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1.
PLoS One ; 17(4): e0266750, 2022.
Article in English | MEDLINE | ID: covidwho-1785204

ABSTRACT

OBJECTIVES: Cardiovascular conditions were shown to be predictive of clinical deterioration in hospitalised patients with coronavirus disease 2019 (COVID-19). Whether this also holds for outpatients managed in primary care is yet unknown. The aim of this study was to determine the incremental value of cardiovascular vulnerability in predicting the risk of hospital referral in primary care COVID-19 outpatients. DESIGN: Analysis of anonymised routine care data extracted from electronic medical records from three large Dutch primary care registries. SETTING: Primary care. PARTICIPANTS: Consecutive adult patients seen in primary care for COVID-19 symptoms in the 'first wave' of COVID-19 infections (March 1 2020 to June 1 2020) and in the 'second wave' (June 1 2020 to April 15 2021) in the Netherlands. OUTCOME MEASURES: A multivariable logistic regression model was fitted to predict hospital referral within 90 days after first COVID-19 consultation in primary care. Data from the 'first wave' was used for derivation (n = 5,475 patients). Age, sex, the interaction between age and sex, and the number of cardiovascular conditions and/or diabetes (0, 1, or ≥2) were pre-specified as candidate predictors. This full model was (i) compared to a simple model including only age and sex and its interaction, and (ii) externally validated in COVID-19 patients during the 'second wave' (n = 16,693). RESULTS: The full model performed better than the simple model (likelihood ratio test p<0.001). Older male patients with multiple cardiovascular conditions and/or diabetes had the highest predicted risk of hospital referral, reaching risks above 15-20%, whereas on average this risk was 5.1%. The temporally validated c-statistic was 0.747 (95%CI 0.729-0.764) and the model showed good calibration upon validation. CONCLUSIONS: For patients with COVID-19 symptoms managed in primary care, the risk of hospital referral was on average 5.1%. Older, male and cardiovascular vulnerable COVID-19 patients are more at risk for hospital referral.


Subject(s)
COVID-19 , Clinical Deterioration , Adult , COVID-19/epidemiology , COVID-19/therapy , Hospitalization , Humans , Male , Primary Health Care , SARS-CoV-2
2.
Sci Rep ; 12(1): 2630, 2022 02 16.
Article in English | MEDLINE | ID: covidwho-1692561

ABSTRACT

The COVID-19 pandemic has been spreading worldwide since December 2019, presenting an urgent threat to global health. Due to the limited understanding of disease progression and of the risk factors for the disease, it is a clinical challenge to predict which hospitalized patients will deteriorate. Moreover, several studies suggested that taking early measures for treating patients at risk of deterioration could prevent or lessen condition worsening and the need for mechanical ventilation. We developed a predictive model for early identification of patients at risk for clinical deterioration by retrospective analysis of electronic health records of COVID-19 inpatients at the two largest medical centers in Israel. Our model employs machine learning methods and uses routine clinical features such as vital signs, lab measurements, demographics, and background disease. Deterioration was defined as a high NEWS2 score adjusted to COVID-19. In the prediction of deterioration within the next 7-30 h, the model achieved an area under the ROC curve of 0.84 and an area under the precision-recall curve of 0.74. In external validation on data from a different hospital, it achieved values of 0.76 and 0.7, respectively.


Subject(s)
COVID-19 , Clinical Deterioration , Machine Learning , Models, Statistical , Humans , Retrospective Studies , Software
3.
BMJ ; 376: e068576, 2022 02 17.
Article in English | MEDLINE | ID: covidwho-1691357

ABSTRACT

OBJECTIVE: To create and validate a simple and transferable machine learning model from electronic health record data to accurately predict clinical deterioration in patients with covid-19 across institutions, through use of a novel paradigm for model development and code sharing. DESIGN: Retrospective cohort study. SETTING: One US hospital during 2015-21 was used for model training and internal validation. External validation was conducted on patients admitted to hospital with covid-19 at 12 other US medical centers during 2020-21. PARTICIPANTS: 33 119 adults (≥18 years) admitted to hospital with respiratory distress or covid-19. MAIN OUTCOME MEASURES: An ensemble of linear models was trained on the development cohort to predict a composite outcome of clinical deterioration within the first five days of hospital admission, defined as in-hospital mortality or any of three treatments indicating severe illness: mechanical ventilation, heated high flow nasal cannula, or intravenous vasopressors. The model was based on nine clinical and personal characteristic variables selected from 2686 variables available in the electronic health record. Internal and external validation performance was measured using the area under the receiver operating characteristic curve (AUROC) and the expected calibration error-the difference between predicted risk and actual risk. Potential bed day savings were estimated by calculating how many bed days hospitals could save per patient if low risk patients identified by the model were discharged early. RESULTS: 9291 covid-19 related hospital admissions at 13 medical centers were used for model validation, of which 1510 (16.3%) were related to the primary outcome. When the model was applied to the internal validation cohort, it achieved an AUROC of 0.80 (95% confidence interval 0.77 to 0.84) and an expected calibration error of 0.01 (95% confidence interval 0.00 to 0.02). Performance was consistent when validated in the 12 external medical centers (AUROC range 0.77-0.84), across subgroups of sex, age, race, and ethnicity (AUROC range 0.78-0.84), and across quarters (AUROC range 0.73-0.83). Using the model to triage low risk patients could potentially save up to 7.8 bed days per patient resulting from early discharge. CONCLUSION: A model to predict clinical deterioration was developed rapidly in response to the covid-19 pandemic at a single hospital, was applied externally without the sharing of data, and performed well across multiple medical centers, patient subgroups, and time periods, showing its potential as a tool for use in optimizing healthcare resources.


