The preliminary comparative results between Covid-19 and non-Covid-19 patients in Western China

A Retrospective Comparison of Clinical and Laboratory Aspects of Patients With COVID-19-Related Acute Respiratory Distress Syndrome (ARDS) and Non-COVID-19-Related ARDS

AIM/OBJECTIVE

This study investigated demographic characteristics, hemodynamic values, respiratory datas, laboratory values ​​such as biochemistry and blood gas, and treatment approaches of coronavirus disease 2019 (COVID-19)-related and non-COVID-19-related acute respiratory distress syndrome (ARDS) patients hospitalized in the intensive care unit (ICU).

BACKGROUND

Determining the differences and similarities between COVID-19-related ARDS (CARDS) patients and non-COVID-19-related ARDS (NCARDS) patients will be useful to better understand these two diseases.

MATERIALS AND METHODS

A total of 32 NCARDS patients who were followed and treated in the ICU for various reasons between January 2015 and December 2020 and 32 CARDS patients who were followed and treated in the ICU for various reasons between March 2020 and December 2020 were examined retrospectively. Age, gender, comorbidities, Glasgow Coma Scale (GCS), Acute Physiology and Chronic Health Evaluation (APACHE) II Score, blood pressure, heart rate, saturation, laboratory results, arterial blood gas (ABG) values, length of stay in the ICU, intubation, the number of days till the patient was extubated, the treatments applied, admission to the service, and mortality were evaluated.

RESULTS

In the comparison between the two groups, the demographic data of the patients, the number of days intubated and extubated, APACHE II scores, and ICU length of stay were not statistically different. Values of positive end-expiratory pressure (PEEP), first hospitalization GCS, first hospitalization hemoglobin (Hgb), albumin at first admission, alanine aminotransferase (ALT) at first admission, and steroid use were found to be significantly different in patients with CARDS (p < 0.001). The median of PEEP values (p = 0.04), first admission GCS values (p = 0.04), first admission Hgb values (p = 0.005), albumin values at the first admission (p = 0.03), ALT values (p = 0.03), and the rate of steroid use (p = 0.001) of CARDS patients were significantly higher than those of NCARDS patients. The median of the first hospitalization heart rate values (p = 0.009), first hospitalization saturation values (p = 0.001), and first admission neutrophil values (p = 0.03) in NCARDS patients were significantly higher than that of CARDS patients. There was no significant difference between the two groups in terms of mortality, sedation use, inotropic support, C-reactive protein (CRP), and procalcitonin values.

CONCLUSIONS

CARDS and NCARDS have clinical and laboratory similarities and differences. Therefore, there should be differences in our follow-up and treatment approach to these two disease groups.

Signs and symptoms to determine if a patient presenting in primary care or hospital outpatient settings has COVID-19

BACKGROUND

COVID-19 illness is highly variable, ranging from infection with no symptoms through to pneumonia and life-threatening consequences. Symptoms such as fever, cough, or loss of sense of smell (anosmia) or taste (ageusia), can help flag early on if the disease is present. Such information could be used either to rule out COVID-19 disease, or to identify people who need to go for COVID-19 diagnostic tests. This is the second update of this review, which was first published in 2020.

OBJECTIVES

To assess the diagnostic accuracy of signs and symptoms to determine if a person presenting in primary care or to hospital outpatient settings, such as the emergency department or dedicated COVID-19 clinics, has COVID-19.

SEARCH METHODS

We undertook electronic searches up to 10 June 2021 in the University of Bern living search database. In addition, we checked repositories of COVID-19 publications. We used artificial intelligence text analysis to conduct an initial classification of documents. We did not apply any language restrictions.

SELECTION CRITERIA

Studies were eligible if they included people with clinically suspected COVID-19, or recruited known cases with COVID-19 and also controls without COVID-19 from a single-gate cohort. Studies were eligible when they recruited people presenting to primary care or hospital outpatient settings. Studies that included people who contracted SARS-CoV-2 infection while admitted to hospital were not eligible. The minimum eligible sample size of studies was 10 participants. All signs and symptoms were eligible for this review, including individual signs and symptoms or combinations. We accepted a range of reference standards.

DATA COLLECTION AND ANALYSIS

Pairs of review authors independently selected all studies, at both title and abstract, and full-text stage. They resolved any disagreements by discussion with a third review author. Two review authors independently extracted data and assessed risk of bias using the QUADAS-2 checklist, and resolved disagreements by discussion with a third review author. Analyses were restricted to prospective studies only. We presented sensitivity and specificity in paired forest plots, in receiver operating characteristic (ROC) space and in dumbbell plots. We estimated summary parameters using a bivariate random-effects meta-analysis whenever five or more primary prospective studies were available, and whenever heterogeneity across studies was deemed acceptable.

