A Scoping Review: Urinary Markers of Metabolic Maturation in Preterm Infants and Future Interventions to Improve Growth

Abstract Background: Growth failure in infants born preterm is a significant issue, increasing the risk of poorer neurodevelopmental outcomes and metabolic syndrome later in life. During the first 1000 days of life biological systems mature rapidly involving developmental programming, cellular senescence, and metabolic maturation, regulating normal growth and development. However, little is known about metabolic maturation in infants born preterm and the relationship with growth. Objective: To examine the available evidence on urinary markers of metabolic maturation and their relationship with growth in infants born preterm. Eligibility criteria: Studies including in this scoping review using qualitative or quantitative methods to describe urinary markers of metabolic maturation and the relationship with growth in infants born preterm. Results: After a screening process 15 titles were included in this review, from 1998–2021 drawing from China (n = 1), Italy (n = 3), Germany (n = 3), Greece (n = 1), Japan (n = 2), Norway (n = 1), Portugal (n = 1), Spain (n = 2) and USA (n = 1). The included studies examined urinary metabolites in 1131 infants. A content analysis identified 4 overarching themes relating to; (i) metabolic maturation relative to gestational age, (ii) metabolic signature and changes in urinary metabolites over time, (iii) nutrition and (iv) growth. Conclusion: The results of this scoping review suggest there are considerable gaps in our knowledge relating to factors associated with metabolic instability, what constitutes normal maturation of preterm infants, and how the development of reference phenome age z scores for metabolites of interest could improve nutritional and growth outcomes.


Introduction
Globally, an estimated 15 million infants are born preterm (before 37 weeks gestational age) each year, with a prevalence of 5 to 18% depending on country of birth [1]. Current recommendations suggest the growth of preterm infants should aim to approximate the in utero growth of infants of the equivalent gestation [2][3][4], although defining optimal growth relative to short and long term outcomes continues to be debated [5]. During the first 1000 days growth not only involves increasing weight and body length, but also rapid maturation of the immune system, endocrine system and metabolic pathways [6][7][8]. Post-natal growth failure in preterm infants is a persistent problem and may result in poorer neurocognitive outcomes [5], as well as increasing the risk of morbidity and mortality [5,9,10]. Conversely rapid weight gain, particularly between 2.5 and 6 years of age, is associated with the development of metabolic syndrome and cardiovascular disease later in life [11,12]. Reasons for constrained growth are numerous but may include (i) failure to deliver sufficient nutrition, (ii) intestinal immaturity resulting in alterations of nutrient utilisation by the intestine or losses via renal system, (iii) metabolic immaturity leading to transient intolerance of lipids and glucose, (iv) dysregulated maturation of metabolic pathways and urinary losses of important metabolites, (v) dysbiosis of the microbiome with poor diversity and low abundance of intestinal microbiota, (vi) medical management including use of pharmacopeia (i.e., diuretics) increasing urinary losses of electrolytes and (vii) disruption in achieving nutrition targets [5,6,[13][14][15].
Although there are well established nutritional recommendations from various expert groups pertaining to macro-and micronutrient requirements of preterm infants [4,16], the recommendations do not account for an individual preterm infant's ability to assimilate nutrients or the ability to overcome potential aberrance in metabolic pathways [5,9,17]. As an example, some preterm infants, (especially those around the threshold of viability) experience metabolic immaturity and instability leading to sustained periods of hyperglycaemia and hypertriglyceridemia, meaning that some nutritional goals are not met during a time of rapid growth and organ development [9,17]. Current strategies to manage metabolic complications include the use of insulin (which is not without risk), or potentially an even cruder strategy of reducing the amount substrate (e.g., glucose and lipid) delivered with associated negative sequalae on macro-and micronutrient intake [9,10,17,18].
With the advent of high throughput analytic techniques to quantify components of biological samples, it is increasingly possible to consider the development a more nuanced approach to medical and nutritional management for a whole range of conditions [19]. To this end 1 H nuclear magnetic resonance ( 1 H-NMR) spectroscopy and mass spectroscopy (MS) can be used to analyse the metabolome in biological fluids such as urine [20,21] and identify signatures associated with different health and disease states [13]. Although blood has been comprehensively studied with regard to metabolomic analysis, preterm infants have small circulating blood volumes. As urine is chemically complex, metabolomic analysis has been shown to provide information on varying physiological states, metabolism signatures and functions [22]. In addition, urine is readily available, collection is noninvasive and easy making it an accessible biological fluid to study. Giallourou et al. used urinary metabolic profiling to study metabolic maturation of infants (n = 1131) from resource constrained settings over 3 continents in the first 1000 day. From this work they identified eight metabolic signatures which were independent of feeding practices. These were developed into time dependent variation in healthy compared to growth constrained infants phenome age for z scores (PAZ) [13]. In this setting the development of PAZ for the metabolites of interest provided the opportunity to plot individual metabolic maturity in real time and provide the opportunity to offer interventions targeted to an infant's precise metabolic predisposition [13]. Developing PAZ scores for preterm infants may provide a better understanding of metabolic factors which may be contributing to extra uterine growth retardation [23].
Developing a better understand of dynamic changes to post-natal metabolic stability and maturity in preterm infants, may help to (i) develop normative z-scores for age for metabolites associated with metabolic stability and maturation in preterm infants, (ii) refine our understanding of nutritional needs based on metabolic maturity rather than chronological maturation, (iii) provide an opportunity to identify potential future targets for nutritional supplementation to promote metabolic maturation and improve growth outcomes [13,[24][25][26][27].
A scoping review was chosen over a systematic review as the use of urinary metabolomics to quantify metabolic stability and maturity in preterm infants is a relatively unexplored area of nutritional and metabolic research. As a result, it was not possible to complete a systematic review with/without meta-analysis. The rationale for this methodological approach is explored by Munn et al. [28] further. This scoping review was carried out to gain a better understanding of where the current evidence base is in terms of achieving these goals.

