Table 4.
Mortality risk and severity of COVID-19 prediction.
| Study | Outcome | Highest-weighted features | ML approaches | Sample size (no. of survivors and non-survivors) | Performance |
|---|---|---|---|---|---|
| Valid et al. [66] | Prediction of mortality and critical events | Acute Kidney Injury, LDH, tachypnea, glucose, diastolic blood pressure, CRP | XGBoost | 4098 patients (−) | AUC of 80% at 3 days 79% at 5 days, 80% at 7 days, and 81% at 10 days |
| Yan et al. [67] | Prediction of mortality and critical COVID-19 | LDH, lymphocytes, hsCRP | XGBoost | 375 patients (201 survivors, 174 non-survivors) | Accuracy of 93% |
| Yan et al. [68] | Prediction of mortality and critical COVID-19 | LDH, lymphocytes, hsCRP | XGBoost | 404 patients (213 survivors and 191 non-survivors) | Accuracy of 90% |
| Wang et al. [69] | Prediction of mortality | Age, hsCRP, SpO2, neutrophil and lymphocyte count, D-dimer, AST, GFR | XGBoost | 296 patients (19 non-survivor) | AUC of 88% |
| Rechtman et al. [70] | Prediction of mortality | Age, male sex, higher BMI, higher respiratory rate, higher heart rate, CKD | LR, XGBoost (selected) | 8770 patients (1114 non-survivors) | AUC of 86% |
| Bertsimas et al. [71] | Prediction of mortality | Age, SpO2, CRP, BUN, blood creatinine | XGBoost | 3927 patients (−) | AUC ranged between 92% and 81% using three validation cohorts. |
| Guan et al. [72] | Prediction of mortality | severity, age, serum levels of hs-CRP, LDH, ferritin, IL-10 | XGBoost | 1270 patients (−) | Precision ¿90%, sensitivity ¿85%, and F1 scores ¿0.90 |
| Booth et al. [73] | Prediction of mortality risk | CRP, lactic acid, calcium, BUN, serum albumin | LR and SVM (selected) | 398 patients (355 survivors and 43 non-survivors from COVID-19) | AUC 93%, 91% sensitivity, and 91% specificity |
| Sun et al. [74] | Prediction of critical COVID-19 | Age, GSH, CD3 ratio, total protein | SVM | 336 patients (26 severe/critical) | AUC of 97.57% |
| Yao et al. [75] | Prediction of critical COVID-19 | Age, neutrophil %, calcium, monocyte %, urine test values (urine protein, red blood cells (occult), and pH (urine)) | SVM | 137 patients (75 severe) | Accuracy of 81.48% |
| Zhao et al. [76] | Prediction of critical COVID-19 | IL-6, high-sensitivity cTnI, procalcitonin, hsCRP, chest distress, calcium | SVM | 172 patients (60 severe) | SVM achieved accuracy of 91.38%, sensitivity of 90% and specificity of 94% |
| Schwab et al. [95] | Prediction of ICU admission | pCO2, creatinine, pH | SVM | 556 patients (35 admitted, 16 ICU) | AUC of 98%, a sensitivity of 80%, and a specificity of 96% |
| Hu et al. [77] | Prediction of mortality risk | Age, hsCRP, lymphocyte count, D-dimer | PLS regression, EN model, RF, FDA, and LR (selected) | 183 patients (115 survivors and 68 non-survivors from COVID-19) | AUC of 88.1%, sensitivity of 83.9%, and specificity of 79.4% |
| Zhao et al. [78] | Prediction of mortality | Heart failure, procalcitonin, LDH, COPD, SpO2, heart rate, age | LR | 641 patients (195 admitted to the ICU, 82 non-survivors) | AUC of 82% |
| Zhao et al. [78] | Prediction of ICU admission | LDH, procalcitonin, smoking history, SpO2, lymphocyte count | LR | 641 patients (195 admitted to the ICU, 82 non-survivors) | AUC of 74% |
| Huang et al. [79] | Prediction of critical COVID-19 | Comorbidities, respiratory rate, CRP, LDH | LR | 125 patients (32 severe) | AUC of 94.4%, sensitivity of 94.1%, and specificity of 90.2%. |
