Accuracy of smartphone application to quantify jaundice in neonates: A systematic review with meta-analysis

Accuracy of smartphone application to quantify jaundice in neonates: A systematic review with meta-analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Accuracy of smartphone application to quantify jaundice in neonates: A systematic review with meta-analysis Deeparaj Hegde, Chandra Rath, Sathika Amarasekara, Chitra Saraswati, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2719342/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 27 Jun, 2023 Read the published version in European Journal of Pediatrics → Version 1 posted 7 You are reading this latest preprint version Abstract Purpose Neonatal jaundice is a common clinical condition which can progress to acute bilirubin encephalopathy with serious consequences if diagnosis and treatment are delayed. Timely and frequent screening by parents at home has the potential for early identification of high bilirubin levels. In this study, we aimed to analyse the current evidence on the accuracy of smart phone applications to detect neonatal jaundice. Methods PubMed, EMBASE, EMCARE, MEDLINE, The Cochrane Library and Google Scholar were searched from inception until July 2022. Grey literature was searched on ‘Opengrey’ and ‘Mednar’ databases. We included prospective and retrospective cohort studies that recruited infants with a gestation of ≥ 35 weeks and reported paired total serum bilirubin (TSB) and smartphone app-based bilirubin (ABB) levels. Two reviewers independently selected the studies for inclusion. In case of discrepancies, discussions were held with the third reviewer prior to reaching consensus. We conducted the review using the guidelines of the Cochrane Collaboration Diagnostic Test Accuracy Working Group and reported using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses-diagnostic test accuracy (PRISMA-DTA) statement. The data was pooled using the random effects model. The outcome of interest was agreement between ABB and TSB measurements, provided as correlation coefficient. Certainty of Evidence (COE) was assessed based on GRADE guidelines. Results 14 studies (n = 2256) were included in the meta-analysis. The number of infants in individual studies ranged between 35 and 530. The pooled correlation coefficient (r) was 0.77 [95% CI 0.69 to 0.83; p < 0.01], indicating a statistically significant and strong positive correlation between ABB and TSB. Reported sensitivities for predicting a TSB of 250 µmol/L in individual studies ranged between 75 and 100% and specificities 61 to 100%. Similarly, a sensitivity of 83 to 100% and a specificity of 19.5 to 76% were reported for predicting a TSB of 205 µmol/L. Overall COE was considered moderate. Conclusions Smart phone App based bilirubin estimation showed a strong correlation to TSB levels. Well-designed studies are required to determine its utility as a screening tool for various TSB cut-off levels to commence phototherapy. Neonate jaundice Smartphone bilirubin screening Figures Figure 1 Figure 2 Figure 3 What Is Known Neonatal jaundice is common clinical condition. Timely screening and intervention is necessary to prevent both short term and long term neurological morbidities. Transcutaneous bilirubinometer is a widely used non-invasive screening device but mostly used in hospital settings and has cost limitations. Researchers have recently explored the utility of smartphone applications to estimate bilirubin levels in neonates. What is new: This is the first systematic review and meta-analysis conducted to assess the accuracy of smartphone applications to detect neonatal jaundice. Bilirubin estimates of newborns obtained through smartphone applications had a good correlation with serum bilirubin values. Introduction Neonatal jaundice is a global health problem which affects about 60% of term, and 80% of preterm infants during the first week of life( 1 ). It is usually a benign condition but occasionally can progress to acute bilirubin encephalopathy (ABE) which has substantial risk of mortality and morbidity due to long-term neurodevelopmental impairment( 2 ). With improvements in screening and incorporation of preventive strategies, the number of cases of ABE in high-income countries (HIC) has decreased markedly, but the burden is higher in low and middle-income countries (LMIC). The estimated incidences of ABE/Kernicterus are 1 to 3.7 per 100,000 live births in HICs versus 75 per 100,000 live births in LMICs( 3 , 4 ). The ABE related morbidity and mortality are preventable with early identification and timely interventions. The American Academy of Pediatrics (AAP) recommends universal pre-discharge screening using total serum bilirubin (TSB) or transcutaneous bilirubin (TcB) to predict the risk of severe hyperbilirubinemia ( 5 ). The duration of hospital stay for mother and baby varies from country to country and ranges from 0.5 to 6.2 days for singleton vaginal deliveries and 2.5 to 9.3 days for caesarean-section deliveries ( 6 ). Many infants are discharged within few hours of birth at parental request or due to hospital bed shortages. Bilirubin level typically peaks around 3 to 4 days of age when most babies are already discharged. While AAP also recommends outpatient assessment for jaundice by primary health care providers, it may not be feasible. Even if the infant is reviewed by health care providers, visual assessment is not a reliable method to estimate bilirubin levels ( 5 , 7 ). Though there is high degree of correlation between TcB estimation and TSB, high cost precludes its use in LMICs where the burden is the highest. In addition to the cost of the TcB equipment, it needs trained midwifes/nurses to take the measurements. Thus, there is an urgent need for a low-cost, simple, and widely available tool for outpatient and home monitoring of bilirubin levels. Recently smartphone applications have been developed to estimate bilirubin levels and tested against gold standard TSBs. They involve installation of the specific app in the smartphone and obtaining images from predetermined body parts with a colour calibration card placed on the skin site. The image data are then transmitted via the internet to a computer server for analysis using an algorithm to estimate bilirubin levels in real time. In this systematic review, we aimed to analyse the current evidence on the accuracy of smartphone app-based bilirubin (ABB) levels to detect neonatal jaundice. Methods This review was conducted using the guidelines of the Cochrane Collaboration Diagnostic Test Accuracy Working Group (8) and reported using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses-diagnostic test accuracy (PRISMA-DTA) statement (9). It was registered on the international prospective register of systematic reviews (PROSPERO: CRD42022318248). Data sources and searches The electronic databases PubMed, EMBASE, EMCARE, MEDLINE, The Cochrane Library and Google Scholar were searched (since their inception until July 2022) independently by three reviewers. Grey literature was searched on ‘Opengrey’ and ‘Mednar’ databases. PubMed was searched using the following broad keywords: (“jaundice”[MeSH Terms] OR “jaundice”[All Fields] OR “jaundiced”[All Fields] OR ‘jaundices”[All Fields] OR (“bilirubin”[MeSH Terms] OR “bilirubin”[All Fields] OR “bilirubine”[All Fields] OR “bilirubins”[All Fields])) AND (“smartphone”[MeSH Terms] OR “smartphone”[All Fields] OR ‘smartphones”[Al Fields] OR “smartphone s”[All Fields]). Similar terminologies were used while searching other databases. In addition, we hand-searched reference lists of relevant articles. No language or time restrictions were applied. Study selection and outcomes We included prospective and retrospective studies that met the following criteria: (1) Recruited infants with a gestation of ≥35 weeks) (2) Paired TSBs and ABBs were reported and (3) The outcome of interest was agreement between ABB and TSB measurements. The following types of studies were excluded: a) Studies that have used another device in addition to smartphone were excluded as such devices may not be cost effective or user friendly and hence may not be used in the community, b) Studies that used digital camera instead of smartphones, c) Studies that enrolled ≤ 20 neonates, d) Studies that enrolled a mixed population of preterm (≤35 weeks) and term neonates and did not report the bilirubin levels separately for the groups, and e) Studies evaluating ABBs in infants receiving phototherapy. Two reviewers independently selected the studies for inclusion. In case of discrepancies, discussions were held with the third reviewer prior to reaching consensus. Data extraction Data was extracted by two reviewers using a standardised form. Differences in opinion were resolved by discussion amongst all reviewers. All authors were contacted of which one acknowledged our request, but no additional information was provided (10). Assessment of ‘Risk of Bias’ and ‘Applicability Concerns’ The quality of included studies was assessed independently by two reviewers using the QUADAS-2 tool (Quality Assessment of Diagnostic Accuracy Studies) (11). This tool consists of 4 key domains: patient selection, index test, reference standard, and flow and timing. Each study is assessed for risk of bias in each of the domains. Disagreements were resolved by consensus among the members of the review team. The RevMan V.5.2 software was used to generate tables and graphs of risk of bias assessment. Statistical analysis The correlation coefficient between ABBs and TSBs were pooled using a random-effects model as we anticipated between-study heterogeneity. Subgroup analyses were run for measurements using android based smart phones or iOS-based smart phones and type of bilirubin estimation application used. We also conducted subgroup analyses based on the site of measurements (skin, sclera or conjunctiva). Standard error was calculated using sample size. A meta-analysis technique for correlation coefficients was applied, where Fisher’s transformation was performed on the correlation coefficient. The restricted maximum likelihood estimator was used to calculate the heterogeneity variance (12). Knapp-Hartung adjustments were used to calculate the confidence interval around the pooled effect(13). Statistical heterogeneity was assessed using visual inspection of the forest plots and quantified using the I 2 statistic. The I 2 results were interpreted as follows: 0% to 40%: might not be important; 30% to 60%: may represent moderate heterogeneity; 50% to 90%: may represent substantial heterogeneity; 75% to 100%: considerable heterogeneity (Cochrane Handbook)(14). All statistical analyses were performed using the meta package in R 4.2.0 (R Core Team, Austria)(15, 16). The metacor function was used, with function inputs being the correlation coefficient and sample size of each study. Qualitative synthesis was done when meta-analysis was not possible. Certainty of Evidence (COE) was graded as per the GRADE recommendations(17, 18). Results A PRISMA flow chart of screening and selection results is shown in Fig. 1. The initial search identified 366 articles of which 14 studies were included as they met the selection criteria( 10 , 19 – 31 ). All the 14 studies were included in the meta-analysis. The total sample size was 2256 and the number of infants in individual studies ranged between 35 and 530. All the included studies were prospective cohort in design. Among the included studies 3 were conducted in the middle eastern countries( 19 , 25 , 27 ), 2 in Africa( 20 , 23 ), 3 in China( 26 , 28 , 31 ), 2 in India( 22 , 29 ), 2 studies in North America( 21 , 30 ), and 2 studies in Europe( 10 , 24 ) (Table 1 ). Upon assessment, 29% of the studies had low ROB in the domain of patient selection, 64% in the index test, reference standard and flow and timing. There were no significant applicability concerns (e-Figure1). Table 1 Characteristics of the included studies Study ID, Design, Sample size Inclusion criteria Smart phone type, Application, Body part used Ethnicity Results Conclusion Aydin_2016 Turkey, PC, 40 Term neonates, > 24–48 hours old Samsung Galaxy Alpha Smart phone, NA, Skin NA At TSB 160 µmol/L, Sen: 100%, and Spe: 50%. At TSB 195µmol/L, Sen: 83%, and Spe: 19.5%. r: 0.81 for jaundiced babies ABB estimation results are consisted with bilirubin results which are obtained from the standard blood test and the compliance rate is 85%. Rong_ 2016 China, PC, 148 ≥34 weeks up to 15 days of life NA, NA, Skin NA There was no significant difference between ABB (197 ± 51) µmol/L and TSB (191 ± 65) µmol/L (P = 0.109). Bland-Altman analysis (96% (207/215) samples lay within the 95% limits of agreement) showed a strong association. r was 0.593 in the whole population, while the r was 0.628 in the term neonates. The ROC of ABB yielded a 0.743 AUC, and with 82% sensitivity and 60% specificity based on Youden index criterion Based on ABB's agreement with TSB, ABB can be used as a new technique to provide results for objective follow-up for progression and regression of jaundice. Taylor_2017 USA, PC, 530 ≥35 weeks, < 7 days old iPhone 5s, “Bilicam”, Skin White-55.4%, African American-20.8%, Asian American-21.2%, Pacific Islander 2.8%, American Indian- 2.8%, Other-1.5%, Hispanic-26.3% The overall r was 0.91, and correlations among white, African American, Hispanic, and Asian American newborns were 0.92, 0.90, 0.91, and 0.88, respectively. The sensitivities of ABB in identifying newborns with high TSB levels were 84.6% and 100%, respectively; specificities were 75.1% and 76.4%, respectively. The MD between ABB and TSB was 0.18± 32.4 mmol/L, with a range of − 91.8 to + 115.2 mmol/L. ABB provided accurate estimates of TSB values. Smartphones could be used to effectively screen newborns for jaundice. Swarna_2018 India, PC, 35 Term and preterm, < 7 days and more than 7 days iPhone 6s, “Biliscan”, Skin NA There is a good correlation (0.6) between ABB and TSB (p < 0.0001) in the present study on 35 neonates. ABB thorax values correlated better than abdomen values (0.6 versus 0.551) with TSB. Biliscan appears to be a good cost-effective non-invasive option of monitoring new-borns for jaundice where transcutaneous bilirubinometers are not available. Chest is the preferred area for ABB measurement. Yang_2018 China, PC, 194 ≥35 weeks, ≤ 60 days NA, “BiliScan”, Skin NA In the subgroup of TSB >360 \({\mu }\) mol/L, the accuracy of ABB was lower than that of TCB compared to TSB. There was good correlation (r=0.824) and consistency (96.5% samples lay within the 95% limits of agreement) between ABB and TSB. In the subgroup of 180 µmol/L to TSB ≤ 360µmol/L, the correlation and consistency between ABB and TSB were better than those of the subgroups of TSB ≤ 180µmol/Land TSB >360µmol/L. Furthermore, TSBs of 97.5% neonates were not beyond ABB plus 68.4µmol/L. The application BiliScan for newborn Jaundice was suitable for dynamic monitoring mode ate jaundice of neonates and early infants at home. Outlaw_2019 Ghana, PC, 50 Newborns Samsung S8, “NeoSCB”, Sclera NA Colour card method gave Sensitivity of 85%, Specificity of 81% and r was 0.0.80. AS method gave Sensitivity of 100%, Specificity of 78% and r was 0.78. AS method has a higher AUC (0.93) than the CC method (AUC = 0.89). Both colour card and ambient subtraction methods are comparable Rizvi_2019 Saudi Arabia, PC, 100 > 35 weeks, > 2Kg Samsung 10, “BiliCapture”, Conjunctiva NA Correlation was high between TSB and BiliChek (TcB) (r = 0.88) and between TSB and BiliCapture (ABB) (r = 0.73). The Bland-Altman plots showed good agreement when comparing bilirubin values for both BiliChek and BiliCapture devices. Sen and spe were 88.0% and 76.0% using TcB and 92.0% and 75.6% using ABB, respectively. Optical imaging is an alternative aid for immediate diagnosis of hyperbilirubinemia especially in outpatient follow-up, which can help to prevent consequential outcomes. Diaz_2019 Mexico, PC, 166 Healthy newborns > 35 weeks, > 1500 grams, 0–14 days Samsung galaxy S7, NA, Skin Mexican The correlation between TSB levels and ABB was 0.87. For TSB cut off value of 255 µmol/l and ABB value of 186 and 200 µmol/l, Sen: 100% and 90% and Spe: 79.5% and 80.1% respectively. The new smartphone app provided accurate estimates of TSB levels in a Mexican population of newborns. It can have a role as an affordable, available, and accurate supporting diagnosis tool to screen NNJ and closely follow-up newborns with risk to develop dangerous levels of bilirubin in different health care settings. Padidar_2019 Iran, PC, 113 ≥35 weeks, ≤ 9 days old healthy Newborns Android OS, NA, Skin NA ABB had a Sen of 68% and Spe of 92.3% for estimating the bilirubin levels of less than 180 µmol/L and Sen of 82.1% and Spe of 100% for estimating the bilirubin levels of < 270 µmol/L. ABB levels had the r of 0.479 with the TSB. Smartphone-based application can serve as a promising screening tool for neonatal jaundice, and it can aid in determining neonates requiring a blood draw for measuring TSB. Aune_2019 Norway, PC, 185 ≥ 37 weeks 1 to 15 days Samsung galaxy S7, NA, Skin Caucasian, Middle Eastern, Asian, African, and other The correlation between ABB estimates and TSB was measured by Pearson's r and was 0.84 for the whole sample. The r between the image estimates and TCB was 0.81. Sen: 100%, and Spe: 69% for identifying severe jaundice of > 250 µmol/L. Smartphone-based tool that estimated bilirubin levels from digital images identified severe jaundice with high sensitivity and could provide a screening tool for neonatal jaundice. Lingaldinna_2020 India, PC, 143 > 35 weeks, 95th percentile on Bhutani nomogram). Biliscan application is a non-invasive, real-time, inexpensive and an easily available method and has the potential to help in screening neonates thus facilitating recognition of jaundice early and minimising the number of invasive pricks. Outlaw_2020 UK, PC, 37 > 35 weeks Android, “neoSCB”, Sclera NA ABB based on ambient subtracted sclera chromaticity achieved a r of 0.75 (p 250 µmol/L (AUC: 0.86) and Sen: 92% and Spe:67% in identifying infants with TSB > 205 µmol/L. (AUC: 0.85) ABB can predict total serum bilirubin accurately enough to be useful as a screening tool. Ren_2020 China, PC, 179 Mean 36.2 weeks Both android and iPhone, “BiliScan”, Skin NA r: 0.784 and 96.4% samples lay within the 95% CI. Subgroup correlation: good (type of smartphone, detection area, hours after birth, GA) Day time r: 0.924 was better that night r: 0.727. The accuracy of ABB was significantly superior to visual value. The AUC for to predict a TSB > 180 µmol/L: AUC 0.94, Sen 93%, Spe 85. > 270 µmol/L: AUC 0.89, Sen 75, Spe 87 > 360 µmol/L.: AUC 0.84, Sen 50, Spe 88. The accuracy of ABB is noninferior to TCB and significantly superior to visual value. There is a good correlation and strong consistency between ABB and TSB. Enweronu-Laryea_2022 Ghana, PC, 336 Infants 0–28 days Samsung Galaxy S8, “neoSCB”, Sclera NA Single ABB image captures identified infants with TSB > 250 µmol/L) with reasonably high Sen, Spe, and AUC at 0.94 (95% CI) 0.91 to 0.97), 0.73 (95% CI, 0.68 to 0.78), and 0.90, respectively. These findings were comparable to the Sen and Spe of TCB (0.96 [95% CI, 0.90 to 0.99] and 0.81 [95% CI, 0.76 to 0.86], respectively). The TCB/TSB had a larger correlation coefficient (r = 0.93; P < .01) than SCB/TSB (r = 0.78; P < .01). Performance of both devices was lower in infants with previous phototherapy The diagnostic performance of ABB was comparable to TCB and is a potential, affordable, contact-free screening tool for neonatal jaundice. PC: Prospective cohort, TSB: Total Serum Bilirubin, TCB: Transcutaneous Bilirubin, ABB: App Based Bilirubin, CI: Confidence interval, NA: Not available, Sen: Sensitivity, Spe: Specificity, AUC: Area under curve, GA: Gestational age, r: Correlation coefficient, AS: Ambient subtraction, CC: Colour card, MD: Mean difference The pooled correlation between ABB and TSB levels was r = 0.77 (p < 0.01), indicating a statistically significant, strong positive correlation (Fig. 2). There was significant statistical heterogeneity (I 2 = 93%). Heterogeneity was explored by conducting the following subgroup analyses. Subgroup analysis Type of device: The pooled correlation between ABB and TSB levels using an android phone indicated a statistically significant, strong positive correlation (e-Figure 2 and Table 2 ). The use of iOS- based phones indicated a strong association between ABB and TSB; however, it was not statistically significant (e-Figure 3 and Table 2 ). Table 2 Subgroup analysis Subgroup No. of studies Study references Sample size r (p value) Type of phone used Android phones 8 (10, 19–21, 23–25, 27) 1027 0.77 (< 0.01) iOS based phones 3 (22, 29, 30) 131 0.75 (0.07) Body part examined Sclera or Conjunctiva 4 (20, 23, 24, 27) 523 0.77 (p < 0.01) Skin 10 (10, 19, 21, 22, 25, 26, 28–31) 1733 0.77 (p < 0.01) Type of phone application used Biliscan 4 (22, 26, 29, 31) 551 0.73 (p < 0.01) neoSCB 3 (20, 23, 24) 423 0.78 (p < 0.01) r: Correlation coefficient Body part examined: Both examination of the skin and sclera/conjunctiva showed a strong and statistically significant association between ABB and TSB (e-Figures 4,5 and Table 2 ). Type of phone application used: The two types of commonly used ABB estimation apps (“Biliscan”, “neoSCB”) showed a strong and statistically significant association between ABB and TSB (e-Figures 6,7 and Table 2 ). Included studies reported a sensitivity of 75 to 100% and a specificity of 61 to 100% in predicting a TSB of around 250 µmol/L utilising different ABB cut offs ( 10 , 21 , 23 – 26 ). Similarly, sensitivity of 83 to 100% and a specificity of 19.5 to 76% were reported in predicting a TSB of around 205 µmol/L ( 19 , 20 , 24 ). Inspection of the funnel plot (Fig. 3) revealed that studies in our analysis had high variability in their effect size. However, the results of Begg’s test (0.20) or Egger’s test (0.19) suggested that publication bias was unlikely. The seven studies outside of the ideal funnel shape have lower standard errors. This suggests that effect size, which is correlation coefficient between ABB and TSB may vary due to factors other than publication bias. Overall COE was deemed to be only “moderate” in view of unclear risk of bias in more than one domain in some of the included studies, and high statistical heterogeneity (e-Table 1) Discussion This systematic review of 14 studies (n = 2256 infants) showed a strong correlation between ABB and TSB levels in neonatal population born at > 35 weeks of gestation. Timely and frequent screening in the comfort of the home is the primary aim of these device apps. ABB measurement as a screening tool is non-invasive, easy to learn, fast, contact free and user friendly. However, it involves installation of the specific app in the smartphone and hence needs families to be having access to a smartphone. It also requires a level of technology literacy. With the fast-spreading use of smartphones and internet across the globe, increasing number of families are having access to at least one smart phone in their homes. Hence, ABBs