Subject(s)
COVID-19/diagnosis , Clinical Decision Rules , Hospitalization/statistics & numerical data , Machine Learning , Risk Assessment/methods , Adolescent , Adult , Aged , Aged, 80 and over , Area Under Curve , Clinical Deterioration , Electronic Health Records , Female , Hospitals , Humans , Linear Models , Male , Middle Aged , Predictive Value of Tests , Prognosis , ROC Curve , Retrospective Studies , SARS-CoV-2 , Young Adult
4.
PLoS One ; 17(2): e0263922, 2022.
Article in English | MEDLINE | ID: covidwho-1686110

ABSTRACT

IMPORTANCE: When hospitals are at capacity, accurate deterioration indices could help identify low-risk patients as potential candidates for home care programs and alleviate hospital strain. To date, many existing deterioration indices are based entirely on structured data from the electronic health record (EHR) and ignore potentially useful information from other sources. OBJECTIVE: To improve the accuracy of existing deterioration indices by incorporating unstructured imaging data from chest radiographs. DESIGN, SETTING, AND PARTICIPANTS: Machine learning models were trained to predict deterioration of patients hospitalized with acute dyspnea using existing deterioration index scores and chest radiographs. Models were trained on hospitalized patients without coronavirus disease 2019 (COVID-19) and then subsequently tested on patients with COVID-19 between January 2020 and December 2020 at a single tertiary care center who had at least one radiograph taken within 48 hours of hospital admission. MAIN OUTCOMES AND MEASURES: Patient deterioration was defined as the need for invasive or non-invasive mechanical ventilation, heated high flow nasal cannula, IV vasopressor administration or in-hospital mortality at any time following admission. The EPIC deterioration index was augmented with unstructured data from chest radiographs to predict risk of deterioration. We compared discriminative performance of the models with and without incorporating chest radiographs using area under the receiver operating curve (AUROC), focusing on comparing the fraction and total patients identified as low risk at different negative predictive values (NPV). RESULTS: Data from 6278 hospitalizations were analyzed, including 5562 hospitalizations without COVID-19 (training cohort) and 716 with COVID-19 (216 in validation, 500 in held-out test cohort). At a NPV of 0.95, the best-performing image-augmented deterioration index identified 49 more (9.8%) individuals as low-risk compared to the deterioration index based on clinical data alone in the first 48 hours of admission. At a NPV of 0.9, the EPIC image-augmented deterioration index identified 26 more individuals (5.2%) as low-risk compared to the deterioration index based on clinical data alone in the first 48 hours of admission. CONCLUSION AND RELEVANCE: Augmenting existing deterioration indices with chest radiographs results in better identification of low-risk patients. The model augmentation strategy could be used in the future to incorporate other forms of unstructured data into existing disease models.


Subject(s)
Clinical Deterioration , Thorax/diagnostic imaging , Adolescent , Adult , Aged , Aged, 80 and over , COVID-19/pathology , COVID-19/virology , Dyspnea/pathology , Female , Hospitalization , Humans , Machine Learning , Male , Middle Aged , ROC Curve , Respiration, Artificial , Retrospective Studies , Risk Factors , SARS-CoV-2/isolation & purification , Young Adult
5.
Medicine (Baltimore) ; 100(44): e27545, 2021 Nov 05.
Article in English | MEDLINE | ID: covidwho-1570144

ABSTRACT

RATIONALE: This case report demonstrates the use of flourine-18 fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) to rule out Richter transformation (RT) as the cause of clinical deterioration in a patient with chronic lymphatic leukemia (CLL) and severe COVID-19. 18F-FDG PET/CT can be used to establish the diagnosis of RT in patients with CLL, but the use of 18F-FDG PET/CT to exclude RT as the cause of clinical deterioration in patients with CLL and severe COVID-19 has not previously been described. PATIENT CONCERNS: A 61-year-old male with CLL and COVID-19 developed increased dyspnea, malaise and fever during hospitalization for treatment of severe and prolonged COVID-19. DIAGNOSES: 18F-FDG PET/CT ruled out RT and revealed progression of opacities in both lungs consistent with exacerbation of severe acute respiratory syndrome coronavirus 2 pneumonia. INTERVENTIONS: 18F-FDG PET/CT imaging. OUTCOMES: The patient was discharged at day 52 without the need of supplemental oxygen, with normalized infection marks and continued care for CLL with venetoclax. LESSONS: 18F-FDG PET/CT ruled out RT as the cause of deteriorations in a patient with CLL and severe COVID-19, enabling directed care of exacerbation of severe acute respiratory syndrome coronavirus 2 pneumonia.


