FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2562759091> ?p ?o ?g. }

• W2562759091 endingPage "285" @default.
• W2562759091 startingPage "269" @default.
• W2562759091 abstract "Congenital talipes equinovarus (CTEV), or clubfoot, is a structural malformation that develops early in gestation. Birth prevalence of clubfoot is reported to vary both between and within low- and middle-income countries (LMICs), and this information is needed to plan treatment services. This systematic review aimed to understand the birth prevalence of clubfoot in LMIC settings. Six databases were searched for studies that reported birth prevalence of clubfoot in LMICs. Results were screened and assessed for eligibility using pre-defined criteria. Data on birth prevalence were extracted and weighted pooled estimates were calculated for different regions. Wilcoxon rank-sum test was used to examine changes in birth prevalence over time. Included studies were appraised for their methodological quality, and a narrative synthesis of findings was conducted. Forty-eight studies provided data from 13 962 989 children in 20 countries over 55 years (1960–2015). The pooled estimate for clubfoot birth prevalence in LMICs within the Africa region is 1.11 (0.96, 1.26); in the Americas 1.74 (1.69, 1.80); in South-East Asia (excluding India) 1.21 (0.73, 1.68); in India 1.19 (0.96, 1.42); in Turkey (Europe region) 2.03 (1.54, 2.53); in Eastern Mediterranean region 1.19 (0.98, 1.40); in West Pacific (excluding China) 0.94 (0.64, 1.24); and in China 0.51 (0.50, 0.53). Birth prevalence of clubfoot varies between 0.51 and 2.03/1000 live births in LMICs. A standardised approach to the study of the epidemiology of clubfoot is required to better understand the variations of clubfoot birth prevalence and identify possible risk factors. Le pied bot (varus équin) congénital est une malformation structurale qui se développe au début de la gestation. La prévalence de naissance du pied bot varie à la fois entre et au sein des pays à faible revenu et à revenu intermédiaire (PRF-RI) et cette information est nécessaire pour planifier les services de traitement. Cette revue systématique a pour but de comprendre la prévalence de naissance du pied bot dans les PRF-RI. Six bases de données ont été recherchées pour les études rapportant la prévalence de la naissance du pied bot dans les PRF-RI. Les résultats ont été examinés et évalués pour l'admissibilité en utilisant des critères prédéfinis. Les données sur la prévalence des naissances ont été extraites et les estimations poolées pondérées ont été calculées pour différentes régions. Le test de la somme de rang de Wilcoxon a été utilisé pour examiner les changements dans la prévalence de naissance au fil du temps. Les études incluses ont été évaluées pour leur qualité méthodologique et une synthèse narrative des résultats a été menée. 48 études ont fourni des données de 13 962 989 enfants dans 20 pays sur 55 ans (1960 - 2015). L'estimation poolée de la prévalence de naissance du pied bot dans les PRF-RI de la région Afrique est de 1,11 (0,96 - 1,26); dans les Amériques 1,74 (1,69 - 1,80); en Asie du sud-est (hors Inde) 1,21 (0,73 - 1,68); en Inde 1,19 (0,96 - 1,42); en Turquie (Région Europe) 2,03 (1,54 - 2,53); dans la région de la Méditerranée orientale 1,19 (0,98, 1,40); dans le Pacifique occidental (hors Chine) 0,94 (0,64 - 1,24) et en Chine 0,51 (0,50 - 0,53). La prévalence de naissance du pied bot varie entre 0,51 et 2,03/1 000 naissances vivantes dans les PRF-RI. Une approche standardisée pour l’étude de l’épidémiologie du pied bot est nécessaire pour mieux comprendre les variations de la prévalence de naissance du pied bot et identifier les facteurs de risque possibles. El pie equinovaro congénito (PEC) o pie zambo es una malformación estructural que se desarrolla durante etapas tempranas de la gestación. Se ha reportado que la prevalencia al nacer del pie zambo varía entre y dentro de países con ingresos bajos y medios (PIBMs) y esta información es necesaria con el fin de planificar los servicios de tratamiento. Esta revisión sistemática busca entender la prevalencia al nacer del pie zambo en PIBMs. Se realizó la búsqueda en seis bases de datos para estudios que reportaran la prevalencia del pie equinovaro congénito en PIBMs. Los resultados fueron revisados y evaluados para determinar su elegibilidad utilizando criterios predefinidos. Los datos sobre prevalencia al nacer se extrajeron y se calcularon estimaciones ponderadas agrupadas para las diferentes regiones. Se utilizó la prueba de Wilcoxon para examinar los cambios en la prevalencia al nacer a lo largo del tiempo. De los estudios incluídos se evaluó la calidad metodológica, y se realizó la síntesis narrativa de los hallazgos. 