Dataset Information

Triage process for the assessment of coronavirus disease 2019-positive patients with cancer: The ONCOVID prospective study.

ABSTRACT:

Background

Patients with cancer are considered at high risk for the novel respiratory illness coronavirus disease 2019 (COVID-19). General measures to keep COVID-19-free cancer divisions have been adopted worldwide. The objective of this study was to evaluate the efficacy of triage to identify COVID-19 among patients with cancer.

Methods

From March 20 to April 17, 2020, data were collected from patients who were treated or followed at the authors' institution in a prospective clinical trial. The primary endpoint was to estimate the cumulative incidence of COVID-19-positive patients who were identified using a triage process through the aid of medical and patient questionnaires. Based on a diagnostic algorithm, patients with suspect symptoms underwent an infectious disease specialist's evaluation and a COVID-19 swab. Serologic tests were proposed for patients who had symptoms or altered laboratory tests that did not fall into the diagnostic algorithm but were suspicious for COVID-19.

Results

Overall, 562 patients were enrolled. Six patients (1%) were diagnosed with COVID-19, of whom 4 (67%) had the disease detected through telehealth triage, and 2 patients (33%) without suspect symptoms at triage had the disease detected later. Seventy-one patients (13%) had suspect symptoms and/or altered laboratory tests that were not included in the diagnostic algorithm and, of these, 47 patients (73%) underwent testing for severe acute respiratory syndrome coronavirus 2 antibody: 6 (13%) were positive for IgG (n = 5) or for both IgM and IgG (n = 1), and antibody tests were negative in the remaining 41 patients.

Conclusions

The triage process had a positive effect on the detection of COVID-19 in patients with cancer. Telehealth triage was helpful in detecting suspect patients and to keep a COVID-19-free cancer center. The overall incidence of COVID-19 diagnosis (1%) and antibody positivity (13%) in patients with suspect symptoms was similar to that observed in the general population.

SUBMITTER: Indini A

PROVIDER: S-EPMC7753308 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Publications

Triage process for the assessment of coronavirus disease 2019-positive patients with cancer: The ONCOVID prospective study.

Indini Alice A Cattaneo Monica M Ghidini Michele M Rijavec Erika E Bareggi Claudia C Galassi Barbara B Gambini Donatella D Ceriani Rosalia R Ceriotti Ferruccio F Berti Emilio E Grossi Francesco F

Cancer 20201203 7

<h4>Background</h4>Patients with cancer are considered at high risk for the novel respiratory illness coronavirus disease 2019 (COVID-19). General measures to keep COVID-19-free cancer divisions have been adopted worldwide. The objective of this study was to evaluate the efficacy of triage to identify COVID-19 among patients with cancer.<h4>Methods</h4>From March 20 to April 17, 2020, data were collected from patients who were treated or followed at the authors' institution in a prospective clin ...[more]

PMID: 33270908

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Project description:ObjectivesTriaging patients at admission to determine subsequent deterioration risk can be difficult. This is especially true of coronavirus disease 2019 patients, some of whom experience significant physiologic deterioration due to dysregulated immune response following admission. A well-established acuity measure, the Rothman Index, is evaluated for stratification of patients at admission into high or low risk of subsequent deterioration.DesignMulticenter retrospective study.SettingOne academic medical center in Connecticut, and three community hospitals in Connecticut and Maryland.PatientsThree thousand four hundred ninety-nine coronavirus disease 2019 and 14,658 noncoronavirus disease 2019 adult patients admitted to a medical service between January 1, 2020, and September 15, 2020.InterventionsNone.Measurements and main resultsPerformance of the Rothman Index at admission to predict in-hospital mortality or ICU utilization for both general medical and coronavirus disease 2019 populations was evaluated using the area under the curve. Precision and recall for mortality prediction were calculated, high- and low-risk thresholds were determined, and patients meeting threshold criteria were characterized. The Rothman Index at admission has good to excellent discriminatory performance for in-hospital mortality in the coronavirus disease 2019 (area under the curve, 0.81-0.84) and noncoronavirus disease 2019 (area under the curve, 0.90-0.92) populations. We show that for a given admission acuity, the risk of deterioration for coronavirus disease 2019 patients is significantly higher than for noncoronavirus disease 2019 patients. At admission, Rothman Index-based thresholds segregate the majority of patients into either high- or low-risk groups; high-risk groups have mortality rates of 34-45% (coronavirus disease 2019) and 17-25% (noncoronavirus disease 2019), whereas low-risk groups have mortality rates of 2-5% (coronavirus disease 2019) and 0.2-0.4% (noncoronavirus disease 2019). Similarly large differences in ICU utilization are also found.ConclusionsAcuity level at admission may support rapid and effective risk triage. Notably, in-hospital mortality risk associated with a given acuity at admission is significantly higher for coronavirus disease 2019 patients than for noncoronavirus disease 2019 patients. This insight may help physicians more effectively triage coronavirus disease 2019 patients, guiding level of care decisions and resource allocation.