Subject(s)
COVID-19 , Clinical Deterioration , Leukemia, Lymphocytic, Chronic, B-Cell , Lymphoma, Large B-Cell, Diffuse , COVID-19/complications , Fluorodeoxyglucose F18 , Humans , Leukemia, Lymphocytic, Chronic, B-Cell/complications , Leukemia, Lymphocytic, Chronic, B-Cell/diagnostic imaging , Male , Middle Aged , Positron Emission Tomography Computed Tomography , Positron-Emission Tomography , Radiopharmaceuticals
6.
Diabetes Metab ; 48(1): 101307, 2022 01.
Article in English | MEDLINE | ID: covidwho-1549728

ABSTRACT

BACKGROUND AND OBJECTIVES: Type 2 diabetes mellitus (T2DM) patients with Coronavirus Disease 2019 (COVID-19) have poorer prognosis. Inconclusive evidence suggested dipeptidyl peptidase-4 inhibitors (DPP4i) might reduce inflammation and prevent Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) entry, hence further evaluation on DPP4i is needed. METHODS: 1214 Patients with T2DM were admitted with COVID-19 between 21st January 2020 and 31st January 2021 in Hong Kong. Exposure was DPP4i use within the 90 days prior to admission for COVID-19. Assessed outcomes included clinical deterioration, clinical improvement, low viral load, positive Immunoglobulin G (IgG) antibody, hyperinflammatory syndrome, proportion of IgG antibody, clinical status and length of hospitalization. Multivariable logistic and linear regression models were performed to estimate odds ratios (OR) and their 95% confidence intervals (CI) of event outcomes and continuous outcomes, respectively. RESULTS: DPP4i users (N = 107) was associated with lower odds of clinical deterioration (OR=0.71, 95%CI 0.54 to 0.93, P = 0.013), hyperinflammatory syndrome (OR=0.56, 95%CI 0.45 to 0.69, P < 0.001), invasive mechanical ventilation (OR=0.30, 95%CI 0.21 to 0.42, P < 0.001), reduced length of hospitalization (-4.82 days, 95%CI -6.80 to -2.84, P < 0.001), proportion of positive IgG antibody on day-3 (13% vs 8%, p = 0.007) and day-7 (41% vs 26%, P < 0.001), despite lack of association between DPP4i use and in-hospital mortality. CONCLUSION: DPP4i use was associated with reduced odds of clinical deterioration and hyperinflammatory syndrome. Prospective studies are warranted to elucidate the role of DPP4i in T2DM and COVID-19.


Subject(s)
COVID-19 , Clinical Deterioration , Diabetes Mellitus, Type 2 , Dipeptidyl-Peptidase IV Inhibitors , Diabetes Mellitus, Type 2/complications , Diabetes Mellitus, Type 2/drug therapy , Diabetes Mellitus, Type 2/epidemiology , Hong Kong/epidemiology , Humans , Propensity Score , SARS-CoV-2
7.
Drugs ; 81(18): 2081-2089, 2021 Dec.
Article in English | MEDLINE | ID: covidwho-1544607

ABSTRACT

SARS-CoV-2 infection causes COVID-19, which frequently leads to clinical deterioration and/or long-lasting morbidity. Academic and governmental experts throughout the USA met in 2021 to discuss the potential for use of fluvoxamine as early treatment of SARS-CoV-2 infection. Fluvoxamine is a selective serotonin reuptake inhibitor (SSRI) that is a strong sigma-1 receptor agonist, and this may effectively reduce cytokine production, preventing clinical deterioration. This repurposed psychiatric medication has a well-known safety record, is inexpensive, easy to use, and widely available, all of which are advantages during this global COVID-19 pandemic. At the meeting, experts reviewed the existing published literature on the use of fluvoxamine as experimental COVID-19 treatment, as well as prior research on the potential mechanisms for anti-inflammatory effects of fluvoxamine, including for other conditions including sepsis. Investigators shared current trials underway and existing gaps in knowledge. Two randomized controlled trials and one observational study examining the effect of fluvoxamine in COVID-19 treatment have found high efficacy. Four larger randomized clinical trials are currently underway, including three in the USA and Canada. More data are needed on dosing and mechanisms of effect; however, fluvoxamine appears to have substantial potential as a safe and widely available medication that could be repurposed to ameliorate serious COVID-19-related morbidity and mortality. As of April 2021, fluvoxamine was mentioned in the NIH COVID-19 treatment guidelines, although no recommendation is made for or against use. Available data may warrant clinician discussion of fluvoxamine as a treatment option for COVID-19, using shared decision making. Video Abstract.


Subject(s)
COVID-19/drug therapy , Fluvoxamine/therapeutic use , SARS-CoV-2/pathogenicity , Serotonin Uptake Inhibitors/therapeutic use , Animals , COVID-19/diagnosis , COVID-19/virology , Clinical Deterioration , Evidence-Based Medicine , Fluvoxamine/adverse effects , Host-Pathogen Interactions , Humans , Randomized Controlled Trials as Topic , Research Design , Serotonin Uptake Inhibitors/adverse effects , Treatment Outcome
8.
Intern Med J ; 52(4): 550-558, 2022 Apr.
Article in English | MEDLINE | ID: covidwho-1528380

ABSTRACT

BACKGROUND: Early recognition of severe COVID-19 is essential for timely patient triage. AIMS: To report clinical and laboratory findings and patient outcomes at a tertiary hospital in Melbourne, Australia. METHODS: This is a retrospective study of adult inpatients with COVID-19 admitted to Northern Health from March to September 2020. Data were extracted from electronic medical records. RESULTS: Key admission data were available for 182 patients (median age 67.0 years (interquartile range, 47.9-83.1); 51.1% female). Fifty-six (30.8%) were from residential care. One hundred and seventeen (64.3%) patients were assigned Goals of Patient Care (GOPC) A or B and 65 (35.7%) GOPC C or D. Comorbidities were present in 135 patients (74.2%). 63.2% of patients received antibiotics, 6.6% had antivirals, 45.6% received systemic glucocorticoid and 3.3% had tocilizumab. Fifty-six (30.8%) developed clinical deterioration (24 requiring ventilation, 21 receiving critical care, 34 died). Overall, inhospital clinical deterioration was significantly associated with older age (P < 0.001), history of diabetes (P = 0.038), lower lymphocyte count (P = 0.002) and platelet count (P = 0.004), higher neutrophil-to-lymphocyte ratio (P = 0.002), elevated fibrinogen (P = 0.004), higher serum ferritin (P = 0.027) and C-reactive protein (CRP; P = 0.002). The accuracy of the 4C Deterioration model was moderate, with an area under the curve (AUC) of 0.79 (95% confidence interval (CI), 0.68-0.90) compared with an AUC of 0.77 (95% CI, 0.76-0.78) in the original validation cohort. CONCLUSIONS: In the present study, high neutrophil-to-lymphocyte ratio, abnormal d-dimer, high serum CRP and ferritin appear to be useful prognostic markers.