48 estudios proveyeron datos de 13,962,989 niños en 20 países y a lo largo de 55 años (1960 – 2015). El cálculo estimado agrupado de la prevalencia del pie equinovaro al nacer en PIBMs dentro de la región Africana es de 1.11 (0.96, 1.26); en las Américas 1.74 (1.69,1.80); en el Sudeste Asiático (excluyendo India) 1.21 (0.73, 1.68); en India 1.19 (0.96, 1.42); en Turquía (Región Europea) 2.03 (1.54, 2.53); en el Mediterráneo Oriental 1.19 (0.98, 1.40); en el Pacífico Occidental (excluyendo China) 0.94 (0.64, 1.24) y en China 0.51 (0.50, 0.53). La prevalencia al nacer del pie equinovaro varía entre 0.51 y 2.03/1,000 nacidos vivos en PIBMs. Se requiere una metodología estandarizada para el estudio de la epidemiología del pie equinovaro con el fin de entender mejor las variaciones en la prevalencia al nacer del pie zambo, e identificar los posibles factores de riesgo. Congenital anomalies, also known as birth defects, are one of the leading causes of disability in children 1. Clubfoot, or congenital talipes equinovarus (CTEV), is one of the most common congenital deformities that cause mobility impairment 2. The structure and position of the foot are affected, and untreated clubfoot results in pain and reduced mobility, which potentially leads to participation restrictions and activity limitation 3. Clubfoot forms in the early weeks of gestational development, and this may be part of specific syndromes or secondary to neurologic or systemic disease. However, the majority of cases occur in isolation and are termed ‘idiopathic’ 4, the cause of which is not fully understood 5. Genetic factors have been implied 6, 7, while environmental factors, for example seasonal variation and intrauterine immobility, have been reported in some studies 5, 8. Associations with ethnicity are not clear. Other risk factors that have been reported are male gender 9-11, maternal smoking 10-15 and maternal diabetes 10, 13. However, the underlying pathogenesis for these factors remains a matter of scientific debate. A multifactorial aetiologic model that involves both environmental and genetic factors is likely 8. Epidemiological studies consistently report higher birth prevalence 16 of idiopathic clubfoot in males and in firstborn children 17. The condition is bilateral in half of the cases 18. Typically, a small set of statistics are routinely cited for birth prevalence of clubfoot with reports of 0.39 per 1000 births in Chinese populations, 1.1 per 1000 in Caucasian and 6.8 per 1000 in Polynesian populations 19. Overall, it is estimated that 80% of children born with clubfoot each year live in low- and middle-income countries (LMICs) 18. Accurate collection of data on population birth rate and prevalence of birth defects is essential to plan, initiate and develop healthcare services. The aim of this study was to conduct a systematic literature review to estimate the birth prevalence of clubfoot in different World Health Organisation (WHO) regions, in order to inform planning of services and programme management in LMICs. The systematic review was planned, conducted and reported according to established MOOSE (Meta-analysis of Observational Studies in Epidemiology) guidelines 20 (Appendix S1). A systematic literature search was conducted in January 2016 for peer-reviewed articles that presented original research findings on the birth prevalence of clubfoot in LMIC settings. EMBASE, Medline, Global Health, LLACS, Africa-Wide Information and the Cumulative Index to Nursing and Allied Health Literature (CINAHL) were examined for studies published between January 1960 and December 2015 to capture 55 years of data. It was hypothesised that studies that reported on several congenital birth deformities may not include clubfoot in the search terms. Consequently, to capture all relevant studies, a search was carried out using both birth defects and clubfoot terms, with LMIC keywords. Boolean, truncation and proximity operators were used to construct and combine searches for the key concepts as required for individual databases, and an example is available as Appendix S2. The articles returned by the literature search were screened by one reviewer (TS) first by title and then by abstract. 