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1.
Heart ; 109(Suppl 3):A243, 2023.
Article in English | ProQuest Central | ID: covidwho-20237725

ABSTRACT

209 Figure 1Kaplan-Meier curves displaying cumulative all-cause mortality[Figure omitted. See PDF]Conflict of InterestNo conflicts of interest

2.
researchsquare; 2020.
Preprint in English | PREPRINT-RESEARCHSQUARE | ID: ppzbmed-10.21203.rs.3.rs-101592.v1

ABSTRACT

Prognostic characteristics inform risk stratification in intensive care unit (ICU) patients with coronavirus disease 2019 (COVID-19). We obtained blood samples (n = 474) from hospitalized COVID-19 patients (n = 123), non-COVID-19 ICU sepsis patients (n = 25) and healthy controls (n = 30). Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA was detected in plasma or serum (RNAemia) of COVID-19 ICU patients when neutralizing antibody response was low. RNAemia was associated with higher 28-day ICU mortality (hazard ratio [HR], 1.84 [95% CI, 1.22–2.77] adjusted for age and sex). In longitudinal comparisons, COVID-19 ICU patients had a distinct proteomic trajectory associated with RNAemia and mortality. Among COVID-19-enriched proteins, galectin-3 binding protein (LGALS3BP) and proteins of the complement system were identified as interaction partners of SARS-CoV-2 spike glycoprotein. Finally, machine learning identified ‘Age, RNAemia’ and ‘Age, pentraxin-3 (PTX3)’ as the best binary signatures associated with 28-day ICU mortality.


Subject(s)
Severe Acute Respiratory Syndrome , Sepsis , COVID-19
3.
ssrn; 2020.
Preprint in English | PREPRINT-SSRN | ID: ppzbmed-10.2139.ssrn.3719886

ABSTRACT

Background: Understanding the spectrum and course of biological responses to coronavirus disease 2019 (COVID-19) may have important therapeutic implications. We sought to characterise biological responses among patients hospitalised with severe COVID-19 based on their serial physiological and blood biomarker values.Methods and Findings: We performed a retrospective cohort study of 1335 patients hospitalised with laboratory-confirmed COVID-19 (median age 70 years, 56% male), between 1st March and 30th April, 2020. Latent profile analysis was performed on serial physiological and blood biomarkers. Patient characteristics, comorbidities and rates of death and admission to intensive care, were compared between the latent classes. A five class solution provided the best fit. Class 1 “Typical response” exhibited a moderately elevated and rising C-reactive protein (CRP), stable lymphopaenia, and the lowest rates of 14-day adverse outcomes. Class 2 “Rapid hyperinflammatory response” comprised older patients, with higher admission white cell and neutrophil counts, which declined over time, and were accompanied by a very high and rising CRP and platelet count, and the greatest risk of mortality. Class 3 “Progressive inflammatory response” was similar to the typical response except for a higher and rising CRP, though similar mortality rate. Class 4 “Inflammatory response with kidney injury” had prominent lymphopaenia, moderately elevated (and rising) CRP, and severe renal failure. Class 5 “Hyperinflammatory response with kidney injury” comprised older patients, with a very high and rising CRP, and severe renal failure that attenuated over time. Physiological measures did not substantially vary between classes at baseline or early admission.Conclusions and Relevance: Our identification of five distinct classes of biomarker profiles provides empirical evidence for heterogeneous biological responses to COVID-19. Early hyperinflammatory responses and kidney injury may signify unique pathophysiology that requires targeted therapy.Funding Statement: This paper represents independent research part-funded by the National Institute for Health Research (NIHR) Biomedical Research Centres at South London and Maudsley NHS Foundation Trust, London AI Medical Imaging Centre for Value-Based Healthcare, and Guy’s & St Thomas’ NHS Foundation Trust, both with King’s College London.Declaration of Interests: JTHT received research support and funding from InnovateUK, Bristol-Myers-Squibb, iRhythm Technologies, and holds shares Ethics Approval Statement: This project was conducted under London South East Research Ethics Committee (reference 18/LO/2048) approval granted to the King’s Electronic Records Research Interface (KERRI); specific work on COVID-19 research was reviewed with expert patient input on a virtual committee with Caldicott Guardian oversight.


