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Take a look at a selection of our recent media coverage:

Serum albumin independent risk factor for severe infection and mortality in COVID-19

7th October 2021

Reduced serum albumin levels in patients hospitalised with COVID-19 appears to be an independent risk factor for severe disease and mortality.

In systemic inflammatory conditions such as sepsis, low serum albumin levels are associated with an increased risk of death in patients with severe disease. However, whether serum albumin (SA) levels can used predictively to identify those at risk of both severe disease and mortality in COVID-19 remains unclear. This was the question addressed in a retrospective study by a team from the Emergency Department, Alto Adige, Italy. The team considered consecutive patients with COVID-19 seen at the emergency department (ED) of three hospitals during March to April 2020. Serum albumin levels were added to the panel of blood samples routinely performed on those with suspected COVID-19 upon arrival at the ED. The primary outcome of the study was the presence of severe COVID-19 infection. In addition, the team explored 30-day mortality after the initial ED assessment as a secondary outcome. The researchers categorised SA levels upon ED admission as < 3 g/dL, 3 – 3.49 g/dL and greater than 3.5 g/dL.

Findings

There were 296 patients with COVID-19 for whom the overall mean SA value was 3.7 g/dL. Serum albumin levels were higher for patients aged under 75 years of age (3.9 vs 3.4, under 75 years vs over 75 years, p < 0.001) although there were no gender differences. Most patients (59.8%) had SA levels above 3.5 g/dL with only 10.1% having levels below 3 g/dL. Nearly two thirds (63.2%) of patients had severe COVID-19 infection and 18.2% of all patients died within 30 days of their arrival at the ED.

In their analysis, the authors calculated that SA levels < 3.5 g/dL was an independent risk factor for both severe infection (adjusted odds ratio, aOR = 2.92, 95% CI 1.51 – 5.66) and 30-day mortality (aOR – 2.62, 95% CI 1.13 – 6.1).

In their conclusion, the authors stated that their preliminary data suggested that “serum albumin level in the ED may play a role in the assessment of the severity of SARS-CoV-2 infection and the risk of death at 30 days.” They also called for more prospective evaluations to confirm whether albumin levels was an important prognostic factor in patients with COVID-19.

Citation

Turcato G et al. Severity of SARS-CoV-2 infection and albumin levels recorded at the first emergency department evaluation: a multicentre retrospective observational study. Emerg Med J 2021

Increased rate pre-term births in mothers with COVID-19

16th August 2021

A comprehensive analysis has found an increase rate of pre-term births in those with COVID-19 but was otherwise reassuring.

Pregnant women have been deemed to be at a higher risk of severe illness from COVID-19. Moreover, in a systematic review in May 2020, it was concluded that mothers infected with COVID-19 were at an increased risk of pre-term birth although the authors urged caution, as their data were derived from a small number of cases and also included the SARS and MERS viruses. In order to provide as much information as possible on the pregnancy outcomes associated with COVID-19 infection, a team from the Department of Obstetrics and Gynaecology, St George’s University Hospitals NHS Foundation Trust, London, UK, undertook a systematic review of all available literature on COVID-19 and pregnancy in order to provide comprehensive data and to direct the course of ongoing research and studies. They searched all major databases and included a wide range of studies e.g., case reports, case series, and randomised trials, provided that studies reported on women with a PCR-confirmed diagnosis of COVID-19. Extracted information on maternal outcomes including clinical symptoms, laboratory findings, any obstetric complications and perinatal outcomes including death and vertical transmission were also collected.

Findings
A total of 86 studies were identified which included 2567 pregnancies. Nearly a third of mothers (30.6%) were older than 35 years and half of the cohort (50.8%) were of Black, Asian or other ethnic minority groups. Overall, antiviral therapy was given to a fifth (21.1%) of women though a much higher proportion (51.15%) received anticoagulation and 18.2% required nasal or non-invasive oxygen support.
COVID-19 symptoms were predominately cough (71.4%), fever (63.3%), dyspnoea (34.4%) and loss of taste or smell (22.9%). The most common laboratory abnormality was a raised D-dimer (84.6%), followed by a raised C-reactive protein or procalcitonin (54%). Fortunately, only 7% of women needed admission to an intensive care unit. Pre-term birth which was primarily iatrogenic was found to be common (21.8%) though this was medically indicated in 18.4% of all cases. The incidence of neonatal COVID-19 infection was low at 1.2%.

