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1.
Medicine (Baltimore) ; 100(40): e27422, 2021 Oct 08.
Article in English | MEDLINE | ID: covidwho-2191077

ABSTRACT

ABSTRACT: As severe acute respiratory syndrome coronavirus 2 continues to spread, easy-to-use risk models that predict hospital mortality can assist in clinical decision making and triage. We aimed to develop a risk score model for in-hospital mortality in patients hospitalized with 2019 novel coronavirus (COVID-19) that was robust across hospitals and used clinical factors that are readily available and measured standardly across hospitals.In this retrospective observational study, we developed a risk score model using data collected by trained abstractors for patients in 20 diverse hospitals across the state of Michigan (Mi-COVID19) who were discharged between March 5, 2020 and August 14, 2020. Patients who tested positive for severe acute respiratory syndrome coronavirus 2 during hospitalization or were discharged with an ICD-10 code for COVID-19 (U07.1) were included. We employed an iterative forward selection approach to consider the inclusion of 145 potential risk factors available at hospital presentation. Model performance was externally validated with patients from 19 hospitals in the Mi-COVID19 registry not used in model development. We shared the model in an easy-to-use online application that allows the user to predict in-hospital mortality risk for a patient if they have any subset of the variables in the final model.Two thousand one hundred and ninety-three patients in the Mi-COVID19 registry met our inclusion criteria. The derivation and validation sets ultimately included 1690 and 398 patients, respectively, with mortality rates of 19.6% and 18.6%, respectively. The average age of participants in the study after exclusions was 64 years old, and the participants were 48% female, 49% Black, and 87% non-Hispanic. Our final model includes the patient's age, first recorded respiratory rate, first recorded pulse oximetry, highest creatinine level on day of presentation, and hospital's COVID-19 mortality rate. No other factors showed sufficient incremental model improvement to warrant inclusion. The area under the receiver operating characteristics curve for the derivation and validation sets were .796 (95% confidence interval, .767-.826) and .829 (95% confidence interval, .782-.876) respectively.We conclude that the risk of in-hospital mortality in COVID-19 patients can be reliably estimated using a few factors, which are standardly measured and available to physicians very early in a hospital encounter.


Subject(s)
COVID-19/mortality , Hospital Mortality/trends , Age Factors , Aged , Aged, 80 and over , Body Mass Index , Comorbidity , Creatinine/blood , Female , Health Behavior , Humans , Logistic Models , Male , Michigan/epidemiology , Middle Aged , Oximetry , Prognosis , ROC Curve , Retrospective Studies , Risk Assessment , Risk Factors , SARS-CoV-2 , Severity of Illness Index , Sex Factors , Socioeconomic Factors
2.
PLoS One ; 17(2): e0263936, 2022.
Article in English | MEDLINE | ID: covidwho-1910532

ABSTRACT

BACKGROUND: The updated Surviving Sepsis Campaign guidelines recommend a 1-hour window for completion of a sepsis care bundle; however, the effectiveness of the hour-1 bundle has not been fully evaluated. The present study aimed to evaluate the impact of hour-1 bundle completion on clinical outcomes in sepsis patients. METHODS: This was a multicenter, prospective, observational study conducted in 17 intensive care units in tertiary hospitals in Japan. We included all adult patients who were diagnosed as having sepsis by Sepsis-3 and admitted to intensive care units from July 2019 to August 2020. Impacts of hour-1 bundle adherence and delay of adherence on risk-adjusted in-hospital mortality were estimated by multivariable logistic regression analyses. RESULTS: The final study cohort included 178 patients with sepsis. Among them, 89 received bundle-adherent care. Completion rates of each component (measure lactate level, obtain blood cultures, administer broad-spectrum antibiotics, administer crystalloid, apply vasopressors) within 1 hour were 98.9%, 86.2%, 51.1%, 94.9%, and 69.1%, respectively. Completion rate of all components within 1 hour was 50%. In-hospital mortality was 18.0% in the patients with and 30.3% in the patients without bundle-adherent care (p = 0.054). The adjusted odds ratio of non-bundle-adherent versus bundle-adherent care for in-hospital mortality was 2.32 (95% CI 1.09-4.95) using propensity scoring. Non-adherence to obtaining blood cultures and administering broad-spectrum antibiotics within 1 hour was related to in-hospital mortality (2.65 [95% CI 1.25-5.62] and 4.81 [95% CI 1.38-16.72], respectively). The adjusted odds ratio for 1-hour delay in achieving hour-1 bundle components for in-hospital mortality was 1.28 (95% CI 1.04-1.57) by logistic regression analysis. CONCLUSION: Completion of the hour-1 bundle was associated with lower in-hospital mortality. Obtaining blood cultures and administering antibiotics within 1 hour may have been the components most contributing to decreased in-hospital mortality.


Subject(s)
Hospital Mortality/trends , Patient Care Bundles/methods , Sepsis/therapy , Aged , Aged, 80 and over , Female , Guideline Adherence , Humans , Intensive Care Units , Japan , Logistic Models , Male , Prospective Studies , Sepsis/mortality , Tertiary Care Centers , Time Factors
3.
Clin J Am Soc Nephrol ; 17(3): 342-349, 2022 03.
Article in English | MEDLINE | ID: covidwho-1714924

