Table 8.
Multiparametric algorithms for prediction of disease outcome and progression
| Author | Design | Statistical model | Population | Score components | Diagnostic performances | RoB |
| Prediction of hospitalisation | ||||||
| Jehi et al66 | Retrospective | LASSO logistic regression | Training: 2852 Validation: 1684 |
Age, race, ethnicity, gender, smoking, BMI, socioeconomic status, fever, fatigue, shortness of breath, diarrhoea, vomiting, asthma, diabetes, hypertension, immunosuppressive disease, NSAIDs, immunosuppressive treatment, platelets, AST, chloride, potassium, blood urea nitrogen | Prediction of Hospitalisation Training: AUC=0.9, Scaled Brier Score 42.6% (95% CI 37.8%, 47.4%) Validation: AUC=0.813 Scaled Brier Score 25.6% (19.9%, 31.3%) |
High |
| Prediction of survival | ||||||
| Wu et al68 | Retrospective | Univariate and multivariate Cox regression analyses | Training: 210 Validation: 60 |
Neutrophil count, lymphocyte count, procalcitonin, age and C reactive protein | Survival Training: AUC=0.955 Validation: AUC=0.945 |
High |
| Dong et al67 | Retrospective | LASSO logistic regression and multivariate Cox regression | Training: 369 Validation: 259 |
Hypertension, higher neutrophil-to-lymphocyte ratio and increased NT-proBNP | Survival Training: AUC=0.92 Validation: AUC=0.92 |
High |
| Zhang et al69 | Retrospective | Multivariate logistic regression | Training: 516 Validation: 186 |
Age, lactate dehydrogenase level, neutrophil-to-lymphocyte ratio and direct bilirubin level | 14 and 28 days Survival Training: C-index=0.886 Validation: C-index=0.879 |
High |
| Prediction of mortality | ||||||
| Wang et al70 | Retrospective | Multivariate logistic regression | Training: 199 Validation: 44 |
FAD-85 score age+0.01 * ferritin+D-dimer | 28-day mortality Training: AUC=0.871 Validation: AUC=NA Sensitivity 86.4% Specificity 81.8% |
High |
| Weng et al71 | Retrospective | LASSO logistic regression | Training: 176 Validation: 125 |
Age, neutrophil-to-lymphocyte ratio, D-dimer and C reactive protein | 28-day mortality Training: AUC=0.921 Validation: AUC=0.975 Sensitivity 86.4% SPECIFICITY 81.8% |
High |
| Prediction of disease progression | ||||||
| Gerotziafas et al75 | Prospective | Multivariate logistic regression | Training: 310 Validation: 120 |
COMPASS-COVID-19 score: Obesity, gender, haemoglobin, lymphocyte, and the cDIC-ISTH (International Society on Thrombosis and Haemostasis score for compensated disseminated intravascular coagulation score) including platelet count, prothrombin time, D-dimers, antithombin and protein C levels |
Disease progression Training: AUC=0.77 Validation: AUC=NA Sensitivity 81% Specificity 60% |
High |
| Bartoletti et al76 | Retrospective | Multivariate logistic regression | Training: 644 Validation: 469 |
PREDI-CO score: Age, obesity, body temperature, respiratory rate, lymphocyte count, creatinine≥1 mg/dL, C reactive protein and lactate dehydrogenase |
Disease progression Training: AUC=0.89 Validation: AUC=0.85 Sensitivity 71.6% Specificity 89.1% |
Unsure |
| Ji et al74 | Retrospective | Multivariate logistic regression | Training: 86 Validation: 62 |
Comorbidity, dyspnoea on admission, lactate dehydrogenase, lymphocyte count | Disease progression Training: AUC=0.856 Validation: AUC=0.819 Sensitivity 94% Specificity 63.1% |
High |
| Li et al73 | Retrospective | Multivariate logistic regression | Training: 322 Validation: 317 |
(Age×LDH)/CD4 T-cell count | Disease progression Training: AUC=0.92 Validation: AUC=0.92 Sensitivity 81% Specificity 93% |
High |
| Xu et al72 | Retrospective | Multivariate logistic regression | Training: 315 Validation N°1: 69 Validation N°2: 123 |
Age, comorbid diseases, neutrophil‐to‐lymphocyte ratio, d‐dimer, C-reactive protein, and platelet count | Disease progression to critical illness Training: AUC=0.923 Validation N°1: AUC=0.882 Validation N°2: AUC=0.906 |
High |
| Xiao et al77 | Retrospective | Multivariate logistic regression | Training: 231 Validation No 1: 101 Validation No 2: 110 |
HNC-LL (hypertension, neutrophil count, C reactive protein, lymphocyte count, lactate dehydrogenase | Disease severity Training: AUC=0.861, p<0.001 Validation: AUC=0.871, p<0.001 V Validation No 2: AUC=0.826, p<0.001 |
Unsure |
| Zhang et al78 | Retrospective | Multivariate logistic regression | Training: 80 Validation: 22 |
Age, white cell count, neutrophil, glomerular filtration rate and myoglobin | Disease severity Training: AUC=0.906 Validation: AUC=0.958 Sensitivity 70.8% Specificity 89.3% |
High |
| Laing et al79 | Retrospective | LASSO and multivariate logistic regression | Training: 1590 Validation: 710 |
Chest radiographic abnormality, age, hemoptysis, dyspnoea, unconsciousness, number of comorbidities, cancer history, neutrophil-to-lymphocyte ratio, lactate dehydrogenase and direct bilirubin | Disease progression to critical illness Training: AUC=0.9 Validation: AUC=0.813 |
Unsure |
AUC, area under the curve; RoB, risk of bias.