Subject(s)
COVID-19 , Clinical Deterioration , Aged , Aged, 80 and over , Australia/epidemiology , C-Reactive Protein/metabolism , Female , Ferritins , Hospital Mortality , Humans , Inpatients , Male , Middle Aged , Retrospective Studies , Risk Factors , SARS-CoV-2 , Tertiary Care Centers
9.
BMC Cardiovasc Disord ; 21(1): 528, 2021 11 08.
Article in English | MEDLINE | ID: covidwho-1505900

ABSTRACT

BACKGROUND: The value of mechanical circulatory support (MCS) in cardiogenic shock, especially the combination of the ECMELLA approach (Impella combined with ECMO), remains controversial. CASE PRESENTATION: A previously healthy 33-year-old female patient was submitted to a local emergency department with a flu-like infection and febrile temperatures up to 39 °C. The patient was tested positive for type-A influenza, however negative for SARS-CoV-2. Despite escalated invasive ventilation, refractory hypercapnia (paCO2: 22 kPa) with severe respiratory acidosis (pH: 6.9) and a rising norepinephrine rate occurred within a few hours. Due to a Horovitz-Index < 100, out-of-centre veno-venous extracorporeal membrane oxygenation (vv-ECMO)-implantation was performed. A CT-scan done because of anisocoria revealed an extended dissection of the right vertebral artery. While the initial left ventricular function was normal, echocardiography revealed severe global hypokinesia. After angiographic exclusion of coronary artery stenoses, we geared up LV unloading by additional implantation of an Impella CP and expanded the vv-ECMO to a veno-venous-arterial ECMO (vva-ECMO). Clinically relevant bleeding from the punctured femoral arteries resulted in massive transfusion and was treated by vascular surgery later on. Under continued MCS, LVEF increased to approximately 40% 2 days after the initiation of ECMELLA. After weaning, the Impella CP was explanted at day 5 and the vva-ECMO was removed on day 9, respectively. The patient was discharged in an unaffected neurological condition to rehabilitation 25 days after the initial admission. CONCLUSIONS: This exceptional case exemplifies the importance of aggressive MCS in severe cardiogenic shock, which may be especially promising in younger patients with non-ischaemic cardiomyopathy and potentially reversible causes of cardiogenic shock. This case impressively demonstrates that especially young patients may achieve complete neurological restoration, even though the initial prognosis may appear unfavourable.


Subject(s)
Extracorporeal Membrane Oxygenation/methods , Heart-Assist Devices , Influenza A virus/isolation & purification , Influenza, Human , Respiration, Artificial/methods , Respiratory Insufficiency , Ventricular Dysfunction, Left , Adult , COVID-19/diagnosis , Clinical Deterioration , Critical Care/methods , Echocardiography/methods , Female , Heart Failure/physiopathology , Heart Failure/therapy , Humans , Influenza, Human/complications , Influenza, Human/diagnosis , Influenza, Human/physiopathology , Respiratory Insufficiency/etiology , Respiratory Insufficiency/physiopathology , Respiratory Insufficiency/therapy , SARS-CoV-2 , Serologic Tests/methods , Severity of Illness Index , Shock, Cardiogenic/etiology , Shock, Cardiogenic/physiopathology , Shock, Cardiogenic/therapy , Treatment Outcome , Ventricular Dysfunction, Left/etiology , Ventricular Dysfunction, Left/physiopathology , Ventricular Dysfunction, Left/therapy
11.
Rev Clin Esp (Barc) ; 222(1): 22-30, 2022 01.
Article in English | MEDLINE | ID: covidwho-1401809

ABSTRACT

INTRODUCTION: There is controversy regarding the best predictors of clinical deterioration in COVID-19. OBJECTIVE: This work aims to identify predictors of risk factors for deterioration in patients hospitalized due to COVID-19. METHODS DESIGN: Nested case-control study within a cohort. SETTING: 13 acute care centers of the Osakidetza-Basque Health Service. PARTICIPANTS: patients hospitalized for COVID-19 with clinical deterioration-defined as onset of severe ARDS, ICU admission, or death-were considered cases. Two controls were matched to each case based on age. Sociodemographic data; comorbidities; baseline treatment; symptoms; date of onset; previous consultations; and clinical, analytical, and radiological variables were collected. An explanatory model of clinical deterioration was created by means of conditional logistic regression. RESULTS: A total of 99 cases and 198 controls were included. According to the logistic regression analysis, the independent variables associated with clinical deterioration were: emergency department O2 saturation ≤90% (OR 16.6; 95%CI 4-68), pathological chest X-ray (OR 5.6; 95%CI 1.7-18.4), CRP > 100 mg/dL (OR 3.62; 95%CI 1.62-8), thrombocytopenia with <150,000 platelets (OR 4; 95%CI 1.84-8.6); and a medical history of acute myocardial infarction (OR 15.7; 95%CI, 3.29-75.09), COPD (OR 3.05; 95%CI 1.43-6.5), or HT (OR 2.21; 95%CI 1.11-4.4). The model's AUC was 0.86. On the univariate analysis, female sex and presence of dry cough and sore throat were associated with better clinical progress, but were not found to be significant on the multivariate analysis. CONCLUSION: The variables identified could be useful in clinical practice for the detection of patients at high risk of poor outcomes.


