Clinical outcome, risk assessment, and seasonal variation in hospitalized COVID-19 patients—Results from the CORONA Germany study

Background After one year of the pandemic and hints of seasonal patterns, temporal variations of in-hospital mortality in COVID-19 are widely unknown. Additionally, heterogeneous data regarding clinical indicators predicting disease severity has been published. However, there is a need for a risk stratification model integrating the effects on disease severity and mortality to support clinical decision-making. Methods We conducted a multicenter, observational, prospective, epidemiological cohort study at 45 hospitals in Germany. Until 1 January 2021, all hospitalized SARS CoV-2 positive patients were included. A comprehensive data set was collected in a cohort of seven hospitals. The primary objective was disease severity and prediction of mild, severe, and fatal cases. Ancillary analyses included a temporal analysis of all hospitalized COVID-19 patients for the entire year 2020. Findings A total of 4704 COVID-19 patients were hospitalized with a mortality rate of 19% (890/4704). Rates of mortality, need for ventilation, pneumonia, and respiratory insufficiency showed temporal variations, whereas age had a strong influence on the course of mortality. In cohort conducting analyses, prognostic factors for fatal/severe disease were: age (odds ratio (OR) 1.704, CI:[1.221–2.377]), respiratory rate (OR 1.688, CI:[1.222–2.333]), lactate dehydrogenase (LDH) (OR 1.312, CI:[1.015–1.695]), C-reactive protein (CRP) (OR 2.132, CI:[1.533–2.965]), and creatinine values (OR 2.573, CI:[1.593–4.154]. Conclusions Age, respiratory rate, LDH, CRP, and creatinine at baseline are associated with all cause death, and need for ventilation/ICU treatment in a nationwide series of COVID 19 hospitalized patients. Especially age plays an important prognostic role. In-hospital mortality showed temporal variation during the year 2020, influenced by age. Trial registration number NCT04659187.

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Factors Associated with Disease Severity and Mortality among Patients with Coronavirus Disease 2019: A Systematic Review and Meta-Analysis

10.1101/2020.08.07.20166868 ◽

2020 ◽

Author(s):

Vignesh Chidambaram ◽

Nyan Lynn Tun ◽

Waqas Haque ◽

Marie Gilbert Majella ◽

Ranjith Kumar Sivakumar ◽

...

Keyword(s):

Systematic Review ◽

Disease Severity ◽

English Language ◽

Clinical Decision Making ◽

Clinical Laboratory ◽

Data Extraction ◽

Meta Analysis ◽

Severe Disease ◽

Factors Associated ◽

Risk Of Mortality

Background: Understanding the factors associated with disease severity and mortality in Coronavirus disease (COVID19) is imperative to effectively triage patients. We performed a systematic review to determine the demographic, clinical, laboratory and radiological factors associated with severity and mortality in COVID-19. Methods: We searched PubMed, Embase and WHO database for English language articles from inception until May 8, 2020. We included Observational studies with direct comparison of clinical characteristics between a) patients who died and those who survived or b) patients with severe disease and those without severe disease. Data extraction and quality assessment were performed by two authors independently. Results: Among 15680 articles from the literature search, 109 articles were included in the analysis. The risk of mortality was higher in patients with increasing age, male gender (RR 1.45; 95%CI 1.23,1.71), dyspnea (RR 2.55; 95%CI 1.88,2.46), diabetes (RR 1.59; 95%CI 1.41,1.78), hypertension (RR 1.90; 95%CI 1.69,2.15). Congestive heart failure (OR 4.76; 95%CI 1.34,16.97), hilar lymphadenopathy (OR 8.34; 95%CI 2.57,27.08), bilateral lung involvement (OR 4.86; 95%CI 3.19,7.39) and reticular pattern (OR 5.54; 95%CI 1.24,24.67) were associated with severe disease. Clinically relevant cut-offs for leukocytosis(>10.0 x109/L), lymphopenia(< 1.1 x109/L), elevated C-reactive protein(>100mg/L), LDH(>250U/L) and D-dimer(>1mg/L) had higher odds of severe disease and greater risk of mortality. Conclusion: Knowledge of the factors associated of disease severity and mortality identified in our study may assist in clinical decision-making and critical-care resource allocation for patients with COVID-19.