MAIN RESULTS

We identified 90 studies; for this update we focused on the results of 42 prospective studies with 52,608 participants. Prevalence of COVID-19 disease varied from 3.7% to 60.6% with a median of 27.4%. Thirty-five studies were set in emergency departments or outpatient test centres (46,878 participants), three in primary care settings (1230 participants), two in a mixed population of in- and outpatients in a paediatric hospital setting (493 participants), and two overlapping studies in nursing homes (4007 participants). The studies did not clearly distinguish mild COVID-19 disease from COVID-19 pneumonia, so we present the results for both conditions together. Twelve studies had a high risk of bias for selection of participants because they used a high level of preselection to decide whether reverse transcription polymerase chain reaction (RT-PCR) testing was needed, or because they enrolled a non-consecutive sample, or because they excluded individuals while they were part of the study base. We rated 36 of the 42 studies as high risk of bias for the index tests because there was little or no detail on how, by whom and when, the symptoms were measured. For most studies, eligibility for testing was dependent on the local case definition and testing criteria that were in effect at the time of the study, meaning most people who were included in studies had already been referred to health services based on the symptoms that we are evaluating in this review. The applicability of the results of this review iteration improved in comparison with the previous reviews. This version has more studies of people presenting to ambulatory settings, which is where the majority of assessments for COVID-19 take place. Only three studies presented any data on children separately, and only one focused specifically on older adults. We found data on 96 symptoms or combinations of signs and symptoms. Evidence on individual signs as diagnostic tests was rarely reported, so this review reports mainly on the diagnostic value of symptoms. Results were highly variable across studies. Most had very low sensitivity and high specificity. RT-PCR was the most often used reference standard (40/42 studies). Only cough (11 studies) had a summary sensitivity above 50% (62.4%, 95% CI 50.6% to 72.9%)); its specificity was low (45.4%, 95% CI 33.5% to 57.9%)). Presence of fever had a sensitivity of 37.6% (95% CI 23.4% to 54.3%) and a specificity of 75.2% (95% CI 56.3% to 87.8%). The summary positive likelihood ratio of cough was 1.14 (95% CI 1.04 to 1.25) and that of fever 1.52 (95% CI 1.10 to 2.10). Sore throat had a summary positive likelihood ratio of 0.814 (95% CI 0.714 to 0.929), which means that its presence increases the probability of having an infectious disease other than COVID-19. Dyspnoea (12 studies) and fatigue (8 studies) had a sensitivity of 23.3% (95% CI 16.4% to 31.9%) and 40.2% (95% CI 19.4% to 65.1%) respectively. Their specificity was 75.7% (95% CI 65.2% to 83.9%) and 73.6% (95% CI 48.4% to 89.3%). The summary positive likelihood ratio of dyspnoea was 0.96 (95% CI 0.83 to 1.11) and that of fatigue 1.52 (95% CI 1.21 to 1.91), which means that the presence of fatigue slightly increases the probability of having COVID-19. Anosmia alone (7 studies), ageusia alone (5 studies), and anosmia or ageusia (6 studies) had summary sensitivities below 50% but summary specificities over 90%. Anosmia had a summary sensitivity of 26.4% (95% CI 13.8% to 44.6%) and a specificity of 94.2% (95% CI 90.6% to 96.5%). Ageusia had a summary sensitivity of 23.2% (95% CI 10.6% to 43.3%) and a specificity of 92.6% (95% CI 83.1% to 97.0%). Anosmia or ageusia had a summary sensitivity of 39.2% (95% CI 26.5% to 53.6%) and a specificity of 92.1% (95% CI 84.5% to 96.2%). The summary positive likelihood ratios of anosmia alone and anosmia or ageusia were 4.55 (95% CI 3.46 to 5.97) and 4.99 (95% CI 3.22 to 7.75) respectively, which is just below our arbitrary definition of a 'red flag', that is, a positive likelihood ratio of at least 5. The summary positive likelihood ratio of ageusia alone was 3.14 (95% CI 1.79 to 5.51). Twenty-four studies assessed combinations of different signs and symptoms, mostly combining olfactory symptoms. By combining symptoms with other information such as contact or travel history, age, gender, and a local recent case detection rate, some multivariable prediction scores reached a sensitivity as high as 90%.

AUTHORS' CONCLUSIONS

Most individual symptoms included in this review have poor diagnostic accuracy. Neither absence nor presence of symptoms are accurate enough to rule in or rule out the disease. The presence of anosmia or ageusia may be useful as a red flag for the presence of COVID-19. The presence of cough also supports further testing. There is currently no evidence to support further testing with PCR in any individuals presenting only with upper respiratory symptoms such as sore throat, coryza or rhinorrhoea. Combinations of symptoms with other readily available information such as contact or travel history, or the local recent case detection rate may prove more useful and should be further investigated in an unselected population presenting to primary care or hospital outpatient settings. The diagnostic accuracy of symptoms for COVID-19 is moderate to low and any testing strategy using symptoms as selection mechanism will result in both large numbers of missed cases and large numbers of people requiring testing. Which one of these is minimised, is determined by the goal of COVID-19 testing strategies, that is, controlling the epidemic by isolating every possible case versus identifying those with clinically important disease so that they can be monitored or treated to optimise their prognosis. The former will require a testing strategy that uses very few symptoms as entry criterion for testing, the latter could focus on more specific symptoms such as fever and anosmia.