10% of the abstracts were reviewed by a second reviewer (HK) to check for agreement. The full text was obtained for any paper that was included at abstract screening. Studies of all languages were included and translated as required. The reference list of all included studies was examined for further relevant studies. All full texts were reviewed independently by two reviewers (TS and either AF, CL or HK), and differences were agreed by discussion. The search strategy is presented in Figure 1. Congenital talipes equinovarus (CTEV) was defined as a rigid deformity where the foot is fixed in a plantarflexed, supinated and adducted position. Studies were eligible if they met the following criteria: (1) original research that included CTEV; (2) results reported, or allowed calculation of, birth prevalence of clubfoot; (3) all children were screened for clubfoot; and (4) undertaken in a LMIC as defined by the World Bank country classification 2015. Exclusion criteria comprised the following: (1) full text unavailable, (2) unclear that all children were screened for clubfoot (e.g. large reviews of medical records), (3) unclear source population that prevented clear definition of the population denominator or (4) duplicate reports from the same study. Data were extracted from articles that met inclusion criteria according to The Centre for Reviews and Dissemination guidelines 21. The following data were extracted: All extracted values were examined by the second reviewer to ensure accuracy. Differences between the reviewers were discussed, and a consensus was reached on all papers. One author was contacted for further information. Data reporting per 1000 births were assumed to be live births unless it was stated that stillbirths were included. Birth prevalence rates were calculated per 1000 live births with 95% confidence intervals (Wilson score intervals), on the basis of the binomial distribution using Stata 14.0 (StataCorp LP, College Station, Texas), from the reported study population and the number of babies identified with clubfoot. It was decided a priori that the populations of China and India would be analysed independently of their WHO region due to their large population size. Tests for heterogeneity were performed. Weighted summary measures were estimated for the six WHO regions, India and China with a random-effects model 22 in the meta-analysis. The relative weight that each study contributed was defined by the sample size of the study. The overall effect estimate is therefore a weighted combination of the studies that contribute to it. Summary measures were graphed with forest plots. As the time frame for the included studies is wide, an analysis was undertaken to identify whether the birth prevalence of clubfoot was different in the oldest estimates. A two-sample Wilcoxon rank-sum (Mann–Whitney) test was used to compare the birth prevalence in the time periods 1960–1985 and 1986–2015, consisting of 25 and 30 years, respectively. Cases born per million total population per year were estimated according to regional clubfoot birth prevalence and crude birth rate per 1000 people. The Global Health Observatory data repository provided estimates of crude birth rate. A total of 1835 studies were retrieved for assessment (Figure 1). Of these, 72 studies reported on birth prevalence of clubfoot and provided data from 25 countries (Appendix S3). Twenty-four full texts were excluded, of which 16 papers were retrospective data collection and analysis and it was unclear whether all children were screened (Appendix S4 contains details on the studies excluded). Therefore, 48 studies were selected for inclusion and provided data from 13 962 989 children in 20 countries. Table 1 summarises the characteristics of the studies eligible for inclusion. All the studies drew cases from a hospital setting. Eight of 37 studies (21.6%) that used a prospective design with physical examination were undertaken in more than one hospital 23-30. Nine studies used a large database review in settings where there was systematic screening for clubfoot 31-39, one study analysed data from a single hospital defects monitoring system 40 and one study used a cluster sample survey 41. Thirteen papers (27%) were from the South-East Asia region, with 11 papers in the region published from India. The West Pacific region consisted primarily of research undertaken in China and used large database reviews. Turkey was the only LMIC represented in Europe. 