Subject(s)
COVID-19 , Clinical Deterioration , Case-Control Studies , Female , Humans , Risk Factors , SARS-CoV-2
12.
Viral Immunol ; 34(5): 336-341, 2021 06.
Article in English | MEDLINE | ID: covidwho-1343609

ABSTRACT

COVID-19 is spreading and ravaging all over the world, and the number of deaths is increasing day by day without downward trend. However, there is limited knowledge of pathogenesis on the deterioration of COVID-19 at present. In this study we aim to determine whether cytokine storm is really the chief culprit for the deterioration of COVID-19. The confirmed COVID-19 patients were divided into moderate group (n = 89), severe group (n = 37), and critical group (n = 41). Demographic data were collected and recorded on admission to ICU. Clinical data were obtained when moderate, severe, or critical COVID-19 was diagnosed, and then compared between groups. The proportion of enrolled COVID-19 patients was slightly higher among males (52.5%) than females (47.5%), with an average age of 64.87 years. The number of patients without comorbidities exceed one third (36.1%), and patients with 1, 2, 3, 4 kinds of comorbidities accounted for 23.0%, 23.0%, 13.1%, and 4.9%, respectively. IL-6, IL-10, TNF, and IFN-γ, including oxygenation index, sequential organ failure assessment score, white blood cell count, lymphocyte count, lymphocyte percentage, platelet, C-reaction protein, lactate dehydrogenase, creatine kinase isoenzyme, albumin, D-Dimer, and fibrinogen showed significant difference between groups. Some, but not all, cytokines and chemokines were involved in the deterioration of COVID-19, and thus cytokine storm maybe just the tip of the iceberg and should be used with caution to explain pathogenesis on the deterioration of COVID-19, which might be complex and related to inflammation, immunity, blood coagulation, and multiple organ functions. Future studies should focus on identification of specific signaling pathways and mechanisms after severe acute respiratory syndrome coronavirus 2 infections (IRB number: IRB-AF/SC-04/01.0).


Subject(s)
COVID-19/immunology , COVID-19/physiopathology , Clinical Deterioration , Cytokine Release Syndrome/immunology , Cytokines/blood , Adult , Aged , Aged, 80 and over , China/epidemiology , Comorbidity , Cytokines/immunology , Female , Humans , Inflammation , Male , Middle Aged , Retrospective Studies , Young Adult
14.
Crit Care ; 25(1): 226, 2021 06 30.
Article in English | MEDLINE | ID: covidwho-1286048

ABSTRACT

BACKGROUND: Rapid response systems aim to achieve a timely response to the deteriorating patient; however, the existing literature varies on whether timing of escalation directly affects patient outcomes. Prior studies have been limited to using 'decision to admit' to critical care, or arrival in the emergency department as 'time zero', rather than the onset of physiological deterioration. The aim of this study is to establish if duration of abnormal physiology prior to critical care admission ['Score to Door' (STD) time] impacts on patient outcomes. METHODS: A retrospective cross-sectional analysis of data from pooled electronic medical records from a multi-site academic hospital was performed. All unplanned adult admissions to critical care from the ward with persistent physiological derangement [defined as sustained high National Early Warning Score (NEWS) > / = 7 that did not decrease below 5] were eligible for inclusion. The primary outcome was critical care mortality. Secondary outcomes were length of critical care admission and hospital mortality. The impact of STD time was adjusted for patient factors (demographics, sickness severity, frailty, and co-morbidity) and logistic factors (timing of high NEWS, and out of hours status) utilising logistic and linear regression models. RESULTS: Six hundred and thirty-two patients were included over the 4-year study period, 16.3% died in critical care. STD time demonstrated a small but significant association with critical care mortality [adjusted odds ratio of 1.02 (95% CI 1.0-1.04, p = 0.01)]. It was also associated with hospital mortality (adjusted OR 1.02, 95% CI 1.0-1.04, p = 0.026), and critical care length of stay. Each hour from onset of physiological derangement increased critical care length of stay by 1.2%. STD time was influenced by the initial NEWS, but not by logistic factors such as out-of-hours status, or pre-existing patient factors such as co-morbidity or frailty. CONCLUSION: In a strictly defined population of high NEWS patients, the time from onset of sustained physiological derangement to critical care admission was associated with increased critical care and hospital mortality. If corroborated in further studies, this cohort definition could be utilised alongside the 'Score to Door' concept as a clinical indicator within rapid response systems.