Commenting on their findings, the authors noted that generally, pregnancy outcomes were good. The incidence of admission to maternal intensive care was low and likely to be similar to the rates for other non-infected women. Furthermore, there was a very low incidence of maternal mortality. The authors did note how their analysis had several limitations including the retrospective nature of most studies and a lack of standardisation of care, given that studies came from several different countries. While the incidence of vertical transmission appeared to be low, the authors felt that more evidence was needed to confirm whether this represents a significant problem. However, there was a higher-than-average increase in pre-term births which was consistent with findings from other studies.

Citation
Khalil A et al. SARS-CoV-2 infection in pregnancy: A systematic review and meta- analysis of clinical features and pregnancy outcomes. EClinicalMedicine 2021

IBD patients develop new gastrointestinal symptoms with COVID-19

12th August 2021

New gastrointestinal symptoms in patients with irritable bowel disease is a feature of infection with COVID-19 rather than a disease flare.

The presence of gastrointestinal (GI) symptoms among those infected with COVID-19, occurs in around 17.6% of patients. Whether or not the presence of GI symptoms is prognostic for more severe disease, however, remains unclear except perhaps for abdominal pain. In contrast, other studies have indicated that the development of GI symptoms could even attenuate any COVID-19 associated inflammation. The term inflammatory bowel disease (IBD) is essential an umbrella term which covers both Crohn’s disease and ulcerative colitis although typically, both groups of patients will experience symptoms of diarrhoea, abdominal pain, fatigue, rectal bleeding and weight loss. Some evidence indicates that among those with IBD infected with COVID-19, there is a higher incidence of both diarrhoea and abdominal pain, compared to non-IBD patients. In fact, in a review of 1028 patients with IBD infected with COVID-19, 20% experienced diarrhoea. Given that infection with COVID-19 can lead to gastrointestinal symptoms in nearly a fifth of patients without IBD, researchers from the Henry D Janowitz Division of Gastroenterology, Icahn School of Medicine, New York, US, decided to examine the extent of symptoms experienced by IBD patients using data held within a global disease registry. The Surveillance Epidemiology of Coronavirus Under Research Exclusion for Inflammatory Bowel Disease (SECURE-IBD) is an international registry, created to monitor the outcomes of COVID-19 in both adults and children with IBD. Clinicians are advised to the voluntarily report all cases of PCR-confirmed infections in all their IBD patients onto the registry to enable the capture of data related to those with IBD. Using this registry, the team sought to determine the association between any new GI symptoms with the odds of death due to COVID-19.

Findings
Data were available for 2917 IBD patients who had COVID-19, of whom, 26.4%, with a mean age of 43 years (55.5% female) developed new GI symptoms when infected with the virus. There was no significant difference in the incidence of new GI symptoms in those with Crohn’s disease or ulcerative colitis. Moreover, new gastrointestinal symptoms occurred more frequently in those with active disease compared to those in remission (29.4% vs 23.3%, p < 0.01). The pattern of symptoms however, was broadly similar apart from abdominal pain. For instance, diarrhoea occurred in 83% vs 76% (active disease vs remission) and nausea in 24% vs 25% (active disease vs remission). The greatest disparity was in abdominal pain (44% vs 26%, active disease vs remission). In addition, patients with IBD experiencing new GI symptoms were more likely to be hospitalised because of COVID-19 (31.4% vs 19.2%, p < 0.01) although the development of new symptoms was not associated with a higher risk of death.

The authors discussed how the development of new gastrointestinal symptoms were unlikely to represent a disease flare, because a large number of those in remission also experienced new symptoms after becoming infected. They concluded that the presence of new gastrointestinal symptoms in a patient with IBD should clinicians to consider infection with COVID-19 although the team also felt that further studies were needed to determine if infection could trigger an IBD flare or even alter the subsequent course of the disease.

Citation
Ungaro RC et al. New Gastrointestinal Symptoms Are Common in Inflammatory Bowel Disease Patients With COVID-19: Data from an International Registry. Inflamm Bowel Dis 2021

Machine learning model detects COVID-19 after 3 days of self-reported symptoms

4th August 2021

Using self-reported symptoms, a machine learning model was able to predict the early stages of COVID-19 infection after only three days.