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Patient trajectories and risk factors for severe outcomes among persons hospitalized for COVID-19 in the Maryland/DC region

10.1101/2020.05.24.20111864 ◽

2020 ◽

Cited By ~ 1

Author(s):

Brian T. Garibaldi ◽

Jacob Fiksel ◽

John Muschelli ◽

Matthew Robinson ◽

Masoud Rouhizadeh ◽

...

Keyword(s):

Risk Factors ◽

Respiratory Rate ◽

Disease Severity ◽

Clinical Features ◽

Hospital Admissions ◽

Severe Disease ◽

Cohort Analysis ◽

Ordinal Scale ◽

Severe Illness ◽

Poor Outcomes

AbstractBackgroundRisk factors for poor outcomes from COVID-19 are emerging among US cohorts, but patient trajectories during hospitalization ranging from mild-moderate, severe, and death and the factors associated with these outcomes have been underexplored.MethodsWe performed a cohort analysis of consecutive COVID-19 hospital admissions at 5 Johns Hopkins hospitals in the Baltimore/DC area between March 4 and April 24, 2020. Disease severity and outcomes were classified using the WHO COVID-19 disease severity ordinal scale. Cox proportional-hazards regressions were performed to assess relationships between demographics, clinical features and progression to severe disease or death.Results832 COVID-19 patients were hospitalized; 633 (76.1%) were discharged, 113 (13.6%) died, and 85 (10.2%) remained hospitalized. Among those discharged, 518 (82%) had mild/moderate and 116 (18%) had severe illness. Mortality was statistically significantly associated with increasing age per 10 years (adjusted hazard ratio (aHR) 1.54; 95%CI 1.28-1.84), nursing home residence (aHR 2.13, 95%CI 1.41-3.23), Charlson comorbidity index (1.13; 95% CI 1.02-1.26), respiratory rate (aHR 1.13; 95%CI 1.09-1.17), D-dimer greater than 1mg/dL (aHR 2.79; 95% 1.53-5.09), and detectable troponin (aHR 2.79; 95%CI 1.53-5.09). In patients under 60, only male sex (aHR 1.7;95%CI 1.11-2.58), increasing body mass index (BMI) (aHR1.25 1.14-1.37), Charlson score (aHR 1.27; 1.1-1.46) and respiratory rate (aHR 1.16; 95%CI 1.13-1.2) were associated with severe illness or death.ConclusionsA combination of demographic and clinical features on admission is strongly associated with progression to severe disease or death in a US cohort of COVID-19 patients. Younger patients have distinct risk factors for poor outcomes.

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Spatio-temporal analysis of seismic anisotropy associated with the Cook Strait and Kaikōura earthquake sequences in New Zealand

10.26686/wgtn.14298617.v1 ◽

2021 ◽

Author(s):

KM Graham ◽

Martha Savage ◽

Richard Arnold ◽

HJ Zal ◽

T Okada ◽

...

Keyword(s):

New Zealand ◽

Seismic Anisotropy ◽

Temporal Analysis ◽

Temporal Variations ◽

Orthogonal Direction ◽

Data Set ◽

Systematic Analysis ◽

Crustal Earthquakes ◽

Cook Strait ◽

Earthquake Sequences

© 2020 The Author(s) 2020. Published by Oxford University Press on behalf of The Royal Astronomical Society. Large earthquakes can diminish and redistribute stress, which can change the stress field in the Earth's crust. Seismic anisotropy, measured through shear wave splitting (SWS), is often considered to be an indicator of stress in the crust because the closure of cracks due to differential stress leads to waves polarized parallel to the cracks travelling faster than in the orthogonal direction. We examine spatial and temporal variations in SWS measurements and the Vp/Vs ratio associated with the 2013 Cook Strait (Seddon, Grassmere) and 2016 Kaikōura earthquakes in New Zealand. These earthquake sequences provide a unique data set, where clusters of closely spaced earthquakes occurred. We use an automatic, objective splitting analysis algorithm and automatic local S-phase pickers to expedite the processing and to minimize observer bias. We present SWS and Vp/Vs measurements for over 40 000 crustal earthquakes across 36 stations spanning close to $5\frac{1}{2}$ yr between 2013 and 2018. We obtain a total of 102 260 (out of 398 169) high-quality measurements. We observe significant spatial variations in the fast polarization orientation, φ. The orientation of gravitational stresses are consistent with most of the observed anisotropy. However, multiple mechanisms (such as structural, tectonic stresses and gravitational stresses) may control some of the observed crustal anisotropy in the study area. Systematic analysis of SWS parameters and Vp/Vs ratios revealed that apparent temporal variations are caused by variation in earthquake path through spatially varying media.