are expected to become popular if found to be reliable in estimating bilirubin levels. The new Icterometers such as Bili-strip and Bili-ruler that do not require smartphones have been found to be cost-effective tools in LMICs ( 32 , 33 ). However, this needs further evaluation involving different ethnicities and skin colours. Advanced technological methods such as wearable devices for continuous monitoring are being evaluated but will be able to cater to only high- income families( 34 ). Factors that can affect ABB measurements include skin pigmentation, type of device used and ambient light. One of the included studies reported efficacy of ABB measurements to predict TSB in babies belonging to different ethnicities( 30 ). They reported that though the correlations were similar in different ethnicities, it was marginally higher for white neonates ( 32 ). Another study reported that the correlation in the Caucasian subgroup was higher than the non-Caucasian group( 10 ). However, in that study the number of non-Caucasian infants was only 23% of the total sample size. The included studies have been conducted in various countries around the world and majority of the studies have reported a similar correlation coefficient except the studies from India where it was reported to be low( 22 , 29 ). Some researchers have used sclera for imaging and claimed certain advantages over skin as it does not contain melanin or haemoglobin chromophores. However, in our systematic review we found both skin and sclera are equally effective in predicting TSB. Incorrect estimation of TSB value secondary to skin melanin concentration is an important issue which needs to be addressed in the future studies. The effect of melanin levels in the skin should be factored into the mathematical models in all future ABB devices. In our review though pooling of data from iOS-based devices showed a strong correlation between ABB and TSB, it was not statistically significant which may have been due to the small sample size. Ambient lighting might be an important factor as the process involves taking a digital photo. One of the included studies reported a better correlation coefficient during daytime compared to night-time( 26 ). A colour calibration card helps to attenuate variations in the lighting conditions of the surrounding environment and facilitates image capture. Researchers have also used novel models to negate the effect of ambient light( 23 ). Some of the included studies compared the accuracy of TcB and ABB in their study participants and found TcB to be marginally better than ABB in providing estimates of TSB values ( 10 , 20 , 27 , 31 ). The reported correlations between TcB and TSB had a range from 0.77 to 0.97 with highest correlations seen in newborn infants during their birth hospitalization and lowest in outpatient settings where ABB measurements are intended to be used ( 35 – 39 ). The strengths of our review are its rigorous methodology, assessment of risk of bias and publication bias. To our knowledge, this is the first systematic review with meta-analysis on this topic. Our systematic review has several limitations. First, there was significant statistical heterogeneity. It is well known that heterogeneity is common in meta-analyses of diagnostic studies, because of the non-randomized design of the included studies. Hence, we used a random-effects model for meta-analysis. We also attempted to minimize heterogeneity by conducting various subgroup analyses, but heterogeneity continued to persist. It should also be noted here that \({I}^{2}\) statistic can be biased in small meta-analyses ( 40 ). Second the pooled mean ABB-TSB difference could not be estimated as very few studies have provided the difference plot. Thirdly very few studies have provided sensitivity, specificity, positive predictive value and negative predictive value around multiple TSB cut offs, hence these could not be pooled. Fourth, we could not derive pooled estimates of different ABB cut offs to predict corresponding TSB values. In conclusion, Smart phone App based bilirubin estimation showed a strong correlation to serum bilirubin levels. We anticipate that technological advancements will make it even more effective and useful. Further well-designed studies conducted on a diverse population using different types of commonly used phone devices are required to determine its utility as a screening tool at the community level. Each app will also need to be evaluated at a larger scale and validated. Future studies should endeavour to report true positive, false positive, false negative and true negative values for different TSB cut offs levels for phototherapy to make the results clinically more meaningful. Abbreviations ABE Acute bilirubin encephalopathy HIC High income countries LMIC Low and middle-income countries TSB Total serum bilirubin TcB Transcutaneous bilirubin ABB App based bilirubin COE Certainty of evidence Declarations Funding Source: No funding was secured for this study. Financial Disclosure: The authors have no financial relationships relevant to this article to disclose. Conflict of Interest: The authors have no conflicts of interest to disclose. Ethic Committee approval : Not applicable Consent to participate: Not applicable Consent for publication: Not applicable Contributors’ Statement : Dr Chandra Rath (CR) conceptualized and designed the study, drafted the initial manuscript, designed the data collection instrument and reviewed and revised the manuscript. Drs Deeparaj Hegde (DH), and Sathika Amarasekhara (SA) designed the data collection instruments, collected data, carried out the initial analyses, and reviewed and revised the manuscript. Ms Chitra Saraswati (CS) carried out the statistical analysis and reviewed the manuscript. Drs Associate Professor Shripada Rao (SR) and Professor Sanjay Patole (SP) coordinated and supervised data collection and critically reviewed the manuscript for important intellectual content. All authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work. References Bhutani VK, Stark AR, Lazzeroni LC, Poland R, Gourley GR, Kazmierczak S, et al. Predischarge screening for severe neonatal hyperbilirubinemia identifies infants who need phototherapy. The Journal of pediatrics. 2013;162(3):477-82. e1. Olusanya BO, Kaplan M, Hansen TW. Neonatal hyperbilirubinaemia: a global perspective. The Lancet Child & Adolescent Health. 2018;2(8):610-20. 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Test accuracy: inconsistency, imprecision, publication bias, and other domains for rating the certainty of evidence and presenting it in evidence profiles and summary of findings tables. J Clin Epidemiol. 2020;122:142-52. Schünemann HJ, Mustafa RA, Brozek J, Steingart KR, Leeflang M, Murad MH, et al. GRADE guidelines: 21 part 1. Study design, risk of bias, and indirectness in rating the certainty across a body of evidence for test accuracy. J Clin Epidemiol. 2020;122:129-41. Aydın M, Hardalaç F, Ural B, Karap S. Neonatal jaundice detection system. Journal of medical systems. 2016;40(7):1-11. Enweronu-Laryea C, Leung T, Outlaw F, Brako NO, Insaidoo G, Hagan-Seneadza NA, et al. Validating a Sclera-Based Smartphone Application for Screening Jaundiced Newborns in Ghana. Pediatrics. 2022. Jiménez Díaz G. Validation of a new smartphone app to assess neonatal jaundice in a Mexican population: NTNU; 2019. Lingaldinna S, Konda KC, Bapanpally N, Alimelu M, Singh H, Ramaraju M. Validity of bilirubin measured by biliscan (smartphone application) in neonatal jaundice–an observational study. Journal of Nepal Paediatric Society. 2021;41(1):93-8. Outlaw F, Nixon M, Brako NO, MacDonald LW, Meek J, Enweronu-Laryea C, et al., editors. Smartphone colorimetry using ambient subtraction: application to neonatal jaundice screening in Ghana. Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers; 2019. Outlaw F, Nixon M, Odeyemi O, MacDonald LW, Meek J, Leung TS. Smartphone screening for neonatal jaundice via ambient-subtracted sclera chromaticity. PloS one. 2020;15(3):e0216970. Padidar P, Shaker M, Amoozgar H, Khorraminejad-Shirazi M, Hemmati F, Najib KS, et al. Detection of neonatal jaundice by using an android OS-based smartphone application. Iranian Journal of Pediatrics. 2019;29(2). Ren Y, Huang D, Yang B, Gao X. AB036. The effects on accuracy of image-based estimating neonatal jaundice with a smartphone APP in the different conditions. Pediatric Medicine. 2020;3:AB036. Rizvi MR, Alaskar FM, Albaradie RS, Rizvi NF, Al-Abdulwahab K. A novel non-invasive technique of measuring bilirubin levels using bilicapture. Oman medical journal. 2019;34(1):26. Rong Z, Luo F, Ma L, Chen L, Wu L, Liu W, et al. Evaluation of an automatic image-based screening technique for neonatal hyperbilirubinemia. Zhonghua er ke za zhi= Chinese Journal of Pediatrics. 2016;54(8):597-600. Swarna S, Pasupathy S, Chinnasami B, Manasa D, Ramraj B. The smart phone study: assessing the reliability and accuracy of neonatal jaundice measurement using smart phone application. International Journal of Contemporary Pediatrics. 2018;5(2):285-9. Taylor JA, Stout JW, de Greef L, Goel M, Patel S, Chung EK, et al. Use of a smartphone app to assess neonatal jaundice. Pediatrics. 2017;140(3). Yang B, Huang D, Gao X, SU M, LI M, Lei H, et al. Neonatal and early infantile jaundice: assessment by the use of the smartphone. Chinese Journal of Neonatology. 2018:277-82. Lee AC, Folger LV, Rahman M, Ahmed S, Bably NN, Schaeffer L, et al. A novel Icterometer for hyperbilirubinemia screening in low-resource settings. Pediatrics. 2019;143(5). Olusanya BO, Slusher TM, Imosemi DO, Emokpae AA. Maternal detection of neonatal jaundice during birth hospitalization using a novel two-color icterometer. PLoS One. 2017;12(8):e0183882. Inamori G, Kamoto U, Nakamura F, Isoda Y, Uozumi A, Matsuda R, et al. Neonatal wearable device for colorimetry-based real-time detection of jaundice with simultaneous sensing of vitals. Science Advances. 2021;7(10):eabe3793. Ebbesen F, Rasmussen L, Wimberley P. A new transcutaneous bilirubinometer, BiliCheck, used in the neonatal intensive care unit and the maternity ward. Acta Paediatrica. 2002;91(2):203-11. Engle WD, Jackson GL, Engle NG, editors. Transcutaneous bilirubinometry. Seminars in perinatology; 2014: Elsevier. Maisels M, Engle W, Wainer S, Jackson G, McManus S, Artinian F. Transcutaneous bilirubin levels in an outpatient and office population. Journal of Perinatology. 2011;31(9):621-4. Samanta S, Tan M, Kissack C, Nayak S, Chittick R, Yoxall C. The value of Bilicheck as a screening tool for neonatal jaundice in term and near‐term babies. Acta Paediatrica. 2004;93(11):1486-90. Taylor J, Burgos A, Flaherman V, Chung E, Simpson E, Goyal N, et al. Better Outcomes through Research for Newborns Network. Discrepancies between transcutaneous and serum bilirubin measurements. Pediatrics. 2015;135(2):224-31. von Hippel PT. The heterogeneity statistic I2 can be biased in small meta-analyses. BMC medical research methodology. 