Subject(s)
Renal Insufficiency , Acute Kidney Injury , COVID-19
4.
Eur J Heart Fail ; 22(6): 967-974, 2020 06.
Article in English | MEDLINE | ID: covidwho-702780

ABSTRACT

AIMS: The SARS-CoV-2 virus binds to the angiotensin-converting enzyme 2 (ACE2) receptor for cell entry. It has been suggested that angiotensin-converting enzyme inhibitors (ACEi) and angiotensin II receptor blockers (ARB), which are commonly used in patients with hypertension or diabetes and may raise tissue ACE2 levels, could increase the risk of severe COVID-19 infection. METHODS AND RESULTS: We evaluated this hypothesis in a consecutive cohort of 1200 acute inpatients with COVID-19 at two hospitals with a multi-ethnic catchment population in London (UK). The mean age was 68 ± 17 years (57% male) and 74% of patients had at least one comorbidity. Overall, 415 patients (34.6%) reached the primary endpoint of death or transfer to a critical care unit for organ support within 21 days of symptom onset. A total of 399 patients (33.3%) were taking ACEi or ARB. Patients on ACEi/ARB were significantly older and had more comorbidities. The odds ratio for the primary endpoint in patients on ACEi and ARB, after adjustment for age, sex and co-morbidities, was 0.63 (95% confidence interval 0.47-0.84, P < 0.01). CONCLUSIONS: There was no evidence for increased severity of COVID-19 in hospitalised patients on chronic treatment with ACEi or ARB. A trend towards a beneficial effect of ACEi/ARB requires further evaluation in larger meta-analyses and randomised clinical trials.


Subject(s)
Angiotensin Receptor Antagonists/therapeutic use , Betacoronavirus , Coronavirus Infections/epidemiology , Heart Failure/drug therapy , Pneumonia, Viral/epidemiology , Aged , Angiotensin-Converting Enzyme Inhibitors/therapeutic use , COVID-19 , Comorbidity , Coronavirus Infections/drug therapy , Disease Progression , Female , Follow-Up Studies , Heart Failure/epidemiology , Humans , Male , Pandemics , Pneumonia, Viral/drug therapy , SARS-CoV-2 , Severity of Illness Index , Treatment Outcome , United Kingdom/epidemiology
5.
medrxiv; 2020.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2020.07.08.20148965

ABSTRACT

BackgroundPeople of minority ethnic background may be disproportionately affected by severe COVID-19 for reasons that are unclear. We sought to examine the relationship between ethnic background and (1) hospital admission for severe COVID-19; (2) in-hospital mortality. MethodsWe conducted a case-control study of 872 inner city adult residents admitted to hospital with confirmed COVID-19 (cases) and 3,488 matched controls randomly sampled from a primary healthcare database comprising 344,083 people resident in the same region. To examine in-hospital mortality, we conducted a cohort study of 1827 adults consecutively admitted with COVID-19. Data collected included hospital admission for COVID-19, demographics, comorbidities, in-hospital mortality. The primary exposure variable was self-defined ethnicity. ResultsThe 872 cases comprised 48.1% Black, 33.7% White, 12.6% Mixed/Other and 5.6% Asian patients. In conditional logistic regression analyses, Black and Mixed/Other ethnicity were associated with higher admission risk than white (OR 3.12 [95% CI 2.63-3.71] and 2.97 [2.30-3.85] respectively). Adjustment for comorbidities and deprivation modestly attenuated the association (OR 2.28 [1.87-2.79] for Black, 2.66 [2.01-3.52] for Mixed/Other). Asian ethnicity was not associated with higher admission risk (OR 1.20 [0.86-1.66]). In the cohort study of 1827 patients, 455 (28.9%) died over a median (IQR) of 8 (4-16) days. Age and male sex, but not Black (adjusted HR 0.84 [0.63-1.11]) or Mixed/Other ethnicity (adjusted HR 0.69 [0.43-1.10]), were associated with in-hospital mortality. Asian ethnicity was associated with higher in-hospital mortality (adjusted HR 1.54 [0.98-2.41]). ConclusionsBlack and Mixed ethnicity are independently associated with greater admission risk with COVID-19 and may be risk factors for development of severe disease. Comorbidities and socioeconomic factors only partly account for this and additional ethnicity-related factors may play a large role. The impact of COVID-19 may be different in Asians. Funding sourcesBritish Heart Foundation (CH/1999001/11735 and RE/18/2/34213 to AMS); the National Institute for Health Research Biomedical Research Centre (NIHR BRC) at Guys & St Thomas NHS Foundation Trust and Kings College London (IS-BRC-1215-20006); and the NIHR BRC at South London and Maudsley NHS Foundation Trust and Kings College London (IS-BRC-1215-20018).