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Factors associated with disease severity and mortality among patients with COVID-19: A systematic review and meta-analysis

PLoS ONE ◽

10.1371/journal.pone.0241541 ◽

2020 ◽

Vol 15 (11) ◽

pp. e0241541 ◽

Cited By ~ 1

Author(s):

Vignesh Chidambaram ◽

Nyan Lynn Tun ◽

Waqas Z. Haque ◽

Marie Gilbert Majella ◽

Ranjith Kumar Sivakumar ◽

...

Keyword(s):

Systematic Review ◽

Disease Severity ◽

English Language ◽

Clinical Decision Making ◽

Clinical Laboratory ◽

Data Extraction ◽

Meta Analysis ◽

Severe Disease ◽

Factors Associated ◽

Risk Of Mortality

Background Understanding the factors associated with disease severity and mortality in Coronavirus disease (COVID-19) is imperative to effectively triage patients. We performed a systematic review to determine the demographic, clinical, laboratory and radiological factors associated with severity and mortality in COVID-19. Methods We searched PubMed, Embase and WHO database for English language articles from inception until May 8, 2020. We included Observational studies with direct comparison of clinical characteristics between a) patients who died and those who survived or b) patients with severe disease and those without severe disease. Data extraction and quality assessment were performed by two authors independently. Results Among 15680 articles from the literature search, 109 articles were included in the analysis. The risk of mortality was higher in patients with increasing age, male gender (RR 1.45, 95%CI 1.23–1.71), dyspnea (RR 2.55, 95%CI 1.88–2.46), diabetes (RR 1.59, 95%CI 1.41–1.78), hypertension (RR 1.90, 95%CI 1.69–2.15). Congestive heart failure (OR 4.76, 95%CI 1.34–16.97), hilar lymphadenopathy (OR 8.34, 95%CI 2.57–27.08), bilateral lung involvement (OR 4.86, 95%CI 3.19–7.39) and reticular pattern (OR 5.54, 95%CI 1.24–24.67) were associated with severe disease. Clinically relevant cut-offs for leukocytosis(>10.0 x109/L), lymphopenia(< 1.1 x109/L), elevated C-reactive protein(>100mg/L), LDH(>250U/L) and D-dimer(>1mg/L) had higher odds of severe disease and greater risk of mortality. Conclusion Knowledge of the factors associated of disease severity and mortality identified in our study may assist in clinical decision-making and critical-care resource allocation for patients with COVID-19.

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A spatio-temporal analysis of fires in South Africa

South African Journal of Science ◽

10.17159/sajs.2016/20150489 ◽

2016 ◽

Vol Volume 112 (Number 11/12) ◽

Cited By ~ 10

Author(s):

Sheldon Strydom ◽

Michael J. Savage ◽

◽

Keyword(s):