2015;15(1):1-8. Additional Declarations No competing interests reported. Supplementary Files Supplementalfile.docx Cite Share Download PDF Status: Published Journal Publication published 27 Jun, 2023 Read the published version in European Journal of Pediatrics → Version 1 posted Editorial decision: Major revision 17 May, 2023 Reviews received at journal 20 Apr, 2023 Reviewers agreed at journal 03 Apr, 2023 Reviewers invited by journal 31 Mar, 2023 Editor assigned by journal 28 Mar, 2023 Submission checks completed at journal 28 Mar, 2023 First submitted to journal 21 Mar, 2023 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2719342","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":187022250,"identity":"dd0fbc91-c781-47a1-94a0-1ba926e37eb3","order_by":0,"name":"Deeparaj Hegde","email":"","orcid":"","institution":"King Edward Memorial Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Deeparaj","middleName":"","lastName":"Hegde","suffix":""},{"id":187022251,"identity":"17194e4f-45a2-4c4b-a181-976c45b31e2d","order_by":1,"name":"Chandra Rath","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAx0lEQVRIiWNgGAWjYDCCAxAqgR9MFhCvxSBBsgGkxYAULQZgBjFa+G4ffva4ouZPnvH51YkfHhgwyPOLHcCvRfJcmrnhmWMGxWY33m6WADrMcObsBPxaDM7wsEk2sBkkbrtxdgNIS4LBbaK0/DNI3Dzj7OYfxGtpbDNI3MDfu404WyTPsJkbNvYZJ864wbvNIsFAgrBf+M4wP3vY8E0usb//7OabPyps5PmlCWgBAjYIJQFWKUFQOZIW/gNEqR4Fo2AUjIIRCAD14Ea1QUvQJQAAAABJRU5ErkJggg==","orcid":"","institution":"King Edward Memorial Hospital","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Chandra","middleName":"","lastName":"Rath","suffix":""},{"id":187022252,"identity":"8890f354-f4aa-4647-8cd9-596e90980580","order_by":2,"name":"Sathika Amarasekara","email":"","orcid":"","institution":"Perth Children’s Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Sathika","middleName":"","lastName":"Amarasekara","suffix":""},{"id":187022253,"identity":"9ce6fd32-34f0-4c41-b91e-bb7d1c0fd7f0","order_by":3,"name":"Chitra Saraswati","email":"","orcid":"","institution":"Telethon Kids Institute","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Chitra","middleName":"","lastName":"Saraswati","suffix":""},{"id":187022255,"identity":"8ac17fcb-63ec-4c26-94fe-61cf2ba22927","order_by":4,"name":"Sanjay Patole","email":"","orcid":"","institution":"King Edward Memorial Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Sanjay","middleName":"","lastName":"Patole","suffix":""},{"id":187022257,"identity":"b71f5bc6-94b2-422c-b2b7-730183d537fd","order_by":5,"name":"Shripada Rao","email":"","orcid":"","institution":"Perth Children’s Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Shripada","middleName":"","lastName":"Rao","suffix":""}],"badges":[],"createdAt":"2023-03-21 15:59:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2719342/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2719342/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00431-023-05073-2","type":"published","date":"2023-06-27T21:25:12+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":35007747,"identity":"e8c6d253-07bd-4339-b15b-ae0a644ac81e","added_by":"auto","created_at":"2023-03-29 22:49:39","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":165376,"visible":true,"origin":"","legend":"\u003cp\u003eFlow chart for study selection\u003c/p\u003e","description":"","filename":"Figure1PRISMAflowchart.png","url":"https://assets-eu.researchsquare.com/files/rs-2719342/v1/876a371c317fc98d64cbcb0d.png"},{"id":35008661,"identity":"c143ce04-b803-4e46-9289-defc8d5da0ea","added_by":"auto","created_at":"2023-03-29 22:57:39","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":435221,"visible":true,"origin":"","legend":"\u003cp\u003eRandom-effects pooled correlation coefficient for ABB and TSB levels for all studies. Horizontal lines for individual studies represent the 95% confidence interval; the black diamond represents the overall estimate. (CI- Confidence interval, IV- Inverse variance)\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-2719342/v1/00779e5c694f43f58253c0e3.png"},{"id":35007746,"identity":"1f134566-052f-4570-9739-8dba236392ec","added_by":"auto","created_at":"2023-03-29 22:49:39","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":117484,"visible":true,"origin":"","legend":"\u003cp\u003eFunnel plot for the studies reporting correlation coefficient.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-2719342/v1/9010484919256952e8f5d443.png"},{"id":44734490,"identity":"a51c6d5c-440d-4d88-8f04-8d33f424eabd","added_by":"auto","created_at":"2023-10-16 22:18:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1190982,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2719342/v1/69076cc1-41bb-487b-b1a6-4afed66109c9.pdf"},{"id":35007749,"identity":"37f0e606-4573-4ea5-bc20-81a0121bbfda","added_by":"auto","created_at":"2023-03-29 22:49:39","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":280186,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementalfile.docx","url":"https://assets-eu.researchsquare.com/files/rs-2719342/v1/2cc423df5a0584ef3646a782.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Accuracy of smartphone application to quantify jaundice in neonates: A systematic review with meta-analysis","fulltext":[{"header":"What Is Known","content":"\u003cp\u003eNeonatal jaundice is common clinical condition. Timely screening and intervention is necessary to prevent both short term and long term neurological morbidities.\u003c/p\u003e\n\u003cp\u003eTranscutaneous bilirubinometer is a widely used non-invasive screening device but mostly used in hospital settings and has cost limitations. Researchers have recently explored the utility of smartphone applications to estimate bilirubin levels in neonates.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWhat is new:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis is the first systematic review and meta-analysis conducted to assess the accuracy of smartphone applications to detect neonatal jaundice.\u003c/p\u003e\n\u003cp\u003eBilirubin estimates of newborns obtained through smartphone applications had a good correlation with serum bilirubin values.\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003eNeonatal jaundice is a global health problem which affects about 60% of term, and 80% of preterm infants during the first week of life(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). It is usually a benign condition but occasionally can progress to acute bilirubin encephalopathy (ABE) which has substantial risk of mortality and morbidity due to long-term neurodevelopmental impairment(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). With improvements in screening and incorporation of preventive strategies, the number of cases of ABE in high-income countries (HIC) has decreased markedly, but the burden is higher in low and middle-income countries (LMIC). The estimated incidences of ABE/Kernicterus are 1 to 3.7 per 100,000 live births in HICs versus 75 per 100,000 live births in LMICs(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe ABE related morbidity and mortality are preventable with early identification and timely interventions. The American Academy of Pediatrics (AAP) recommends universal pre-discharge screening using total serum bilirubin (TSB) or transcutaneous bilirubin (TcB) to predict the risk of severe hyperbilirubinemia (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). The duration of hospital stay for mother and baby varies from country to country and ranges from 0.5 to 6.2 days for singleton vaginal deliveries and 2.5 to 9.3 days for caesarean-section deliveries (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Many infants are discharged within few hours of birth at parental request or due to hospital bed shortages. Bilirubin level typically peaks around 3 to 4 days of age when most babies are already discharged. While AAP also recommends outpatient assessment for jaundice by primary health care providers, it may not be feasible. Even if the infant is reviewed by health care providers, visual assessment is not a reliable method to estimate bilirubin levels (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Though there is high degree of correlation between TcB estimation and TSB, high cost precludes its use in LMICs where the burden is the highest. In addition to the cost of the TcB equipment, it needs trained midwifes/nurses to take the measurements.\u003c/p\u003e \u003cp\u003eThus, there is an urgent need for a low-cost, simple, and widely available tool for outpatient and home monitoring of bilirubin levels. Recently smartphone applications have been developed to estimate bilirubin levels and tested against gold standard TSBs. They involve installation of the specific app in the smartphone and obtaining images from predetermined body parts with a colour calibration card placed on the skin site. The image data are then transmitted via the internet to a computer server for analysis using an algorithm to estimate bilirubin levels in real time. In this systematic review, we aimed to analyse the current evidence on the accuracy of smartphone app-based bilirubin (ABB) levels to detect neonatal jaundice.\u003c/p\u003e "},{"header":"Methods","content":"\u003cp\u003eThis review was conducted using the guidelines of the Cochrane Collaboration Diagnostic Test Accuracy Working Group\u0026nbsp;(8)\u0026nbsp;and reported using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses-diagnostic test accuracy (PRISMA-DTA) statement\u0026nbsp;(9). It was registered on the international prospective register of systematic reviews (PROSPERO:\u0026nbsp;CRD42022318248).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData sources and searches\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe electronic databases PubMed, EMBASE, EMCARE, MEDLINE, The Cochrane Library and Google Scholar were searched (since their inception until July 2022) independently by three reviewers. Grey literature was searched on \u0026lsquo;Opengrey\u0026rsquo; and \u0026lsquo;Mednar\u0026rsquo; databases. PubMed was searched using the following broad keywords: (\u0026ldquo;jaundice\u0026rdquo;[MeSH Terms] OR \u0026ldquo;jaundice\u0026rdquo;[All Fields] OR \u0026ldquo;jaundiced\u0026rdquo;[All Fields] OR \u0026lsquo;jaundices\u0026rdquo;[All Fields] OR (\u0026ldquo;bilirubin\u0026rdquo;[MeSH Terms] OR \u0026ldquo;bilirubin\u0026rdquo;[All Fields] OR \u0026ldquo;bilirubine\u0026rdquo;[All Fields] OR \u0026ldquo;bilirubins\u0026rdquo;[All Fields])) AND (\u0026ldquo;smartphone\u0026rdquo;[MeSH Terms] OR \u0026ldquo;smartphone\u0026rdquo;[All Fields] OR \u0026lsquo;smartphones\u0026rdquo;[Al Fields] OR \u0026ldquo;smartphone s\u0026rdquo;[All Fields]). Similar terminologies were used while searching other databases. In addition, we hand-searched reference lists of relevant articles. No language or time restrictions were applied.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy selection and outcomes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe included prospective and retrospective studies that met the following criteria: (1)\u0026nbsp;Recruited infants with a gestation of \u0026ge;35 weeks) (2) Paired TSBs and ABBs were reported and (3)\u0026nbsp;The outcome of interest was agreement between ABB and TSB measurements. The following types of studies were excluded: a)\u0026nbsp;Studies that have used another device in addition to smartphone were excluded as such devices may not be cost effective or user friendly and hence may not be used in the community, b) Studies that used digital camera instead of smartphones, c)\u0026nbsp;Studies that enrolled \u0026le; 20 neonates, d) Studies that enrolled a mixed population of preterm (\u0026le;35 weeks) and term neonates and did not report the bilirubin levels separately for the groups, and e) Studies evaluating ABBs in infants receiving phototherapy. Two reviewers independently selected the studies for inclusion. In case of discrepancies, discussions were held with the third reviewer prior to reaching consensus.