## 3 Results
### Meta-Analysis Results  
The meta-analysis included 24 studies. The HSROC models for the estimation of a Summary ROC (SROC) curve project the results of each of the 24 studies in the ROC space, with the covariate of the index test subgroup, and display the summary estimates of sensitivity and the false positive rate (1--specificity), with 95% confidence and 95% predictive regions (Figure 3). The results indicate that sensitivity values for the index tests vary between 0.49 and 0.95 and the specificity values vary between 0.50 and 0.91. Innovative digital solutions presented values for sensitivity that vary between 0.78 and 0.94 and specificity values that vary between 0.50 and 0.90. The sensitivity of paper-based digital solutions varies between 0.49 and 0.95 and their specificity varies between 0.72 and 0.91. The results of the sensitivity analysis of the original model (a random-effects meta-analysis of all digital solutions), when removing the studies of paper-based digital solutions (sensitivity analysis model), are displayed in Figure 4.  
Figure 4: Original model (random-effects meta-analysis of all digital solutions) sensitivity analysis, without the studies of paper-based digital solutions (sensitivity analysis model)—Summary ROC (SROC) curve, summary estimates of sensitivity and the false positive rate (I—specificity), with 95% confidence and 95% predictive regions. Figure 3: Random-effects meta-analysis of all digital solutions—Summary ROC (SROC) curve, summary estimates of sensitivity and the false positive rate (I—specificity), with 95% confidence and 95% predictive regions, presenting the covariate index test subgroup. Figures 5 and 6 display the summary estimates of sensitivity and the false positive rate (1--specificity), presenting the 95% confidence and 95% predictive regions for the index tests subgrouped according to the type of test (paper-based digital solutions or innovative digital solutions). Each study is represented with a circle in the ROC space. The forest plots of sensitivity and specificity are presented per study. Figure 5: (a) Random-effects meta-analysis of innovative digital solutions—Summary ROC (SROC) curve, summary estimates of sensitivity and the false positive rate (1—specificity), with 95% confidence and 95% predictive regions; (b) forest plot of sensitivity; (c) forest plot of specificity. References: [PERSON] et al. (2010), [PERSON] et al. (2016), [PERSON] et al. (2016), [PERSON] et al. (2016), [PERSON] et al. (2018), [PERSON] et al. (2015), [PERSON] et al. (2016), [PERSON] et al. (2017), [PERSON] et al. (2019). The meta-analysis's accuracy estimates of the sensitivity, specificity, and false positive rate, with 95% confidence intervals (CI), are presented in Table 2.  
Figure 6: (**a**) Random-effects meta-analysis of paper-based digital solutions—Summary ROC (SROC) curve, summary estimates of sensitivity and the false positive rate (1—specificity), with 95% confidence and 95% predictive regions; (**b**) forest plot of sensitivity; (**c**) forest plot of specificity. References: [PERSON] et al. (2018); [PERSON] et al. (2018); [PERSON] et al. (2018); [PERSON] et al. (2018); [PERSON] et al. (2018); [PERSON] et al. (2018); [PERSON] et al. (2018); [PERSON] et al. (2018); [PERSON] et al. (2018); [PERSON] et al. (2018); [PERSON] et al. (2018); [PERSON] et al. (2018); [PERSON] et al. (2018); [PERSON] et al. (2018); [PERSON] et al. (2018). For the meta-analysis of all digital solutions, a low-quality estimate of the sensitivity is 0.79 (95% CI: 0.75-0.83), and a low-quality estimate of the specificity is 0.77 (95% CI: 0.73-0.81) (Table 3). For the meta-analysis of innovative digital solutions, a moderate quality estimate of the sensitivity is 0.82 (95% IC: 0.79-0.86), and a low-quality estimate of the specificity is 0.73 (95% IC: 0.64-0.80), and for the meta-analysis of paper-based digital solutions, a low-quality estimate of the sensitivity is 0.77 (95% IC: 0.70-0.83), and a moderate quality estimate of the specificity estimate is 0.78 (95% IC: 0.74-0.82) (Table 3).