Materials and Methods
We chose to complete a scoping review, as a method to systematically review the available literature completing a content and narrative review.

Preparing to Scope the Literature and Protocol Development
A scoping review was conducted to understand the range of evidence currently available and to map key concepts within it. Specifically, it aimed to address the question "Are there specific metabolic signatures which could be used to develop reference phenome age z score for metabolites of interest associated with metabolic maturation and growth?" For the purposes of this review, we defined preterm infants as born <37 weeks gestational age.
Scoping review methodology was chosen because it offers a framework to examine a broad range of evidence in an emerging field [28] and allows the analysis of current knowledge gaps and future research priorities. The Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) [29] was used to report the evidence examined in this review.

Protocol Development
The protocol was developed using the PRISMA-ScR checklist [29] and previously published work [30]. The protocol described; (1) the research question, (2) the information sources to be searched, (3) a description of the full electronic search strategy, (4) study inclusion and exclusion criteria (5) data extraction and charting, (6) collation of data, analysis, and critical appraisal to answer the research questions posed.

Data Sources Searched
The research questions were used to complete a literature search across multiple databases and thus identify relevant studies. The databases searched were PubMed, the Cochrane Library, NHS Evidence and the NICE Healthcare Databases Advanced Search website (HDAS) (https://hdas.nice.org.uk/) (accessed 30 January 2022). HDAS was used to allow searches within multiple databases, including AMED, BNI, Cinahl, Embase, Health Business Elite, HMIC, Medline and PsycInfo.

The Search Strategy
A search strategy was devised with the assistance of a PubMed information specialist. The search strategy used key words from articles relating to infants born preterm (Appendix A Tables A1 and A2). Searches were adapted for the additional electronic databases. Forward and backward citation searching was completed on full text articles selected with no predefined start date until February 2022.

Study Selection
Studies were eligible for inclusion if they were written in the English language, describing urinary markers of metabolic maturation or growth in preterm infants. Opinion pieces, editorials and congress abstracts were excluded as per the scoping methodology advocated by Aksey and O'Malley [31]. Article titles and abstracts were screened, duplicates deleted, and then full text articles reviewed for eligibility (SP, LVM, JJA, CW). Where multiple articles described the same cohort of children these were only counted once. Bibliographies of included studies were hand searched for additional studies which may fulfil the inclusion criteria. Exclusion criteria included studies, infants with other primary pathologies and metabolites described in other fluids.

Data Extraction and Charting
Data extraction was completed using a two-stage process. For quality control article titles and abstracts were screened, duplicates deleted, and then full text articles reviewed for eligibility (SP, LVM, JJA, CW). A data extraction template (Microsoft 2010, Redmond, WA, USA) was used to capture the study design, results, and conclusions. This was followed by content analysis.

