Simplified models to assess newborn gestational age in low-middle income countries: findings from a multicountry, prospective cohort study

Introduction Preterm birth is the leading cause of child mortality. This study aimed to develop and validate programmatically feasible and accurate approaches to estimate newborn gestational age (GA) in low resource settings. Methods The WHO Alliance for Maternal and Newborn Health Improvement (AMANHI) study recruited pregnant women from population-based cohorts in five countries (Bangladesh, Ghana, Pakistan, Tanzania and Zambia). Women <20 weeks gestation by ultrasound-based dating were enrolled. Research staff assessed newborns for: (1) anthropometry, (2) neuromuscular/physical signs and (3) feeding maturity. Machine-learning techniques were used to construct ensemble models. Diagnostic accuracy was assessed by areas under the receiver operating curve (AUC) and Bland-Altman analysis. Results 7428 liveborn infants were included (n=536 preterm, <37 weeks). The Ballard examination was biased compared with ultrasound dating (mean difference: +9 days) with 95% limits of agreement (LOA) −15.3 to 33.6 days (precision ±24.5 days). A model including 10 newborn characteristics (birth weight, head circumference, chest circumference, foot length, breast bud diameter, breast development, plantar creases, skin texture, ankle dorsiflexion and infant sex) estimated GA with no bias, 95% LOA ±17.3 days and an AUC=0.88 for classifying the preterm infant. A model that included last menstrual period (LMP) with the 10 characteristics had 95% LOA ±15.7 days and high diagnostic accuracy (AUC 0.91). An alternative simpler model including birth weight and LMP had 95% LOA of ±16.7 and an AUC of 0.88. Conclusion The best machine-learning model (10 neonatal characteristics and LMP) estimated GA within ±15.7 days of early ultrasound dating. Simpler models performed reasonably well with marginal increases in prediction error. These models hold promise for newborn GA estimation when ultrasound dating is unavailable

Simplified models to assess newborn gestational age in low-middle income countries: findings from a multicountry, prospective cohort study.

INTRODUCTION: Preterm birth is the leading cause of child mortality. This study aimed to develop and validate programmatically feasible and accurate approaches to estimate newborn gestational age (GA) in low resource settings. METHODS: The WHO Alliance for Maternal and Newborn Health Improvement (AMANHI) study recruited pregnant women from population-based cohorts in five countries (Bangladesh, Ghana, Pakistan, Tanzania and Zambia). Women <20 weeks gestation by ultrasound-based dating were enrolled. Research staff assessed newborns for: (1) anthropometry, (2) neuromuscular/physical signs and (3) feeding maturity. Machine-learning techniques were used to construct ensemble models. Diagnostic accuracy was assessed by areas under the receiver operating curve (AUC) and Bland-Altman analysis. RESULTS: 7428 liveborn infants were included (n=536 preterm, <37 weeks). The Ballard examination was biased compared with ultrasound dating (mean difference: +9 days) with 95% limits of agreement (LOA) -15.3 to 33.6 days (precision ±24.5 days). A model including 10 newborn characteristics (birth weight, head circumference, chest circumference, foot length, breast bud diameter, breast development, plantar creases, skin texture, ankle dorsiflexion and infant sex) estimated GA with no bias, 95% LOA ±17.3 days and an AUC=0.88 for classifying the preterm infant. A model that included last menstrual period (LMP) with the 10 characteristics had 95% LOA ±15.7 days and high diagnostic accuracy (AUC 0.91). An alternative simpler model including birth weight and LMP had 95% LOA of ±16.7 and an AUC of 0.88. CONCLUSION: The best machine-learning model (10 neonatal characteristics and LMP) estimated GA within ±15.7 days of early ultrasound dating. Simpler models performed reasonably well with marginal increases in prediction error. These models hold promise for newborn GA estimation when ultrasound dating is unavailable

Female Rats are More Vulnerable to the Long-Term Consequences of Neonatal Inflammatory Injury

Premature infants are routinely exposed to invasive medical procedures during neonatal intensive care treatment that are largely performed in the absence of anesthetics or analgesics. Data collected to date suggest that exposure to early insult during this time of increased plasticity alters the development of the CNS and influences future pain responses. As previous studies examining the impact of neonatal injury on nociception have been conducted primarily in males, the potential adverse effects on females are not known. Therefore, the present studies were conducted to determine whether neonatal injury differentially impacts male and female sensory thresholds in adulthood. A short lasting inflammatory response was evoked in male and female rats on the day of birth with an injection of carrageenan (CGN; 1% or 2%) into the right hindpaw. Nociceptive thresholds were assessed using a noxious thermal stimulus at both adolescence (P40) and adulthood (P60). A more persistent inflammation was subsequently evoked in adult rats with an intraplantar injection of Complete Freund’s adjuvant (CFA). Neonatally injured females exhibited significantly greater hypoalgesia at P60, and displayed enhanced inflammatory hyperalgesia following re-injury in adulthood compared to neonatally injured males and controls. These results demonstrate that the long-term adverse effects of neonatal injury are exacerbated in females, and may contribute to the higher prevalence, severity and duration of pain syndromes noted in women compared to men

