Validated tool for early prediction of intensive care unit admission in COVID-19 patients.

BACKGROUND: The novel coronavirus disease 2019 (COVID-19) pandemic is a global threat caused by the severe acute respiratory syndrome coronavirus-2. AIM: To develop and validate a risk stratification tool for the early prediction of intensive care unit (ICU) admission among COVID-19 patients at hospital admission. METHODS: The training cohort included COVID-19 patients admitted to the Wuhan Third Hospital. We selected 13 of 65 baseline laboratory results to assess ICU admission risk, which were used to develop a risk prediction model with the random forest (RF) algorithm. A nomogram for the logistic regression model was built based on six selected variables. The predicted models were carefully calibrated, and the predictive performance was evaluated and compared with two previously published models. RESULTS: There were 681 and 296 patients in the training and validation cohorts, respectively. The patients in the training cohort were older than those in the validation cohort (median age: 63.0 vs 49.0 years, P < 0.001), and the percentages of male gender were similar (49.6% vs 49.3%, P = 0.958). The top predictors selected in the RF model were neutrophil-to-lymphocyte ratio, age, lactate dehydrogenase, C-reactive protein, creatinine, D-dimer, albumin, procalcitonin, glucose, platelet, total bilirubin, lactate and creatine kinase. The accuracy, sensitivity and specificity for the RF model were 91%, 88% and 93%, respectively, higher than those for the logistic regression model. The area under the receiver operating characteristic curve of our model was much better than those of two other published methods (0.90 vs 0.82 and 0.75). Model A underestimated risk of ICU admission in patients with a predicted risk less than 30%, whereas the RF risk score demonstrated excellent ability to categorize patients into different risk strata. Our predictive model provided a larger standardized net benefit across the major high-risk range compared with model A. CONCLUSION: Our model can identify ICU admission risk in COVID-19 patients at admission, who can then receive prompt care, thus improving medical resource allocation.

Clinical diagnosis of severe COVID-19: A derivation and validation of a prediction rule.

BACKGROUND: The widespread coronavirus disease 2019 (COVID-19) has led to high morbidity and mortality. Therefore, early risk identification of critically ill patients remains crucial. AIM: To develop predictive rules at the time of admission to identify COVID-19 patients who might require intensive care unit (ICU) care. METHODS: This retrospective study included a total of 361 patients with confirmed COVID-19 by reverse transcription-polymerase chain reaction between January 19, 2020, and March 14, 2020 in Shenzhen Third People's Hospital. Multivariate logistic regression was applied to develop the predictive model. The performance of the predictive model was externally validated and evaluated based on a dataset involving 126 patients from the Wuhan Asia General Hospital between December 2019 and March 2020, by area under the receiver operating curve (AUROC), goodness-of-fit and the performance matrix including the sensitivity, specificity, and precision. A nomogram was also used to visualize the model. RESULTS: Among the patients in the derivation and validation datasets, 38 and 9 participants (10.5% and 2.54%, respectively) developed severe COVID-19, respectively. In univariate analysis, 21 parameters such as age, sex (male), smoker, body mass index (BMI), time from onset to admission (> 5 d), asthenia, dry cough, expectoration, shortness of breath, asthenia, and Rox index < 18 (pulse oxygen saturation, SpO2)/(FiO2 × respiratory rate, RR) showed positive correlations with severe COVID-19. In multivariate logistic regression analysis, only six parameters including BMI [odds ratio (OR) 3.939; 95% confidence interval (CI): 1.409-11.015; P = 0.009], time from onset to admission (≥ 5 d) (OR 7.107; 95%CI: 1.449-34.849; P = 0.016), fever (OR 6.794; 95%CI: 1.401-32.951; P = 0.017), Charlson index (OR 2.917; 95%CI: 1.279-6.654; P = 0.011), PaO2/FiO2 ratio (OR 17.570; 95%CI: 1.117-276.383; P = 0.041), and neutrophil/lymphocyte ratio (OR 3.574; 95%CI: 1.048-12.191; P = 0.042) were found to be independent predictors of COVID-19. These factors were found to be significant risk factors for severe patients confirmed with COVID-19. The AUROC was 0.941 (95%CI: 0.901-0.981) and 0.936 (95%CI: 0.886-0.987) in both datasets. The calibration properties were good. CONCLUSION: The proposed predictive model had great potential in severity prediction of COVID-19 in the ICU. It assisted the ICU clinicians in making timely decisions for the target population.

Virus load and virus shedding of SARS-CoV-2 and their impact on patient outcomes.