Collating, Summarising and Reporting Results
Data synthesis was completed using a content analysis approach. Content analysis was chosen as it is an established technique for reporting subjects common to multiple data sets [31,32]. Descriptive aspects about the population studied, methodology, outcomes and any key findings were coded. Content analysis was completed by coding initial themes, which were grouped into sub-categories and then into overarching themes. The overarching themes and sub-categories from this process were used to develop a summary table. A narrative data synthesis was also completed [33] summarising results of the identified studies.

Narrative Data Synthesis
A narrative data synthesis identified preterm birth was associated with deficiencies in amino acid, carbohydrate, and fatty acid metabolism pathways and metabolites associated with energy and protein pathways are downregulated (Table 1) [34][35][36][37][38][39][40][41][42][43][44][45][46]. 1. From day 1 to day 3 multiple changes are noted in the urinary metabolic profiles of healthy term infants. Specifically stronger signals of creatinine, taurine, myo-inositol and weaker signals of creatine and glycine are seen on the first day of life when compared to the third day of life. 2. Trends in differentiation of metabolite levels between late preterm and term infants and observed at day 1 but lost by day 3. 3. There are specific differences between the urinary metabolic profiles of male and female infants, as well of those whose mothers who smoked during pregnancy. All enterally fed with formula or a combination of breast/formula milk. 10 had additional PN 1. ADMA (asymmetric dimethylarginine) and hArg (l-homoarginine) plasma levels were significantly higher in the extremely preterm infants than preterm infants' group. 2. Urinary ADMA, SDMA and hArg did not correlate with GA, weight, or head circumference in either group. 3. There was no difference with respect to Arg in the plasma or nitrite/nitrate in the plasma or urine. 4. hArg seems to be of higher significance for the female than for the male foetus. Therefore, it is proposed that ADMA and hArg are involved in foetal growth, and that this manner is dependent on the gender  To determine the effect of human milk on markers of oxidative stress.
1. Preterm: GA < 37 weeks, Full enteral feeding either exclusively with human milk (own mother's milk or donor) or with preterm formula, consistent and adequate weight gain the week before enrolment; Controls: healthy, term, fed human milk 2. Both preterm groups, when compared with term new-borns, had significantly higher urinary markers of oxidative stress. 3. The formula fed preterm infants eliminated significantly higher amounts of 8-oxodG and o-Tyr than the preterm infants fed human milk, leading to the conclusion that prematurity is associated with protracted oxidative stress, from which human milk is partially protective 4. When all the data was combined there was a significant correlation between markers of oxidative stress and birth weight.

2, 3, 4
Comparison between tryptophan methoxy indole and kynurenine metabolic pathways in normal and preterm neonates and in neonates with acute foetal distress Munoz-Hoyas [41] 1998 1. Diurnal differences exist cord in blood melatonin concentration and the urinary excretion of kynurenine-with greater concentrations of Kynurenine in the day and greater concentrations of Melatonin at night. This diurnal pattern is blunted in preterm infants and those with foetal distress.   1. At term-corrected age, fat mass, both in terms of percentage and absolute content, was significantly higher in preterm infants than in full-term infants.
At 3 months corrected the body composition parameters were similar between the two groups. 2. There were significant differences in the urinary metabolic profiles of the two groups. At term corrected the preterm group exhibited higher urinary citrate, choline/phosphocholine, lactate, betaine, and glucose but lower myo-inositol, creatinine, dimethylamine, and ethanolamine. At 3 months corrected the preterm group exhibited higher urinary creatinine, choline/phosphocholine and lactate and a lower betaine, glycine, and citrate.

Content Analysis and Overarching Themes
Content analysis identified four overarching themes relating to, (i) metabolic maturation relative to gestational age, (ii) metabolic signature and changes in urinary metabolites over time, (iii) nutrition and (iv) growth (Table 2 and Figure 2). These were used to develop a summary of factors affecting metabolic maturation in infants born preterm (Figure 3), and describe metabolites associated with each of the themes (Table 2). • Alanine, lysine and creatine are associated with amino acid and nitrogen metabolism. Biosynthesis of creatinine is associated with increase muscle mass in infants [44].