How does intrauterine crowding affect locomotor performance in newborn pigs? : a study of force generating capacity and muscle composition of the hind limb

Intrauterine crowding (IUC) considerably influences postnatal traits in a polytocous species such as the pig. Previously, our group described how IUC affects locomotion during the piglet's first days of life (until 96 h after birth). We noted a reduced motor performance in piglets with a low birth weight and low vitality (L piglets), compared to piglets with a normal birth weight and normal vitality (N piglets), indicating L piglets are unable to produce enough force. Our current study investigates whether this observed force deficit in L piglets is caused by a reduced force generating capacity in the muscles and/or a lower percentage of type II (fast-contracting) fibers. Volume and fiber length of the main extensor muscles of the hind limb were used to estimate the physiological cross-sectional area (PSCA) and hence calculate the maximal isometric force generating capacity (Fiso-max) of the hind limb. To check for developmental differences between the muscles of L and N piglets, Fiso-max was normalized to body weight (BW), thus yielding a dimensionless variable F'iso-max. To check for differences in muscle composition, m. vastus lateralis was stained immunohistochemically in order to determine the percentage of type II fibers through image analysis. Our results indicate that L piglets have a reduced absolute force generating capacity due to a lesser muscle mass, compared to N piglets. However, when normalized to BW L piglets actually show a larger force generating capacity, suggesting their muscles are more voluminous, given their body mass, than those of N piglets. However, no differences between L and N piglets were detected with regard to muscle composition of the m. vastus lateralis. Based on our data, we can say that neither normalized force generating capacity, nor muscle composition (of the m. vastus lateralis) can explain the observed force deficit in L piglets and as such the effect of IUC on locomotor performance

Gait characteristics and electromyographic activity in people with diabetes in early stages of the international working group on diabetic foot classification risk