1 Hospital [General RSUPP Medan] The pooled estimates for clubfoot birth prevalence for Africa (1.11 [0.96, 1.26]), South-East Asia (1.21 [0.73, 1.68]), India (1.19 [0.96, 1.42]) and the Eastern Mediterranean region (1.19 [0.98, 1.40]) are similar. The pooled estimate for clubfoot birth prevalence in LMICs within the Americas region is 1.74 (1.69, 1.80); in Turkey (Europe region) 2.03 (1.54, 2.53); and in West Pacific (excluding China) 0.94 (0.64, 1.24). The birth prevalence is lowest in China at 0.51 (0.50, 0.53). Analysis of the birth prevalence of clubfoot reported in two date ranges (1960–1985 and 1986–2015) demonstrated no evidence of a difference over time (P = 0.56). A meta-analysis by region was undertaken (Figures 2-9). The individual study results are displayed in the first column, identified under ‘Study’. The summary birth prevalence is displayed in the final row with the test for heterogeneity denoted as I2 (if I2 ≤ 25%, studies are regarded as homogeneous). The second column visually displays the study results. The third column is the summary estimate of the birth prevalence of clubfoot, denoted by ES (95% CI) or effect size. This column gives the corresponding numerical results. The vertical line is the pooled estimate of birth prevalence, and the x-axis is the value of clubfoot cases per 1000 live births. The size of the box is directly related to the ‘weighting’ of the study in the meta-analysis, and the weight in % in the final column indicates the influence of the study on the overall results. The horizontal lines through the boxes depict the length of the confidence intervals. The diamond in the last row of the graph illustrates the overall result of the meta-analysis. The middle of the diamond sits on the value of the summary birth prevalence, and the width of the diamond depicts the width of the overall CI. Based on the evidence since 1960, figures to plan for clubfoot management can be calculated for the eight populations given the birth rate per million population (Table 2). Population numbers are based on WHO region population birth rates. For planning purposes, regional estimates of birth prevalence should be applied to country specific birth rates. This review summarises 48 studies of clubfoot birth prevalence from LMIC settings with data from 13 962 989 children in 20 countries. To our knowledge, this is the first systematic review of birth prevalence of clubfoot. The results demonstrate a range in birth prevalence from 0.51 (0.50, 0.53) per 1000 live births in China to 2.03 (1.54, 2.53) per 1000 in Turkey. Pooled estimates of birth prevalence rates appear to be similar in Africa, South-East Asia and Eastern Mediterranean regions and India. There was no evidence for a difference in clubfoot birth prevalence in LMICs between 1960–1985 and 1986–2015. The case numbers and denominator population size differ in the individual studies included in the meta-analyses. The birth prevalence of clubfoot in China is strongly influenced by two large outlier studies 32, 36 that decrease the pooled estimate. Both studies were database reviews of data from hospitals that monitored birth defects through physical examination, and the data were collated on a congenital anomaly registration form. The authors note it is possible that cases were missed. Alternatively, the data may represent a unique feature of inheritance in the idiopathic clubfoot population of China. Only two papers contribute to the estimates of Turkey and the South-East Asia region with combined screened populations of 31 854 and 20 637 children, respectively. Many LMICs lack rigorous congenital anomaly surveillance programmes 72, which makes calculation of birth prevalence difficult. Current estimates range from 4 to 12 cases per 1000 births 73 in LMIC settings. These are likely underestimated due to stigma and exclusion 74 and are also reliant on case definition and robust screening methods. This analysis suggests some variation in the birth prevalence of clubfoot as previously indicated 75; however, the range is not as large as reported by others 19. Except for China, there were similar estimates across the regions. Current data heterogeneity suggests the resulting variation in clubfoot birth prevalence in LMICs is likely