ABSTRACT

BACKGROUND AND OBJECTIVES: AKI is a common complication of coronavirus disease 2019 (COVID-19) and is associated with high mortality. Palliative care, a specialty that supports patients with serious illness, is valuable for these patients but is historically underutilized in AKI. The objectives of this paper are to describe the use of palliative care in patients with AKI and COVID-19 and their subsequent health care utilization. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: We conducted a retrospective analysis of New York University Langone Health electronic health data of COVID-19 hospitalizations between March 2, 2020 and August 25, 2020. Regression models were used to examine characteristics associated with receiving a palliative care consult. RESULTS: Among patients with COVID-19 (n=4276; 40%), those with AKI (n=1310; 31%) were more likely than those without AKI (n=2966; 69%) to receive palliative care (AKI without KRT: adjusted odds ratio, 1.81; 95% confidence interval, 1.40 to 2.33; P<0.001; AKI with KRT: adjusted odds ratio, 2.45; 95% confidence interval, 1.52 to 3.97; P<0.001), even after controlling for markers of critical illness (admission to intensive care units, mechanical ventilation, or modified sequential organ failure assessment score); however, consults came significantly later (10 days from admission versus 5 days; P<0.001). Similarly, 66% of patients initiated on KRT received palliative care versus 37% (P<0.001) of those with AKI not receiving KRT, and timing was also later (12 days from admission versus 9 days; P=0.002). Despite greater use of palliative care, patients with AKI had a significantly longer length of stay, more intensive care unit admissions, and more use of mechanical ventilation. Those with AKI did have a higher frequency of discharges to inpatient hospice (6% versus 3%) and change in code status (34% versus 7%) than those without AKI. CONCLUSIONS: Palliative care was utilized more frequently for patients with AKI and COVID-19 than historically reported in AKI. Despite high mortality, consultation occurred late in the hospital course and was not associated with reduced initiation of life-sustaining interventions. PODCAST: This article contains a podcast at https://www.asn-online.org/media/podcast/CJASN/2022_02_24_CJN11030821.mp3.


Subject(s)
Acute Kidney Injury/therapy , COVID-19/therapy , Health Resources/trends , Palliative Care/trends , Practice Patterns, Physicians'/trends , Acute Kidney Injury/mortality , Acute Kidney Injury/virology , Aged , Aged, 80 and over , COVID-19/mortality , COVID-19/virology , Critical Care/trends , Electronic Health Records , Female , Hospital Mortality/trends , Humans , Male , Middle Aged , Referral and Consultation/trends , Respiration, Artificial/trends , Retrospective Studies , Risk Assessment , Risk Factors , Time Factors , Treatment Outcome
4.
Crit Care Med ; 50(2): 245-255, 2022 02 01.
Article in English | MEDLINE | ID: covidwho-1672309

ABSTRACT

OBJECTIVES: To determine the association between time period of hospitalization and hospital mortality among critically ill adults with coronavirus disease 2019. DESIGN: Observational cohort study from March 6, 2020, to January 31, 2021. SETTING: ICUs at four hospitals within an academic health center network in Atlanta, GA. PATIENTS: Adults greater than or equal to 18 years with coronavirus disease 2019 admitted to an ICU during the study period (i.e., Surge 1: March to April, Lull 1: May to June, Surge 2: July to August, Lull 2: September to November, Surge 3: December to January). MEASUREMENTS AND MAIN RESULTS: Among 1,686 patients with coronavirus disease 2019 admitted to an ICU during the study period, all-cause hospital mortality was 29.7%. Mortality differed significantly over time: 28.7% in Surge 1, 21.3% in Lull 1, 25.2% in Surge 2, 30.2% in Lull 2, 34.7% in Surge 3 (p = 0.007). Mortality was significantly associated with 1) preexisting risk factors (older age, race, ethnicity, lower body mass index, higher Elixhauser Comorbidity Index, admission from a nursing home); 2) clinical status at ICU admission (higher Sequential Organ Failure Assessment score, higher d-dimer, higher C-reactive protein); and 3) ICU interventions (receipt of mechanical ventilation, vasopressors, renal replacement therapy, inhaled vasodilators). After adjusting for baseline and clinical variables, there was a significantly increased risk of mortality associated with admission during Lull 2 (relative risk, 1.37 [95% CI = 1.03-1.81]) and Surge 3 (relative risk, 1.35 [95% CI = 1.04-1.77]) as compared to Surge 1. CONCLUSIONS: Despite increased experience and evidence-based treatments, the risk of death for patients admitted to the ICU with coronavirus disease 2019 was highest during the fall and winter of 2020. Reasons for this increased mortality are not clear.


Subject(s)
COVID-19/mortality , Hospital Mortality/trends , Hospitalization/trends , Intensive Care Units/trends , SARS-CoV-2 , Academic Medical Centers , Aged , Cohort Studies , Critical Illness , Female , Humans , Male , Middle Aged , Time Factors
5.
Viruses ; 14(2)2022 01 28.
Article in English | MEDLINE | ID: covidwho-1667344

ABSTRACT

Unselected data of nationwide studies of hospitalized patients with COVID-19 are still sparse, but these data are of outstanding interest to avoid exceeding hospital capacities and overloading national healthcare systems. Thus, we sought to analyze seasonal/regional trends, predictors of in-hospital case-fatality, and mechanical ventilation (MV) in patients with COVID-19 in Germany. We used the German nationwide inpatient samples to analyze all hospitalized patients with a confirmed COVID-19 diagnosis in Germany between 1 January and 31 December in 2020. We analyzed data of 176,137 hospitalizations of patients with confirmed COVID-19-infection. Among those, 31,607 (17.9%) died, whereby in-hospital case-fatality grew exponentially with age. Overall, age ≥ 70 years (OR 5.91, 95%CI 5.70-6.13, p < 0.001), pneumonia (OR 4.58, 95%CI 4.42-4.74, p < 0.001) and acute respiratory distress syndrome (OR 8.51, 95%CI 8.12-8.92, p < 0.001) were strong predictors of in-hospital death. Most COVID-19 patients were treated in hospitals in urban areas (n = 92,971) associated with the lowest case-fatality (17.5%), as compared to hospitals in suburban (18.3%) or rural areas (18.8%). MV demand was highest in November/December 2020 (32.3%, 20.3%) in patients between the 6th and 8th age decade. In the first age decade, 78 of 1861 children (4.2%) with COVID-19-infection were treated with MV, and five of them died (0.3%). The results of our study indicate seasonal and regional variations concerning the number of COVID-19 patients, necessity of MV, and case fatality in Germany. These findings may help to ensure the flexible allocation of intensive care (human) resources, which is essential for managing enormous societal challenges worldwide to avoid overloaded regional healthcare systems.


