic health records, hospital information systems, private patient databases, and imaging datasets, and involved the use of big data analytics for noncommunicable diseases. "Probability of dying from any of cardiovascular, cancer, diabetes or chronic renal disease" and "suicide mortality rate" were the most commonly assessed health indicators and core priorities within the WHO General Programme of Work 2019/2023 and the EPW 2020/2025. Big data analytics have shown moderate to high accuracy for the diagnosis and prediction of complications of diabetes mellitus as well as for the diagnosis and classification of mental disorders; prediction of suicide attempts and behaviors; and the diagnosis, treatment, and prediction of important clinical outcomes of several chronic diseases. Confidence in the results was rated as "critically low" for 25 reviews, as "low" for 7 reviews, and as "moderate" for 3 reviews. The most frequently identified challenges were establishment of a well-designed and structured data source, and a secure, transparent, and standardized database for patient data. CONCLUSIONS: Although the overall quality of included studies was limited, big data analytics has shown moderate to high accuracy for the diagnosis of certain diseases, improvement in managing chronic diseases, and support for prompt and real-time analyses of large sets of varied input data to diagnose and predict disease outcomes. TRIAL REGISTRATION: International Prospective Register of Systematic Reviews (PROSPERO) CRD42020214048; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=214048.

Clinical, laboratory and radiological characteristics and outcomes of novel coronavirus (SARS-CoV-2) infection in humans: A systematic review and series of meta-analyses.

New evidence on the COVID-19 pandemic is being published daily. Ongoing high-quality assessment of this literature is therefore needed to enable clinical practice to be evidence-based. This review builds on a previous scoping review and aimed to identify associations between disease severity and various clinical, laboratory and radiological characteristics. We searched MEDLINE, CENTRAL, EMBASE, Scopus and LILACS for studies published between January 1, 2019 and March 22, 2020. Clinical studies including ≥10 patients with confirmed COVID-19 of any study design were eligible. Two investigators independently extracted data and assessed risk of bias. A quality effects model was used for the meta-analyses. Subgroup analysis and meta-regression identified sources of heterogeneity. For hospitalized patients, studies were ordered by overall disease severity of each population and this order was used as the modifier variable in meta-regression. Overall, 86 studies (n = 91,621) contributed data to the meta-analyses. Severe disease was strongly associated with fever, cough, dyspnea, pneumonia, any computed tomography findings, any ground glass opacity, lymphocytopenia, elevated C-reactive protein, elevated alanine aminotransferase, elevated aspartate aminotransferase, older age and male sex. These variables typically increased in prevalence by 30-73% from mild/early disease through to moderate/severe disease. Among hospitalized patients, 30-78% of heterogeneity was explained by severity of disease. Elevated white blood cell count was strongly associated with more severe disease among moderate/severe hospitalized patients. Elevated lymphocytes, low platelets, interleukin-6, erythrocyte sedimentation rate and D-dimers showed potential associations, while fatigue, gastrointestinal symptoms, consolidation and septal thickening showed non-linear association patterns. Headache and sore throat were associated with the presence of disease, but not with more severe disease. In COVID-19, more severe disease is strongly associated with several clinical, laboratory and radiological characteristics. Symptoms and other variables in early/mild disease appear non-specific and highly heterogeneous. Clinical Trial Registration: PROSPERO CRD42020170623.