Project description:BackgroundCoronavirus disease 2019 (COVID-19) is sweeping the globe. Despite multiple case-series, actionable knowledge to tailor decision-making proactively is missing.Research questionCan a statistical model accurately predict infection with COVID-19?Study design and methodsWe developed a prospective registry of all patients tested for COVID-19 in Cleveland Clinic to create individualized risk prediction models. We focus here on the likelihood of a positive nasal or oropharyngeal COVID-19 test. A least absolute shrinkage and selection operator logistic regression algorithm was constructed that removed variables that were not contributing to the model's cross-validated concordance index. After external validation in a temporally and geographically distinct cohort, the statistical prediction model was illustrated as a nomogram and deployed in an online risk calculator.ResultsIn the development cohort, 11,672 patients fulfilled study criteria, including 818 patients (7.0%) who tested positive for COVID-19; in the validation cohort, 2295 patients fulfilled criteria, including 290 patients who tested positive for COVID-19. Male, African American, older patients, and those with known COVID-19 exposure were at higher risk of being positive for COVID-19. Risk was reduced in those who had pneumococcal polysaccharide or influenza vaccine or who were on melatonin, paroxetine, or carvedilol. Our model had favorable discrimination (c-statistic = 0.863 in the development cohort and 0.840 in the validation cohort) and calibration. We present sensitivity, specificity, negative predictive value, and positive predictive value at different prediction cutoff points. The calculator is freely available at https://riskcalc.org/COVID19.InterpretationPrediction of a COVID-19 positive test is possible and could help direct health-care resources. We demonstrate relevance of age, race, sex, and socioeconomic characteristics in COVID-19 susceptibility and suggest a potential modifying role of certain common vaccinations and drugs that have been identified in drug-repurposing studies.

Project description:Importance:Severe acute respiratory syndrome coronavirus 2 has caused a global outbreak of coronavirus disease 2019 (COVID-19). Severe acute respiratory syndrome coronavirus 2 binds angiotensin-converting enzyme 2 of the rennin-angiotensin system, resulting in hypokalemia. Objective:To investigate the prevalence, causes, and clinical implications of hypokalemia, including its possible association with treatment outcomes, among patients with COVID-19. Design, Setting, and Participants:This cohort study was conducted at Wenzhou Central Hospital and Sixth People's Hospital of Wenzhou, Wenzhou, China, from January 11, 2020, to February 15, 2020. Participants included patients who received a diagnosis of COVID-19 according to the criteria issued by the Chinese Health Bureau and were admitted to the hospital. The patients were classified as having severe hypokalemia (plasma potassium <3 mmol/L), hypokalemia (plasma potassium 3-3.5 mmol/L), and normokalemia (plasma potassium >3.5 mmol/L). The clinical features, therapy, and outcomes were compared between the 3 groups. Data analysis was conducted in March 2020. Interventions:The patients were given general support and antiviral therapy. Their epidemiological and clinical features were collected. Main Outcomes and Measures:The prevalence of hypokalemia and response to treatment with potassium supplements were measured by analyzing plasma and urine potassium levels. Results:One hundred seventy-five patients (87 female patients [50%]; mean [SD] age, 45?[14] years) were classified as having severe hypokalemia (31 patients [18%]), hypokalemia (64 patients [37%]), and normokalemia (80 patients [46%]). Patients with severe hypokalemia had statistically significantly higher body temperature (mean [SD], 37.6 °C [0.9 °C]) than the patients with hypokalemia (mean [SD],?37.2 °C?[0.7 °C]; difference, 0.4 °C; 95% CI, 0.2-0.6 °C; P?=?.02) and the patients with normokalemia (mean [SD],?37.1 °C?[0.8 °C]; difference, 0.5 °C; 95% CI, 0.3-0.7 °C; P?=?.005). Patients with higher levels of hypokalemia also had higher creatine kinase levels (severe hypokalemia, mean [SD], 200?[257] U/L [median, 113 U/L; interquartile range {IQR}, 61-242 U/L]; hypokalemia, mean [SD], 97?[85] U/L; and normokalemia, mean [SD], 82?[57] U/L), higher creatine kinase-MB fraction (severe hypokalemia, mean [SD], 32?[39] U/L [median, 14 U/L; IQR, 11-36 U/L]; hypokalemia, mean [SD], 18?[15] U/L; and normokalemia, mean [SD], 15?[8] U/L), higher lactate dehydrogenase levels (mean [SD], severe hypokalemia, 256?[88] U/L; hypokalemia, 212?[59] U/L; and normokalemia, 199?[61] U/L), and higher C-reactive protein levels (severe hypokalemia, mean [SD], 29?[23] mg/L; hypokalemia, mean [SD], 18?[20] mg/L [median, 12, mg/L; IQR, 4-25 mg/L]; and normokalemia, mean [SD], 15?[18] mg/L [median, 6 U/L; IQR, 3-17 U/L]). Of 40 severely and critically ill patients, 34 (85%) had hypokalemia. Patients with severe hypokalemia were given potassium at a dose of 40 mEq per day, for a total mean (SD) of 453 (53) mEq potassium chloride, during the hospital stay. The patients responded well to potassium supplements as they recovered. Conclusions and Relevance:The correction of hypokalemia is challenging because of continuous renal potassium loss resulting from the degradation of angiotensin-converting enzyme 2. The high prevalence of hypokalemia among patients with COVID-19 suggests the presence of disordered rennin-angiotensin system activity, which increases as a result of reduced counteractivity of angiotensin-converting enzyme 2, which is bound by severe acute respiratory syndrome coronavirus 2.

Dataset Information

Triage process for the assessment of coronavirus disease 2019-positive patients with cancer: The ONCOVID prospective study.

Background

Methods

Results

Conclusions

Publications

Triage process for the assessment of coronavirus disease 2019-positive patients with cancer: The ONCOVID prospective study.

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