Subject(s)
COVID-19/epidemiology , COVID-19/mortality , Hospital Mortality/trends , Hospitalization/statistics & numerical data , Inpatients/statistics & numerical data , Aged , Aged, 80 and over , Female , Germany/epidemiology , Hospitalization/trends , Humans , Intensive Care Units/statistics & numerical data , Intensive Care Units/trends , Male , Middle Aged , Respiration, Artificial/statistics & numerical data , Respiration, Artificial/trends , Risk Factors , SARS-CoV-2/pathogenicity
6.
Int J Mol Sci ; 23(3)2022 Jan 29.
Article in English | MEDLINE | ID: covidwho-1667195

ABSTRACT

(1) Background: In COVID-19 survivors there is an increased prevalence of pulmonary fibrosis of which the underlying molecular mechanisms are poorly understood; (2) Methods: In this multicentric study, n = 12 patients who succumbed to COVID-19 due to progressive respiratory failure were assigned to an early and late group (death within ≤7 and >7 days of hospitalization, respectively) and compared to n = 11 healthy controls; mRNA and protein expression as well as biological pathway analysis were performed to gain insights into the evolution of pulmonary fibrogenesis in COVID-19; (3) Results: Median duration of hospitalization until death was 3 (IQR25-75, 3-3.75) and 14 (12.5-14) days in the early and late group, respectively. Fifty-eight out of 770 analyzed genes showed a significantly altered expression signature in COVID-19 compared to controls in a time-dependent manner. The entire study group showed an increased expression of BST2 and IL1R1, independent of hospitalization time. In the early group there was increased activity of inflammation-related genes and pathways, while fibrosis-related genes (particularly PDGFRB) and pathways dominated in the late group; (4) Conclusions: After the first week of hospitalization, there is a shift from pro-inflammatory to fibrogenic activity in severe COVID-19. IL1R1 and PDGFRB may serve as potential therapeutic targets in future studies.


Subject(s)
COVID-19/genetics , COVID-19/metabolism , Pulmonary Fibrosis/pathology , Aged , COVID-19/mortality , Female , Hospital Mortality/trends , Hospitalization , Humans , Lung/pathology , Male , Middle Aged , Pulmonary Fibrosis/metabolism , Respiratory Insufficiency/pathology , SARS-CoV-2/pathogenicity
7.
PLoS One ; 17(1): e0261711, 2022.
Article in English | MEDLINE | ID: covidwho-1643247

ABSTRACT

OBJECTIVE: To describe the impact of different doses of corticosteroids on the evolution of patients with COVID-19 pneumonia, based on the potential benefit of the non-genomic mechanism of these drugs at higher doses. METHODS: Observational study using data collected from the SEMI-COVID-19 Registry. We evaluated the epidemiological, radiological and analytical scenario between patients treated with megadoses therapy of corticosteroids vs low-dose of corticosteroids and the development of complications. The primary endpoint was all-cause in-hospital mortality according to use of corticosteroids megadoses. RESULTS: Of a total of 14,921 patients, corticosteroids were used in 5,262 (35.3%). Of them, 2,216 (46%) specifically received megadoses. Age was a factor that differed between those who received megadoses therapy versus those who did not in a significant manner (69 years [IQR 59-79] vs 73 years [IQR 61-83]; p < .001). Radiological and analytical findings showed a higher use of megadoses therapy among patients with an interstitial infiltrate and elevated inflammatory markers associated with COVID-19. In the univariate study it appears that steroid use is associated with increased mortality (OR 2.07 95% CI 1.91-2.24 p < .001) and megadose use with increased survival (OR 0.84 95% CI 0.75-0.96, p 0.011), but when adjusting for possible confounding factors, it is observed that the use of megadoses is also associated with higher mortality (OR 1.54, 95% CI 1.32-1.80; p < .001). There is no difference between megadoses and low-dose (p .298). Although, there are differences in the use of megadoses versus low-dose in terms of complications, mainly infectious, with fewer pneumonias and sepsis in the megadoses group (OR 0.82 95% CI 0.71-0.95; p < .001 and OR 0.80 95% CI 0.65-0.97; p < .001) respectively. CONCLUSION: There is no difference in mortality with megadoses versus low-dose, but there is a lower incidence of infectious complications with glucocorticoid megadoses.


Subject(s)
Adrenal Cortex Hormones/therapeutic use , COVID-19/drug therapy , COVID-19/epidemiology , Prednisone/therapeutic use , Registries , SARS-CoV-2/pathogenicity , Sepsis/drug therapy , Adult , Age Factors , Aged , Aged, 80 and over , COVID-19/mortality , COVID-19/virology , Drug Administration Schedule , Female , Hospital Mortality/trends , Humans , Male , Middle Aged , SARS-CoV-2/growth & development , Sepsis/epidemiology , Sepsis/mortality , Sepsis/virology , Spain/epidemiology , Survival Analysis , Treatment Outcome
8.
PLoS One ; 17(1): e0261142, 2022.
Article in English | MEDLINE | ID: covidwho-1622334

ABSTRACT

BACKGROUND: The Covid-19 pandemic in the United Kingdom has seen two waves; the first starting in March 2020 and the second in late October 2020. It is not known whether outcomes for those admitted with severe Covid were different in the first and second waves. METHODS: The study population comprised all patients admitted to a 1,500-bed London Hospital Trust between March 2020 and March 2021, who tested positive for Covid-19 by PCR within 3-days of admissions. Primary outcome was death within 28-days of admission. Socio-demographics (age, sex, ethnicity), hypertension, diabetes, obesity, baseline physiological observations, CRP, neutrophil, chest x-ray abnormality, remdesivir and dexamethasone were incorporated as co-variates. Proportional subhazards models compared mortality risk between wave 1 and wave 2. Cox-proportional hazard model with propensity score adjustment were used to compare mortality in patients prescribed remdesivir and dexamethasone. RESULTS: There were 3,949 COVID-19 admissions, 3,195 hospital discharges and 733 deaths. There were notable differences in age, ethnicity, comorbidities, and admission disease severity between wave 1 and wave 2. Twenty-eight-day mortality was higher during wave 1 (26.1% versus 13.1%). Mortality risk adjusted for co-variates was significantly lower in wave 2 compared to wave 1 [adjSHR 0.49 (0.37, 0.65) p<0.001]. Analysis of treatment impact did not show statistically different effects of remdesivir [HR 0.84 (95%CI 0.65, 1.08), p = 0.17] or dexamethasone [HR 0.97 (95%CI 0.70, 1.35) p = 0.87]. CONCLUSION: There has been substantial improvements in COVID-19 mortality in the second wave, even accounting for demographics, comorbidity, and disease severity. Neither dexamethasone nor remdesivir appeared to be key explanatory factors, although there may be unmeasured confounding present.