Subject(s)
COVID-19
6.
medrxiv; 2020.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2020.04.24.20078006

ABSTRACT

BackgroundThe National Early Warning Score (NEWS2) is currently recommended in the United Kingdom for risk stratification of COVID outcomes, but little is known about its ability to detect severe cases. We aimed to evaluate NEWS2 for severe COVID outcome and identify and validate a set of routinely-collected blood and physiological parameters taken at hospital admission to improve the score. MethodsTraining cohorts comprised 1276 patients admitted to Kings College Hospital NHS Foundation Trust with COVID-19 disease from 1st March to 30th April 2020. External validation cohorts included 5037 patients from four UK NHS Trusts (Guys and St Thomas Hospitals, University Hospitals Southampton, University Hospitals Bristol and Weston NHS Foundation Trust, University College London Hospitals), and two hospitals in Wuhan, China (Wuhan Sixth Hospital and Taikang Tongji Hospital). The outcome was severe COVID disease (transfer to intensive care unit or death) at 14 days after hospital admission. Age, physiological measures, blood biomarkers, sex, ethnicity and comorbidities (hypertension, diabetes, cardiovascular, respiratory and kidney diseases) measured at hospital admission were considered in the models. ResultsA baseline model of NEWS2 + age had poor-to-moderate discrimination for severe COVID infection at 14 days (AUC in training sample = 0.700; 95% CI: 0.680, 0.722; Brier score = 0.192; 95% CI: 0.186, 0.197). A supplemented model adding eight routinely-collected blood and physiological parameters (supplemental oxygen flow rate, urea, age, oxygen saturation, CRP, estimated GFR, neutrophil count, neutrophil/lymphocyte ratio) improved discrimination (AUC = 0.735; 95% CI: 0.715, 0.757) and these improvements were replicated across five UK and non-UK sites. However, there was evidence of miscalibration with the model tending to underestimate risks in most sites. ConclusionsNEWS2 score had poor-to-moderate discrimination for medium-term COVID outcome which raises questions about its use as a screening tool at hospital admission. Risk stratification was improved by including readily available blood and physiological parameters measured at hospital admission, but there was evidence of miscalibration in external sites. This highlights the need for a better understanding of the use of early warning scores for COVID. KO_SCPLOWEYC_SCPLOWO_SCPCAP C_SCPCAPO_SCPLOWMESSAGESC_SCPLOWO_LIThe National Early Warning Score (NEWS2), currently recommended for stratification of severe COVID-19 disease in the UK, showed poor-to-moderate discrimination for medium-term outcomes (14-day transfer to ICU or death) among COVID-19 patients. C_LIO_LIRisk stratification was improved by the addition of routinely-measured blood and physiological parameters routinely at hospital admission (supplemental oxygen, urea, oxygen saturation, CRP, estimated GFR, neutrophil count, neutrophil/lymphocyte ratio) which provided moderate improvements in a risk stratification model for 14-day ICU/death. C_LIO_LIThis improvement over NEWS2 alone was maintained across multiple hospital trusts but the model tended to be miscalibrated with risks of severe outcomes underestimated in most sites. C_LIO_LIWe benefited from existing pipelines for informatics at KCH such as CogStack that allowed rapid extraction and processing of electronic health records. This methodological approach provided rapid insights and allowed us to overcome the complications associated with slow data centralisation approaches. C_LI


Subject(s)
COVID-19
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