Subject(s)
Clinical Deterioration , Hospital Administration/statistics & numerical data , Mortality/trends , Time-to-Treatment/standards , Aged , Cross-Sectional Studies , Female , Hospital Administration/standards , Humans , Intensive Care Units/organization & administration , Intensive Care Units/statistics & numerical data , Length of Stay/statistics & numerical data , Male , Middle Aged , Organ Dysfunction Scores , Regression Analysis , Retrospective Studies , Risk Assessment/methods , Risk Assessment/standards , Risk Assessment/statistics & numerical data , Time-to-Treatment/statistics & numerical data
15.
Life Sci ; 281: 119718, 2021 Sep 15.
Article in English | MEDLINE | ID: covidwho-1271709

ABSTRACT

AIMS: Hypoxia, a pathophysiological condition, is profound in several cardiopulmonary diseases (CPD). Every individual's lethality to a hypoxia state differs in terms of hypoxia exposure time, dosage units and dependent on the individual's genetic makeup. Most of the proposed markers for CPD were generally aim to distinguish disease samples from normal samples. Although, as per the 2018 GOLD guidelines, clinically useful biomarkers for several cardio pulmonary disease patients in stable condition have yet to be identified. We attempt to address these key issues through the identification of Dynamic Network Biomarkers (DNB) to detect hypoxia induced early warning signals of CPD before the catastrophic deterioration. MATERIALS AND METHODS: The human microvascular endothelial tissues microarray datasets (GSE11341) of lung and cardiac expose to hypoxia (1% O2) for 3, 24 and 48 h were retrieved from the public repository. The time dependent differentially expressed genes were subjected to tissue specificity and promoter analysis to filtrate the noise levels in the networks and to dissect the tissue specific hypoxia induced genes. These filtered out genes were used to construct the dynamic segmentation networks. The hypoxia induced dynamic differentially expressed genes were validated in the lung and heart tissues of male rats. These rats were exposed to hypobaric hypoxia (simulated altitude of 25,000 or PO2 - 282 mm of Hg) progressively for 3, 24 and 48 h. KEY FINDINGS: To identify the temporal key genes regulated in hypoxia, we ranked the dominant genes based on their consolidated topological features from tissue specific networks, time dependent networks and dynamic networks. Overall topological ranking described VEGFA as a single node dynamic hub and strongly communicated with tissue specific genes to carry forward their tissue specific information. We named this type of VEGFAcentric dynamic networks as "V-DNBs". As a proof of principle, our methodology helped us to identify the V-DNBs specific for lung and cardiac tissues namely V-DNBL and V-DNBC respectively. SIGNIFICANCE: Our experimental studies identified VEGFA, SLC2A3, ADM and ENO2 as the minimum and sufficient candidates of V-DNBL. The dynamic expression patterns could be readily exploited to capture the pre disease state of hypoxia induced pulmonary vascular remodelling. Whereas in V-DNBC the minimum and sufficient candidates are VEGFA, SCL2A3, ADM, NDRG1, ENO2 and BHLHE40. The time dependent single node expansion indicates V-DNBC could also be the pre disease state pathological hallmark for hypoxia-associated cardiovascular remodelling. The network cross-talk and expression pattern between V-DNBL and V-DNBC are completely distinct. On the other hand, the great clinical advantage of V-DNBs for pre disease predictions, a set of samples during the healthy condition should suffice. Future clinical studies might further shed light on the predictive power of V-DNBs as prognostic and diagnostic biomarkers for CPD.


Subject(s)
Heart Diseases/metabolism , Hypoxia/metabolism , Lung Diseases/metabolism , Vascular Endothelial Growth Factor A/metabolism , Animals , Biomarkers/metabolism , Clinical Deterioration , Gene Expression Regulation , Heart Diseases/etiology , Heart Diseases/pathology , Humans , Hypoxia/complications , Hypoxia/genetics , Lung Diseases/etiology , Lung Diseases/pathology , Male , Rats , Rats, Sprague-Dawley
16.
Chest ; 160(1): e39-e44, 2021 07.
Article in English | MEDLINE | ID: covidwho-1291398

ABSTRACT

CASE PRESENTATION: A 65-year-old man presented with shortness of breath, gradually worsening for the previous 2 weeks, associated with dry cough, sore throat, and diarrhea. He denied fever, chills, chest pain, abdominal pain, nausea, or vomiting. He did not have any sick contacts or travel history outside of Michigan. His medical history included hypertension, diabetes mellitus, chronic kidney disease, morbid obesity, paroxysmal atrial fibrillation, and tobacco use. He was taking amiodarone, carvedilol, furosemide, pregabalin, and insulin. The patient appeared to be in mild respiratory distress. He was afebrile and had saturation at 93% on 3 L of oxygen, heart rate of 105 beats/min, BP of 145/99 mm Hg, and respiratory rate of 18 breaths/min. On auscultation, there were crackles on bilateral lung bases and chronic bilateral leg swelling with hyperpigmented changes. His WBC count was 6.0 K/cumm (3.5 to 10.6 K/cumm) with absolute lymphocyte count 0.7 K/cumm (1.0 to 3.8 K/cumm); serum creatinine was 2.81 mg/dL (0.7 to 1.3 mg/dL). He had elevated inflammatory markers (serum ferritin, C-reactive protein, lactate dehydrogenase, D-dimer, and creatinine phosphokinase). Chest radiography showed bilateral pulmonary opacities that were suggestive of multifocal pneumonia (Fig 1). Nasopharyngeal swab for SARS-CoV-2 was positive. Therapy was started with ceftriaxone, doxycycline, hydroxychloroquine, and methylprednisolone 1 mg/kg IV for 3 days. By day 3 of hospitalization, he required endotracheal intubation, vasopressor support, and continuous renal replacement. Blood cultures were negative; respiratory cultures revealed only normal oral flora, so antibiotic therapy was discontinued. On day 10, WBC count increased to 28 K/cumm, and chest radiography showed persistent bilateral opacities with left lower lobe consolidation. Repeat respiratory cultures grew Pseudomonas aeruginosa (Table 1). Antibiotic therapy with IV meropenem was started. His condition steadily improved; eventually by day 20, he was off vasopressors and was extubated. However, on day 23, he experienced significant hemoptysis that required reintubation and vasopressor support.


