Risk factors for severe disease in patients admitted with COVID-19 to a hospital in London, England: a retrospective cohort study

Were metabolic and other chronic diseases the driven onset epidemic forces of COVID-19 in Mexico?

The underline hypothesis of this study was that SARS-CoV-2 can infect individuals regardless of health condition, sex, and age in opposition to the classical epidemiological assumption of an identifiable susceptible subpopulation for epidemic development. To address this issue, a population cohort with 24.4 million metadata associated with 226,089 official RT-qPCR positive and 283,450 negative cases, including 27,769 deceased, linked putatively to B.1. and B.1.1. SARS-CoV-2 lineages were analyzed. The analysis baseline was to determine the infection and mortality structure of the diseased cohort at the onset-exponential phase of the first epidemic wave in Mexico under the assumption of limited herd immunity. Individuals with nonchronic diseases (NOCDs) were compared with those exhibiting at least one of 10 chronic diseases (CDs) adjusted by age and sex. Risk factors for infection and mortality were estimated with classification and regression tree (CART) and cluster analysis based on Spearman's matrix of rho-values in RStudio®, complemented with two proposed mortality indices. SARS-CoV-2 infection was independent of health condition (52.8% NOCD vs. 47.2% CDs; p = 0.001-0.009) but influenced by age >46 in one risk analysis scenario (p < 0.001). Sex contributed 9.7% to the overall risk. The independent effect was supported by the health structure of negative cases with a similar tendency but a higher proportion of NOCDs (61.4%, p = 0.007). The infection probability in individuals with one CD was determined by the disease type and age, which was higher in those older individuals (≥56 years) exhibiting diabetes (12.3%, cp = 0.0006), hypertension (10.1%, cp < 0.0001), and obesity (7.8%, cp = 0.001). In contrast, the mortality risk was heavily influenced by CD conditioned by sex and age, accounting for 72.3% of total deaths (p = 0.001-0.008). Significant mortality risk (48%) was comprised of women and men (w, m) aged ≥56 years with diabetes (19% w and 27.9% m, cp < 0.0004), hypertension (11.5% w, cp = 0.0001), and CKD (3.5% w and 5.3% m, cp = 0.0009). Older people with diabetes and hypertension comorbidity increased the risk to 60.5% (p = 0.001). Based on a mortality-weighted index, women were more vulnerable to preexisting metabolic or cardiovascular diseases. These findings support our hypothesis and justify the need for surveillance systems at a communitarian level. This is the first study addressing this fundamental epidemiological question.

Comorbid asthma decreased the risk for COVID-19 mortality in the United Kingdom: Evidence based on a meta-analysis

The study aimed to investigate the influence of comorbid asthma on the risk for mortality among patients with coronavirus disease 2019 (COVID-19) in the United Kingdom (UK) by utilizing a quantitative meta-analysis. The pooled odds ratio (OR) with 95% confidence interval (CI) was estimated by conducting a random-effects model. Sensitivity analysis, I² statistic, meta-regression, subgroup analysis, Begg's analysis and Egger's analysis were all implemented. Our results presented that comorbid asthma was significantly related to a decreased risk for COVID-19 mortality in the UK based on 24 eligible studies with 1,209,675 COVID-19 patients (pooled OR = 0.81, 95% CI: 0.71-0.93; I² = 89.2%, P < 0.01). Coming through further meta-regression to seek the possible cause of heterogeneity, none of elements might be responsible for heterogeneity. A sensitivity analysis proved the stability and reliability of the overall results. Both Begg's analysis (P = 1.000) and Egger's analysis (P = 0.271) manifested that publication bias did not exist. In conclusion, our data demonstrated that COVID-19 patients with comorbid asthma might bear a lower risk for mortality in the UK. Furthermore, routine intervention and treatment of asthma patients with severe acute respiratory syndrome coronavirus 2 infection should be continued in the UK.

Can lactate levels and lactate kinetics predict mortality in patients with COVID-19 with using qCSI scoring system?

INTRODUCTION

In this study, we aimed to investigate the relationship between blood lactate levels and lactate kinetics (lactate clearance and Δ lactate) for predicting mortality in patients with COVID-19 admitted to the emergency department.

METHODS

This study was performed as a retrospective study that included patients admitted to the emergency department between March 1st, 2020, and January 1st, 2022. Lactate levels were recorded at the first admission (0 h lactate) and the highest blood lactate levels in the first 24 h of follow-up (2nd highest lactate). Lactate kinetics were calculated. Clinical severity was determined according to the quick COVID Severity Index (qCSI).

