142 research outputs found

    Ten months of temporal variation in the clinical journey of hospitalised patients with COVID-19: an observational cohort

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    Background: There is potentially considerable variation in the nature and duration of the care provided to hospitalised patients during an infectious disease epidemic or pandemic. Improvements in care and clinician confidence may shorten the time spent as an inpatient, or the need for admission to an intensive care unit (ICU) or high density unit (HDU). On the other hand, limited resources at times of high demand may lead to rationing. Nevertheless, these variables may be used as static proxies for disease severity, as outcome measures for trials, and to inform planning and logistics. Methods: We investigate these time trends in an extremely large international cohort of 142,540 patients hospitalised with COVID-19. Investigated are: time from symptom onset to hospital admission, probability of ICU/HDU admission, time from hospital admission to ICU/HDU admission, hospital case fatality ratio (hCFR) and total length of hospital stay. Results: Time from onset to admission showed a rapid decline during the first months of the pandemic followed by peaks during August/September and December 2020. ICU/HDU admission was more frequent from June to August. The hCFR was lowest from June to August. Raw numbers for overall hospital stay showed little variation, but there is clear decline in time to discharge for ICU/HDU survivors. Conclusions: Our results establish that variables of these kinds have limitations when used as outcome measures in a rapidly-evolving situation. Funding: This work was supported by the UK Foreign, Commonwealth and Development Office and Wellcome [215091/Z/18/Z] and the Bill and Melinda Gates Foundation [OPP1209135]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

    Ten months of temporal variation in the clinical journey of hospitalised patients with COVID-19: an observational cohort

    Get PDF
    Background: There is potentially considerable variation in the nature and duration of the care provided to hospitalised patients during an infectious disease epidemic or pandemic. Improvements in care and clinician confidence may shorten the time spent as an inpatient, or the need for admission to an intensive care unit (ICU) or high density unit (HDU). On the other hand, limited resources at times of high demand may lead to rationing. Nevertheless, these variables may be used as static proxies for disease severity, as outcome measures for trials, and to inform planning and logistics. Methods: We investigate these time trends in an extremely large international cohort of 142,540 patients hospitalised with COVID-19. Investigated are: time from symptom onset to hospital admission, probability of ICU/HDU admission, time from hospital admission to ICU/HDU admission, hospital case fatality ratio (hCFR) and total length of hospital stay. Results: Time from onset to admission showed a rapid decline during the first months of the pandemic followed by peaks during August/September and December 2020. ICU/HDU admission was more frequent from June to August. The hCFR was lowest from June to August. Raw numbers for overall hospital stay showed little variation, but there is clear decline in time to discharge for ICU/HDU survivors. Conclusions: Our results establish that variables of these kinds have limitations when used as outcome measures in a rapidly-evolving situation. Funding: This work was supported by the UK Foreign, Commonwealth and Development Office and Wellcome [215091/Z/18/Z] and the Bill and Melinda Gates Foundation [OPP1209135]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

    StopCOVID cohort : An observational study of 3,480 patients admitted to the Sechenov University hospital network in Moscow city for suspected COVID-19 infection

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    © 2020 Oxford University Press. This is a pre-copyedited, author-produced PDF of an article accepted for publication in Clinical Infectious Diseases following peer review. The version of record is available online at: https://doi.org/10.1093/cid/ciaa1535.BACKGROUND: The epidemiology, clinical course, and outcomes of COVID-19 patients in the Russian population are unknown. Information on the differences between laboratory-confirmed and clinically-diagnosed COVID-19 in real-life settings is lacking. METHODS: We extracted data from the medical records of adult patients who were consecutively admitted for suspected COVID-19 infection in Moscow, between April 8 and May 28, 2020. RESULTS: Of the 4261 patients hospitalised for suspected COVID-19, outcomes were available for 3480 patients (median age 56 years (interquartile range 45-66). The commonest comorbidities were hypertension, obesity, chronic cardiac disease and diabetes. Half of the patients (n=1728) had a positive RT-PCR while 1748 were negative on RT-PCR but had clinical symptoms and characteristic CT signs suggestive of COVID-19 infection.No significant differences in frequency of symptoms, laboratory test results and risk factors for in-hospital mortality were found between those exclusively clinically diagnosed or with positive SARS-CoV-2 RT-PCR.In a multivariable logistic regression model the following were associated with in-hospital mortality; older age (per 1 year increase) odds ratio [OR] 1.05 (95% confidence interval (CI) 1.03 - 1.06); male sex (OR 1.71, 1.24 - 2.37); chronic kidney disease (OR 2.99, 1.89 - 4.64); diabetes (OR 2.1, 1.46 - 2.99); chronic cardiac disease (OR 1.78, 1.24 - 2.57) and dementia (OR 2.73, 1.34 - 5.47). CONCLUSIONS: Age, male sex, and chronic comorbidities were risk factors for in-hospital mortality. The combination of clinical features were sufficient to diagnoseCOVID-19 infection indicating that laboratory testing is not critical in real-life clinical practice.Peer reviewe

    Major adverse cardiovascular events (MACE) in patients with severe COVID-19 registered in the ISARIC WHO clinical characterization protocol:A prospective, multinational, observational study