South Africa ◽

Human Life ◽

Summer Rainfall ◽

Temporal Analysis ◽

Temporal Variations ◽

Fire Frequency ◽

Western Cape ◽

Financial Loss ◽

Data Set ◽

Mountainous Regions

Abstract The prevalence and history of fires in Africa has led to the continent being named ‘the fire continent’. Fires are common on the continent and lead to a high number of annual fire disasters which result in many human fatalities and considerable financial loss. Increased population growth and concentrated settlement planning increase the probability of fire disasters and the associated loss of human life and financial loss when disasters occur. In order to better understand the spatial and temporal variations and characteristics of fires in South Africa, an 11-year data set of MODIS-derived Active Fire Hotspots was analysed using an open source geographic information system. The study included the mapping of national fire frequency over the 11-year period. Results indicate that the highest fire frequency occurred in the northeastern regions of South Africa, in particular the mountainous regions of KwaZulu-Natal and Mpumalanga, and in the Western Cape. Increasing trends in provincial fire frequency were observed in eight of the nine provinces of South Africa, with Mpumalanga the only province for which a decrease in annual fire frequency was observed. Temporally, fires were observed in all months for all provinces, although distinct fire seasons were observed and were largely driven by rainfall seasons. The southwestern regions of South Africa (winter-rainfall regions) experienced higher fire frequencies during the summer months and the rest of the country (summer-rainfall regions) during the winter months. Certain regions – those which experienced bimodal rainfall seasons – did not display distinct fire seasons because of the complex wet and dry seasons. Investigation into the likely effects of climate change on South African fire frequency revealed that increased air temperatures and events such as La Niña have a marked effect on fire activity.

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Spatio-temporal analysis of seismic anisotropy associated with the Cook Strait and Kaikōura earthquake sequences in New Zealand

Geophysical Journal International ◽

10.1093/gji/ggaa433 ◽

2020 ◽

Vol 223 (3) ◽

pp. 1987-2008

Author(s):

Kenny M Graham ◽

Martha K Savage ◽

Richard Arnold ◽

Hubert J Zal ◽

Tomomi Okada ◽

...

Keyword(s):

New Zealand ◽

Seismic Anisotropy ◽

Temporal Analysis ◽

Temporal Variations ◽

Orthogonal Direction ◽

Data Set ◽

Systematic Analysis ◽

Crustal Earthquakes ◽

Cook Strait ◽

Earthquake Sequences

SUMMARY Large earthquakes can diminish and redistribute stress, which can change the stress field in the Earth’s crust. Seismic anisotropy, measured through shear wave splitting (SWS), is often considered to be an indicator of stress in the crust because the closure of cracks due to differential stress leads to waves polarized parallel to the cracks travelling faster than in the orthogonal direction. We examine spatial and temporal variations in SWS measurements and the Vp/Vs ratio associated with the 2013 Cook Strait (Seddon, Grassmere) and 2016 Kaikōura earthquakes in New Zealand. These earthquake sequences provide a unique data set, where clusters of closely spaced earthquakes occurred. We use an automatic, objective splitting analysis algorithm and automatic local S-phase pickers to expedite the processing and to minimize observer bias. We present SWS and Vp/Vs measurements for over 40 000 crustal earthquakes across 36 stations spanning close to $5\frac{1}{2}$ yr between 2013 and 2018. We obtain a total of 102 260 (out of 398 169) high-quality measurements. We observe significant spatial variations in the fast polarization orientation, ϕ. The orientation of gravitational stresses are consistent with most of the observed anisotropy. However, multiple mechanisms (such as structural, tectonic stresses and gravitational stresses) may control some of the observed crustal anisotropy in the study area. Systematic analysis of SWS parameters and Vp/Vs ratios revealed that apparent temporal variations are caused by variation in earthquake path through spatially varying media.

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MR-proADM as prognostic factor of outcome in COVID-19 patients

Scientific Reports ◽

10.1038/s41598-021-84478-1 ◽

2021 ◽

Vol 11 (1) ◽

Cited By ~ 1

Author(s):

Emanuela Sozio ◽

Carlo Tascini ◽

Martina Fabris ◽

Federica D’Aurizio ◽

Chiara De Carlo ◽

...

Keyword(s):