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData extraction\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData was extracted by two reviewers using a standardised form. Differences in opinion were resolved by discussion amongst all reviewers. All authors were contacted of which one acknowledged our request, but no additional information was provided\u0026nbsp;(10).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssessment of \u0026lsquo;Risk of Bias\u0026rsquo; and \u0026lsquo;Applicability Concerns\u0026rsquo;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe quality of included studies was assessed independently by two reviewers using the QUADAS-2 tool (Quality Assessment of Diagnostic Accuracy Studies)\u0026nbsp;(11).\u0026nbsp;This tool consists of 4 key domains: patient selection, index test, reference standard, and flow and timing. Each study is assessed for risk of bias in each of the domains. Disagreements were resolved by consensus among the members of the review team. The RevMan V.5.2 software was used to generate tables and graphs of risk of bias assessment.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe correlation coefficient between ABBs and TSBs were pooled using a random-effects model as we anticipated between-study heterogeneity. Subgroup analyses were run for measurements using android based smart phones or iOS-based smart phones and type of bilirubin estimation application used. We also conducted subgroup analyses based on the site of measurements (skin, sclera or conjunctiva).\u003c/p\u003e\n\u003cp\u003eStandard error was calculated using sample size. A meta-analysis technique for correlation coefficients was applied, where Fisher\u0026rsquo;s\u0026nbsp;\u0026nbsp;transformation was performed on the correlation coefficient.\u0026nbsp;The restricted maximum likelihood estimator was used to calculate the heterogeneity variance\u0026nbsp;\u0026nbsp;\u0026nbsp;(12). Knapp-Hartung adjustments were used to calculate the confidence interval around the pooled effect(13).\u0026nbsp;Statistical heterogeneity was assessed using visual inspection of the forest plots and quantified using the I\u003csup\u003e2\u003c/sup\u003e statistic. The I\u003csup\u003e2\u003c/sup\u003e results were interpreted as follows: 0% to 40%: might not be important; 30% to 60%: may represent moderate heterogeneity; 50% to 90%: may represent substantial heterogeneity; 75% to 100%: considerable heterogeneity (Cochrane Handbook)(14).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll statistical analyses were performed using the \u003cem\u003emeta\u003c/em\u003e package in R 4.2.0 (R Core Team, Austria)(15, 16). \u0026nbsp;The \u003cem\u003emetacor\u003c/em\u003e function was used, with function inputs being the correlation coefficient and sample size of each study. Qualitative synthesis was done when meta-analysis was not possible. Certainty of Evidence (COE) was graded as per the GRADE recommendations(17, 18).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eA PRISMA flow chart of screening and selection results is shown in Fig.\u0026nbsp;1. The initial search identified 366 articles of which 14 studies were included as they met the selection criteria(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan additionalcitationids=\"CR20 CR21 CR22 CR23 CR24 CR25 CR26 CR27 CR28 CR29 CR30\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). All the 14 studies were included in the meta-analysis. The total sample size was 2256 and the number of infants in individual studies ranged between 35 and 530. All the included studies were prospective cohort in design. Among the included studies 3 were conducted in the middle eastern countries(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e), 2 in Africa(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e), 3 in China(\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e), 2 in India(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e), 2 studies in North America(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e), and 2 studies in Europe(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Upon assessment, 29% of the studies had low ROB in the domain of patient selection, 64% in the index test, reference standard and flow and timing. There were no significant applicability concerns (e-Figure1).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of the included studies\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudy ID, Design, Sample size\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInclusion criteria\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSmart phone type, Application, Body part used\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEthnicity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eResults\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eConclusion\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAydin_2016\u003c/p\u003e \u003cp\u003eTurkey, PC, 40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTerm neonates, \u0026gt;\u0026thinsp;24\u0026ndash;48 hours old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSamsung Galaxy Alpha Smart phone, NA, Skin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAt TSB 160 \u0026micro;mol/L, Sen: 100%, and Spe: 50%. At TSB 195\u0026micro;mol/L, Sen: 83%, and Spe: 19.5%. r: 0.81 for jaundiced babies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eABB estimation results are consisted with bilirubin results which are obtained from the standard blood test and the compliance rate is 85%.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRong_ 2016\u003c/p\u003e \u003cp\u003eChina, PC, 148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;34 weeks up to 15 days of life\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNA, NA, Skin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eThere was no significant difference between ABB (197\u0026thinsp;\u0026plusmn;\u0026thinsp;51) \u0026micro;mol/L and TSB (191\u0026thinsp;\u0026plusmn;\u0026thinsp;65) \u0026micro;mol/L (P\u0026thinsp;=\u0026thinsp;0.109). Bland-Altman analysis (96% (207/215) samples lay within the 95% limits of agreement) showed a strong association. r was 0.593 in the whole population, while the r was 0.628 in the term neonates. The ROC of ABB yielded a 0.743 AUC, and with 82% sensitivity and 60% specificity based on Youden index criterion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBased on ABB's agreement with TSB, ABB can be used as a new technique to provide results for objective follow-up for progression and regression of jaundice.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTaylor_2017\u003c/p\u003e \u003cp\u003eUSA, PC, 530\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;35 weeks, \u0026lt; 7 days old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eiPhone 5s, \u0026ldquo;Bilicam\u0026rdquo;, Skin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWhite-55.4%, African American-20.8%, Asian American-21.2%, Pacific Islander 2.8%, American Indian- 2.8%, Other-1.5%, Hispanic-26.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eThe overall r was 0.91, and correlations among white, African American, Hispanic, and Asian American newborns were 0.92, 0.90, 0.91, and 0.88, respectively. The sensitivities of ABB in identifying newborns with high TSB levels were 84.6% and 100%, respectively; specificities were 75.1% and 76.4%, respectively. The MD between ABB and TSB was 0.18\u0026plusmn; 32.4 mmol/L, with a range of \u0026minus;\u0026thinsp;91.8 to +\u0026thinsp;115.2 mmol/L.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eABB provided accurate estimates of TSB values. Smartphones could be used to effectively screen newborns for jaundice.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSwarna_2018 India, PC, 35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTerm and preterm, \u0026lt;\u0026thinsp;7 days and more than 7 days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eiPhone 6s, \u0026ldquo;Biliscan\u0026rdquo;, Skin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eThere is a good correlation (0.6) between ABB and TSB (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) in the present study on 35 neonates. ABB thorax values correlated better than abdomen values (0.6 versus 0.551) with TSB.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBiliscan appears to be a good cost-effective non-invasive option of monitoring new-borns for jaundice where transcutaneous bilirubinometers are not available. Chest is the preferred area for ABB measurement.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYang_2018\u003c/p\u003e \u003cp\u003eChina, PC, 194\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;35 weeks, \u0026le; 60 days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNA, \u0026ldquo;BiliScan\u0026rdquo;, Skin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIn the subgroup of TSB \u0026gt;360 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\mu }\\)\u003c/span\u003e\u003c/span\u003emol/L, the accuracy of ABB was lower than that of TCB compared to TSB. There was good correlation (r=0.824) and consistency (96.5% samples lay within the 95% limits of agreement) between ABB and TSB. In the subgroup of 180 \u0026micro;mol/L to TSB\u0026thinsp;\u0026le;\u0026thinsp;360\u0026micro;mol/L, the correlation and consistency between ABB and TSB were better than those of the subgroups of TSB\u0026thinsp;\u0026le;\u0026thinsp;180\u0026micro;mol/Land TSB \u0026gt;360\u0026micro;mol/L. Furthermore, TSBs of 97.5% neonates\u0026nbsp;were not beyond ABB plus 68.4\u0026micro;mol/L.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eThe application BiliScan for\u0026nbsp;newborn\u0026nbsp;Jaundice\u0026nbsp;was suitable for dynamic\u0026nbsp;monitoring\u0026nbsp;mode ate\u0026nbsp;jaundice\u0026nbsp;of\u0026nbsp;neonates\u0026nbsp;and early\u0026nbsp;infants\u0026nbsp;at home.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutlaw_2019 Ghana, PC, 50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNewborns\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSamsung S8, \u0026ldquo;NeoSCB\u0026rdquo;, Sclera\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eColour card method gave Sensitivity of 85%, Specificity of 81% and r was 0.0.80. AS method gave Sensitivity of 100%, Specificity of 78% and r was 0.78. AS method has a higher AUC (0.93) than the CC method (AUC\u0026thinsp;=\u0026thinsp;0.89).\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBoth colour card and ambient subtraction methods are comparable\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRizvi_2019\u003c/p\u003e \u003cp\u003eSaudi Arabia, PC, 100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;35 weeks, \u0026gt; 2Kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSamsung 10, \u0026ldquo;BiliCapture\u0026rdquo;, Conjunctiva\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCorrelation was high between TSB and BiliChek (TcB) (r\u0026thinsp;=\u0026thinsp;0.88) and between TSB and BiliCapture (ABB) (r\u0026thinsp;=\u0026thinsp;0.73). The Bland-Altman plots showed good agreement when comparing bilirubin values for both BiliChek and BiliCapture devices. Sen and spe were 88.0% and 76.0% using TcB and 92.0% and 75.6% using ABB, respectively.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOptical imaging is an alternative aid for immediate diagnosis of hyperbilirubinemia especially in outpatient follow-up, which can help to prevent consequential outcomes.