Subject(s)
Aspergillus niger/isolation & purification , COVID-19 , Hemoptysis , Invasive Pulmonary Aspergillosis , Pseudomonas aeruginosa/isolation & purification , SARS-CoV-2/isolation & purification , Superinfection , Voriconazole/administration & dosage , Aged , Antifungal Agents/administration & dosage , COVID-19/complications , COVID-19/diagnosis , COVID-19/physiopathology , COVID-19/therapy , Clinical Deterioration , Critical Illness/therapy , Critical Pathways , Diagnosis, Differential , Hemoptysis/diagnosis , Hemoptysis/etiology , Hemoptysis/therapy , Humans , Invasive Pulmonary Aspergillosis/complications , Invasive Pulmonary Aspergillosis/diagnosis , Invasive Pulmonary Aspergillosis/physiopathology , Lung/diagnostic imaging , Lung/physiopathology , Male , Radiography, Thoracic/methods , Respiration, Artificial/methods , Superinfection/diagnosis , Superinfection/microbiology , Superinfection/physiopathology , Superinfection/therapy , Tomography, X-Ray Computed/methods , Treatment Outcome
17.
Cells ; 10(6)2021 05 23.
Article in English | MEDLINE | ID: covidwho-1243957

ABSTRACT

The dysregulation of both the innate and adaptive responses to SARS-CoV-2 have an impact on the course of COVID-19, and play a role in the clinical outcome of the disease. Here, we performed a comprehensive analysis of peripheral blood lymphocyte subpopulations in 82 patients with COVID-19, including 31 patients with a critical course of the disease. In COVID-19 patients who required hospitalization we analyzed T cell subsets, including Treg cells, as well as TCRα/ß and γ/δ, NK cells, and B cells, during the first two weeks after admission to hospital due to the SARS-CoV-2 infection, with marked reductions in leukocytes subpopulations, especially in critically ill COVID-19 patients. We showed decreased levels of Th, Ts cells, Treg cells (both naïve and induced), TCRα/ß and γ/δ cells, as well as CD16+CD56+NK cells in ICU compared to non-ICU COVID-19 patients. We observed impaired function of T and NK cells in critically ill COVID-19 patients with extremely low levels of secreted cytokines. We found that the IL-2/INFγ ratio was the strongest indicator of a critical course of COVID-19, and was associated with fatal outcomes. Our findings showed markedly impaired innate and adaptive responses in critically ill COVID-19 patients, and suggest that the immunosuppressive state in the case of a critical course of SARS-CoV-2 infection might reflect subsequent clinical deterioration and predict a fatal outcome.


Subject(s)
COVID-19/immunology , Immune Tolerance , Lymphocyte Subsets/immunology , SARS-CoV-2/immunology , Severity of Illness Index , Adaptive Immunity , Aged , COVID-19/diagnosis , COVID-19/mortality , COVID-19/virology , Clinical Deterioration , Critical Illness , Female , Hospital Mortality , Hospitalization , Humans , Immunity, Innate , Leukocyte Count , Male , Middle Aged , Poland/epidemiology , Prospective Studies , Risk Assessment/methods
18.
Am J Emerg Med ; 49: 76-79, 2021 Nov.
Article in English | MEDLINE | ID: covidwho-1240142

ABSTRACT

BACKGROUND: The COVID-19 outbreak has put an unprecedented strain on Emergency Departments (EDs) and other critical care resources. Early detection of patients that are at high risk of clinical deterioration and require intensive monitoring, is key in ED evaluation and disposition. A rapid and easy risk-stratification tool could aid clinicians in early decision making. The Shock Index (SI: heart rate/systolic blood pressure) proved useful in detecting hemodynamic instability in sepsis and myocardial infarction patients. In this study we aim to determine whether SI is discriminative for ICU admission and in-hospital mortality in COVID-19 patients. METHODS: Retrospective, observational, single-center study. All patients ≥18 years old who were hospitalized with COVID-19 (defined as: positive result on reverse transcription polymerase chain reaction (PCR) test) between March 1, 2020 and December 31, 2020 were included for analysis. Data were collected from electronic medical patient records and stored in a protected database. ED shock index was calculated and analyzed for its discriminative value on in-hospital mortality and ICU admission by a ROC curve analysis. RESULTS: In total, 411 patients were included. Of all patients 249 (61%) were male. ICU admission was observed in 92 patients (22%). Of these, 37 patients (40%) died in the ICU. Total in-hospital mortality was 28% (114 patients). For in-hospital mortality the optimal cut-off SI ≥ 0.86 was not discriminative (AUC 0.49 (95% CI: 0.43-0.56)), with a sensitivity of 12.3% and specificity of 93.6%. For ICU admission the optimal cut-off SI ≥ 0.57 was also not discriminative (AUC 0.56 (95% CI: 0.49-0.62)), with a sensitivity of 78.3% and a specificity of 34.2%. CONCLUSION: In this cohort of patients hospitalized with COVID-19, SI measured at ED presentation was not discriminative for ICU admission and was not useful for early identification of patients at risk of clinical deterioration.