Subject(s)
COVID-19/mortality , Hospital Mortality/trends , Inpatients/statistics & numerical data , Adenosine Monophosphate/analogs & derivatives , Adenosine Monophosphate/therapeutic use , Aged , Alanine/analogs & derivatives , Alanine/therapeutic use , COVID-19/drug therapy , Cohort Studies , Comorbidity/trends , Dexamethasone/therapeutic use , Female , Hospitalization/statistics & numerical data , Humans , London , Male , Middle Aged , Pandemics/statistics & numerical data , Patient Discharge/statistics & numerical data , Proportional Hazards Models
9.
BMC Endocr Disord ; 22(1): 13, 2022 Jan 06.
Article in English | MEDLINE | ID: covidwho-1613234

ABSTRACT

BACKGROUND: Research regarding the association between severe obesity and in-hospital mortality is inconsistent. We evaluated the impact of body mass index (BMI) levels on mortality in the medical wards. The analysis was performed separately before and during the COVID-19 pandemic. METHODS: We retrospectively retrieved data of adult patients admitted to the medical wards at the Mount Sinai Health System in New York City. The study was conducted between January 1, 2011, to March 23, 2021. Patients were divided into two sub-cohorts: pre-COVID-19 and during-COVID-19. Patients were then clustered into groups based on BMI ranges. A multivariate logistic regression analysis compared the mortality rate among the BMI groups, before and during the pandemic. RESULTS: Overall, 179,288 patients were admitted to the medical wards and had a recorded BMI measurement. 149,098 were admitted before the COVID-19 pandemic and 30,190 during the pandemic. Pre-pandemic, multivariate analysis showed a "J curve" between BMI and mortality. Severe obesity (BMI > 40) had an aOR of 0.8 (95% CI:0.7-1.0, p = 0.018) compared to the normal BMI group. In contrast, during the pandemic, the analysis showed a "U curve" between BMI and mortality. Severe obesity had an aOR of 1.7 (95% CI:1.3-2.4, p < 0.001) compared to the normal BMI group. CONCLUSIONS: Medical ward patients with severe obesity have a lower risk for mortality compared to patients with normal BMI. However, this does not apply during COVID-19, where obesity was a leading risk factor for mortality in the medical wards. It is important for the internal medicine physician to understand the intricacies of the association between obesity and medical ward mortality.


Subject(s)
Body Mass Index , COVID-19/mortality , Hospital Mortality/trends , Hospitalization/statistics & numerical data , Obesity/physiopathology , SARS-CoV-2/isolation & purification , Aged , COVID-19/epidemiology , COVID-19/pathology , COVID-19/virology , Case-Control Studies , Female , Humans , Male , Middle Aged , New York City/epidemiology , Prognosis , Retrospective Studies , Risk Factors , Survival Rate
10.
BMC Pulm Med ; 22(1): 6, 2022 Jan 06.
Article in English | MEDLINE | ID: covidwho-1605048

ABSTRACT

BACKGROUND: Mortality in severe COVID-19 pneumonia is associated with thrombo-inflammation. Corticosteroids are given to attenuate the inflammation, but they are associated with thrombosis. The aims of this study were to determine the risk of venous thromboembolism between no methylprednisolone and methylprednisolone (dose versus duration) and to evaluate any synergistic dose-dependent association of heparin and methylprednisolone to 30 days in hospital survival. METHODS: This was a secondary analysis of a retrospective cohort. Patients included in this study were ≥ 18 years of age and admitted for severe COVID-19 pneumonia between March and June 2020 in 13 hospitals in New Jersey, United States. A propensity score analysis between administration of methylprednisolone and no methylprednisolone was fitted for 11 variables and Youden Index Method was used to determine cut-off between low dose and high dose methylprednisolone. Multivariate cox regression was to assess risk. RESULTS: In 759 patients, the incidence of venous thromboembolism was 9% of patients who received methylprednisolone and 3% of patients who did not receive methylprednisolone with a [RR 2.92 (95% CI 1.54, 5.55 P < 0.0001)]. There was a higher incidence of mechanical ventilation in the methylprednisolone group. The median d-dimer between patients with venous thromboembolism was higher compared to those without (P < 0.0003). However, the d-dimer was not statistically significant between those who had venous thromboembolism between methylprednisolone and no methylprednisolone groups (P = 0.40). There was no higher risk in high dose versus low dose [RR = 0.524 (95% CI 0.26, 1.06 P 0.4)]; however, the risk for venous thromboembolism between methylprednisolone for > 7 days and ≤ 7 days was statistically significant (RR 5.46 95% CI 2.87, 10.34 P < 0.0001). Patients who received low dose methylprednisolone and therapeutic heparin had a trend towards higher risk of mortality compared to prophylactic heparin (HR 1.81 95% CI 0.994 to 3.294) (P = 0.0522). There was no difference in 30 days in hospital survival between high dose methylprednisolone with prophylactic or therapeutic heparin (HR 0.827 95% CI 0.514 to 1.33) (P = 0.4335). CONCLUSION: Methylprednisolone for > 7 days had a higher association of venous thromboembolism. There was no added benefit of therapeutic heparin to methylprednisolone on mechanically ventilated patients.