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiaz_2019\u003c/p\u003e \u003cp\u003eMexico, PC, 166\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHealthy newborns\u0026thinsp;\u0026gt;\u0026thinsp;35 weeks, \u0026gt;\u0026thinsp;1500 grams, 0\u0026ndash;14 days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSamsung galaxy S7, NA, Skin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMexican\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eThe correlation between TSB levels and ABB was 0.87. For TSB cut off value of 255 \u0026micro;mol/l and ABB value of 186 and 200 \u0026micro;mol/l, Sen: 100% and 90% and Spe: 79.5% and 80.1% respectively.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eThe new smartphone app provided accurate estimates of TSB levels in a Mexican population of newborns. It can have a role as an affordable, available, and accurate supporting diagnosis tool to screen NNJ and closely follow-up newborns with risk to develop dangerous levels of bilirubin in different health care settings.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePadidar_2019 Iran, PC, 113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;35 weeks, \u0026le; 9 days old healthy Newborns\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAndroid OS, NA, Skin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eABB had a Sen of 68% and Spe of 92.3% for estimating the bilirubin levels of less than 180 \u0026micro;mol/L and Sen of 82.1% and Spe of 100% for estimating the bilirubin levels of \u0026lt;\u0026thinsp;270 \u0026micro;mol/L. ABB levels had the r of 0.479 with the TSB.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSmartphone-based application can serve as a promising screening tool for neonatal jaundice, and it can aid in determining neonates requiring a blood draw for measuring TSB.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAune_2019\u003c/p\u003e \u003cp\u003eNorway, PC, 185\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge; 37 weeks 1 to 15 days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSamsung galaxy S7, NA, Skin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCaucasian, Middle Eastern, Asian, African, and other\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eThe correlation between ABB estimates and TSB was measured by Pearson's r and was 0.84 for the whole sample. The r between the image estimates and TCB was 0.81. Sen: 100%, and Spe: 69% for identifying severe jaundice of \u0026gt;\u0026thinsp;250 \u0026micro;mol/L.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSmartphone-based tool that estimated bilirubin levels from digital images identified severe jaundice with high sensitivity and could provide a screening tool for neonatal jaundice.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLingaldinna_2020\u003c/p\u003e \u003cp\u003eIndia, PC, 143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;35 weeks, \u0026lt;\u0026thinsp;7 days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eiPhone 6s, \u0026ldquo;Biliscan\u0026rdquo;, Skin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eABB and serum bilirubin showed moderate agreement with a r of 0.6. ABB had a good Sen of 90% in identifying high levels of serum bilirubin (\u0026gt;\u0026thinsp;95th percentile on Bhutani nomogram).\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBiliscan application is a non-invasive, real-time, inexpensive and an easily available method and has the potential to help in screening neonates thus facilitating recognition of jaundice early and minimising the number of invasive pricks.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutlaw_2020 UK, PC, 37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;35 weeks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAndroid, \u0026ldquo;neoSCB\u0026rdquo;, Sclera\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eABB based on ambient subtracted sclera chromaticity achieved a r of 0.75 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) with TSB. Using ABB decision threshold of 190 \u0026micro;mol/L Sen: 100% and Spe: 61% in identifying newborns with TSB\u0026thinsp;\u0026gt;\u0026thinsp;250 \u0026micro;mol/L (AUC: 0.86) and Sen: 92% and Spe:67% in identifying infants with TSB\u0026thinsp;\u0026gt;\u0026thinsp;205 \u0026micro;mol/L. (AUC: 0.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eABB can predict total serum bilirubin accurately enough to be useful as a screening tool.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRen_2020 China, PC, 179\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean 36.2 weeks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBoth android and iPhone, \u0026ldquo;BiliScan\u0026rdquo;, Skin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003er: 0.784 and 96.4% samples lay within the 95% CI. Subgroup correlation: good (type of smartphone, detection area, hours after birth, GA)\u003c/p\u003e \u003cp\u003eDay time r: 0.924 was better that night r: 0.727. The accuracy of ABB was significantly superior to visual value.\u003c/p\u003e \u003cp\u003eThe AUC for to predict a TSB\u0026thinsp;\u0026gt;\u0026thinsp;180 \u0026micro;mol/L: AUC 0.94, Sen 93%, Spe 85.\u003c/p\u003e \u003cp\u003e\u0026gt;\u0026thinsp;270 \u0026micro;mol/L: AUC 0.89, Sen 75, Spe 87\u003c/p\u003e \u003cp\u003e\u0026gt;\u0026thinsp;360 \u0026micro;mol/L.: AUC 0.84, Sen 50, Spe 88.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eThe accuracy of ABB is noninferior to TCB and significantly superior to visual value. There is a good correlation and strong consistency between ABB and TSB.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnweronu-Laryea_2022\u003c/p\u003e \u003cp\u003eGhana, PC, 336\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInfants 0\u0026ndash;28 days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSamsung Galaxy S8, \u0026ldquo;neoSCB\u0026rdquo;, Sclera\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSingle ABB image captures identified infants with TSB\u0026thinsp;\u0026gt;\u0026thinsp;250 \u0026micro;mol/L) with reasonably high Sen, Spe, and AUC at 0.94 (95% CI) 0.91 to 0.97), 0.73 (95% CI, 0.68 to 0.78), and 0.90, respectively. These findings were comparable to the Sen and Spe of TCB (0.96 [95% CI, 0.90 to 0.99] and 0.81 [95% CI, 0.76 to 0.86], respectively). The TCB/TSB had a larger correlation coefficient (r\u0026thinsp;=\u0026thinsp;0.93; P\u0026thinsp;\u0026lt;\u0026thinsp;.01) than SCB/TSB (r\u0026thinsp;=\u0026thinsp;0.78; P\u0026thinsp;\u0026lt;\u0026thinsp;.01). Performance of both devices was lower in infants with previous phototherapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eThe diagnostic performance of ABB was comparable to TCB and is a potential, affordable, contact-free screening tool for neonatal jaundice.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003ePC: Prospective cohort, TSB: Total Serum Bilirubin, TCB: Transcutaneous Bilirubin, ABB: App Based Bilirubin, CI: Confidence interval, NA: Not available, Sen: Sensitivity, Spe: Specificity, AUC: Area under curve, GA: Gestational age, r: Correlation coefficient, AS: Ambient subtraction, CC: Colour card, MD: Mean difference\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe pooled correlation between ABB and TSB levels was r\u0026thinsp;=\u0026thinsp;0.77 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), indicating a statistically significant, strong positive correlation (Fig.\u0026nbsp;2). There was significant statistical heterogeneity (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;93%). Heterogeneity was explored by conducting the following subgroup analyses.\u003c/p\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eSubgroup analysis\u003c/h2\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eType of device:\u003c/h2\u003e \u003cp\u003eThe pooled correlation between ABB and TSB levels using an android phone indicated a statistically significant, strong positive correlation (e-Figure 2 and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The use of iOS- based phones indicated a strong association between ABB and TSB; however, it was not statistically significant (e-Figure 3 and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSubgroup analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubgroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo. of studies\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStudy references\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSample size\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003er (p value)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eType of phone used\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAndroid phones\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(10, 19\u0026ndash;21, 23\u0026ndash;25, 27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.77 (\u0026lt;\u0026thinsp;0.01)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eiOS based phones\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(22, 29, 30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.75 (0.07)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBody part examined\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSclera or Conjunctiva\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(20, 23, 24, 27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e523\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.77 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSkin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(10, 19, 21, 22, 25, 26, 28\u0026ndash;31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1733\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.77 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eType of phone application used\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBiliscan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(22, 26, 29, 31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e551\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.73 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eneoSCB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(20, 23, 24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e423\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.78 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003er: Correlation coefficient\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eBody part examined:\u003c/h2\u003e \u003cp\u003eBoth examination of the skin and sclera/conjunctiva showed a strong and statistically significant association between ABB and TSB (e-Figures 4,5 and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eType of phone application used:\u003c/h2\u003e \u003cp\u003eThe two types of commonly used ABB estimation apps (\u0026ldquo;Biliscan\u0026rdquo;, \u0026ldquo;neoSCB\u0026rdquo;) showed a strong and statistically significant association between ABB and TSB (e-Figures 6,7 and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIncluded studies reported a sensitivity of 75 to 100% and a specificity of 61 to 100% in predicting a TSB of around 250 \u0026micro;mol/L utilising different ABB cut offs (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan additionalcitationids=\"CR24 CR25\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Similarly, sensitivity of 83 to 100% and a specificity of 19.5 to 76% were reported in predicting a TSB of around 205 \u0026micro;mol/L (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eInspection of the funnel plot (Fig.\u0026nbsp;3) revealed that studies in our analysis had high variability in their effect size. However, the results of Begg\u0026rsquo;s test (0.20) or Egger\u0026rsquo;s test (0.19) suggested that publication bias was unlikely. The seven studies outside of the ideal funnel shape have lower standard errors. This suggests that effect size, which is correlation coefficient between ABB and TSB may vary due to factors other than publication bias.