•
The inositol pathway is formed of eight inositol isomers, all of which are formed from the epimerisation of myo-inositol. Myo-inositol is involved in the intracellular transmission of insulin's metabolic signal and is also important for the oxidative use of glucose and its storage as glycogen. Aberrance in myo-inositol is associated with insulin resistance [49]. Lower levels of amino acids in urine of preterm infants may be due to lower protein deposition of essential amino acids or lack of metabolic enzymes required for nutrient utilization [39]. • Lower lactose levels may occur due to lower lactase enzyme activity in preterm infants intestinal tract with lower sugar metabolism and storage [39]. • Lower ketone bodies and ketogenic amino acid lysine may be associated with deranged energy metabolism, as well as an increased reliance of fatty acids as a source of energy, with lower levels of lactate and potential enhanced use of pyruvate in the TCA cycle • Lower metabolites related to the gut microbiome; dimethylamine (DMA) and 1-methyl-histidine and reduced biotin status [44]. • ADMA and l-homoarginine are part of the nitric oxide pathway which is associated with many physiological processes including regulation of blood pressure, inhibition of platelet aggregation and neurotransmission [38]. • Tryptophan metabolism in the brain involves the methoxyindole and kynurenine metabolic pathways, includes the metabolite melatonin, associated with circadian rhythm with tryptophan degradation occurring via methyoxyindoles [41].

•
The most important metabolic cycles related to variations in metabolites between preterm and term infants were; tyrosine metabolism (tyrosine and tryptophan); phenylalanine biosynthesis; TCA cycle; arginine and proline metabolism [36].

Nutrition
Formula vs.

Birth weight
• Markers of oxidative stress inversely correlate with birth weight • Variation in ethanolamine and myo-inositol may also reflect changes in membrane synthesis of phosphatidylinositol (PI) which act as lung surfactants, as such decrease myo-inositol may reflect a temporary increase in PI requirements [40]. • 3-methylhistidine is a constituent of actin and myosin of white muscle fibres. It is not reutilised for protein synthesis and can be used as a measure of muscle protein turnover. Creatinine is formed from creatine and creatine phosphatase in muscle and can be used as an indirect measure of lean muscle mass. Urinary 3-methylhistidine/creatinine ratio can be used as an indicator of nutritional and metabolic status. Infants with a higher ratio were more likely to have growth failure [34]. • Increased urinary excretion of choline, a betaine precursor, could reflect a potential altered metabolism in preterm infants [48].

Category 1: Metabolic|Maturation
Four studies characterised changes to the urinary metabolome in preterm infants associated with postnatal maturation in the first few days [35], and first few weeks of life [34,37,45,46]. They identified postnatal changes to the metabolism of glucogenic amino acids, the tricarboxylic acid (TCA) cycle and choline metabolism. These changes correlate with both post-menstrual age (PMA) and gestational age at birth, demonstrating a unique preterm pattern of metabolic maturation.

Category 2: Metabolic|Signatures
Nine studies [35][36][37][38][39][40]44,45,48] included suggested a distinct metabolic signature of prematurity. Preterm birth was associated with deficiencies in amino acid, carbohydrate, and fatty acid metabolism pathways. Extremely preterm infants had the most significant metabolic aberration with variation in metabolites of tyrosine metabolism including tyrosine, tryptophan, and phenylalanine biosynthesis along with the TCA cycle including arginine and proline metabolism, consistent with a role in foetal maturation. None of the included studies addressed issues relating to early life metabolic instability, hyperglycaemia, and hypertriglyceridemia although Morniroli et al. [48] reported higher losses of glucose in urine of preterm infants compared to those at term.

Category 3: Metabolic|Nutrition
Seven studies [37,40,[42][43][44]46,47] examined the effects of differing nutritional sources on the urinary metabolites of preterm infants. Markers of oxidative stress are higher in preterm than term infants. Nutrition can alter these markers of oxidative stress, with parenteral nutrition (PN), as well as formula feeding leading to higher levels being excreted when compared to breast feeding. Urinary metabolites of choline metabolism are increased in response to breast feeding.

Category 4: Metabolic|Growth
Six studies [34,37,40,44,46,48] commented on the metabolic profiles of preterm infants with regard to growth parameters. Only two studies directly compared the urinary metabolomes of preterm infants with differing growth profiles. Hulsemann et al. [34] who found infants with stagnating or decreasing weight to have higher 3-methylhistidine/creatinine ratios. Moltu et al. [37] found no difference in urinary metabolic profiles between preterm infants fed an interventional enhanced nutritional plan and the controls, despite the intervention arm demonstrating significantly better growth.