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    Purpose To determine its cumulative incidence, identify the risk factors associated with Major Adverse Cardiovascular Events (MACE) development, and its impact clinical outcomes. Materials and methods This multinational, multicentre, prospective cohort study from the ISARIC database. We used bivariate and multivariate logistic regressions to explore the risk factors related to MACE development and determine its impact on 28-day and 90-day mortality. Results 49,479 patients were included. Most were male 63.5% (31,441/49,479) and from high-income countries (84.4% [42,774/49,479]); however, >6000 patients were registered in low-and-middle-income countries. MACE cumulative incidence during their hospital stay was 17.8% (8829/49,479). The main risk factors independently associated with the development of MACE were older age, chronic kidney disease or cardiovascular disease, smoking history, and requirement of vasopressors or invasive mechanical ventilation at admission. The overall 28-day and 90-day mortality were higher among patients who developed MACE than those who did not (63.1% [5573/8829] vs. 35.6% [14,487/40,650] p < 0.001; 69.9% [6169/8829] vs. 37.8% [15,372/40,650] p < 0.001, respectively). After adjusting for confounders, MACE remained independently associated with higher 28-day and 90-day mortality (Odds Ratio [95% CI], 1.36 [1.33–1.39];1.47 [1.43–1.50], respectively). Conclusions Patients with severe COVID-19 frequently develop MACE, which is independently associated with worse clinical outcomes

    The significance of tumour microarchitectural features in breast cancer prognosis: a digital image analysis

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    BACKGROUND: As only a minor portion of the information present in histological sections is accessible by eye, recognition and quantification of complex patterns and relationships among constituents relies on digital image analysis. In this study, our working hypothesis was that, with the application of digital image analysis technology, visually unquantifiable breast cancer microarchitectural features can be rigorously assessed and tested as prognostic parameters for invasive breast carcinoma of no special type. METHODS: Digital image analysis was performed using public domain software (ImageJ) on tissue microarrays from a cohort of 696 patients, and validated with a commercial platform (Visiopharm). Quantified features included elements defining tumour microarchitecture, with emphasis on the extent of tumour-stroma interface. The differential prognostic impact of tumour nest microarchitecture in the four immunohistochemical surrogates for molecular classification was analysed. Prognostic parameters included axillary lymph node status, breast cancer-specific survival, and time to distant metastasis. Associations of each feature with prognostic parameters were assessed using logistic regression and Cox proportional models adjusting for age at diagnosis, grade, and tumour size. RESULTS: An arrangement in numerous small nests was associated with axillary lymph node involvement. The association was stronger in luminal tumours (odds ratio (OR) = 1.39, p = 0.003 for a 1-SD increase in nest number, OR = 0.75, p = 0.006 for mean nest area). Nest number was also associated with survival (hazard ratio (HR) = 1.15, p = 0.027), but total nest perimeter was the parameter most significantly associated with survival in luminal tumours (HR = 1.26, p = 0.005). In the relatively small cohort of triple-negative tumours, mean circularity showed association with time to distant metastasis (HR = 1.71, p = 0.027) and survival (HR = 1.8, p = 0.02). CONCLUSIONS: We propose that tumour arrangement in few large nests indicates a decreased metastatic potential. By contrast, organisation in numerous small nests provides the tumour with increased metastatic potential to regional lymph nodes. An outstretched pattern in small nests bestows tumours with a tendency for decreased breast cancer-specific survival. Although further validation studies are required before the argument for routine quantification of microarchitectural features is established, our approach is consistent with the demand for cost-effective methods for triaging breast cancer patients that are more likely to benefit from chemotherapy

    Clinical characteristics, risk factors and outcomes in patients with severe COVID-19 registered in the International Severe Acute Respiratory and Emerging Infection Consortium WHO clinical characterisation protocol: a prospective, multinational, multicentre, observational study

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    Due to the large number of patients with severe coronavirus disease 2019 (COVID-19), many were treated outside the traditional walls of the intensive care unit (ICU), and in many cases, by personnel who were not trained in critical care. The clinical characteristics and the relative impact of caring for severe COVID-19 patients outside the ICU is unknown. This was a multinational, multicentre, prospective cohort study embedded in the International Severe Acute Respiratory and Emerging Infection Consortium World Health Organization COVID-19 platform. Severe COVID-19 patients were identified as those admitted to an ICU and/or those treated with one of the following treatments: invasive or noninvasive mechanical ventilation, high-flow nasal cannula, inotropes or vasopressors. A logistic generalised additive model was used to compare clinical outcomes among patients admitted or not to the ICU. A total of 40 440 patients from 43 countries and six continents were included in this analysis. Severe COVID-19 patients were frequently male (62.9%), older adults (median (interquartile range (IQR), 67 (55-78) years), and with at least one comorbidity (63.2%). The overall median (IQR) length of hospital stay was 10 (5-19) days and was longer in patients admitted to an ICU than in those who were cared for outside the ICU (12 (6-23) days versus 8 (4-15) days, p<0.0001). The 28-day fatality ratio was lower in ICU-admitted patients (30.7% (5797 out of 18 831) versus 39.0% (7532 out of 19 295), p<0.0001). Patients admitted to an ICU had a significantly lower probability of death than those who were not (adjusted OR 0.70, 95% CI 0.65-0.75; p<0.0001). Patients with severe COVID-19 admitted to an ICU had significantly lower 28-day fatality ratio than those cared for outside an ICU
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