RESULTS

300 patients were included in the study. Lactate levels at admission were similar in groups with or without mortality, but 2nd highest lactate levels were found to be significantly higher in the group with mortality (p < 0.001). Lactate clearance and ∆ lactate levels were also found to be lower in the mortality group (p < 0.001). Lactate kinetics in patients in the clinically low severity group were lower in the mortality group (p = 0.02 and p = 0.039, respectively). In the low-intermediate and high-intermediate groups, 0-h lactate and 2nd highest lactate levels were found to be higher in the mortality group, and lactate kinetics were similar in the groups with and without mortality. In the group with high clinical severity, 2nd highest lactate levels were found to be higher in the group with mortality (p = 0.010). Lactate kinetics were also found to be significantly lower in the mortality group (p < 0.001). In the high qCSI group, based on ROC analysis, the AUC for 2nd highest lactate levels predicting mortality was 0.642 (95% CI: 0.548-0.728). The optimal cut-off value for mortality was greater than >2.4 mmol/L (60.6% sensitivity, 67.4% specificity). The AUC for lactate clearance was 0.748 (95% CI: 0.659-0.824). The lactate clearance cut-off value was ≤ -177.78% (49.3% sensitivity, 100% specificity). The AUC for ∆ lactate was 0.707 (95% CI: 0.616-0.787). The optimal ∆ lactate cut-off was ≤ -2 mmol/L (45.1% sensitivity, 93.5% specificity).

CONCLUSION

In COVID-19, 2nd highest blood lactate and lactate kinetics were found to be prognostic indicators of the disease. High 2nd highest lactate levels and low lactate kinetics in patients with high clinical severity were guiding physicians regarding the outcome of the disease.

"Day 25": a temporal indicator of stabilization of mortality risk among COVID-19 patients with high viral load

INTRODUCTION

The relationship between SARS-CoV-2 viral load and hospitalization and mortality among COVID-19 patients has been established. However, the estimation of the duration of time after which the risk of mortality of these patients stops escalating was not extensively discussed earlier. Stratifying patients according to their risk of mortality would optimize healthcare services and costs and reduce mortality.

METHODOLOGY

In this retrospective observational study, hospital records were used to collect data of 519 COVID-19 patients from May through November 2020. Data included the clinical condition of patients, their viral loads, their admission chest computed tomography results (CO-RAD scale), and the duration of their hospitalization. A Kaplan-Meier analysis was constructed to estimate mortality risk concerning viral load.

RESULTS

By the end of the study, 20.42% of patients were deceased. The cumulative mortality was: 36.1% (75/208) among patients with high viral load, 12.6% (28/222) in those with moderate viral load, and 3.4% (3/89) among those with low viral load. Predictors of mortality were: older age [adjusted hazard ratio (aHR) = 1.02, 95% CI: [1.00-1.03], (p = 0.05)], "being female" [aHR = 1.53 with 95% CI: [1.03-2.26], (p = 0.031), "high CO-RAD scale" [aHR = 1.32 (1.06-1.64), p = 0.013], "high viral load" [aHR = 4.59 (2.38-20.92), p = 0.017, ICU admission [aHR = 15.95; 95%CI:7.22-35.20, p < 0.001] and lymphocytosis [aHR = 1.89 45;95%CI:1.04-3.45, p = 0.036]. In the ICU-admitted patients, the median survival was 19 days and mortality stabilized at "day 25". For patients with high viral load, mortality rates stabilized at "day 25 post-admission" after which the risks of mortality did not change until day 40, while patients with low and moderate viral loads reached the peak and stabilized at day "20 post-admission".

CONCLUSIONS

Initial high SARS-CoV-2 viral load might be used as an indicator of a delayed stabilization of mortality risk among COVID-19 patients.

Telemonitoring for COVID-19 positive pregnant women; feasibility and user experience of SAFE@home Corona: prospective pilot study

Background

COVID-19 has catalysed digital innovations enabling remote healthcare. Pregnant women are at increased risk for severe course of COVID-19 infection. Also, the pandemic has a negative emotional impact on pregnant women as they worry about their own health and the health of their unborn child. We developed a telemonitoring platform called SAFE@home-corona consisting of a pulse oximeter and an app with symptom checklist. The aim of this study was to examine the feasibility, defined by compliance to the platform and by monitoring the course of COVID-19, patient satisfaction and user experience of a telemonitoring platform in COVID-19 positive pregnant women in the Netherlands.