Elevation of Serum Transaminase Levels Due to Favipiravir Use in the Treatment of COVID-19

Background and aims: Favipiravir is a ribonucleic acid (RNA)-dependent RNA polymerase (RdRP) inhibitor antiviral agent used in the treatment of coronavirus disease-2019 (COVID-19). In this study, we investigated the changes in serum transaminase levels of patients and the relationship between serum transaminase elevation with mortality in patients who were hospitalized with the diagnosis of COVID-19 and received favipiravir treatment.

Materials and methods: 454 patients who received favipiravir and 113 patients who did not receive favipiravir were evaluated. Serum transaminase levels of the patients were compared at baseline and after five days of treatment, and the relationship between serum transaminase elevation and mortality was investigated.

Results: No significant aspartate aminotransferase (AST) or alanine aminotransferase (ALT) elevation was detected due to favipiravir treatment. AST elevation was found, respectively, as 133 (29.3%), 32 (28.3%) (p=0.100), ALT elevation as 112 (24.7%), 35 (29.3%) (p=0.100) in the groups receiving and not receiving favipiravir. High AST level was found as a risk factor for mortality in all patient groups (p=0.008).

Conclusions: There was no statistically significant elevation in serum transaminase levels due to favipiravir use in patients hospitalized for COVID-19. A high level of AST is a significant risk factor to show mortality and intensive care unit (ICU) admission in patients with COVID-19.

Clinical presentation of COVID-19-positive and -negative patients in Lagos Nigeria: A comparative study

Background

A lot has been documented about the pathophysiology and clinical presentation of coronavirus disease 2019 (COVID-19). We compared the clinical features of real-time reverse transcriptase polymerase-chain-reaction (RT-PCR) confirmed COVID-19 positive and negative patients admitted in Lagos State.

Methods

Medical records of all patients admitted in 15 isolation centres across Lagos state between 27^th February 2020 and 30^th September 2020, were abstracted and reviewed. We compared the clinical features, co-morbidities and clinical outcomes of COVID-19 positive and negative patients.

Results

A total of 3157 records of patients admitted in 15 isolation centres in Lagos State were reviewed of which 302 (9.6%) tested negative to RT-PCR COVID-19. There was no gender difference between COVID-19 positive and negative patients (P = 0.687). The average age of the negative patients was higher (46.8 ± 18.3 years) than positive patients (41.9 ± 15.5 years) (P < 0.001). A higher proportion of the COVID-19 negative patients had co-morbidity (38.1% vs. 27.8%), were symptomatic (67.5% vs. 44.6%) and higher mortality (21.9% vs. 6.6%) than positive patients (P < 0.001). The percentages with hypertension (26.2% vs. 21.0%, P = 0.038), diabetes (17.2% vs. 9.4%, P < 0.001), cardiovascular disease (2.3% vs. 0.9%, P < 0.029) and cancer (2.3% vs. 0.5%, P < 0.002) were more among patients without COVID-19. More patients without COVID-19 presented with fever (36.1% vs. 18.8%), cough (33.7% vs. 23.1%) and breathlessness (40.8% vs. 16.1%) than the positive patients (P < 0.001).

Conclusion

Anosmia and dysgeusia were strongly associated with COVID-19. Clinical decision-making should only be used to prioritise testing and isolation of patients suspected to have COVID-19, especially in settings with limited access to diagnostic kits.

A comprehensive evaluation of early potential risk factors for disease aggravation in patients with COVID-19

The 2019 Coronavirus Disease (COVID-19) has become an unprecedented public crisis. We retrospectively investigated the clinical data of 197 COVID-19 patients and identified 88 patients as disease aggravation cases. Compared with patients without disease aggravation, the aggravation cases had more comorbidities, including hypertension (25.9%) and diabetes (20.8%), and presented with dyspnoea (23.4%), neutrophilia (31.5%), and lymphocytopenia (46.7%). These patients were more prone to develop organ damage in liver, kidney, and heart (P < 0.05). A multivariable regression analysis showed that advanced age, comorbidities, dyspnea, lymphopenia, and elevated levels of Fbg, CTnI, IL-6, and serum ferritin were significant predictors of disease aggravation. Further, we performed a Kaplan–Meier analysis to evaluate the prognosis of COVID-19 patients, which suggested that 64.9% of the patients had not experienced ICU transfers and survival from the hospital.