| Xie et al. [80] | Prediction of mortality risk | Age, lymphocyte count, LDH, SpO2 | LR | 444 patients [299 training, 145 validation, 155/299 and 69/145 non-survivors] | (c = 0·89) and (c = 0·98) for internal and external validation. |
| Zhou et al. [81] | Prediction of critical COVID-19 | Age, CRP, D-dimer, product of N/L*CRP*D-dimer | LR | 377 patients (172 severe, 106 non-severe) | AUC of 87.9%, specificity of 73.7% and sensitivity of 88.6% |
| Zhu et al. [82] | Prediction of critical COVID-19 | IL-6, CRP, hypertension | LR | 127 patients (16 severe) | AUC of 90.0% |
| Gong et al. [83] | Prediction of critical COVID-19 | Older age; higher LDH, CRP, RDW, BUN, and direct bilirubin; lower albumin | LASSO regression, DT, RF, and SVM, and LR (selected) | 372 patients (72 severe) | AUC of 85.3%, a sensitivity of 77.5%, and specificity of 78.4% |
| Aloisio et al. [84] | Prediction of mortality and critical COVID-19 | cTnT | Univariate LR | 427 patients (89 non-survivors) | AUC of 94% |
| Aloisio et al. [84] | Prediction of mortality and critical COVID-19 | LDH | Univariate LR | 427 patients (89 non-survivors) | AUC of 89% |
| Aloisio et al. [84] | Prediction of mortality and critical COVID-19 | CRP | Univariate LR | 427 patients (89 non-survivors) | AUC of 87% |
| Aloisio et al. [84] | Prediction of mortality and critical COVID-19 | Albumin | Univariate LR | 427 patients (89 non-survivors) | AUC of 87% |
| Aloisio et al. [84] | Prediction of mortality and critical COVID-19 | D-dimer | Univariate LR | 427 patients (89 non-survivors) | AUC of 84% |
| Aloisio et al. [84] | Prediction of mortality and critical COVID-19 | Ferritin | Univariate LR | 427 patients (89 non-survivors) | AUC of 77% |
| Aloisio et al. [84] | Prediction of mortality and critical COVID-19 | Age, high LDH, low albumin | Multivariate LR | 427 patients (89 non-survivors) | AUC of 88%–89%. |
| Liu et al [85] | Prediction of mortality | Decreased lymphocyte ratio, elevated BUN, raised D-dimer | Multivariate LR | 336 severe patients (34 non-survivors) | AUC of 99.4%, sensitivity of 100.0% and specificity of 97.2% |
| Miao et al. [86] | Prediction of mortality | IL-6 and lymphocyte subsets (CD8+ T cell) | LR | 1018 patients (−) | AUC of 90.7% |
| Bai et al. [96] | Prediction of mortality and the outcome | Creatine kinase | LR | 127 patients (36 non-survivors) | AUC of 86.4% |
| Bai et al. [96] | Prediction of mortality and outcome | CRP | LR | 127 patients (36 non-survivors) | AUC of 87% |
| Bai et al. [96] | Prediction of mortality and outcome | Ferritin | LR | 127 patients (36 non-survivors) | AUC of 83.3% |
| Bai et al. [96] | Prediction of mortality and outcome | IL-6 | LR | 127 patients (36 non-survivors) | AUC of 78.1% |
| Bai et al. [96] | Prediction of mortality and outcome | Lymphocyte CD3+ | LR | 127 patients (36 non-survivors) | AUC of 91.5% |
| Bai et al. [96] | Prediction of mortality and outcome | LDH | LR | 127 patients (36 non-survivors) | AUC of 92.8% |
| Bai et al. [96] | Prediction of mortality and outcome | Troponin I | LR | 127 patients (36 non-survivors) | AUC of 93.9% |
| Bai et al. [96] | Prediction of mortality and outcome | Prothrombin time | LR | 127 patients (36 non-survivors) | AUC of 92% |