Subject(s)
COVID-19/mortality , Heparin/pharmacology , Methylprednisolone/pharmacology , Venous Thromboembolism/prevention & control , Anticoagulants/pharmacology , COVID-19/complications , Follow-Up Studies , Glucocorticoids/pharmacology , Hospital Mortality/trends , Humans , Incidence , Retrospective Studies , SARS-CoV-2 , Survival Rate/trends , Time Factors , United States/epidemiology , Venous Thromboembolism/epidemiology , Venous Thromboembolism/etiology
11.
Crit Care Med ; 50(1): e40-e51, 2022 01 01.
Article in English | MEDLINE | ID: covidwho-1584019

ABSTRACT

OBJECTIVES: Multicenter data on the characteristics and outcomes of children hospitalized with coronavirus disease 2019 are limited. Our objective was to describe the characteristics, ICU admissions, and outcomes among children hospitalized with coronavirus disease 2019 using Society of Critical Care Medicine Discovery Viral Infection and Respiratory Illness Universal Study: Coronavirus Disease 2019 registry. DESIGN: Retrospective study. SETTING: Society of Critical Care Medicine Viral Infection and Respiratory Illness Universal Study (Coronavirus Disease 2019) registry. PATIENTS: Children (< 18 yr) hospitalized with coronavirus disease 2019 at participating hospitals from February 2020 to January 2021. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The primary outcome was ICU admission. Secondary outcomes included hospital and ICU duration of stay and ICU, hospital, and 28-day mortality. A total of 874 children with coronavirus disease 2019 were reported to Viral Infection and Respiratory Illness Universal Study registry from 51 participating centers, majority in the United States. Median age was 8 years (interquartile range, 1.25-14 yr) with a male:female ratio of 1:2. A majority were non-Hispanic (492/874; 62.9%). Median body mass index (n = 817) was 19.4 kg/m2 (16-25.8 kg/m2), with 110 (13.4%) overweight and 300 (36.6%) obese. A majority (67%) presented with fever, and 43.2% had comorbidities. A total of 238 of 838 (28.2%) met the Centers for Disease Control and Prevention criteria for multisystem inflammatory syndrome in children, and 404 of 874 (46.2%) were admitted to the ICU. In multivariate logistic regression, age, fever, multisystem inflammatory syndrome in children, and pre-existing seizure disorder were independently associated with a greater odds of ICU admission. Hospital mortality was 16 of 874 (1.8%). Median (interquartile range) duration of ICU (n = 379) and hospital (n = 857) stay were 3.9 days (2-7.7 d) and 4 days (1.9-7.5 d), respectively. For patients with 28-day data, survival was 679 of 787, 86.3% with 13.4% lost to follow-up, and 0.3% deceased. CONCLUSIONS: In this observational, multicenter registry of children with coronavirus disease 2019, ICU admission was common. Older age, fever, multisystem inflammatory syndrome in children, and seizure disorder were independently associated with ICU admission, and mortality was lower among children than mortality reported in adults.


Subject(s)
COVID-19/complications , COVID-19/epidemiology , COVID-19/physiopathology , Child, Hospitalized/statistics & numerical data , Systemic Inflammatory Response Syndrome/epidemiology , Systemic Inflammatory Response Syndrome/physiopathology , Adolescent , Age Factors , Body Mass Index , COVID-19/mortality , Child , Child, Preschool , Comorbidity , Female , Hospital Mortality/trends , Humans , Infant , Intensive Care Units/statistics & numerical data , Logistic Models , Male , Retrospective Studies , SARS-CoV-2 , Systemic Inflammatory Response Syndrome/mortality
12.
Crit Care ; 25(1): 328, 2021 09 08.
Article in English | MEDLINE | ID: covidwho-1582035

ABSTRACT

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic caused by the SARS-Cov2 virus has become the greatest health and controversial issue for worldwide nations. It is associated with different clinical manifestations and a high mortality rate. Predicting mortality and identifying outcome predictors are crucial for COVID patients who are critically ill. Multivariate and machine learning methods may be used for developing prediction models and reduce the complexity of clinical phenotypes. METHODS: Multivariate predictive analysis was applied to 108 out of 250 clinical features, comorbidities, and blood markers captured at the admission time from a hospitalized cohort of patients (N = 250) with COVID-19. Inspired modification of partial least square (SIMPLS)-based model was developed to predict hospital mortality. Prediction accuracy was randomly assigned to training and validation sets. Predictive partition analysis was performed to obtain cutting value for either continuous or categorical variables. Latent class analysis (LCA) was carried to cluster the patients with COVID-19 to identify low- and high-risk patients. Principal component analysis and LCA were used to find a subgroup of survivors that tends to die. RESULTS: SIMPLS-based model was able to predict hospital mortality in patients with COVID-19 with moderate predictive power (Q2 = 0.24) and high accuracy (AUC > 0.85) through separating non-survivors from survivors developed using training and validation sets. This model was obtained by the 18 clinical and comorbidities predictors and 3 blood biochemical markers. Coronary artery disease, diabetes, Altered Mental Status, age > 65, and dementia were the topmost differentiating mortality predictors. CRP, prothrombin, and lactate were the most differentiating biochemical markers in the mortality prediction model. Clustering analysis identified high- and low-risk patients among COVID-19 survivors. CONCLUSIONS: An accurate COVID-19 mortality prediction model among hospitalized patients based on the clinical features and comorbidities may play a beneficial role in the clinical setting to better management of patients with COVID-19. The current study revealed the application of machine-learning-based approaches to predict hospital mortality in patients with COVID-19 and identification of most important predictors from clinical, comorbidities and blood biochemical variables as well as recognizing high- and low-risk COVID-19 survivors.