Disease Severity ◽

Severe Disease ◽

Scoring Systems ◽

Orotracheal Intubation ◽

Outcome Data ◽

University Hospital ◽

Data Set ◽

Discriminative Performance ◽

Clinical Scoring ◽

Severity Class

AbstractMid Regional pro-ADM (MR-proADM) is a promising novel biomarker in the evaluation of deteriorating patients and an emergent prognosis factor in patients with sepsis, septic shock and organ failure. It can be induced by bacteria, fungi or viruses. We hypothesized that the assessment of MR-proADM, with or without other inflammatory cytokines, as part of a clinical assessment of COVID-19 patients at hospital admission, may assist in identifying those likely to develop severe disease. A pragmatic retrospective analysis was performed on a complete data set from 111 patients admitted to Udine University Hospital, in northern Italy, from 25th March to 15th May 2020, affected by SARS-CoV-2 pneumonia. Clinical scoring systems (SOFA score, WHO disease severity class, SIMEU clinical phenotype), cytokines (IL-6, IL-1b, IL-8, TNF-α), and MR-proADM were measured. Demographic, clinical and outcome data were collected for analysis. At multivariate analysis, high MR-proADM levels were significantly associated with negative outcome (death or orotracheal intubation, IOT), with an odds ratio of 4.284 [1.893–11.413], together with increased neutrophil count (OR = 1.029 [1.011–1.049]) and WHO disease severity class (OR = 7.632 [5.871–19.496]). AUROC analysis showed a good discriminative performance of MR-proADM (AUROC: 0.849 [95% Cl 0.771–0.730]; p < 0.0001). The optimal value of MR-proADM to discriminate combined event of death or IOT is 0.895 nmol/l, with a sensitivity of 0.857 [95% Cl 0.728–0.987] and a specificity of 0.687 [95% Cl 0.587–0.787]. This study shows an association between MR-proADM levels and the severity of COVID-19. The assessment of MR-proADM combined with clinical scoring systems could be of great value in triaging, evaluating possible escalation of therapies, and admission avoidance or inclusion into trials. Larger prospective and controlled studies are needed to confirm these findings.

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Spatio-temporal analysis of seismic anisotropy associated with the Cook Strait and Kaikōura earthquake sequences in New Zealand

10.26686/wgtn.14298617 ◽

2021 ◽

Author(s):

KM Graham ◽

Martha Savage ◽

Richard Arnold ◽

HJ Zal ◽

T Okada ◽

...

Keyword(s):

New Zealand ◽

Seismic Anisotropy ◽

Temporal Analysis ◽

Temporal Variations ◽

Orthogonal Direction ◽

Data Set ◽

Systematic Analysis ◽

Crustal Earthquakes ◽

Cook Strait ◽

Earthquake Sequences

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Clinical correlation of lung ultrasound profiles in patients with COVID-19 infection

10.1101/2021.04.05.21254935 ◽

2021 ◽

Author(s):

Chitrakshi Nagpal ◽

Sanchit Kumar ◽

Naveet Wig ◽

Arvind Kumar ◽

Praful Pandey ◽

...

Keyword(s):

