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1.
ssrn; 2021.
Preprint in English | PREPRINT-SSRN | ID: ppzbmed-10.2139.ssrn.3750679

ABSTRACT

Background: Excess death estimates, reflecting a combination of covid- 19 and non-covid-19 factors, are required to understand the full impact of the pandemic. Relatively little is known about excess deaths in low and middle income countries (LMIC) owing to weaknesses of official statistics on number of deaths and causes of death. India has the second largest number of covid-19 infections globally and is thus an important LMIC. We contribute to the measurement of two key facts: all causes excess deaths and an upper bound for the IFR. Methods: Consumer Pyramids Household Survey (CPHS) is a panel survey dataset across India carried out three times a year. The survey has demographic, economic, and health information about 170,000 households and 600,000 individuals. We use this to estimate excess deaths in the April - August 2020 period across India. We examine correlations between member characteristics such as age, sex, health conditions, urban or rural residence, and economic profile, with the probability of death. We juxtapose this estimated excess death rate with estimates from a seroprevalance survey for the same household dataset, in the state of Karnataka (which has a population of 64 million), to estimate an upper bound for the IFR. Findings: The average annualised crude death rate for May - August 2015-2019 was 8.293 per 1000. This increased to 15.02 per 1000 in May - August 2020. This suggests an annualised excess death rate of 6.7 per 1000. There is a certain divergence of correlations with mortality with member characteristics such as gender, age and income class, as compared with what may be expected with covid-19 related deaths. The estimated upper bound for the IFR in the state of Karnataka is 1.3%.Interpretation: This rise in all-causes deaths, and the socioeconomic characteristics associated with mortality, can help shape improved responses on the part of health policy in understanding the vulnerable and modifying policies to address the problems. These methods can be applied with some panel datasets in other LMIC in order to estimate similar quantities. These results hint at a significant role for non-covid-19 factors in the increased deaths.Funding Statement: None.Declaration of Interests: The authors declare no conflict of interest.Ethics Approval Statement: The work does not involve primary data collection. No ethics approval was therefore taken.


Subject(s)
COVID-19 , Death
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.
medrxiv; 2020.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2020.06.10.20127175

ABSTRACT

Background: Cardiovascular diseases(CVD) increase mortality risk from coronavirus infection(COVID-19), but there are concerns that the pandemic has affected supply and demand of acute cardiovascular care. We estimated excess mortality in specific CVDs, both direct, through infection, and indirect, through changes in healthcare. Methods: We used population-based electronic health records from 3,862,012 individuals in England to estimate pre- and post-COVID-19 mortality risk(direct effect) for people with incident and prevalent CVD. We incorporated: (i)pre-COVID-19 risk by age, sex and comorbidities, (ii)estimated population COVID-19 prevalence, and (iii)estimated relative impact of COVID-19 on mortality(relative risk, RR: 1.5, 2.0 and 3.0). For indirect effects, we analysed weekly mortality and emergency department data for England/Wales and monthly hospital data from England(n=2), China(n=5) and Italy(n=1) for CVD referral, diagnosis and treatment until 1 May 2020. Findings: CVD service activity decreased by 60-100% compared with pre-pandemic levels in eight hospitals across China, Italy and England during the pandemic. In China, activity remained below pre-COVID-19 levels for 2-3 months even after easing lockdown, and is still reduced in Italy and England. Mortality data suggest indirect effects on CVD will be delayed rather than contemporaneous(peak RR 1.4). For total CVD(incident and prevalent), at 10% population COVID-19 rate, we estimated direct impact of 31,205 and 62,410 excess deaths in England at RR 1.5 and 2.0 respectively, and indirect effect of 49932 to 99865 excess deaths. Interpretation: Supply and demand for CVD services have dramatically reduced across countries with potential for substantial, but avoidable, excess mortality during and after the COVID-19 pandemic.


Subject(s)
COVID-19 , Coronavirus Infections , Cardiovascular Diseases
5.
medrxiv; 2020.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2020.05.02.20078642

ABSTRACT

During the current COVID-19 pandemic, it has been suggested that BAME background patients may be disproportionately affected compared to White but few detailed data are available. We took advantage of near real-time hospital data access and analysis pipelines to look at the impact of ethnicity in 1200 consecutive patients admitted between 1st March 2020 and 12th May 2020 to Kings College Hospital NHS Trust in London (UK). Our key findings are firstly that BAME patients are significantly younger and have different co-morbidity profiles than White individuals. Secondly, there is no significant independent effect of ethnicity on severe outcomes (death or ITU admission) within 14-days of symptom onset, after adjustment for age, sex and comorbidities.


Subject(s)
COVID-19 , Death
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
7.
medrxiv; 2020.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2020.04.07.20056788

ABSTRACT

Aims: The SARS-Cov2 virus binds to the ACE2 receptor for cell entry. It has been suggested that ACE- inhibitors (ACEi) and Angiotensin-2 Blockers (ARB), which are commonly used in patients with hypertension or diabetes and may raise ACE2 levels, could increase the risk of severe COVID19 infection. Methods and Results: We evaluated this hypothesis in a consecutive cohort of 1200 acute inpatients with COVID19 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 1 comorbidity. 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. 399 patients (33.3 %) were taking ACEi or ARB. Patients on ACEi/ARB were significantly older and had more comorbidities. The odds ratio (OR) for the primary endpoint in patients on ACEi and ARB, after adjustment for age, sex and co-morbidities, was 0.63 (CI 0.47-0.84, p<0.01). Conclusions: There was no evidence for increased severity of COVID19 disease 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)
Diabetes Mellitus , Hypertension , Death , COVID-19
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