Subject(s)
COVID-19/mortality , Hospital Mortality/trends , Machine Learning/standards , Severity of Illness Index , COVID-19/epidemiology , Cohort Studies , Female , Humans , Male , Prognosis , Respiration, Artificial/statistics & numerical data , Risk Assessment/methods , Risk Factors
13.
PLoS One ; 16(12): e0261272, 2021.
Article in English | MEDLINE | ID: covidwho-1581756

ABSTRACT

BACKGROUND: First reported case of Severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) in Kazakhstan was identified in March 2020. Many specialized tertiary hospitals in Kazakhstan including National Research Cardiac Surgery Center (NRCSC) were re-organized to accept coronavirus disease 2019 (COVID-19) infected patients during summer months of 2020. Although many studies from worldwide reported their experience in treating patients with COVID-19, there are limited data available from the Central Asia countries. The aim of this study is to identify predictors of mortality associated with COVID-19 in NRCSC tertiary hospital in Nur-Sultan, Kazakhstan. METHODS: This is a retrospective cohort study of patients admitted to the NRCSC between June 1st-August 31st 2020 with COVID-19. Demographic, clinical and laboratory data were collected from electronic records. In-hospital mortality was assessed as an outcome. Patients were followed-up until in-hospital death or discharge from the hospital. Descriptive statistics and factors associated with mortality were assessed using univariate and multivariate logistic regression models. RESULTS: Two hundred thirty-nine admissions were recorded during the follow-up period. Mean age was 57 years and 61% were males. Median duration of stay at the hospital was 8 days and 34 (14%) patients died during the hospitalization. Non-survivors were more likely to be admitted later from the disease onset, with higher fever, lower oxygen saturation and increased respiratory rate compared to survivors. Leukocytosis, lymphopenia, anemia, elevated liver and kidney function tests, hypoproteinemia, elevated inflammatory markers (C-reactive protein (CRP), ferritin, and lactate dehydrogenase (LDH)) and coagulation tests (fibrinogen, D-dimer, international normalized ratio (INR), and activated partial thromboplastin time (aPTT)) at admission were associated with mortality. Age (OR 1.2, CI:1.01-1.43), respiratory rate (OR 1.38, CI: 1.07-1.77), and CRP (OR 1.39, CI: 1.04-1.87) were determined to be independent predictors of mortality. CONCLUSION: This study describes 14% mortality rate from COVID-19 in the tertiary hospital. Many abnormal clinical and laboratory variables at admission were associated with poor outcome. Age, respiratory rate and CRP were found to be independent predictors of mortality. Our finding would help healthcare providers to predict the risk factors associated with high risk of mortality. Further investigations involving large cohorts should be provided to support our findings.


Subject(s)
COVID-19/mortality , Hospital Mortality/trends , Adult , Age Factors , Aged , Biomarkers , COVID-19/epidemiology , Cohort Studies , Female , Hospitalization/statistics & numerical data , Hospitalization/trends , Humans , Kazakhstan/epidemiology , Male , Middle Aged , Prognosis , Respiratory Rate , Retrospective Studies , Risk Factors , SARS-CoV-2/pathogenicity
14.
Sci Rep ; 11(1): 23874, 2021 12 13.
Article in English | MEDLINE | ID: covidwho-1569277

ABSTRACT

The worsening progress of coronavirus disease 2019 (COVID-19) is attributed to the proinflammatory state, leading to increased mortality. Statin works with its anti-inflammatory effects and may attenuate the worsening of COVID-19. COVID-19 patients were retrospectively enrolled from two academic hospitals in Wuhan, China, from 01/26/2020 to 03/26/2020. Adjusted in-hospital mortality was compared between the statin and the non-statin group by CHD status using multivariable Cox regression model after propensity score matching. Our study included 3133 COVID-19 patients (median age: 62y, female: 49.8%), and 404 (12.9%) received statin. Compared with the non-statin group, the statin group was older, more likely to have comorbidities but with a lower level of inflammatory markers. The Statin group also had a lower adjusted mortality risk (6.44% vs. 10.88%; adjusted hazard ratio [HR] 0.47; 95% CI, 0.29-0.77). Subgroup analysis of CHD patients showed a similar result. Propensity score matching showed an overall 87% (HR, 0.13; 95% CI, 0.05-0.36) lower risk of in-hospital mortality for statin users than nonusers. Such survival benefit of statin was obvious both among CHD and non-CHD patients (HR = 0.30 [0.09-0.98]; HR = 0.23 [0.1-0.49], respectively). Statin use was associated with reduced in-hospital mortality in COVID-19. The benefit of statin was both prominent among CHD and non-CHD patients. These findings may further reemphasize the continuation of statins in patients with CHD during the COVID-19 era.


Subject(s)
COVID-19/drug therapy , Coronary Disease/drug therapy , Hydroxymethylglutaryl-CoA Reductase Inhibitors/administration & dosage , Inpatients/statistics & numerical data , Adult , Aged , Aged, 80 and over , COVID-19/mortality , China/epidemiology , Comorbidity , Coronary Disease/mortality , Female , Hospital Mortality/trends , Humans , Hydroxymethylglutaryl-CoA Reductase Inhibitors/therapeutic use , Male , Middle Aged , Retrospective Studies , Treatment Outcome
15.
PLoS One ; 16(11): e0260169, 2021.
Article in English | MEDLINE | ID: covidwho-1526694

ABSTRACT

INTRODUCTION: Coronavirus disease 2019 (COVID-19) has affected millions of people worldwide, and several sociodemographic variables, comorbidities and care variables have been associated with complications and mortality. OBJECTIVE: To identify the factors associated with admission to intensive care units (ICUs) and mortality in patients with COVID-19 from 4 clinics in Colombia. METHODS: This was a follow-up study of a cohort of patients diagnosed with COVID-19 between March and August 2020. Sociodemographic, clinical (Charlson comorbidity index and NEWS 2 score) and pharmacological variables were identified. Multivariate analyses were performed to identify variables associated with the risk of admission to the ICU and death (p<0.05). RESULTS: A total of 780 patients were analyzed, with a median age of 57.0 years; 61.2% were male. On admission, 54.9% were classified as severely ill, 65.3% were diagnosed with acute respiratory distress syndrome, 32.4% were admitted to the ICU, and 26.0% died. The factors associated with a greater likelihood of ICU admission were severe pneumonia (OR: 9.86; 95%CI:5.99-16.23), each 1-point increase in the NEWS 2 score (OR:1.09; 95%CI:1.002-1.19), history of ischemic heart disease (OR:3.24; 95%CI:1.16-9.00), and chronic obstructive pulmonary disease (OR:2.07; 95%CI:1.09-3.90). The risk of dying increased in those older than 65 years (OR:3.08; 95%CI:1.66-5.71), in patients with acute renal failure (OR:6.96; 95%CI:4.41-11.78), admitted to the ICU (OR:6.31; 95%CI:3.63-10.95), and for each 1-point increase in the Charlson comorbidity index (OR:1.16; 95%CI:1.002-1.35). CONCLUSIONS: Factors related to increasing the probability of requiring ICU care or dying in patients with COVID-19 were identified, facilitating the development of anticipatory intervention measures that favor comprehensive care and improve patient prognosis.