Methods

We conducted a prospective pilot study among Dutch-speaking COVID-19 symptomatic pregnant women. Women were asked to monitor their oxygen-saturation with a pulse oximeter and COVID-related complaints with an in-app questionnaire daily. Oxygen-saturation and complaints were monitored by the Medical Management Centre with triage protocol. COVID-19, pregnancy, and user experience data were collected. To assess feasibility, compliance of daily self-monitoring and compliance of all intended measurements were calculated. Severity of COVID-19 was assessed via the platform and medical record. Patient satisfaction and user experience were measured through a self-developed questionnaire.

Results

Twenty-eight women were eligible of which 27 (93.1%) completed the study. Compliance of daily measurement and all intended measurements was high with 98.9 and 93.9%, respectively. Six women were hospitalized, of whom one to the intensive care unit. Overall, women indicated high satisfaction scores, varying from 8 to 10/10. Women were more concerned for the health of their unborn child or family then for themselves (66.7%). They stated that the platform offered reassurance. Patients would highly recommend the platform to pregnant peers during COVID infection.

Conclusions

This pilot study demonstrated feasibility of the SAFE@home-corona platform for self-monitoring COVID-19 course in pregnant women. Patients were satisfied, it offered reassurance, women would recommend use to peers. Upscaling the platform is needed to draw conclusions from the early signalling abilities and to keep evaluating patient satisfaction. The platform has great potential for self-monitoring of COVID-19 and possibly other pulmonary infections in pregnant women.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12884-022-04878-7.

Does metformin affect outcomes in COVID-19 patients with new or pre-existing diabetes mellitus? A systematic review and meta-analysis

AIMS

The COVID-19 pandemic is a global public health emergency and patients with diabetes mellitus (DM) are disproportionately affected, exhibiting more severe outcomes. Recent studies have shown that metformin is associated with improved outcomes in patients with COVID-19 and DM and may be a potential candidate for drug repurposing. We aimed to investigate the effects of metformin on outcomes in patients with COVID-19 and DM.

METHODS

Databases (PubMed, Scopus, Web of Science, EMBASE, Clinicaltrials.gov and Cochrane library) were searched up to 10 April 2021 for studies reporting data on metformin use in COVID-19 patients with DM. The risk of bias was assessed using the Newcastle-Ottawa scale. Certainty of evidence was rated using the GRADE approach. The primary outcome was mortality reported as odds ratio (OR). A random-effects meta-analysis was carried out on both unadjusted and adjusted ORs. This study is registered with PROSPERO, CRD42020221842.

RESULTS

In total, 2 916 231 patients from 32 cohort studies were included in the quantitative and qualitative synthesis. The meta-analysis showed that metformin was significantly associated with lower mortality in COVID-19 patients with DM in both unadjusted (OR 0.61 [95% confidence interval: 0.53-0.71], P < .00001, I2  = 70%) and adjusted (OR 0.78 [95% confidence interval: 0.69-0.88], P < .00001, I2  = 67%) models.

CONCLUSION

Poor outcomes in COVID-19 patients with DM can be attributed to inadequate glycaemic control and weakened immune responses. Metformin has multiple effects that can improve outcomes in patients with DM and our findings highlight a possible role of its use. However, robust randomised trials are needed to thoroughly assess its use.

Preadmission use of antidiabetic medications and mortality among patients with COVID-19 having type 2 diabetes: A meta-analysis

BACKGROUND

Diabetes is an independent predictor of poor outcomes in patients with COVID-19. We compared the effects of the preadmission use of antidiabetic medications on the in-hospital mortality of patients with COVID-19 having type 2 diabetes.

METHODS

A systematic search of PubMed, EMBASE, Scopus and Web of Science databases was performed to include studies (except case reports and review articles) published until November 30, 2021. We excluded papers regarding in-hospital use of antidiabetic medications. We used a random-effects meta-analysis to calculate the pooled OR (95% CI) and performed a sensitivity analysis to confirm the robustness of the meta-analyses.