BACKGROUND: Understanding a virus shedding patterns in body fluids/secretions is important to determine the samples to be used for diagnosis and to formulate infection control measures. AIM: To investigate the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) shedding patterns and its risk factors. METHODS: All laboratory-confirmed coronavirus disease 2019 patients with complete medical records admitted to the Shenzhen Third People's Hospital from January 28, 2020 to March 8, 2020 were included. Among 145 patients (54.5% males; median age, 46.1 years), three (2.1%) died. The bronco-alveolar lavage fluid (BALF) had the highest virus load compared with the other samples. The viral load peaked at admission (3.3 × 108 copies) and sharply decreased 10 d after admission. RESULTS: The viral load was associated with prolonged intensive care unit (ICU) duration. Patients in the ICU had significantly longer shedding time compared to those in the wards (P < 0.0001). Age > 60 years [hazard ratio (HR) = 0.6; 95% confidence interval (CI): 0.4-0.9] was an independent risk factor for SARS-CoV-2 shedding, while chloroquine (HR = 22.8; 95%CI: 2.3-224.6) was a protective factor. CONCLUSION: BALF had the highest SARS-CoV-2 load. Elderly patients had higher virus loads, which was associated with a prolonged ICU stay. Chloroquine was associated with shorter shedding duration and increased the chance of viral negativity.

Safety and efficacy assessment of allogeneic human dental pulp stem cells to treat patients with severe COVID-19: structured summary of a study protocol for a randomized controlled trial (Phase I / II).