Subject(s)
COVID-19/epidemiology , Hospital Mortality/trends , Intensive Care Units/statistics & numerical data , Patient Admission/statistics & numerical data , Adult , Age Factors , Aged , Aged, 80 and over , COVID-19/mortality , COVID-19/therapy , Colombia , Comorbidity , Female , Humans , Male , Middle Aged , Myocardial Ischemia/epidemiology , Pulmonary Disease, Chronic Obstructive/epidemiology , Renal Insufficiency/epidemiology , Sex Factors
16.
PLoS One ; 16(11): e0257979, 2021.
Article in English | MEDLINE | ID: covidwho-1526683

ABSTRACT

Public health interventions such as social distancing and mask wearing decrease the incidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, but it is unclear whether they decrease the viral load of infected patients and whether changes in viral load impact mortality from coronavirus disease 2019 (COVID-19). We evaluated 6923 patients with COVID-19 at six New York City hospitals from March 15-May 14, 2020, corresponding with the implementation of public health interventions in March. We assessed changes in cycle threshold (CT) values from reverse transcription-polymerase chain reaction tests and in-hospital mortality and modeled the impact of viral load on mortality. Mean CT values increased between March and May, with the proportion of patients with high viral load decreasing from 47.7% to 7.8%. In-hospital mortality increased from 14.9% in March to 28.4% in early April, and then decreased to 8.7% by May. Patients with high viral loads had increased mortality compared to those with low viral loads (adjusted odds ratio 2.34). If viral load had not declined, an estimated 69 additional deaths would have occurred (5.8% higher mortality). SARS-CoV-2 viral load steadily declined among hospitalized patients in the setting of public health interventions, and this correlated with decreases in mortality.


Subject(s)
COVID-19/virology , Hospital Mortality/trends , Viral Load/statistics & numerical data , COVID-19/epidemiology , COVID-19/mortality , COVID-19 Nucleic Acid Testing/statistics & numerical data , Female , Humans , Male , New York , SARS-CoV-2/isolation & purification , SARS-CoV-2/pathogenicity
17.
Iran J Med Sci ; 46(6): 487-492, 2021 Nov.
Article in English | MEDLINE | ID: covidwho-1513425

ABSTRACT

The cumulative rate of death of acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has necessitated better recognizing the risk factors of the disease and the COVID-19-induced mortality. This cross-sectional study aimed to determine the potential risk factors that predict COVID-19-related mortality concentrating on the initial recorded laboratory tests. We extracted admission's medical records of a total of 136 deaths related to COVID-19 and 272 discharged adult inpatients (≥18 years old) related to four referral centers from February 24th to April 12th, 2020, in Isfahan, Iran, to figure out the relationship between the laboratory findings and mortality beyond demographic and clinical findings. We applied the independent sample t test and a chichi square test with SPSS software to compare the differences between the survivor and non-survivor patients. A P value of less than 0.05 was considered significant. Our results showed that greater length of hospitalization (P≤0.001), pre-existing chronic obstructive pulmonary disease (P≤0.001), high pulse rate, hypoxia (P≤0.001), and high computed tomography scan score (P<0.001), in addition to high values of some laboratory parameters, increase the risk of mortality. Moreover, high neutrophil/lymphocyte ratio (OR, 1.890; 95% CI, 1.074-3.325, P=0.027), increased creatinine levels (OR, 15.488; 95% CI, 0.801-299.479, P=0.07), and elevated potassium levels (OR, 13.400; 95% CI, 1.084-165.618, P=0.043) independently predicted in-hospital death related to COVID-19 infection. These results emphasized the potential role of impaired laboratory parameters for the prognosis of fatal outcomes in adult inpatients.


Subject(s)
COVID-19 , Hospital Mortality , Adult , COVID-19/mortality , COVID-19/therapy , Cross-Sectional Studies , Hospital Mortality/trends , Humans , Iran/epidemiology , Risk Factors
18.
PLoS One ; 16(10): e0258918, 2021.
Article in English | MEDLINE | ID: covidwho-1496517

ABSTRACT

The objective was to describe the clinical characteristics and outcomes of hospitalized COVID-19 patients during the two different epidemic periods. Prospective, observational, cohort study of hospitalized COVID-19. A total of 421 consecutive patients were included, 188 during the first period (March-May 2020) and 233 in the second wave (July-December 2020). Clinical, epidemiological, prognostic and therapeutic data were compared. Patients of the first outbreak were older and more comorbid, presented worse PaO2/FiO2 ratio and an increased creatinine and D-dimer levels at hospital admission. The hospital stay was shorter (14.5[8;29] vs 8[6;14] days, p<0.001), ICU admissions (31.9% vs 13.3%, p<0.001) and the number of patients who required mechanical ventilation (OR = 0.12 [0.05-10.26]; p<0.001) were reduced. There were no significant differences in hospital and 30-day after discharge mortality (adjusted HR = 1.56; p = 0.1056) or hospital readmissions. New treatments and clinical strategies appear to improve hospital length, ICU admissions and the requirement for mechanical ventilation. However, we did not observe differences in mortality or readmissions.