Subject(s)
COVID-19/diagnosis , Clinical Deterioration , Shock/classification , Triage , Adult , Aged , Aged, 80 and over , COVID-19/mortality , Emergency Service, Hospital/statistics & numerical data , Female , Hospital Mortality/trends , Humans , Intensive Care Units/statistics & numerical data , Male , Middle Aged , Netherlands , Organ Dysfunction Scores , ROC Curve , Retrospective Studies , Risk Assessment , Shock/mortality , Young Adult
19.
J Biomed Inform ; 118: 103794, 2021 06.
Article in English | MEDLINE | ID: covidwho-1209791

ABSTRACT

From early March through mid-May 2020, the COVID-19 pandemic overwhelmed hospitals in New York City. In anticipation of ventilator shortages and limited ICU bed capacity, hospital operations prioritized the development of prognostic tools to predict clinical deterioration. However, early experience from frontline physicians observed that some patients developed unanticipated deterioration after having relatively stable periods, attesting to the uncertainty of clinical trajectories among hospitalized patients with COVID-19. Prediction tools that incorporate clinical variables at one time-point, usually on hospital presentation, are suboptimal for patients with dynamic changes and evolving clinical trajectories. Therefore, our study team developed a machine-learning algorithm to predict clinical deterioration among hospitalized COVID-19 patients by extracting clinically meaningful features from complex longitudinal laboratory and vital sign values during the early period of hospitalization with an emphasis on informative missing-ness. To incorporate the evolution of the disease and clinical practice over the course of the pandemic, we utilized a time-dependent cross-validation strategy for model development. Finally, we validated our prediction model on an external validation cohort of COVID-19 patients served in a demographically distinct population from the training cohort. The main finding of our study is the identification of risk profiles of early, late and no clinical deterioration during the course of hospitalization. While risk prediction models that include simple predictors at ED presentation and clinical judgement are able to identify any deterioration vs. no deterioration, our methodology is able to isolate a particular risk group that remain stable initially but deteriorate at a later stage of the course of hospitalization. We demonstrate the superior predictive performance with the utilization of laboratory and vital sign data during the early period of hospitalization compared to the utilization of data at presentation alone. Our results will allow efficient hospital resource allocation and will motivate research in understanding the late deterioration risk group.


Subject(s)
COVID-19/diagnosis , Clinical Deterioration , Computer Simulation , Aged , Female , Hospitalization , Hospitals , Humans , Male , New York City , Pandemics , ROC Curve , Retrospective Studies , Risk Assessment
20.
Medicine (Baltimore) ; 100(15): e25255, 2021 Apr 16.
Article in English | MEDLINE | ID: covidwho-1180670

ABSTRACT

RATIONALE: Fibrinolysis shutdown associated with severe thrombotic complications is a recently recognized syndrome that was previously seldom investigated in patients with severe severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. It presents a unique therapeutic dilemma, as anticoagulation with heparin alone is insufficient to address the imbalance in fibrinolysis. And while the use of fibrinolytic agents could limit the disease severity, it is often associated with bleeding complications. There is a need for biomarkers that will guide the timely stratification of patients into those who may benefit from both anticoagulant and fibrinolytic therapies. PATIENT CONCERNS: All 3 patients presented with shortness of breath along with comorbidities predisposing them to severe SARS-CoV-2 infection. One patient (Patient 3) also suffered from bilateral deep venous thrombosis. DIAGNOSES: All 3 patients tested positive for SARS-CoV-2 RNA by reverse transcription polymerase chain reaction (RT-PCR) and were eventually diagnosed with respiratory failure necessitating intubation. INTERVENTIONS: All 3 patients required mechanical ventilation support, 2 of which also required renal replacement therapy. All 3 patients were also placed on anticoagulation therapy. OUTCOMES: In Patients 1 and 2, the initial D-dimer levels of 0.97 µg/ml fibrinogen equivalent units (FEU) and 0.83 µg/ml FEU were only slightly elevated (normal <0.50 µg/ml FEU). They developed rising D-dimer levels to a peak of 13.21 µg/ml FEU and >20.0 µg/ml FEU, respectively, which dropped to 1.34 µg/ml FEU 8 days later in Patient 1 and to 2.94 µg/ml on hospital day 13 in Patient 2. In Patient 3, the D-dimer level on admission was found to be elevated to >20.00 µg/ml FEU together with imaging evidence of thrombosis. And although he received therapeutic heparin infusion, he still developed pulmonary embolism (PE) and his D-dimer level declined to 5.91 µg/ml FEU. Despite "improvement" in their D-dimer levels, all 3 patients succumbed to multi-system organ failure. On postmortem examination, numerous arterial and venous thromboses of varying ages, many consisting primarily of fibrin, were identified in the lungs of all patients. LESSONS: High D-dimer levels, with subsequent downtrend correlating with clinical deterioration, seems to be an indicator of fibrinolysis suppression. These findings can help form a hypothesis, as larger cohorts are necessary to demonstrate their reproducibility.


Subject(s)
Anticoagulants/therapeutic use , COVID-19 , Fibrin Fibrinogen Degradation Products/analysis , Multiple Organ Failure , Thrombolytic Therapy/methods , Autopsy/methods , COVID-19/blood , COVID-19/complications , COVID-19/physiopathology , COVID-19/therapy , Clinical Deterioration , Female , Fibrinolysis , Humans , Male , Middle Aged , Multiple Organ Failure/blood , Multiple Organ Failure/diagnosis , Multiple Organ Failure/etiology , Predictive Value of Tests , Prognosis , Renal Replacement Therapy/methods , Respiration, Artificial/methods , SARS-CoV-2/isolation & purification , Severity of Illness Index , Venous Thrombosis/blood , Venous Thrombosis/complications , Venous Thrombosis/diagnosis
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