MAIN FINDINGS

We included 61 studies (3,061,584 individuals), which were rated as having low risk of bias. The OR (95% CI) indicated some medications protective against COVID-related death, including metformin [0.54 (0.47-0.62), I² 86%], glucagon-like peptide-1 receptor agonist (GLP-1RA) [0.51 (0.37-0.69), I² 85%], and sodium-glucose transporter-2 inhibitor (SGLT-2i) [0.60 (0.40-0.88), I² 91%]. Dipeptidyl peptidase-4 inhibitor (DPP-4i) [1.23 (1.07-1.42), I² 82%] and insulin [1.70 (1.33-2.19), I² 97%] users were more likely to die during hospitalization. Sulfonylurea, thiazolidinedione, and alpha-glucosidase inhibitor were mortality neutral [0.92 (95% CI 0.83-1.01, I² 44%), 0.90 (95% CI 0.71-1.14, I² 46%), and 0.61 (95% CI 0.26-1.45, I² 77%), respectively]. The sensitivity analysis indicated that our findings were robust.

CONCLUSIONS

Metformin, GLP-1RA, and SGLT-2i were associated with lower mortality rate in patients with COVID-19 having type 2 diabetes. DPP-4i and insulin were linked to increased mortality. Sulfonylurea, thiazolidinedione, and alpha-glucosidase inhibitors were mortality neutral. These findings can have a large impact on the clinicians' decisions amid the COVID-19 pandemic.

Predictors of hospitalisation and death due to SARS-CoV-2 infection in Finland: A population-based register study with implications to vaccinations

INTRODUCTION

The aim of this study was to investigate how age and underlying medical conditions affect the risk of severe outcomes following SARS-CoV-2 infection and how they should be weighed while prioritising vaccinations against COVID-19.

METHODS

This population-based register study includes all SARS-CoV-2 PCR-test-positive cases until 24 Feb 2021, based on the Finnish National Infectious Diseases Register. The cases were linked to other registers to identify presence of predisposing factors and severe outcomes (hospitalisation, intensive care treatment, death). The odds of severe outcomes were compared in those with and without the pre-specified predisposing factors using logistic regression. Furthermore, population-based rates were compared between those with a given predisposing factor and those without any of the specified predisposing factors using negative binomial regression.

RESULTS

Age and various comorbidities were found to be predictors of severe COVID-19. Compared to 60-69-year-olds, the odds ratio (OR) of death was 7.1 for 70-79-year-olds, 26.7 for 80-89-year-olds, and 55.8 for ≥ 90-year-olds. Among the 20-69-year-olds, chronic renal disease (OR 9.4), malignant neoplasms (5.8), hematologic malignancy (5.6), chronic pulmonary disease (5.4), and cerebral palsy or other paralytic syndromes (4.6) were strongly associated with COVID-19 mortality; severe disorders of the immune system (8.0), organ or stem cell transplant (7.2), chronic renal disease (6.7), and diseases of myoneural junction and muscle (5.5) were strongly associated with COVID-19 hospitalisation. Type 2 diabetes and asthma, two very common comorbidities, were associated with all three outcomes, with ORs from 2.1 to 4.3. The population-based rate of SARS-CoV-2 infection decreased with age. Taking the 60-69-year-olds as reference, the rate ratio was highest (3.0) for 20-29-year-olds and < 1 for 70-79-year-olds and 80-89-year-olds.

CONCLUSION

Comorbidities predispose for severe COVID-19 among younger ages. In vaccine prioritisation both the risk of infection and the risk of severe outcomes, if infected, should be considered.

Heterogeneity and Risk of Bias in Studies Examining Risk Factors for Severe Illness and Death in COVID-19: A Systematic Review and Meta-Analysis

This systematic review and meta-analysis synthesized the evidence on the impacts of demographics and comorbidities on the clinical outcomes of COVID-19, as well as the sources of the heterogeneity and publication bias of the relevant studies. Two authors independently searched the literature from PubMed, Embase, Cochrane library, and CINAHL on 18 May 2021; removed duplicates; screened the titles, abstracts, and full texts by using criteria; and extracted data from the eligible articles. The variations among the studies were examined by using Cochrane, Q.; I2, and meta-regression. Out of 11,975 articles that were obtained from the databases and screened, 559 studies were abstracted, and then, where appropriate, were analyzed by meta-analysis (n = 542). COVID-19-related severe illness, admission to the ICU, and death were significantly correlated with comorbidities, male sex, and an age older than 60 or 65 years, although high heterogeneity was present in the pooled estimates. The study design, the study country, the sample size, and the year of publication contributed to this. There was publication bias among the studies that compared the odds of COVID-19-related deaths, severe illness, and admission to the ICU on the basis of the comorbidity status. While an older age and chronic diseases were shown to increase the risk of developing severe illness, admission to the ICU, and death among the COVID-19 patients in our analysis, a marked heterogeneity was present when linking the specific risks with the outcomes.