Diabetes mellitus é uma doença metabólica e crónica grave, caracterizada por altos níveis glicémicos. Com a contínua expansão epidémica, a diabetes não é considerada apenas uma crise de saúde pública, mas uma catástrofe social global, responsável por uma elevada taxa de mortalidade e morbidade mundial. Mais de metade dos pacientes com diabetes há mais de 20 anos desenvolve neuropatia periférica diabética, uma das complicações mais comum e dispendiosa da diabetes. A neuropatia periférica diabética tem sido associada a alterações biomecânicas na marcha, principalmente no membro inferior. De facto, com a alteração do padrão de marcha como uma característica comum desta doença, a análise de marcha de sujeitos diabéticos com neuropatia periférica tem sido objeto de vários estudos. A avaliação da marcha visa aumentar o conhecimento e compreensão da marcha humana, seja como por si só um objetivo, ou de forma a melhorar o diagnóstico e tratamento médico no futuro. Em pacientes diabéticos com neuropatia periférica, a análise tridimensional de movimento permite o estudo e identificação de estratégias de movimento ou musculosqueléticas e pode ser útil para detetar, numa fase inicial, a influência da neuropatia periférica na marcha e no desempenho dos membros inferiores, fornecendo informações decisivas sobre a evolução, características e consequências prejudiciais desta doença. Este estudo teve como objetivo a caracterização da marcha e investigação de desvios na atividade eletromiográfica de sujeitos diabéticos em fases iniciais do Sistema de Classificação de Risco do Grupo de Trabalho Internacional em Pé Diabético (the International Working Group on Diabetic Foot (IWGDF) Risk Classification System). Os dados foram gerados a partir de dois grupos: diabéticos sem neuropatia periférica (nível 0 do IWGDF) e diabéticos com neuropatia periférica, com doença arterial e/ou deformidade do pé (nível 2 do IWGDF). O estudo foi realizado no Laboratório de Biomecânica do Porto, Universidade do Porto (LABIOMEP-UP), através de um sistema de captura de movimento, sistema tridimensional de análise de marcha e quatro plataformas de força. A atividade eletromiográfica dos músculos gastrocnemius medialis e tibialis anterior de ambas as pernas foi avaliada ao longo do ciclo de marcha, em sincronia com o sistema de captura de movimento. Os participantes com neuropatia periférica apresentaram um conjunto de alterações evidentes na marcha, incluindo uma velocidade de marcha significativamente inferior, passos mais curtos, menor cadência, restrição da mobilidade articular dos membros inferiores e alteração dos padrões eletromiográficos dos músculos dos membros inferiores. O grupo neuropata apresentou também valores de força de reação do solo inferiores em amplitude ao longo do ciclo de marcha e posteriores no tempo, o que poderá contribuir para as diferenças observadas na velocidade e cadência de marcha. No geral, os resultados deste estudo destacam as diferenças biomecânicas na marcha de pessoas com diabetes classificadas em grupos de risco distintos. Destaca também a importância da análise de marcha no fornecimento de conhecimento preciso e confiável das características de marcha e estratégias compensatórias adaptadas num dado instante, e também ao longo do tempo, como fator de prevenção, diagnóstico e inovação para a população diabética. No entanto, trabalho futuro é necessário de forma a avaliar os distúrbios da marcha na neuropatia periférica diabética, principalmente na marcha sob condições de 'vida real' em ambientes mais desafiadores, dinâmica inversa e momentos articulares. Estudos adicionais para identificar as alterações do padrão de atividade muscular e esclarecer os fatores específicos relacionados à neuropatia periférica diabética são também necessários.Diabetes mellitus is a serious metabolic and chronic disease, characterized by high blood glucose levels. As the epidemic continues to expand, diabetes is not only considered a health crisis, but a global societal catastrophe, responsible for great mortality and morbidity worldwide. More than half of patients who have diabetes for more than 20 years develop diabetic peripheral neuropathy, one of the most common and costly complication of diabetes. Diabetic peripheral neuropathy has been associated with biomechanical alterations in gait, particularly at the lower limb. Indeed, with alteration of walking patterns has a common characteristic of this disease, the gait analysis of diabetic patients with peripheral neuropathy has been the subject of several studies. Assessment of gait aims to increase the knowledge and understanding of the human gait, either as an end in itself or in order to improve medical diagnosis or treatment in the future. In diabetic patients with peripheral neuropathy, three-dimensional movement analysis allows the study and identification of movements and musculoskeletal strategies and may be useful to detect, in an early stage, the influence of peripheral neuropathy on walking and lower limbs performance, providing decisive information on the evolution, characteristics and detrimental consequences of this disease. The aim of this study was to characterize the gait and investigate electromyographic activity deviations of people with diabetes in early stages of the International Working Group on Diabetic Foot (IWGDF) Risk Classification System. Data were generated from two groups: diabetic subjects with no peripheral neuropathy (level 0 of the IWGDF) and diabetic subjects with peripheral neuropathy, with arterial disease and/or a foot deformity (level 2 of the IWGDF). The study was conducted in Porto Biomechanics Laboratory, University of Porto (LABIOMEP-UP) by means of a Motion Capture system (MoCap), 3Dinstrumented gait analysis system, and four force platforms. The electromyography activity of the gastrocnemius medialis and tibialis anterior muscles for both legs was monitored throughout the gait cycle, in synchrony with the MoCap system. A range of gait alterations were evident in participants with peripheral neuropathy including significantly slower gait speed, shorter steps, lower cadence, restriction of lower-limb joint mobility and altered electromyographic patterns of the lower limb muscles. This group also showed a trend to produce less ground reaction force in amplitude through the gait cycle and later in time, which could contribute for the differences observed in speed and cadence. Overall, the results of this study highlights the biomechanical differences in gait of people with diabetes classified in distinct risk groups. It’s also shown the importance of gait analysis to provide accurate and reliable knowledge of gait characteristics and compensatory strategies adopted at a given time, and also over time, as a factor for prevention, diagnosis and innovation for the diabetic population. Future research is necessary to evaluate gait disorders in diabetic peripheral neuropathy, particularly in terms of gait under ‘real-life’ conditions in more challenging environments, inverse dynamics and net joint moments. Further studies to identify the muscle activity pattern alterations, and clarify the specific factors related to diabetic peripheral neuropathy are also required

Papers on anthropology XIV

Eelkäija: Tartu Ülikooli toimetised. Antropoloogia-alaseid töid, ISSN 0207-4575http://www.ester.ee/record=b1339521*es

The Physical Examination of infants and children

ОСМОТР ДЕТЕЙОСМОТР НОВОРОЖДЕННЫХПЕДИАТРИЯПРОПЕДЕВТИКА ДЕТСКИХ БОЛЕЗНЕЙПособие для иностранных студентов знакомит с методикой проведения осмотра новорожденных и детей