The timely detection of COVID-19 infections through PCR testing is vital to contain the spread of the virus. However, while PCR testing has become the most widely used analytical technique to detect the virus, the result is highly dependent on the timing of sample collection, the type of specimen and the quality of the sample. An alternative means of identifying infected individuals is through a combination of symptoms and then ensuring that only those with appropriate symptoms are tested. This approach was used in an Italian study of nearly 3000 subjects and with the aid of a short diagnostic scale, was able to correctly identify the symptoms associated with infection. This same methodology is utilised in the COVID-19 Symptom Study App which is a longitudinal, self-reported study of the symptom profile of patients with COVID-19. Through the use of machine learning models, the study has been able to develop models to identify the main symptoms of infection and their correlation with outcomes. Nevertheless, current models are not conducive to the early detection of infection. This prompted the COVID-19 Symptom Study team to create a machine learning model that captured self-reported symptoms for only the first three days and used this information to predict an individual’s likelihood of being COVID-19 positive.

The team used three different machine learning models to analyse self-reported symptoms. The first model was based on the NHS algorithm which uses the presence of cough, fever or loss of smell between days 1 and 3 as potentially representative of COVID-19 infection. The second logistic regression model, is based on an algorithm which incorporates loss of smell, persistent cough, fatigue and skipped meals and which has been previously validated and found to correlate well with COVID-19 infection. For the third algorithm, the team used 18 self-reported symptoms combined with co-morbidities as well as demographic data and referred to this as a hierarchical Gaussian process model. All three models were compared in terms of sensitivities, specificities and area under the receiver operating characteristics curve (AUC) and evaluated with a training set, for patients self-reporting symptoms between April and October 2020 and a test set for self-reported symptoms between October and November 2020.

Findings
There were data from 182,991 participants in the training set and 15,049 in the test set with a similar symptom distribution. The predictive power of the three model was different. For example, the hierarchical Gaussian process model showed the highest predictive value (AUC = 0.80, 95% CI 0.80–0.81) using three days of symptoms compared to the logistic regression model (AUC = 0.74) and the NHS model (AUC = 0.67). The hierarchical Gaussian process model for prediction of COVID-19 infection had a sensitivity of 73% and a specificity 72%. This was higher than either the logistic regression model (59%, 76%, sensitivity, specificity, respectively) and the NHS model (60%, 75%, sensitivity, specificity, respectively). Interestingly, the key symptoms predictive of early COVID-19 were loss of smell, chest pain, persistent cough, abdominal pain, feet blisters, eye soreness and unusual pain.

The authors concluded that the hierarchical Gaussian process model was successfully able to predict the early signs of infection and could be used to enable referral for testing and self-isolation when these symptoms were present.

Citation
Canas LS et al. Early detection of COVID-19 in the UK using self-reported symptoms: a large-scale, prospective, epidemiological surveillance study. Lancet Digit Health 2021

Olfactory dysfunction test enables identification of COVID-19 infection

19th July 2021

Olfactory dysfunction is common in those with COVID-19 and a smell test can be used for the identification of infected individuals.

Olfactory dysfunction has been defined as the best predictor of infection with COVID-19. Moreover, in a study of 60 patients, 59 exhibited some dysfunction during a smell identification test. The study also revealed how only 58% of those tested had anosmia indicating in imperfect relationship between olfactory dysfunction and anosmia. It is possible therefore that the use of an inexpensive, rapid and sensitive method, based on olfactory dysfunction would be of potential value in identifying those with COVID-19. Based on this assumption, a team from the Division of Otolaryngology-Head and Neck Surgery, Department of Surgery, University of California, US, sought to evaluate the prognostic value of a smell test for identifying those with COVID-19. The team enrolled healthy adults (18 years and over) from a single university campus screening site. Each of the participants were tested for olfactory dysfunction using a novel scent card (SAFER Diagnostics) and immediately followed up with a PCR test for COVID-19. The card itself contained several different scents under a scratch-off and sniff label and participants had eight options: grape, floral, blueberry, banana, mint, unsure or no scent. Using a QR code, the answers were processed electronically and an incorrect choice was labelled as olfactory dysfunction. The team collected participant demographics, medical history, any COVID-19 symptoms and a subjective smell test on a binary (yes/no) and a 10-point visual analogue scale, where 0 indicated no sense of smell and 10 was a normal sense of smell. Using regression analysis, the team assessed the association between the SAFER card and PCR test results, controlling for the presence of any other COVID-19-related symptoms such as fever, fatigue and cough.