Improving the early identification of COVID-19 pneumonia: a narrative review

Delayed presentation of COVID-19 pneumonia increases the risk of mortality and need for high-intensity healthcare. Conversely, early identification of COVID-19 pneumonia grants an opportunity to intervene early and thus prevent more complicated, protracted and less successful hospital admissions. To improve the earlier detection of COVID-19 pneumonia in the community we provide a narrative review of current evidence examining the clinical parameters associated with early disease progression. Through an evolving literature review, we examined: the symptoms that may suggest COVID-19 progression; the timing of deterioration; the utility of basic observations, clinical examination and chest X-ray; the value of postexertion oxygen saturations; and the use of CRP to monitor disease progression. We go on to discuss the challenges in monitoring the COVID-19 patient in the community and discuss thresholds for further assessment. Confusion, persistent fever and shortness of breath were identified as worrying symptoms suggestive of COVID-19 disease progression necessitating urgent clinical contact. Importantly, a significant proportion of COVID-19 pneumonia patients appear not to suffer dyspnoea despite severe disease. Patients with this asymptomatic hypoxia seem to have a poorer prognosis. Such patients may present with other signs of hypoxia: severe fatigue, exertional fatigue and/or altered mental status. We found duration of symptoms to be largely unhelpful in determining risk, with evidence of deterioration at any point in the disease. Basic clinical parameters (pulse, respiratory rate, blood pressure, temperature and oxygen saturations (SpO₂)) are likely of high value in detecting the deteriorating community COVID-19 patient and/or COVID-19 mimickers/complications (eg, sepsis, bacterial pneumonia and pulmonary embolism). Of these, SpO₂ carried the greatest utility in detecting COVID-19 progression. CRP is an early biochemical parameter predictive of disease progression and used appropriately is likely to contribute to the early identification of COVID-19 pneumonia. Identifying progressive COVID-19 in the community is feasible using basic clinical questions and measurements. As such, if we are to limit the mortality, morbidity and the need for complicated, protracted admissions, monitoring community COVID-19 cases for signs of deterioration to facilitate early intervention is a viable strategy.

Optimal Triage for COVID-19 Patients Under Limited Health Care Resources With a Parsimonious Machine Learning Prediction Model and Threshold Optimization Using Discrete-Event Simulation: Development Study

Background

The COVID-19 pandemic has placed an unprecedented burden on health care systems.

Objective

We aimed to effectively triage COVID-19 patients within situations of limited data availability and explore optimal thresholds to minimize mortality rates while maintaining health care system capacity.

Methods

A nationwide sample of 5601 patients confirmed with COVID-19 until April 2020 was retrospectively reviewed. Extreme gradient boosting (XGBoost) and logistic regression analysis were used to develop prediction models for the maximum clinical severity during hospitalization, classified according to the World Health Organization Ordinal Scale for Clinical Improvement (OSCI). The recursive feature elimination technique was used to evaluate the maintenance of model performance when clinical and laboratory variables were eliminated. Using populations based on hypothetical patient influx scenarios, discrete-event simulation was performed to find an optimal threshold within limited resource environments that minimizes mortality rates.

Results

The cross-validated area under the receiver operating characteristic curve (AUROC) of the baseline XGBoost model that utilized all 37 variables was 0.965 for OSCI ≥6. Compared to the baseline model’s performance, the AUROC of the feature-eliminated model that utilized 17 variables was maintained at 0.963 with statistical insignificance. Optimal thresholds were found to minimize mortality rates in a hypothetical patient influx scenario. The benefit of utilizing an optimal triage threshold was clear, reducing mortality up to 18.1%, compared with the conventional Youden index.

Conclusions

Our adaptive triage model and its threshold optimization capability revealed that COVID-19 management can be achieved via the cooperation of both the medical and health care management sectors for maximum treatment efficacy. The model is available online for clinical implementation.

'Do I, don't I?' A qualitative study addressing parental perceptions about seeking healthcare during the COVID-19 pandemic

BACKGROUND

Paediatric emergency departments have seen reduced attendance during the COVID-19 pandemic. Late paediatric presentations may lead to severe illness and even death. Maintaining provision of healthcare through a pandemic is essential. This qualitative study aims to identify changing care-seeking behaviours in child health during the pandemic and ascertain parental views around barriers to care.

METHODS

Semistructured interviews were conducted with caregivers of children accessing acute paediatric services in a hospital in North-West London. Thematic content analysis was used to derive themes from the data, using a deductive approach.