Subject(s)
COVID-19/epidemiology , COVID-19/mortality , COVID-19/therapy , Adult , Aged , Aged, 80 and over , Cohort Studies , Epidemics/statistics & numerical data , Female , Hospital Mortality/trends , Hospitalization/statistics & numerical data , Hospitalization/trends , Humans , Intensive Care Units/statistics & numerical data , Male , Middle Aged , Prognosis , Prospective Studies , Respiration, Artificial/mortality , Risk Factors , SARS-CoV-2/pathogenicity , Spain/epidemiology , Treatment Outcome
19.
Heart ; 108(6): 458-466, 2022 03.
Article in English | MEDLINE | ID: covidwho-1495503

ABSTRACT

OBJECTIVE: The initial data of the International Study on Acute Coronary Syndromes - ST Elevation Myocardial Infarction COVID-19 showed in Europe a remarkable reduction in primary percutaneous coronary intervention procedures and higher in-hospital mortality during the initial phase of the pandemic as compared with the prepandemic period. The aim of the current study was to provide the final results of the registry, subsequently extended outside Europe with a larger inclusion period (up to June 2020) and longer follow-up (up to 30 days). METHODS: This is a retrospective multicentre registry in 109 high-volume primary percutaneous coronary intervention (PPCI) centres from Europe, Latin America, South-East Asia and North Africa, enrolling 16 674 patients with ST segment elevation myocardial infarction (STEMI) undergoing PPPCI in March/June 2019 and 2020. The main study outcomes were the incidence of PPCI, delayed treatment (ischaemia time >12 hours and door-to-balloon >30 min), in-hospital and 30-day mortality. RESULTS: In 2020, during the pandemic, there was a significant reduction in PPCI as compared with 2019 (incidence rate ratio 0.843, 95% CI 0.825 to 0.861, p<0.0001). This reduction was significantly associated with age, being higher in older adults (>75 years) (p=0.015), and was not related to the peak of cases or deaths due to COVID-19. The heterogeneity among centres was high (p<0.001). Furthermore, the pandemic was associated with a significant increase in door-to-balloon time (40 (25-70) min vs 40 (25-64) min, p=0.01) and total ischaemia time (225 (135-410) min vs 196 (120-355) min, p<0.001), which may have contributed to the higher in-hospital (6.5% vs 5.3%, p<0.001) and 30-day (8% vs 6.5%, p=0.001) mortality observed during the pandemic. CONCLUSION: Percutaneous revascularisation for STEMI was significantly affected by the COVID-19 pandemic, with a 16% reduction in PPCI procedures, especially among older patients (about 20%), and longer delays to treatment, which may have contributed to the increased in-hospital and 30-day mortality during the pandemic. TRIAL REGISTRATION NUMBER: NCT04412655.


Subject(s)
COVID-19 , Cardiologists/trends , Percutaneous Coronary Intervention/trends , Practice Patterns, Physicians'/trends , ST Elevation Myocardial Infarction/therapy , Time-to-Treatment/trends , Aged , Female , Hospital Mortality/trends , Humans , Incidence , Male , Middle Aged , Percutaneous Coronary Intervention/adverse effects , Percutaneous Coronary Intervention/mortality , Registries , Retrospective Studies , Risk Assessment , Risk Factors , ST Elevation Myocardial Infarction/diagnosis , ST Elevation Myocardial Infarction/mortality , Time Factors , Treatment Outcome
20.
Lancet ; 398(10313): 1825-1835, 2021 11 13.
Article in English | MEDLINE | ID: covidwho-1492790

ABSTRACT

BACKGROUND: England's COVID-19 roadmap out of lockdown policy set out the timeline and conditions for the stepwise lifting of non-pharmaceutical interventions (NPIs) as vaccination roll-out continued, with step one starting on March 8, 2021. In this study, we assess the roadmap, the impact of the delta (B.1.617.2) variant of SARS-CoV-2, and potential future epidemic trajectories. METHODS: This mathematical modelling study was done to assess the UK Government's four-step process to easing lockdown restrictions in England, UK. We extended a previously described model of SARS-CoV-2 transmission to incorporate vaccination and multi-strain dynamics to explicitly capture the emergence of the delta variant. We calibrated the model to English surveillance data, including hospital admissions, hospital occupancy, seroprevalence data, and population-level PCR testing data using a Bayesian evidence synthesis framework, then modelled the potential trajectory of the epidemic for a range of different schedules for relaxing NPIs. We estimated the resulting number of daily infections and hospital admissions, and daily and cumulative deaths. Three scenarios spanning a range of optimistic to pessimistic vaccine effectiveness, waning natural immunity, and cross-protection from previous infections were investigated. We also considered three levels of mixing after the lifting of restrictions. FINDINGS: The roadmap policy was successful in offsetting the increased transmission resulting from lifting NPIs starting on March 8, 2021, with increasing population immunity through vaccination. However, because of the emergence of the delta variant, with an estimated transmission advantage of 76% (95% credible interval [95% CrI] 69-83) over alpha, fully lifting NPIs on June 21, 2021, as originally planned might have led to 3900 (95% CrI 1500-5700) peak daily hospital admissions under our central parameter scenario. Delaying until July 19, 2021, reduced peak hospital admissions by three fold to 1400 (95% CrI 700-1700) per day. There was substantial uncertainty in the epidemic trajectory, with particular sensitivity to the transmissibility of delta, level of mixing, and estimates of vaccine effectiveness. INTERPRETATION: Our findings show that the risk of a large wave of COVID-19 hospital admissions resulting from lifting NPIs can be substantially mitigated if the timing of NPI relaxation is carefully balanced against vaccination coverage. However, with the delta variant, it might not be possible to fully lift NPIs without a third wave of hospital admissions and deaths, even if vaccination coverage is high. Variants of concern, their transmissibility, vaccine uptake, and vaccine effectiveness must be carefully monitored as countries relax pandemic control measures. FUNDING: National Institute for Health Research, UK Medical Research Council, Wellcome Trust, and UK Foreign, Commonwealth and Development Office.


Subject(s)
COVID-19 Vaccines/administration & dosage , COVID-19/prevention & control , COVID-19/transmission , Communicable Disease Control/organization & administration , SARS-CoV-2 , Vaccination Coverage/organization & administration , COVID-19/epidemiology , COVID-19/mortality , England/epidemiology , Hospital Mortality/trends , Hospitalization/statistics & numerical data , Humans , Models, Theoretical , Patient Admission/statistics & numerical data
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