Findings
A total of 163 participants were enrolled with a mean age of 31.6 years (56.3% male) with the majority (62.5%) of white ethnicity. There were 16 participants who tested positive for COVID-19 and 7 (4.8%) who tested negative. From the 16 who were PCR positive, 12 (75%) also failed the olfactory dysfunction test. A failed scent card screen was found to be the greatest predictor for COVID-19 positivity (odds ratio, OR = 80.24, 95% CI 14.77–435.90). The authors calculated that the smell test had a sensitivity for detecting COVID-19 of 75% and a specificity of 95.2%. When adding the presence of fatigue as an associated symptom, the sensitivity of the olfactory dysfunction test increased to 93.8% and the specificity to 89.8%. However, when either fever or cough were included, there was no increase in sensitivity. Interestingly, only 6 of the 16 who tested positive for COVID-19 presented with subjective anosmia.

In a discussion of their findings, the authors noted how their rapid olfactory dysfunction test was a valuable screening tool for COVID-19. Nevertheless, they recognised that not all patients experience olfactory dysfunction but that in the presence of fatigue, the test became more sensitive. The authors concluded by calling for future studies to include a larger participant cohort to better account for other olfactory dysfunction risk factors.

Citation
Said M et al. A Rapid Olfactory Test as a Potential Screening Tool for COVID-19. JAMA Otolaryngol Head Neck Surg.

CCK-A agonist reduces disease severity in moderate COVID

20th April 2021

A first-in-class CCK-A agonist has shown benefit in symptom reduction among those hospitalised with moderate COVID-19.

The dual action chemical entity, PNB001, has shown promise as a treatment for those hospitalised with COVID-19. The drug acts as both a cholecystokinin-A (CCK-A) agonist and CCK-B antagonist. Cholecystokinin is a peptide hormone originally identified in the gastrointestinal tract where it serves to mediate pancreatic secretion and contraction of the gall bladder. However, later work has revealed how there are two different types of CCK receptors, and PNB001 has been shown to have both analgesic and anti-inflammatory actions through binding with the different receptors termed A and B. It is the anti-inflammatory effect that is thought to be of greater relevance in COVID-19 and while human safety data on the drug proved to be satisfactory, to date, no trials had been undertaken with COVID-19 patients. In the present study, a team from PNB Vesper Life Science, Kerala, India (the manufacturer of PNB001), examined the impact of their new drug on disease severity scores among those hospitalised with COVID-19. Included patients had pneumonia but not severe disease (defined by an oxygen saturation of < 94%) on room air and with at least two recognised COVID-19 symptoms (e.g., fever, cough, dyspnoea). Excluded patients included those requiring mechanical ventilation. Individuals were randomised to receive either PNB001 (100mg three times daily) along with standard care (SC) or standard care alone which was consistent with India’s current clinical management protocol. Treatment with PNB001 was continued for 14 days and the primary outcome was the change in the 8-point WHO ordinal scale score for disease severity from baseline to day 14 and mortality at day 28.

Findings
A total of 40 patients (20 per arm) were recruited into the study with a mean age (in the PBN001 group) of 52.1 years (30% female). At baseline, both groups had an equal number of patients with a WHO scale score of 4 (i.e., oxygen by mask or nasal prongs). By day 14, the PNB001 group experienced a greater mean reduction in ordinal scale values (0.22 vs 1.12, PNB001 vs SC, p = 0.042) from baseline. For instance, at day 14, 17 (94.4%) vs 12 (70.6%) patients (PNB001 vs SC), had achieved a WHO scale score of 0 (no clinical or virological evidence of infection) and 1 vs 4 patients, maintained a WHO scale score of 4. However, day 28 mortality was similar in both groups although a higher proportion of patients given PNB001 were discharged from hospital by day 14 (19 vs 15, p = 0.048).

In their conclusion, the authors noted that PNB001 was well tolerated and that it showed significant clinical improvements when added to standard care in patients with moderate COVID-19. However, they also recognised the limitations of the study, i.e., a small sample size and the fact that while randomised, it was not blinded.

Citation
Lattmann E et al. Randomised, Comparative, Clinical Trial to Evaluate Efficacy and Safety of PNB001 in Moderate COVID-19 Patients. MedRxiv 2021