\u003c/p\u003e \u003cp\u003eOverall COE was deemed to be only \u0026ldquo;moderate\u0026rdquo; in view of unclear risk of bias in more than one domain in some of the included studies, and high statistical heterogeneity (e-Table\u0026nbsp;1)\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis systematic review of 14 studies (n\u0026thinsp;=\u0026thinsp;2256 infants) showed a strong correlation between ABB and TSB levels in neonatal population born at \u0026gt;\u0026thinsp;35 weeks of gestation. Timely and frequent screening in the comfort of the home is the primary aim of these device apps. ABB measurement as a screening tool is non-invasive, easy to learn, fast, contact free and user friendly. However, it involves installation of the specific app in the smartphone and hence needs families to be having access to a smartphone. It also requires a level of technology literacy. With the fast-spreading use of smartphones and internet across the globe, increasing number of families are having access to at least one smart phone in their homes. Hence, ABBs are expected to become popular if found to be reliable in estimating bilirubin levels.\u003c/p\u003e \u003cp\u003eThe new Icterometers such as Bili-strip and Bili-ruler that do not require smartphones have been found to be cost-effective tools in LMICs (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). However, this needs further evaluation involving different ethnicities and skin colours. Advanced technological methods such as wearable devices for continuous monitoring are being evaluated but will be able to cater to only high- income families(\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFactors that can affect ABB measurements include skin pigmentation, type of device used and ambient light. One of the included studies reported efficacy of ABB measurements to predict TSB in babies belonging to different ethnicities(\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). They reported that though the correlations were similar in different ethnicities, it was marginally higher for white neonates (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). Another study reported that the correlation in the Caucasian subgroup was higher than the non-Caucasian group(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). However, in that study the number of non-Caucasian infants was only 23% of the total sample size. The included studies have been conducted in various countries around the world and majority of the studies have reported a similar correlation coefficient except the studies from India where it was reported to be low(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). Some researchers have used sclera for imaging and claimed certain advantages over skin as it does not contain melanin or haemoglobin chromophores. However, in our systematic review we found both skin and sclera are equally effective in predicting TSB. Incorrect estimation of TSB value secondary to skin melanin concentration is an important issue which needs to be addressed in the future studies. The effect of melanin levels in the skin should be factored into the mathematical models in all future ABB devices.\u003c/p\u003e \u003cp\u003eIn our review though pooling of data from iOS-based devices showed a strong correlation between ABB and TSB, it was not statistically significant which may have been due to the small sample size. Ambient lighting might be an important factor as the process involves taking a digital photo. One of the included studies reported a better correlation coefficient during daytime compared to night-time(\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). A colour calibration card helps to attenuate variations in the lighting conditions of the surrounding environment and facilitates image capture. Researchers have also used novel models to negate the effect of ambient light(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Some of the included studies compared the accuracy of TcB and ABB in their study participants and found TcB to be marginally better than ABB in providing estimates of TSB values (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). The reported correlations between TcB and TSB had a range from 0.77 to 0.97 with highest correlations seen in newborn infants during their birth hospitalization and lowest in outpatient settings where ABB measurements are intended to be used (\u003cspan additionalcitationids=\"CR36 CR37 CR38\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e The strengths of our review are its rigorous methodology, assessment of risk of bias and publication bias. To our knowledge, this is the first systematic review with meta-analysis on this topic. Our systematic review has several limitations. First, there was significant statistical heterogeneity. It is well known that heterogeneity is common in meta-analyses of diagnostic studies, because of the non-randomized design of the included studies. Hence, we used a random-effects model for meta-analysis. We also attempted to minimize heterogeneity by conducting various subgroup analyses, but heterogeneity continued to persist. It should also be noted here that \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({I}^{2}\\)\u003c/span\u003e\u003c/span\u003e statistic can be biased in small meta-analyses (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). Second the pooled mean ABB-TSB difference could not be estimated as very few studies have provided the difference plot. Thirdly very few studies have provided sensitivity, specificity, positive predictive value and negative predictive value around multiple TSB cut offs, hence these could not be pooled. Fourth, we could not derive pooled estimates of different ABB cut offs to predict corresponding TSB values.\u003c/p\u003e \u003cp\u003eIn conclusion, Smart phone App based bilirubin estimation showed a strong correlation to serum bilirubin levels. We anticipate that technological advancements will make it even more effective and useful. Further well-designed studies conducted on a diverse population using different types of commonly used phone devices are required to determine its utility as a screening tool at the community level. Each app will also need to be evaluated at a larger scale and validated. Future studies should endeavour to report true positive, false positive, false negative and true negative values for different TSB cut offs levels for phototherapy to make the results clinically more meaningful.\u003c/p\u003e "},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eABE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAcute bilirubin encephalopathy\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHIC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHigh income countries\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLMIC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLow and middle-income countries\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTSB\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTotal serum bilirubin\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTcB\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTranscutaneous bilirubin\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eABB\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eApp based bilirubin\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCOE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCertainty of evidence\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding Source:\u0026nbsp;\u003c/strong\u003eNo funding was secured for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFinancial Disclosure:\u0026nbsp;\u003c/strong\u003eThe authors have no financial relationships relevant to this article to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest:\u0026nbsp;\u003c/strong\u003eThe authors have no conflicts of interest to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthic Committee approval\u003c/strong\u003e: Not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate:\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u0026nbsp;\u003c/strong\u003eNot applicable\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributors\u0026rsquo; Statement :\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDr Chandra Rath (CR) conceptualized and designed the study, drafted the initial manuscript, designed the data collection instrument and reviewed and revised the manuscript. Drs Deeparaj Hegde (DH), and Sathika Amarasekhara (SA) designed the data collection instruments, collected data, carried out the initial analyses, and reviewed and revised the manuscript. Ms Chitra Saraswati (CS) carried out the statistical analysis and reviewed the manuscript. Drs Associate Professor Shripada Rao (SR) and Professor Sanjay Patole (SP) coordinated and supervised data collection and critically reviewed the manuscript for important intellectual content. All authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBhutani VK, Stark AR, Lazzeroni LC, Poland R, Gourley GR, Kazmierczak S, et al. Predischarge screening for severe neonatal hyperbilirubinemia identifies infants who need phototherapy. The Journal of pediatrics. 2013;162(3):477-82. e1.\u003c/li\u003e\n\u003cli\u003eOlusanya BO, Kaplan M, Hansen TW. Neonatal hyperbilirubinaemia: a global perspective. The Lancet Child \u0026amp; Adolescent Health. 2018;2(8):610-20.\u003c/li\u003e\n\u003cli\u003eBhutani VK, Zipursky A, Blencowe H, Khanna R, Sgro M, Ebbesen F, et al. Neonatal hyperbilirubinemia and Rhesus disease of the newborn: incidence and impairment estimates for 2010 at regional and global levels. Pediatric research. 2013;74(1):86-100.\u003c/li\u003e\n\u003cli\u003eGreco C, Arnolda G, Boo N-Y, Iskander IF, Okolo AA, Rohsiswatmo R, et al. Neonatal jaundice in low-and middle-income countries: lessons and future directions from the 2015 Don Ostrow Trieste Yellow Retreat. Neonatology. 2016;110(3):172-80.\u003c/li\u003e\n\u003cli\u003eKemper AR, Newman TB, Slaughter JL, Maisels MJ, Watchko JF, Downs SM, et al. Clinical practice guideline revision: Management of hyperbilirubinemia in the newborn infant 35 or more weeks of gestation. Pediatrics. 2022;150(3).\u003c/li\u003e\n\u003cli\u003eCampbell OM, Cegolon L, Macleod D, Benova L. Length of stay after childbirth in 92 countries and associated factors in 30 low-and middle-income countries: compilation of reported data and a cross-sectional analysis from nationally representative surveys. PLoS medicine. 2016;13(3):e1001972.\u003c/li\u003e\n\u003cli\u003eRiskin A, Tamir A, Kugelman A, Hemo M, Bader D. Is visual assessment of jaundice reliable as a screening tool to detect significant neonatal hyperbilirubinemia? The Journal of pediatrics. 2008;152(6):782-7. e2.\u003c/li\u003e\n\u003cli\u003eMacaskill P, Gatsonis C, Deeks J, Harbord R, Takwoingi Y. Cochrane handbook for systematic reviews of diagnostic test accuracy. Version; 2010.\u003c/li\u003e\n\u003cli\u003eMcInnes MDF, Moher D, Thombs BD, McGrath TA, Bossuyt PM, Clifford T, et al. Preferred Reporting Items for a Systematic Review and Meta-analysis of Diagnostic Test Accuracy Studies: The PRISMA-DTA Statement. Jama. 2018;319(4):388-96.\u003c/li\u003e\n\u003cli\u003eAune A, Vartdal G, Bergseng H, Randeberg LL, Darj E. Bilirubin estimates from smartphone images of newborn infants\u0026rsquo; skin correlated highly to serum bilirubin levels. Acta Paediatrica. 2020;109(12):2532-8.