RESULTS

From interviews with 15 caregivers an understanding was gained of care-seeking behaviours during the pandemic. Themes identified were; influencers of decision to seek care, experience of primary care, other perceived barriers, experiences of secondary care, advice to others following lived experience. Where delays in decision to seek care occurred this was influenced predominantly by fear, driven by community perception and experience and media portrayal. Delays in reaching care were focused on access to primary care and availability of services. Caregivers were happy with the quality of care received in secondary care and would advise friends to seek care without hesitation, not to allow fear to delay them.

CONCLUSION

A pandemic involving a novel virus is always a challenging prospect in terms of organisation of healthcare provision. This study has highlighted parental perspectives around access to care and care-seeking behaviours which can inform us how to better improve service functioning during such a pandemic and beyond into the recovery period.

Ex vivo SARS-CoV-2 infection of human lung reveals heterogeneous host defense and therapeutic responses

Cell lines are the mainstay in understanding the biology of COVID-19 infection but do not recapitulate many of the complexities of human infection. The use of human lung tissue is one solution for the study of such novel respiratory pathogens. We hypothesized that a cryopreserved bank of human lung tissue would allow for the ex vivo study of the interindividual heterogeneity of host response to SARS-CoV-2, thus providing a bridge between studies with cell lines and studies in animal models. We generated a cryobank of tissues from 21 donors, many of whom had clinical risk factors for severe COVID-19. Cryopreserved tissues preserved 90% cell viability and contained heterogenous populations of metabolically active epithelial, endothelial, and immune cell subsets of the human lung. Samples were readily infected with HCoV-OC43 and SARS-CoV-2 and demonstrated comparable susceptibility to infection. In contrast, we observed a marked donor-dependent heterogeneity in the expression of IL6, CXCL8, and IFNB1 in response to SARS-CoV-2. Treatment of tissues with dexamethasone and the experimental drug N-hydroxycytidine suppressed viral growth in all samples, whereas chloroquine and remdesivir had no detectable effect. Metformin and sirolimus, molecules with predicted but unproven antiviral activity, each suppressed viral replication in tissues from a subset of donors. In summary, we developed a system for the ex vivo study of human SARS-CoV-2 infection using primary human lung tissue from a library of donor tissues. This model may be useful for drug screening and for understanding basic mechanisms of COVID-19 pathogenesis.

Chronic Diseases as a Predictor for Severity and Mortality of COVID-19: A Systematic Review With Cumulative Meta-Analysis

Introduction: Given the ongoing coronavirus disease 2019 (COVID-19) pandemic and the consequent global healthcare crisis, there is an urgent need to better understand risk factors for symptom deterioration and mortality among patients with COVID-19. This systematic review aimed to meet the need by determining the predictive value of chronic diseases for COVID-19 severity and mortality.

Methods: We searched PubMed, Embase, Web of Science, and Cumulative Index to Nursing and Allied Health Complete to identify studies published between December 1, 2019, and December 31, 2020. Two hundred and seventeen observational studies from 26 countries involving 624,986 patients were included. We assessed the risk of bias of the included studies and performed a cumulative meta-analysis.

Results: We found that among COVID-19 patients, hypertension was a very common condition and was associated with higher severity, intensive care unit (ICU) admission, acute respiratory distress syndrome, and mortality. Chronic obstructive pulmonary disease was the strongest predictor for COVID-19 severity, admission to ICU, and mortality, while asthma was associated with a reduced risk of COVID-19 mortality. Patients with obesity were at a higher risk of experiencing severe symptoms of COVID-19 rather than mortality. Patients with cerebrovascular disease, chronic liver disease, chronic renal disease, or cancer were more likely to become severe COVID-19 cases and had a greater probability of mortality.

Conclusions: COVID-19 patients with chronic diseases were more likely to experience severe symptoms and ICU admission and faced a higher risk of mortality. Aggressive strategies to combat the COVID-19 pandemic should target patients with chronic diseases as a priority.

Lactate is associated with mortality in very old intensive care patients suffering from COVID-19: results from an international observational study of 2860 patients

PURPOSE

Lactate is an established prognosticator in critical care. However, there still is insufficient evidence about its role in predicting outcome in COVID-19. This is of particular concern in older patients who have been mostly affected during the initial surge in 2020.

