Unlocking the global health potential of dried blood spot cards

key challenge to providing care for newborn infants in low- and mid-dle-income countries (LMICs) is the lack of timely diagnostic testing due to weak local infrastructures such as laboratory capacity and imaging technologies. To address this challenge, low-cost diagnostic testing that does not require extensive laboratory processing or costly storage pro-cedures has been prioritised. One such example is the shipping of newborn dried blood spot (DBS) samples to international centres where screening for metabolic disorders can be conducted.

[1]  K. Wilson,et al.  A novel way of determining gestational age upon the birth of a child , 2021, Journal of global health.

[2]  J. Stringer,et al.  Metabolic gestational age assessment in low resource settings: a validation protocol , 2021, Gates open research.

[3]  J. Stringer,et al.  Development and external validation of machine learning algorithms for postnatal gestational age estimation using clinical data and metabolomic markers , 2020, medRxiv.

[4]  Matthew Henderson,et al.  External validation of postnatal gestational age estimation using newborn metabolic profiles in Matlab, Bangladesh , 2019, eLife.

[5]  Matthew Henderson,et al.  Incidental screen positive findings in a prospective cohort study in Matlab, Bangladesh: insights into expanded newborn screening for low-resource settings , 2019, Orphanet Journal of Rare Diseases.

[6]  Matthew Henderson,et al.  Building a Newborn Screening Information Management System from Theory to Practice , 2019, International journal of neonatal screening.

[7]  Matthew Henderson,et al.  Metabolic profiles derived from residual blood spot samples: A longitudinal analysis , 2018, Gates open research.

[8]  J. Stringer,et al.  Postnatal gestational age estimation using newborn screening blood spots: a proposed validation protocol , 2017, BMJ Global Health.

[9]  J. Little,et al.  Postnatal Prediction of Gestational Age Using Newborn Fetal Hemoglobin Levels , 2016, EBioMedicine.

[10]  J. Little,et al.  Accurate prediction of gestational age using newborn screening analyte data. , 2016, American journal of obstetrics and gynecology.

[11]  J. Loeber,et al.  Current status of newborn screening worldwide: 2015. , 2015, Seminars in perinatology.

[12]  K. Lim,et al.  Determination of gestational age by ultrasound. , 2014, Journal of obstetrics and gynaecology Canada : JOGC = Journal d'obstetrique et gynecologie du Canada : JOGC.

[13]  W. Lambert,et al.  Dried blood spots in toxicology: from the cradle to the grave? , 2012, Critical reviews in toxicology.

[14]  G. Breart,et al.  Determinants and consequences of discrepancies in menstrual and ultrasonographic gestational age estimates , 2005, BJOG : an international journal of obstetrics and gynaecology.