influenced by study design and data collection methods and possibly by region and therefore ethnicity as well. Case definition, the case mix between tertiary and secondary facilities and the training of observers may affect prospective reporting of clubfoot. The true birth prevalence will be affected by risk factors, genetic and/or environmental, most of which are unknown. A strength of this study is the relatively large population denominator in several regions. It includes all categories of structural clubfoot (e.g. idiopathic or syndromic) as treatment is required in all cases although outcomes may differ. Data were excluded from clinics where it was not clear from the report how many babies were examined and did not have clubfoot, as birth prevalence cannot be calculated without a denominator. This has resulted in the exclusion of some studies 76, 77 that are regularly cited. This review is limited by the quality and representation of the available data from LMICs. The estimated birth prevalence of clubfoot will be useful for the planning of services and to better estimate areas of need for country programmes. For instance, one equipped clinic in each district of 1 million people will be sufficient to handle clubfoot treatment if the new case load is up to 43 cases of clubfoot each year, as estimated by this review. Screening at birth for clubfoot is important, so that cases can be detected and treated early, when treatment is most effective. Scaling up appropriate services for screening and treatment remains a priority. Future studies should ensure that a clear case definition and robust screening methods are undertaken to allow comparison of epidemiological data. Clubfoot is relatively common and should be detected at birth. There is no evidence for a large variation in birth prevalence between regions or of the folklore about a high Polynesian birth prevalence. Comparison of prevalence figures for congenital malformations reported from different parts of the world requires clear case definition and comparable methods of data collection. The published data over the last 55 years for clubfoot in LMIC suggest a birth prevalence in the range of 0.5 to 2.0 cases/1000 live births, which results in an estimated 7–43 cases of clubfoot/year/million population, dependent mainly on birth rate. The regional figures, for example in sub-Saharan Africa of approximately 43 cases/year/million population, provide useful information on planning treatment services for clubfoot in LMIC. A standardised approach to the study of the epidemiology of clubfoot is required to better understand the variations of the birth prevalence of clubfoot and possible risk factors. This work was supported by The Beit Trust and CBM. Appendix S1. MOOSE Checklist [for Meta-analysis Of Observational Studies in Epidemiology]. Appendix S2. Search terms for clubfoot and birth defects and LMICs. Appendix S3. Papers reporting CTEV birth prevalence published by year and WHO region prior to quality assessment. Appendix S4. Full text excluded studies. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article." @default.
• W2562759091 created "2017-01-06" @default.
• W2562759091 creator A5018888984 @default.
• W2562759091 creator A5035626211 @default.
• W2562759091 creator A5074024352 @default.
• W2562759091 creator A5075248766 @default.
• W2562759091 creator A5091416564 @default.
• W2562759091 date "2017-01-22" @default.
• W2562759091 modified "2023-10-12" @default.
• W2562759091 title "Birth prevalence of congenital talipes equinovarus in low- and middle-income countries: a systematic review and meta-analysis" @default.
• W2562759091 cites W1487355251 @default.
• W2562759091 cites W1504861118 @default.
• W2562759091 cites W1963861895 @default.
• W2562759091 cites W1968660943 @default.
• W2562759091 cites W1976917743 @default.
• W2562759091 cites W1979423827 @default.
• W2562759091 cites W1981549897 @default.
• W2562759091 cites W1995607200 @default.
• W2562759091 cites W1996335901 @default.
• W2562759091 cites W2000481808 @default.
• W2562759091 cites W2002967400 @default.
• W2562759091 cites W2013239980 @default.
• W2562759091 cites W2022752922 @default.
• W2562759091 cites W2027135955 @default.
• W2562759091 cites W2028056268 @default.
• W2562759091 cites W2035284367 @default.
• W2562759091 cites W2042270974 @default.
• W2562759091 cites W2043073846 @default.
• W2562759091 cites W2046062877 @default.