| Bai et al. [96] | Prediction of mortality and outcome | Procalcitonin | LR | 127 patients (36 non-survivors) | AUC of 90% |
| Han [87] | Prediction of critical COVID-19 | Gender, APACHE II, SOFA, lymphocytes (including subsets), CRP, LDH, AST, cTnT, BNP, WBC, neutrophil count, urea | LR | 47 patients (24 severe) | (not specified) |
| Han [87] | Prediction of critical COVID-19 | LDH | LR | 47 patients (24 severe) | AUC of 97.27%, sensitivity 100.00% and specificity 86.67% |
| Han [87] | Prediction of critical COVID-19 | AST | LR | 47 patients (24 severe) | AUC of 92.31% |
| Han [87] | Predict critical COVID-19 | CPR | LR | 47 patients (24 severe) | AUC of 92.92% |
| Han [87] | Prediction of critical COVID-19 | Lymphocyte counts (less than 1.045 × 109/L) | LR | 47 patients (24 severe) | AUC of 98.45%, specificity 91.30% and sensitivity 95.24% |
| Han [87] | Prediction of critical COVID-19 | SOFA score | LR | 47 patients (24 severe) | AUC of 94.93% |
| Han [87] | Prediction of critical COVID-19 | CT score | LR | 47 patients (24 severe) | AUC of 95.28% |
| Das et al. [97] | Prediction of mortality risk | Sex, age | SVM, KNN, RF, GB, and (LR, selected) | 3524 patients (74 non-survivors) | AUC of 83% |
| Li et al. [88] | Prediction of mortality risk | Having a chronic disease; gastrointestinal, kidney, cardiac, respiratory symptoms | Autoencoder, LR, RF, SVM, one-class SVM, isolation forest, local outlier factor | Two data sets: A) 28,958 patients (530 non-survivors) B) 1448 patients (123 non-survivors) | Autoencoder model achieved around 73% AUC, and 97% accuracy. |
| Terwangne et al. [89] | Prediction of severity | WHO severity classification, acute kidney injury, age, LDH, lymphocytes, aPTT | Bayesian network analysis | 295 patients (−) | ROC of 83.8% and 91% for the models based on WHO classification only, and EPI-SCORE, respectively. |
| Izquierdo et al. [90] | Prediction of ICU admission | Age, fever, tachypnea with or without respiratory crackles | DT | 10,504 (1353 hospitalized, 83 ICU admission) | AUC of 76%, accuracy 68%, and recall 71% |
| Liang et al. [91] | Prediction of critical COVID-19 | Age, hemoptysis, unconsciousness, comorbidities, cancer history, neutrophil-to- lymphocyte ratio, LDH, direct bilirubin | LASSO then LR | 2300 patients (−) | AUCs of 88% in both the training and validation cohorts |
| Levy et al. [92] | Prediction of critical COVID-19 | BUN, age, absolute neutrophil count, RDW, SpO2, serum sodium | LASSO | 11,095 patients (8499 survivors, 2596 non-survivors) | AUCs of 86%, 82%, and 82%, respectively for internal and external validation |
| Nemati et al. [93] | Survival analysis and discharge time | Age, sex | stagewise GB, IPCRidge, CoxPH, Coxnet, Componentwise GB, fast SVM, and fast Kernel SVM | 1182 patients (−) | C-index of stagewise GB: 71.47 |
| Li et al. [94] | Prediction of mortality | Leukomonocyte %, urea, age, SpO2 | LR, simplified LR, and (GBDT, selected) | 2924 patients (257 non-survivors) | AUC of 94.1% |
| Gao et al. [20] | Prediction of mortality risk, up to 20 days in advance | Increased consciousness, male sex, sputum, BUN, respiratory rate, D-dimer, comorbidities, age. Also decreased platelet count, albumin, SpO2, lymphocytes, CKD | LR, SVM, GBDT, and NN | 2520 COVID-19 patients with known outcomes (survivors or non-survivors) | AUC ranging from 91.86% to 97.62% in an internal validation cohort and two external validation cohorts |