Childhood pneumonia - progress and challenges

No Abstract. South African Medical Journal Vol. 96(9) (Part 2) 2006: 890-89

Connecting species’ geographical distributions to environmental variables: range maps versus observed points of occurrence

Connecting the geographical occurrence of a species with underlying environmental variables is fundamental for many analyses of life history evolution and for modeling species distributions for both basic and practical ends. However, raw distributional information comes principally in two forms: points of occurrence (specific geographical coordinates where a species has been observed), and expert-prepared range maps. Each form has potential short-comings: range maps tend to overestimate the true occurrence of a species, whereas occurrence points (because of their frequent non-random spatial distribution) tend to underestimate it. Whereas previous comparisons of the two forms have focused on how they may differ when estimating species richness, less attention has been paid to the extent to which the two forms actually differ in their representation of a species’ environmental associations. We assess such differences using the globally distributed avian order Galliformes (294 species). For each species we overlaid range maps obtained from IUCN and point-of-occurrence data obtained from GBIF on global maps of four climate variables and elevation. Over all species, the median difference in distribution centroids was 234 km, and median values of all five environmental variables were highly correlated, although there were a few species outliers for each variable. We also acquired species’ elevational distribution mid-points (mid-point between minimum and maximum elevational extent) from the literature; median elevations from point occurrences and ranges were consistently lower (median −420 m) than mid-points. We concluded that in most cases occurrence points were likely to produce better estimates of underlying environmental variables than range maps, although differences were often slight. We also concluded that elevational range mid-points were biased high, and that elevation distributions based on either points or range maps provided better estimates

Lung function in South African children with cystic fibrosis

Objective: To determine the pattern of lung function in stable cystic fibrosis (CF) patients and to investigate the relationship of abnormal lung function to demographic variables, CF genotype and pulmonary colonisation with Pseudomonas aeruginosa (PA)Design: A descriptive study done at the CF clinic at Red Cross War Memorial Children's Hospital in Cape Town.Methods: Data were recorded and pulmonary function testing (PFT) was performed in 42 CF patients.Results: 29 patients (69%) had mild disease,. while 11 (26%) and 2 (5%) had moderate and severe disease respectively. Twenty-four patients (57'%) demonstrated lower airway obstruction (LAO). Patients with moderate or severe disease were significantly older than those with mild disease (13.3 (3.7) years (mean (SD)) compared with 11.1 (3.0) years (t =2.1; P =OM)). PA colonisation status differed significantly with the pattern of lung function (X2 =6.6; P = 0.04) and severity of lung disease (X2=12.6; P =0.002.). Nine (35%) of the 26 patients tested before and after broncbodilator therapy showed a positive response.Conclusion: The majority of patients had mildly impaired or normal lung function, with LAO predominating. A minority of patients were bronchodilator-responsive. PA colonisation may be associated with the development of abnormal lung function and more severe pulmonary disease.

Seasonal abundance of small cladocerans in Lake Mangakaware, Waikato, New Zealand

The seasonal changes in the dynamics and life histories of the Cladocera in Lake Mangakaware, North Island, New Zealand, were studied over 19 months by sampling at weekly or 2-weekly intervals. Lake Mangakaware is a 13.3 ha polymictic lake with high nutrient status, low Secchi disc transparencies, and an unstable thermal regime. The four planktonic cladoceran species (Bosmina longirostris, B. meridionalis, Ceriodaphnia pulchella, and C. dubia) exhibited disjunct population maxima. Only B. longirostris was perennially present. All species exhibited low fecundities and low lipid content, indicating that food resources were limited and that competitive interactions and resistance to starvation were probably important in determining species success. Increases in body size in cooler seasons were unrelated to clutch size, giving further support for the view that available food was limited. These results are consistent with previous experimental findings that subtle differences in life history can determine seasonal success and the outcome of competition between similar species

Issues in the determination of “responders” and “non‐responders” in physiological research

As a follow-up to our 2015 review, we cover more issues on the topic of “response heterogeneity”, which we define as clinically-important individual differences in the physiological responses to the same treatment or intervention that cannot be attributed to random within-subjects variability. We highlight various pitfalls with the common practice of counting the number of “responders”, “non-responders” and “adverse responders” in samples that have been given certain treatments/interventions for research purposes. We focus on the classical parallel-group randomised controlled trial (RCT) design and assume typical good practice in trial design.We show that sample responder counts are biased because individuals differ in terms of pre-to-post within-subjects random variability in the study outcome(s) and not necessarily treatment response. Ironically, sample differences in responder counts may be explained wholly by sample differences in mean response, even if there is no response heterogeneity at all. Sample comparisons of responder counts also have relatively low statistical precision. These problems do not depend on how the response threshold has been selected, e.g. on the basis of a measurement error statistic, and are not rectified fully by the use of confidence intervals for individual responses in the sample