• W2562759091 cites W2050096704 @default.
• W2562759091 cites W2051581901 @default.
• W2562759091 cites W2052266018 @default.
• W2562759091 cites W2054268328 @default.
• W2562759091 cites W2056428077 @default.
• W2562759091 cites W2057671524 @default.
• W2562759091 cites W2058683355 @default.
• W2562759091 cites W2063287476 @default.
• W2562759091 cites W2064683612 @default.
• W2562759091 cites W2065836864 @default.
• W2562759091 cites W2066048508 @default.
• W2562759091 cites W2069852280 @default.
• W2562759091 cites W2071658829 @default.
• W2562759091 cites W2093302935 @default.
• W2562759091 cites W2105787554 @default.
• W2562759091 cites W2106005673 @default.
• W2562759091 cites W2114734109 @default.
• W2562759091 cites W2121025180 @default.
• W2562759091 cites W2133564174 @default.
• W2562759091 cites W2149967826 @default.
• W2562759091 cites W2168922114 @default.
• W2562759091 cites W2253819654 @default.
• W2562759091 cites W2274701970 @default.
• W2562759091 doi "https://doi.org/10.1111/tmi.12833" @default.
• W2562759091 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/28000394" @default.
• W2562759091 hasPublicationYear "2017" @default.
• W2562759091 type Work @default.
• W2562759091 sameAs 2562759091 @default.
• W2562759091 citedByCount "76" @default.
• W2562759091 countsByYear W25627590912017 @default.
• W2562759091 countsByYear W25627590912018 @default.
• W2562759091 countsByYear W25627590912019 @default.
• W2562759091 countsByYear W25627590912020 @default.
• W2562759091 countsByYear W25627590912021 @default.
• W2562759091 countsByYear W25627590912022 @default.
• W2562759091 countsByYear W25627590912023 @default.
• W2562759091 crossrefType "journal-article" @default.
• W2562759091 hasAuthorship W2562759091A5018888984 @default.
• W2562759091 hasAuthorship W2562759091A5035626211 @default.
• W2562759091 hasAuthorship W2562759091A5074024352 @default.
• W2562759091 hasAuthorship W2562759091A5075248766 @default.
• W2562759091 hasAuthorship W2562759091A5091416564 @default.
• W2562759091 hasBestOaLocation W25627590911 @default.
• W2562759091 hasConcept C141071460 @default.
• W2562759091 hasConcept C142724271 @default.
• W2562759091 hasConcept C18903297 @default.
• W2562759091 hasConcept C189708586 @default.
• W2562759091 hasConcept C2779305710 @default.
• W2562759091 hasConcept C2779473830 @default.
• W2562759091 hasConcept C2779982284 @default.
• W2562759091 hasConcept C2909241321 @default.
• W2562759091 hasConcept C3018472363 @default.
• W2562759091 hasConcept C55493867 @default.
• W2562759091 hasConcept C71924100 @default.
• W2562759091 hasConcept C83864248 @default.
• W2562759091 hasConcept C86803240 @default.
• W2562759091 hasConcept C95190672 @default.
• W2562759091 hasConceptScore W2562759091C141071460 @default.
• W2562759091 hasConceptScore W2562759091C142724271 @default.
• W2562759091 hasConceptScore W2562759091C18903297 @default.
• W2562759091 hasConceptScore W2562759091C189708586 @default.
• W2562759091 hasConceptScore W2562759091C2779305710 @default.
• W2562759091 hasConceptScore W2562759091C2779473830 @default.
• W2562759091 hasConceptScore W2562759091C2779982284 @default.
• W2562759091 hasConceptScore W2562759091C2909241321 @default.
• W2562759091 hasConceptScore W2562759091C3018472363 @default.
• W2562759091 hasConceptScore W2562759091C55493867 @default.
• W2562759091 hasConceptScore W2562759091C71924100 @default.
• W2562759091 hasConceptScore W2562759091C83864248 @default.

• next