Discussion
This scoping review has outlined the current understanding of metabolic maturation and the distinct metabolic profiles associated with prematurity. Metabolic maturation can be defined the relationship to 'biochemical maturity relative to chronological age' [13]. Preterm birth was associated with deficiencies in amino acid, carbohydrate, and fatty acid metabolism pathways. This seems to be followed by an increase in glucogenic amino acids TCA cycle metabolites and urinary choline metabolites following birth, which correlate with both premenstrual age (PMA) and gestational age at birth, demonstrating a unique preterm pattern of metabolic maturation. Markers of oxidative stress are higher in preterm than term infants, though these seem modifiable by nutrition, with parenteral nutrition (PN) and formula feeding leading to higher levels being excreted compared to breast feeding.
However, there are several gaps in the current knowledge base, including (i) what is the normal pattern of metabolic maturation for preterm infants, (ii) how metabolic signatures may vary in those infants with metabolic instability (as illustrated by an intolerance of glucose or lipid for example) compared to those who are tolerant of parenteral and enteral nutrition, (iii) what the efficacy of nutritional interventions could be to facilitate metabolic maturation and improve growth outcomes and (iv) whether there is an opportunity to develop reference standards for metabolic maturity, i.e., metabolism may be related to gestational age/corrected gestational age, rather than chronological age.
Briefly, metabolic functions can be split into two categories, bioenergetic functions and metabolic signalling functions. Bioenergetic functions, are highly regulated, supporting canonical metabolic activity such as providing energy or cellular building blocks. Metabolic signalling functions play an instructive or modulatory role in the regulation of metabolic pathways, with metabolites being the rate limiting substrate for epigenetic modification and post-translational modifications [6]. By combining advances in both metabolomic analytics and data analysis with anthropometry it may be possible to define nutritional phenotypes based upon metabolic maturity [6]. With the advent of high throughput analytic techniques to quantify components of biological samples, it increasingly possible to consider the development a more nuanced approach to medical and nutritional management for a whole range of conditions [19].
An elegant study completed by Giallourou et al. [13] demonstrated a potential way metabolites of interest within a paediatric population may be used to assess the efficacy of nutrition interventions. The group characterised changes in urinary metabolic profile of infants (n = 1131) from resource constrained settings over 3 continents over time during the first 1000 days of life. Findings suggest that biochemical immaturity during the first two-years-of-life, is associated with poorer growth outcomes, which were evident from as early as three months of age and persisted until the end of the second year of life. Linear and ponderal growth were associated with eight age-dependent metabolic signatures, from which phenome age z score (PAZ) reference curves were developed. The use of PAZ for these metabolites of interest provided the opportunity to determine an infant's position along this metabolic maturation continuum. In the future, there may be the potential to quantify the effectiveness of a nutrition intervention in real time, as well as targeting the individual infants metabolic age rather than chronological age. This is an attractive model for optimising nutrition support in preterm infants, especially those with metabolic instability, as it provides a non-invasive way to measure nutritional responsiveness in preterm infants together with the opportunity to offer interventions targeted to more precise metabolic predisposition [13].
As growth failure is linked to increased risk of metabolic disease later in life, developing nutrition interventions favouring growth in all children affected by malnutrition is imperative [51], including infants born preterm [13]. Metabolic pathways are also influenced by epigenetic marks early in life [52], and this overlaps with changes in metabolic signatures during the evolution of carbohydrate metabolism which coincide with increasing intestinal uptake of disaccharides in the growing infant. Myoinositol plays an essential role in glucose metabolism and transport, as well as being a precursor for several secondary messaging pathways related to intracellular insulin signalling. Myo-inositol is also a component of structural and signalling lipids such as phyosphatidylinositol [53]. Prematurity also affects metabolic pathways involving hydroxyproline, creatine and myo-inositol [54][55][56][57][58], which may contribute to future cardiometabolic disease [44,54]. This temporal relationship has been eloquently described in a small cohort of pre-pubertal children (4-9 years of age) who were SGA at birth. Myo-inositol (urine) levels were decreased by 4-fold in SGA catch-up growth compared with non-catch-up growth. Transcriptomic analysis identified myo-inositol was associated with gene clusters coding for insulin and insulin like growth factor 1 (IGF-1) children [53].
Preterm infants are known to have altered body composition, which has implications for future cardiometabolic disease risk [59,60] and developing PAZ for metabolites associated with neurodevelopment and body composition (particularly lean mass) may serve as a useful reference against which to identify metabolic age compared to chronological age. Betaine and choline, are important precursors for acetylcholine (a neurotransmitter) and phospholipid (an important structural and signalling component of cell membrane), and low levels in animals are associated with neurodevelopmental delay [61]. Choline is a also a precursor for betaine synthesis which is used to form homocysteine and me-thionine, essential for protein synthesis and linear growth [62] and higher urinary levels of choline in the first few weeks of life are seen in breastfed infants [63]. A low urinary 3-methylhistidine/creatinine ratio has been shown to be positively correlated with body weight and tissue accretion [63]. Preterm infants with plateauing or decreasing weight have been shown to have 3-methylhistidine/creatinine ratios above normal range [34], and developing PAZ for these metabolites would complement existing work [13,44]. Other significant differences in urinary metabolic signatures in preterm infants include increased 3hydroxyisovalerate (3-HVA), with decreased dimethylamine (DMA) and 1-methylhistidine which are related to gut microbiome and muscle protein turnover [44]. Aberrance with regard to these metabolites leads to poor nutrient utilisation and development of skeletal and lean muscle mass. Finally, with regard to energy balance, preterm infants have significantly lower urinary concentrations of succinic acid and lactose compared to term infants [44,62] and this in part may be due to age related differences in TCA cycle activity. Higher losses of these end products of metabolism appear to be related to growth faltering resulting in poor weight gain [63], suggesting there may be windows of opportunity for intervention if higher urinary levels than phenome age z scores were found. Further research is required to understand the temporal relationships between urinary metabolites of interest and growth in preterm infants.