METHODS

This prospective international observation study (The COVIP study) recruited patients aged 70 years or older (ClinicalTrials.gov ID: NCT04321265) admitted to an intensive care unit (ICU) with COVID-19 disease from March 2020 to February 2021. In addition to serial lactate values (arterial blood gas analysis), we recorded several parameters, including SOFA score, ICU procedures, limitation of care, ICU- and 3-month mortality. A lactate concentration ≥ 2.0 mmol/L on the day of ICU admission (baseline) was defined as abnormal. The primary outcome was ICU-mortality. The secondary outcomes 30-day and 3-month mortality.

RESULTS

In total, data from 2860 patients were analyzed. In most patients (68%), serum lactate was lower than 2 mmol/L. Elevated baseline serum lactate was associated with significantly higher ICU- and 3-month mortality (53% vs. 43%, and 71% vs. 57%, respectively, p < 0.001). In the multivariable analysis, the maximum lactate concentration on day 1 was independently associated with ICU mortality (aOR 1.06 95% CI 1.02-1.11; p = 0.007), 30-day mortality (aOR 1.07 95% CI 1.02-1.13; p = 0.005) and 3-month mortality (aOR 1.15 95% CI 1.08-1.24; p < 0.001) after adjustment for age, gender, SOFA score, and frailty. In 826 patients with baseline lactate ≥ 2 mmol/L sufficient data to calculate the difference between maximal levels on days 1 and 2 (∆ serum lactate) were available. A decreasing lactate concentration over time was inversely associated with ICU mortality after multivariate adjustment for SOFA score, age, Clinical Frailty Scale, and gender (aOR 0.60 95% CI 0.42-0.85; p = 0.004).

CONCLUSION

In critically ill old intensive care patients suffering from COVID-19, lactate and its kinetics are valuable tools for outcome prediction.

TRIAL REGISTRATION NUMBER

NCT04321265.

The effect of metformin on mortality and severity in COVID-19 patients with diabetes mellitus

AIM

COVID-19 has spread globally with heavy impact on most countries and our therapeutic strategies in COVID-19 patients with diabetes are still limited. Recently, some new information was added to this field. We performed this updated meta-analysis to reveal the underlying effect of metformin on COVID-19 patients with diabetes.

METHODS

We searched the PubMed, Embase and CNKI (China National Knowledge Infrastructure) databases for all articles. The odds ratio (OR) corresponding to the 95% confidence interval (95% CI) was used to assess the effect of metformin on COVID-19 patients with diabetes. The statistical heterogeneity among studies was assessed with the Q-test and I² statistics.

RESULTS

We collected 17 studies including 20,719 COVID-19 patients with diabetes. Our results found that metformin was associated with significantly decreased mortality and severity in COVID-19 patients with diabetes (OR = 0.64, 95% CI = 0.51-0.79 for mortality, and OR = 0.81, 95% CI = 0.66-0.99 for severity).

CONCLUSIONS

Our meta-analysis indicated that following metformin treatment might benefit the patients with T2DM, both the mortality and severity. However, patients with severe COVID-19 should be monitored closely for the development of lactic acidosis, acidosis, and decreased kidney function.

Is there a need to reconsider the use of metformin in COVID-19 patients with type 2 diabetes mellitus?

INTRODUCTION

Diabetes has been linked with poorer outcomes in coronavirus disease (COVID-19) patients. However, the question to whether continue or withdraw metformin therapy in COVID-19 patients with type 2 diabetes mellitus remains contentious. This study aims to investigate the association between metformin and poor COVID-19 outcomes.

METHODS

Eligible studies published up to 21 October 2020 were included and appraised for validity, importance, and applicability. The included studies were further ranked according to the level of evidence (LOE).

RESULTS

Nine studies were included for further assessments, of which seven studies stated that metformin was not associated with poor COVID-19 outcomes (LOE II-V), while the other two with poorer designs stated otherwise (LOE V). Although metformin may increase the risk of developing acidosis and lactic acidosis (LOE IV), the observed risks were more accentuated in patients with severe COVID-19 disease or kidney impairment and in patients with > 2 daily metformin doses. Interestingly, one study revealed that metformin may even yield therapeutic role in reducing the risk of COVID-19 mortality (LOE II), although further studies are required to confirm these findings.

CONCLUSIONS

Our findings indicated that metformin may be safely continued in COVID-19 patients. The benefit of metformin therapy with simultaneous continuous monitoring of COVID-19 severity and kidney function may outweigh the risks of lactic acidosis, of which incidence is relatively rare.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s13410-021-00924-w.