\u003c/li\u003e\n\u003cli\u003eWhiting PF, Rutjes AW, Westwood ME, Mallett S, Deeks JJ, Reitsma JB, et al. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med. 2011;155(8):529-36.\u003c/li\u003e\n\u003cli\u003eViechtbauer W. Bias and efficiency of meta-analytic variance estimators in the random-effects model. Journal of Educational and Behavioral Statistics. 2005;30(3):261-93.\u003c/li\u003e\n\u003cli\u003eKnapp G, Hartung J. Improved tests for a random effects meta‐regression with a single covariate. Statistics in medicine. 2003;22(17):2693-710.\u003c/li\u003e\n\u003cli\u003eHiggins JP, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, et al. Cochrane handbook for systematic reviews of interventions: John Wiley \u0026amp; Sons; 2019.\u003c/li\u003e\n\u003cli\u003eBalduzzi S, R\u0026uuml;cker G, Schwarzer G. How to perform a meta-analysis with R: a practical tutorial. Evidence-based mental health. 2019;22(4):153-60.\u003c/li\u003e\n\u003cli\u003eTeam RC. R Core Team: A language and environment for statistical computing. Vienna, Austria. 2015.\u003c/li\u003e\n\u003cli\u003eSch\u0026uuml;nemann HJ, Mustafa RA, Brozek J, Steingart KR, Leeflang M, Murad MH, et al. GRADE guidelines: 21 part 2. Test accuracy: inconsistency, imprecision, publication bias, and other domains for rating the certainty of evidence and presenting it in evidence profiles and summary of findings tables. J Clin Epidemiol. 2020;122:142-52.\u003c/li\u003e\n\u003cli\u003eSch\u0026uuml;nemann HJ, Mustafa RA, Brozek J, Steingart KR, Leeflang M, Murad MH, et al. GRADE guidelines: 21 part 1. Study design, risk of bias, and indirectness in rating the certainty across a body of evidence for test accuracy. J Clin Epidemiol. 2020;122:129-41.\u003c/li\u003e\n\u003cli\u003eAydın M, Hardala\u0026ccedil; F, Ural B, Karap S. Neonatal jaundice detection system. Journal of medical systems. 2016;40(7):1-11.\u003c/li\u003e\n\u003cli\u003eEnweronu-Laryea C, Leung T, Outlaw F, Brako NO, Insaidoo G, Hagan-Seneadza NA, et al. Validating a Sclera-Based Smartphone Application for Screening Jaundiced Newborns in Ghana. Pediatrics. 2022.\u003c/li\u003e\n\u003cli\u003eJim\u0026eacute;nez D\u0026iacute;az G. Validation of a new smartphone app to assess neonatal jaundice in a Mexican population: NTNU; 2019.\u003c/li\u003e\n\u003cli\u003eLingaldinna S, Konda KC, Bapanpally N, Alimelu M, Singh H, Ramaraju M. Validity of bilirubin measured by biliscan (smartphone application) in neonatal jaundice\u0026ndash;an observational study. Journal of Nepal Paediatric Society. 2021;41(1):93-8.\u003c/li\u003e\n\u003cli\u003eOutlaw F, Nixon M, Brako NO, MacDonald LW, Meek J, Enweronu-Laryea C, et al., editors. Smartphone colorimetry using ambient subtraction: application to neonatal jaundice screening in Ghana. Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers; 2019.\u003c/li\u003e\n\u003cli\u003eOutlaw F, Nixon M, Odeyemi O, MacDonald LW, Meek J, Leung TS. Smartphone screening for neonatal jaundice via ambient-subtracted sclera chromaticity. PloS one. 2020;15(3):e0216970.\u003c/li\u003e\n\u003cli\u003ePadidar P, Shaker M, Amoozgar H, Khorraminejad-Shirazi M, Hemmati F, Najib KS, et al. Detection of neonatal jaundice by using an android OS-based smartphone application. Iranian Journal of Pediatrics. 2019;29(2).\u003c/li\u003e\n\u003cli\u003eRen Y, Huang D, Yang B, Gao X. AB036. The effects on accuracy of image-based estimating neonatal jaundice with a smartphone APP in the different conditions. Pediatric Medicine. 2020;3:AB036.\u003c/li\u003e\n\u003cli\u003eRizvi MR, Alaskar FM, Albaradie RS, Rizvi NF, Al-Abdulwahab K. A novel non-invasive technique of measuring bilirubin levels using bilicapture. Oman medical journal. 2019;34(1):26.\u003c/li\u003e\n\u003cli\u003eRong Z, Luo F, Ma L, Chen L, Wu L, Liu W, et al. Evaluation of an automatic image-based screening technique for neonatal hyperbilirubinemia. Zhonghua er ke za zhi= Chinese Journal of Pediatrics. 2016;54(8):597-600.\u003c/li\u003e\n\u003cli\u003eSwarna S, Pasupathy S, Chinnasami B, Manasa D, Ramraj B. The smart phone study: assessing the reliability and accuracy of neonatal jaundice measurement using smart phone application. International Journal of Contemporary Pediatrics. 2018;5(2):285-9.\u003c/li\u003e\n\u003cli\u003eTaylor JA, Stout JW, de Greef L, Goel M, Patel S, Chung EK, et al. Use of a smartphone app to assess neonatal jaundice. Pediatrics. 2017;140(3).\u003c/li\u003e\n\u003cli\u003eYang B, Huang D, Gao X, SU M, LI M, Lei H, et al. Neonatal and early infantile jaundice: assessment by the use of the smartphone. Chinese Journal of Neonatology. 2018:277-82.\u003c/li\u003e\n\u003cli\u003eLee AC, Folger LV, Rahman M, Ahmed S, Bably NN, Schaeffer L, et al. A novel Icterometer for hyperbilirubinemia screening in low-resource settings. Pediatrics. 2019;143(5).\u003c/li\u003e\n\u003cli\u003eOlusanya BO, Slusher TM, Imosemi DO, Emokpae AA. Maternal detection of neonatal jaundice during birth hospitalization using a novel two-color icterometer. PLoS One. 2017;12(8):e0183882.\u003c/li\u003e\n\u003cli\u003eInamori G, Kamoto U, Nakamura F, Isoda Y, Uozumi A, Matsuda R, et al. Neonatal wearable device for colorimetry-based real-time detection of jaundice with simultaneous sensing of vitals. Science Advances. 2021;7(10):eabe3793.\u003c/li\u003e\n\u003cli\u003eEbbesen F, Rasmussen L, Wimberley P. A new transcutaneous bilirubinometer, BiliCheck, used in the neonatal intensive care unit and the maternity ward. Acta Paediatrica. 2002;91(2):203-11.\u003c/li\u003e\n\u003cli\u003eEngle WD, Jackson GL, Engle NG, editors. Transcutaneous bilirubinometry. Seminars in perinatology; 2014: Elsevier.\u003c/li\u003e\n\u003cli\u003eMaisels M, Engle W, Wainer S, Jackson G, McManus S, Artinian F. Transcutaneous bilirubin levels in an outpatient and office population. Journal of Perinatology. 2011;31(9):621-4.\u003c/li\u003e\n\u003cli\u003eSamanta S, Tan M, Kissack C, Nayak S, Chittick R, Yoxall C. The value of Bilicheck as a screening tool for neonatal jaundice in term and near‐term babies. Acta Paediatrica. 2004;93(11):1486-90.\u003c/li\u003e\n\u003cli\u003eTaylor J, Burgos A, Flaherman V, Chung E, Simpson E, Goyal N, et al. Better Outcomes through Research for Newborns Network. Discrepancies between transcutaneous and serum bilirubin measurements. Pediatrics. 2015;135(2):224-31.\u003c/li\u003e\n\u003cli\u003evon Hippel PT. The heterogeneity statistic I2 can be biased in small meta-analyses. BMC medical research methodology. 2015;15(1):1-8.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejpe","sideBox":"Learn more about [European Journal of Pediatrics](https://www.springer.com/journal/431)","snPcode":"431","submissionUrl":"https://submission.nature.com/new-submission/431/3","title":"European Journal of Pediatrics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Neonate, jaundice, Smartphone, bilirubin, screening","lastPublishedDoi":"10.21203/rs.3.rs-2719342/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2719342/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eNeonatal jaundice is a common clinical condition which can progress to acute bilirubin encephalopathy with serious consequences if diagnosis and treatment are delayed. Timely and frequent screening by parents at home has the potential for early identification of high bilirubin levels. In this study, we aimed to analyse the current evidence on the accuracy of smart phone applications to detect neonatal jaundice.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003ePubMed, EMBASE, EMCARE, MEDLINE, The Cochrane Library and Google Scholar were searched from inception until July 2022. Grey literature was searched on \u0026lsquo;Opengrey\u0026rsquo; and \u0026lsquo;Mednar\u0026rsquo; databases. We included prospective and retrospective cohort studies that recruited infants with a gestation of \u0026ge;\u0026thinsp;35 weeks and reported paired total serum bilirubin (TSB) and smartphone app-based bilirubin (ABB) levels. Two reviewers independently selected the studies for inclusion. In case of discrepancies, discussions were held with the third reviewer prior to reaching consensus. We conducted the review using the guidelines of the Cochrane Collaboration Diagnostic Test Accuracy Working Group and reported using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses-diagnostic test accuracy (PRISMA-DTA) statement. The data was pooled using the random effects model. The outcome of interest was agreement between ABB and TSB measurements, provided as correlation coefficient. Certainty of Evidence (COE) was assessed based on GRADE guidelines.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003e14 studies (n\u0026thinsp;=\u0026thinsp;2256) were included in the meta-analysis. The number of infants in individual studies ranged between 35 and 530. The pooled correlation coefficient (r) was 0.77 [95% CI 0.69 to 0.83; p\u0026thinsp;\u0026lt;\u0026thinsp;0.01], indicating a statistically significant and strong positive correlation between ABB and TSB. Reported sensitivities for predicting a TSB of 250 \u0026micro;mol/L in individual studies ranged between 75 and 100% and specificities 61 to 100%. Similarly, a sensitivity of 83 to 100% and a specificity of 19.5 to 76% were reported for predicting a TSB of 205 \u0026micro;mol/L. Overall COE was considered moderate.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eSmart phone App based bilirubin estimation showed a strong correlation to TSB levels. Well-designed studies are required to determine its utility as a screening tool for various TSB cut-off levels to commence phototherapy.\u003c/p\u003e","manuscriptTitle":"Accuracy of smartphone application to quantify jaundice in neonates: A systematic review with meta-analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-03-29 22:49:34","doi":"10.21203/rs.3.rs-2719342/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2023-05-17T16:32:57+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2023-04-21T01:11:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"31925868-26fb-4a7c-893e-98ab867398cf","date":"2023-04-04T01:59:48+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2023-04-01T01:39:21+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-03-28T04:24:07+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2023-03-28T04:22:09+00:00","index":"","fulltext":""},{"type":"submitted","content":"European Journal of Pediatrics","date":"2023-03-21T15:53:32+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejpe","sideBox":"Learn more about [European Journal of Pediatrics](https://www.springer.com/journal/431)","snPcode":"431","submissionUrl":"https://submission.nature.com/new-submission/431/3","title":"European Journal of Pediatrics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"09e3fb4a-8ae0-4582-8390-ce064ba74107","owner":[],"postedDate":"March 29th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2023-10-16T22:00:54+00:00","versionOfRecord":{"articleIdentity":"rs-2719342","link":"https://doi.org/10.1007/s00431-023-05073-2","journal":{"identity":"european-journal-of-pediatrics","isVorOnly":false,"title":"European Journal of Pediatrics"},"publishedOn":"2023-06-27 21:25:12","publishedOnDateReadable":"June 27th, 2023"},"versionCreatedAt":"2023-03-29 22:49:34","video":"","vorDoi":"10.1007/s00431-023-05073-2","vorDoiUrl":"https://doi.org/10.1007/s00431-023-05073-2","workflowStages":[]},"version":"v1","identity":"rs-2719342","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2719342","identity":"rs-2719342","version":["v1"]},"buildId":"zQwnuV7TCBrMSSSToR1PI","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}