Limitations
This is a scoping review to present the current range of evidence specific to urinary metabolites in preterm infants compared to healthy newborns. A significant issue that this review highlights is the relative lack of longitudinal data describing metabolic maturation within these infant cohorts, which is why the literature included in this scoping review explores what is known about urinary metabolomics in preterm infants. Given this, it was not possible to meta-analyse the results or reliably identify metabolites associated with metabolic stability and growth to allow the development of phenome age z scores.

Future Research Priorities
Future research is required to describe and define the normal range for urinary metabolites in healthy infants and those with complex disease and of different gestational age to allow the development of PAZ charts for metabolites of interest. This in turn may allow age, and disease specific nutritional interventions. As suggested by Gallouri et al. [13] a priority should be to develop age-specific reference curves for urinary metabolites in preterm infants compared to healthy infants. However, the development of aggregated PAZ for metabolites of interest requires large numbers and longitudinal data. Collaborative efforts to develop these would provide a unique opportunity to further our insight into better supporting ideal growth within these vulnerable infant cohorts.
Developing a better understanding of this relationship [6,13] will help (i) refine our understanding of phenotypic and metabolic responses to nutritional interventions, (ii) provide an opportunity to identify nutritional supplementation, (iii) define age related reference ranges for specific metabolites and (iv) identify specific windows in which targeted supplementation might improve growth outcomes considering metabolic maturity rather than chronological maturity [13,[24][25][26].

Conclusions
The results of this scoping suggest that preterm birth is associated with particular metabolic signatures, and that these signatures change in relation to both increasing PMA and in response to certain patterns of nutrition. However, considerable gaps in our knowledge remain, relating to metabolic maturation of infants, especially those born preterm. Although medical and nutritional management of these infants has significantly improved, a proportion continues to be growth constrained despite adequate nutritional support, for reasons that are unclear. Characterising metabolites of interest and developing PAZ for metabolites associated with the metabolic maturation and growth may elucidate windows of opportunity for nutrition supplementation allowing early intervention before growth failure is identified using anthropometry alone.

Conflicts of Interest:
The authors declare no conflict of interest. Provide an explicit statement of the questions and objectives being addressed with reference to their key elements (e.g., population or participants, concepts, and context) or other relevant key elements used to conceptualize the review questions and/or objectives.    (7) and the JBI guidance (4,5) refer to the process of data extraction in a scoping review as data charting. § The process of systematically examining research evidence to assess its validity, results, and relevance before using it to inform a decision. This term is used for items 12 and 19 instead of "risk of bias" (which is more applicable to systematic reviews of interventions) to include and acknowledge the various sources of evidence that may be used in a scoping review (e.g., quantitative and/or qualitative research, expert opinion, and policy document).