Hypoxia may be a determinative factor in COVID-19 progression

The disease which develops following SARS-CoV-2 virus infection, known as COVID-19, in most affected countries displays mortality from 1.5% to 9.8%. When leukocytosis due to granulocytosis, thrombocytopenia, and increased level of D-dimers are detected early during the disease course, they are accurate predictors of mortality. Based on the published observations that each of the aforementioned disturbances by itself may appear as a consequence of hypoxia, a hypothesis is presented that early hypoxia consequential to sleep apnea and/or blunted respiratory response to chemical stimuli is an early determinant of COVID-19 progression to the severe and critical stage. Further, it is noted that host-directed therapies which may counteract hypoxia and its early downstream effects are initiated only upon hospitalization of COVID-19 patients, which is too late to be fully effective. An example is anticoagulation treatment with low molecular weight heparin. Repurposing drugs which could counteract some early posthypoxic events, such as fluvoxamine, amantadine and N-acetylcysteine, for post-exposure prophylaxis of SARS-CoV-2 infection and early prehospital treatment of COVID-19, is indicated.

Case Report: Convalescent Plasma Achieves SARS-CoV-2 Viral Clearance in a Patient With Persistently High Viral Replication Over 8 Weeks Due to Severe Combined Immunodeficiency (SCID) and Graft Failure

We describe the unique disease course and cure of SARS-CoV-2 infection in a patient with SCID and graft failure. In absence of a humoral immune response, viral clearance was only achieved after transfusion of convalescent plasma. This observation underscores the necessity of the humoral immune response for SARS-CoV-2 clearance.

Obstructive sleep apnea (OSA) and outcomes from coronavirus disease 2019 (COVID-19) pneumonia: a systematic review and meta-analysis

Background

Obstructive sleep apnea (OSA) is the most prevalent sleep-related breathing disorder which could impair someone's quality of life and is also associated with poor outcomes from many diseases. Currently, the evidence regarding the link between OSA and coronavirus disease 2019 (COVID-19) is still conflicting. This study aims to analyze the relationship between OSA and poor outcomes of COVID-19.

Materials and methods

We systematically searched the PubMed and Europe PMC database using specific keywords related to our aims until December 10th, 2020. All articles published on COVID-19 and OSA were retrieved. The quality of the study was assessed using the Newcastle–Ottawa Scale (NOS) tool for observational studies. Statistical analysis was done using Review Manager 5.4 software.

Results

A total of 21 studies with 54,276 COVID-19 patients were included in this meta-analysis. This meta-analysis showed that OSA was associated with composite poor outcome [OR 1.72 (95% CI 1.55–1.91), p < 0.00001, I² = 36%, random-effect modeling] and its subgroup which comprised of severe COVID-19 [OR 1.70 (95% CI 1.18–2.45), p = 0.005], ICU admissions [OR 1.76 (95% CI 1.51–2.05), p < 0.00001], the need for mechanical ventilation [OR 1.67 (95% CI 1.48–1.88), p < 0.00001], and mortality [OR 1.74 (95% CI 1.39–2.19), p < 0.00001].

Conclusions

Extra care and close monitoring should be provided to patients with OSA to minimize the risk of infections. Simple questionnaires such as STOP-Bang questionnaire can be used for screening patients who may be at risk for severe adverse outcomes.

Clinical characteristics and outcomes of adult patients admitted with COVID-19 in East London: a retrospective cohort analysis

Background

Descriptions of clinical characteristics of patients hospitalised withCOVID-19, their clinical course and short-term inpatient and outpatient outcomes in deprived urban populations in the UK are still relatively sparse. We describe the epidemiology, clinical course, experience of non-invasive ventilation and intensive care, mortality and short-term sequelae of patients admitted to two large District General Hospitals across a large East London National Health Service Trust during the first wave of the pandemic.

Methods

A retrospective analysis was carried out on a cohort of 1946 patients with a clinical or laboratory diagnosis of COVID-19, including descriptive statistics and survival analysis. A more detailed analysis was undertaken of a subset of patients admitted across three respiratory units in the trust.

Results

Increasing age, male sex and Asian ethnicity were associated with worse outcomes. Increasing severity of chest X-ray abnormalities trended with mortality. Radiological changes persisted in over 50% of cases at early follow-up (6 weeks). Ongoing symptoms including hair loss, memory impairment, breathlessness, cough and fatigue were reported in 70% of survivors, with 39% of patients unable to return to work due to ongoing symptoms.

Conclusions

Understanding the acute clinical features, course of illness and outcomes of COVID-19 will be crucial in understanding the effect of differences in risk, as well as the effectiveness of new interventions and vaccination between the successive waves of the pandemic.