Influencing the extremes of growth : too tall - too small

Growth is an important indicator of physical and emotional well-being in childhood. Deviations from the normal range both for height and for height velocity may indicate an underlying congenital or acquired problem. A thorough understanding of the factors influencing the process of normal growth is essential in order to understand the pathophysiology of extremes of growth

Growth hormone treatment in children with short stature born small for gestational age: 5-year results of a randomized, double-blind, dose-response trial

The growth-promoting effect of continuous GH treatment was evaluated over 5 yr in 79 children with short stature (height SD score, less than -1.88) born small for gestational age (SGA; birth length SD score, less than -1.88). Patients were randomly and blindly assigned to 1 of 2 GH dosage groups (3 vs. 6 IU/m2 body surface-day). GH deficiency was not an exclusion criterium. After 5 yr of GH treatment almost every child had reached a height well within the normal range for healthy Dutch children and in the range of their target height SD score. Only in children who remained prepubertal during the study period was the 5-yr increase in height SD score (HSDS) for chronological age significantly higher in the study group receiving 6 compared to 3 IU GH/m2 x day. Remarkably, the 5-yr increment in HSDS for chronological age was not related to spontaneous GH secretion, maximum GH levels after provocation, or baseline insulin-like growth factor I levels. GH treatment was associated with an acceleration of bone maturation regardless of the GH dose given. The HSDS for bone age and predicted adult height increased significantly. GH treatment was well tolerated. In conclusion, our 5-yr data show that long term continuous GH treatment at a dose of 3 or 6 IU/m2 x day in short children born SGA results in a normalization of height during childhood followed by growth along the target height percentile

Plasma lipid profiles discriminate bacterial from viral infection in febrile children

Fever is the most common reason that children present to Emergency Departments. Clinical signs and symptoms suggestive of bacterial infection ar

The diagnostic value of nasal microbiota and clinical parameters in a multi-parametric prediction model to differentiate bacterial versus viral infections in lower respiratory tract infections

Background The ability to accurately distinguish bacterial from viral infection would help clinicians better target antimicrobial therapy during suspected lower respiratory tract infections (LRTI). Although technological developments make it feasible to rapidly generate patient-specific microbiota profiles, evidence is required to show the clinical value of using microbiota data for infection diagnosis. In this study, we investigated whether adding nasal cavity microbiota profiles to readily available clinical information could improve machine learning classifiers to distinguish bacterial from viral infection in patients with LRTI. Results Various multi-parametric Random Forests classifiers were evaluated on the clinical and microbiota data of 293 LRTI patients for their prediction accuracies to differentiate bacterial from viral infection. The most predictive variable was C-reactive protein (CRP). We observed a marginal prediction improvement when 7 most prevalent nasal microbiota genera were added to the CRP model. In contrast, adding three clinical variables, absolute neutrophil count, consolidation on X-ray, and age group to the CRP model significantly improved the prediction. The best model correctly predicted 85% of the 'bacterial' patients and 82% of the 'viral' patients using 13 clinical and 3 nasal cavity microbiota genera (Staphylococcus, Moraxella, and Streptococcus). Conclusions We developed high-accuracy multi-parametric machine learning classifiers to differentiate bacterial from viral infections in LRTI patients of various ages. We demonstrated the predictive value of four easy-to-collect clinical variables which facilitate personalized and accurate clinical decision-making. We observed that nasal cavity microbiota correlate with the clinical variables and thus may not add significant value to diagnostic algorithms that aim to differentiate bacterial from viral infections

Antibiotic misuse in respiratory tract infections in children and adults—a prospective, multicentre study (TAILORED Treatment)

Respiratory tract infections (RTI) are more commonly caused by viral pathogens in children than in adults. Surprisingly, little is known about antibiotic use in children as compared to adults with RTI. This prospective study aimed to determine antibiotic misuse in children and adults with RTI, using an expert panel reference standard, in order to prioritise the target age population for antibiotic stewardship interventions. We recruited children and adults who presented at the emergency department or were hospitalised with clinical presentation of RTI in The Netherlands and Israel. A panel of three experienced physicians adjudicated a reference standard diagnosis (i.e. bacterial or viral infection) for all the patients using all available clinical and laboratory information, including a 28-day follow-up assessment. The cohort included 284 children and 232 adults with RTI (median age, 1.3 years and 64.5 years, respectively). The proportion of viral infections was larger in children than in adults (209(74%) versus 89(38%), p < 0.001). In case of viral RTI, antibiotics were prescribed (i.e. overuse) less frequently in children than in adults (77/209 (37%) versus 74/89 (83%), p < 0.001). One (1%) child and three (2%) adults with bacterial infection were not treated with antibiotics (i.e. underuse); all were mild cases. This international, prospective study confirms major antibiotic overuse in patients with RTI. Viral infection is more common in children, but antibiotic overuse is more frequent in adults with viral RTI. Together, these findings support the need for effective interventions to decrease antibiotic overuse in RTI patients of all ages