Respiratory Rate ◽

Lung Ultrasound ◽

Severe Disease ◽

Primary Objective ◽

Clinical Severity ◽

Lung Pathology ◽

Cross Sectional ◽

Total N ◽

Arterial Blood ◽

B Lines

Background: Lung ultrasound is a popular point of care test that correlates well with computed tomography for lung pathologies. While previous studies have shown its ability to detect COVID-19 related lung pathology, we aimed to evaluate the utility of lung ultrasound in the triage and prognostication of COVID-19 patients by determining its ability to predict clinical severity and outcomes. Methods: This was a prospective, cross-sectional, observational, single centre study done at JPNATC and AIIMS, New Delhi, India. Consenting eligible patients aged 18 years or more were included if hospitalised with microbiologically confirmed COVID-19 and classified as mild, moderate (respiratory rate >24/min OR SpO2<94% on room air) and severe COVID-19 (respiratory rate >30/min OR SpO2<90% on room air) at the time of enrolment. The lungs were systematically assessed with ultrasound after division into 14 zones (4 anteriorly, 4 axillary and 6 posteriorly). Clinical and laboratory parameters including arterial blood gas analysis at the time of evaluation were recorded. Patients were followed till death or discharge. The primary objective was to determine the correlation between clinical severity and lung ultrasound profiles (no. of A, B and C profiles, and the total number of areas involved). Secondary objectives included assessment of the correlation between lung ultrasound profiles and clinical outcomes and development of a statistical model incorporating ultrasound and clinical parameters to allow prediction of COVID-19 related severity and outcomes. Findings: Between October 1, 2020, and January 31,2021, patients were screened for inclusion and total n=60 patients were evaluated and included in the final analysis. The most common abnormality seen were B lines, seen in at least one zone in n=53 (88.33%) of cases. A median of 9 (IQR: 5-12) zones of the 14 assessed had a B-profile. The total number of abnormal areas (zones with a B or C profile) correlated significantly with the PaO2/FiO2 ratio (ρ= -0.7232, p<0.0001) and SpO2/FiO2 ratio (ρ= -0.6866, p<0.0001), and differed significantly between mild and moderate vs severe cases (p=0.0026 mild vs moderate, p<0.0001 mild vs severe, p=0.0175 moderate vs severe). The total number of B lines were predictors of mortality (p=0.0188, OR 1.03, 95% CI 1.003-1.060). Statistical models that incorporated total number of B-lines, CRP and anticoagulation use could predict mortality (p=0.0124, pseudo R2=0.1740) with an AUC= 0.7682 (95% CI=0.6176-0.9188), and the total number of involved areas and LDH levels could distinguish severe disease from mild/moderate disease (p<0.0001, Pseudo R2=0.3822), AUC = 0.8743 (95% CI=0.7752-0.9733). A simplified cut off of ≥6 involved areas (of the 14 assessed) was 100% sensitive and 52% specific for differentiating severe disease from mild and moderate ones. Interpretation: In patients with COVID-19, increasing involvement of the lungs as assessed by ultrasonography correlates significantly with clinical severity and outcomes. These findings may be utilized in future prospective studies to validate the use of lung ultrasound to triage and prognosticate patients with COVID-19 infection.

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Development and temporal external validation of a simple risk score tool for prediction of outcomes after severe head injury based on admission characteristics from level-1 trauma centre of India using retrospectively collected data

BMJ Open ◽

10.1136/bmjopen-2020-040778 ◽

2021 ◽

Vol 11 (1) ◽

pp. e040778

Author(s):

Vineet Kumar Kamal ◽

Ravindra Mohan Pandey ◽

Deepak Agrawal

Keyword(s):

Hospital Mortality ◽

External Validation ◽

Trauma Centre ◽

Unfavourable Outcome ◽

Motor Score ◽

Validation Data ◽

Data Set ◽

Development Data ◽

Level 1 ◽

Pupillary Reactivity

ObjectiveTo develop and validate a simple risk scores chart to estimate the probability of poor outcomes in patients with severe head injury (HI).DesignRetrospective.SettingLevel-1, government-funded trauma centre, India.ParticipantsPatients with severe HI admitted to the neurosurgery intensive care unit during 19 May 2010–31 December 2011 (n=946) for the model development and further, data from same centre with same inclusion criteria from 1 January 2012 to 31 July 2012 (n=284) for the external validation of the model.Outcome(s)In-hospital mortality and unfavourable outcome at 6 months.ResultsA total of 39.5% and 70.7% had in-hospital mortality and unfavourable outcome, respectively, in the development data set. The multivariable logistic regression analysis of routinely collected admission characteristics revealed that for in-hospital mortality, age (51–60, >60 years), motor score (1, 2, 4), pupillary reactivity (none), presence of hypotension, basal cistern effaced, traumatic subarachnoid haemorrhage/intraventricular haematoma and for unfavourable outcome, age (41–50, 51–60, >60 years), motor score (1–4), pupillary reactivity (none, one), unequal limb movement, presence of hypotension were the independent predictors as its 95% confidence interval (CI) of odds ratio (OR)_did not contain one. The discriminative ability (area under the receiver operating characteristic curve (95% CI)) of the score chart for in-hospital mortality and 6 months outcome was excellent in the development data set (0.890 (0.867 to 912) and 0.894 (0.869 to 0.918), respectively), internal validation data set using bootstrap resampling method (0.889 (0.867 to 909) and 0.893 (0.867 to 0.915), respectively) and external validation data set (0.871 (0.825 to 916) and 0.887 (0.842 to 0.932), respectively). Calibration showed good agreement between observed outcome rates and predicted risks in development and external validation data set (p>0.05).ConclusionFor clinical decision making, we can use of these score charts in predicting outcomes in new patients with severe HI in India and similar settings.

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