OBJECTIVES: To assess the safety and therapeutic effects of allogeneic human dental pulp stem cells (DPSCs) in treating severe pneumonia caused by COVID-19. TRIAL DESIGN: This is a single centre, two arm ratio 1:1, triple blinded, randomized, placebo-controlled, parallel group, clinical trial. PARTICIPANTS: Twenty serious COVID-19 cases will be enrolled in the trial from April 6th to December 31st 2020. INCLUSION CRITERIA: hospitalised patients at Renmin Hospital of Wuhan University satisfy all criteria as below: 1)Adults aged 18-65 years;2)Voluntarily participate in this clinical trial and sign the "informed consent form" or have consent from a legal representative.3)Diagnosed with severe pneumonia of COVID-19: nucleic acid test SARS-CoV-2 positive; respiratory distress (respiratory rate > 30 times / min); hypoxia (resting oxygen saturation < 93% or arterial partial pressure of oxygen / oxygen concentration < 300 mmHg).4)COVID-19 featured lung lesions in chest X-ray image. EXCLUSION CRITERIA: Patients will be excluded from the study if they meet any of the following criteria. 1.Patients have received other experimental treatment for COVID-19 within the last 30 days;2.Patients have severe liver condition (e.g., Child Pugh score >=C or AST> 5 times of the upper limit);3.Patients with severe renal insufficiency (estimated glomerular filtration rate <=30mL / min/1.73 m2) or patients receiving continuous renal replacement therapy, hemodialysis, peritoneal dialysis;4.Patients who are co-infected with HIV, hepatitis B, tuberculosis, influenza virus, adenovirus or other respiratory infection viruses;5.Female patients who have no sexual protection in the last 30 days prior to the screening assessment;6.Pregnant or lactating women or women using estrogen contraception;7.Patients who are planning to become pregnant during the study period or within 6 months after the end of the study period;8.Other conditions that the researchers consider not suitable for participating in this clinical trial. INTERVENTION AND COMPARATOR: There will be two study groups: experimental and control. Both will receive all necessary routine treatment for COVID-19. The experimental group will receive an intravenous injection of dental pulp stem cells suspension (3.0x107 human DPSCs in 30ml saline solution) on day 1, 4 and 7; The control group will receive an equal amount of saline (placebo) on the same days. Clinical and laboratory observations will be performed for analysis during a period of 28 days for each case since the commencement of the study. MAIN OUTCOMES: 1. Primary outcome The primary outcome is Time To Clinical Improvement (TTCI). By definition, TTCI is the time (days) it takes to downgrade two levels from the following six ordered grades [(grade 1) discharge to (grade 6) death] in the clinical state of admission to the start of study treatments (hDPSCs or placebo). Six grades of ordered variables: GradeDescriptionGrade 1:Discharged of patient;Grade 2:Hospitalized without oxygen supplement;Grade 3:Hospitalized, oxygen supplement is required, but NIV / HFNC is not required;Grade 4:Hospitalized in intensive care unit, and NIV / HFNC treatment is required;Grade 5:Hospitalized in intensive care unit, requiring ECMO and/or IMV;Grade 6:Death. ABBREVIATIONS: NIV, non-invasive mechanical ventilation; HFNC, high-flow nasal catheter; IMV, invasive mechanical ventilation. 2. Secondary outcomes 2.1 vital signs: heart rate, blood pressure (systolic blood pressure, diastolic blood pressure). During the screening period, hospitalization every day (additional time points of D1, D4, D7 30min before injection, 2h ± 30min, 24h ± 30min after the injection) and follow-up period D90 ± 3 days. 2.2 Laboratory examinations: during the screening period, 30 minutes before D1, D4, D7 infusion, 2h ± 30min, 24h ± 30min after the end of infusion, D10, D14, D28 during hospitalization or discharge day and follow-up period D90 ± 3 days. 2.3 Blood routine: white blood cells, neutrophils, lymphocytes, monocytes, eosinophils, basophils, neutrophils, lymphocytes, monocytes, eosinophils Acidic granulocyte count, basophil count, red blood cell, hemoglobin, hematocrit, average volume of red blood cells, average red blood cell Hb content, average red blood cell Hb concentration, RDW standard deviation, RDW coefficient of variation, platelet count, platelet specific platelet average Volume, platelet distribution width,% of large platelets; 2.4 Liver and kidney function tests: alanine aminotransferase, aspartate aminotransferase, alkaline phosphatase, γ-glutamyl transferase, prealbumin, total protein, albumin, globulin, white / globule ratio , Total bilirubin, direct bilirubin, cholinesterase, urea, creatinine, total carbon dioxide, uric acid glucose, potassium, sodium, chlorine, calcium, corrected calcium, magnesium, phosphorus, calcium and phosphorus product, anion gap, penetration Pressure, total cholesterol, triacylglycerol, high density lipoprotein cholesterol, Low density lipoprotein cholesterol, lipoprotein a, creatine kinase, lactate dehydrogenase, estimated glomerular filtration rate. 2.5 Inflammation indicators: hypersensitive C-reactive protein, serum amyloid (SAA); 2.6 Infectious disease testing: Hepatitis B (HBsAg, HBsAb, HBeAg, HBeAb, HBcAb), Hepatitis C (Anti-HCV), AIDS (HIVcombin), syphilis (Anti-TP), cytomegalovirus CMV-IgM, cytomegalovirus CMV-IgG; only during the screening period and follow-up period D90 ± 3. 2.7 Immunological testing: Collect peripheral blood to detect the phenotype of T lymphocyte, B lymphocyte, natural killer cell, Macrophage and neutrophil by using flow cytometry. Collect peripheral blood to detect the gene profile of mononuclear cells by using single-cell analyses. Collect peripheral blood serum to detect various immunoglobulin changes: IgA, IgG, IgM, total IgE; Collect peripheral blood serum to explore the changes of cytokines, Th1 cytokines (IL-1 ß, IL-2, TNF-a, ITN-γ), Th2 cytokines (IL-4, IL-6, IL -10). 2.8 Pregnancy test: blood ß-HCG, female subjects before menopause are examined during the screening period and follow-up period D90 ± 3. 2.9 Urine routine: color, clarity, urine sugar, bilirubin, ketone bodies, specific gravity, pH, urobilinogen, nitrite, protein, occult blood, leukocyte enzymes, red blood cells, white blood cells, epithelial cells, non-squamous epithelial cells , Transparent cast, pathological cast, crystal, fungus; 2.10 Stool Routine: color, traits, white blood cells, red blood cells, fat globules, eggs of parasites, fungi, occult blood (chemical method), occult blood (immune method), transferrin (2h ± 30min after the injection and not detected after discharge). RANDOMIZATION: Block randomization method will be applied by computer to allocate the participants into experimental and control groups. The random ratio is 1:1. BLINDING (MASKING): Participants, outcomes assessors and investigators (including personnel in laboratory and imaging department who issue the sample report or image observations) will be blinded. Injections of cell suspension and saline will be coded in accordance with the patient's randomisation group. The blind strategy is kept by an investigator who does not deliver the medical care or assess primary outcome results. NUMBERS TO BE RANDOMIZED (SAMPLE SIZE): Twenty participants will be randomized to the experimental and control groups (10 per group). TRIAL STATUS: Protocol version number, hDPSC-CoVID-2019-02-2020 Version 2.0, March 13, 2020. Patients screening commenced on 16th April and an estimated date of the recruitment of the final participants will be around end of July. . TRIAL REGISTRATION: Registration: World Health Organization Trial Registry: ChiCTR2000031319; March 27,2020. ClinicalTrials.gov Identifier: NCT04336254; April 7, 2020 Other Study ID Numbers: hDPSC-CoVID-2019-02-2020 FULL PROTOCOL: The full protocol is attached as an additional file, accessible from the Trials website (Additional file 1). In the interest in expediting dissemination of this material, the familiar formatting has been eliminated; this Letter serves as a summary of the key elements of the full protocol.