Prognosis of patients with HIV-1 infection starting antiretroviral therapy in sub-Saharan Africa: a collaborative analysis of scale-up programmes

Background Prognostic models have been developed for patients infected with HIV-1 who start combination antiretroviral therapy (ART) in high-income countries, but not for patients in sub-Saharan Africa. We developed two prognostic models to estimate the probability of death in patients starting ART in sub-Saharan Africa. Methods We analysed data for adult patients who started ART in four scale-up programmes in Côte d'Ivoire, South Africa, and Malawi from 2004 to 2007. Patients lost to follow-up in the first year were excluded. We used Weibull survival models to construct two prognostic models: one with CD4 cell count, clinical stage, bodyweight, age, and sex (CD4 count model); and one that replaced CD4 cell count with total lymphocyte count and severity of anaemia (total lymphocyte and haemoglobin model), because CD4 cell count is not routinely measured in many African ART programmes. Death from all causes in the first year of ART was the primary outcome. Findings 912 (8·2%) of 11 153 patients died in the first year of ART. 822 patients were lost to follow-up and not included in the main analysis; 10 331 patients were analysed. Mortality was strongly associated with high baseline CD4 cell count (≥200 cells per μL vs <25; adjusted hazard ratio 0·21, 95% CI 0·17–0·27), WHO clinical stage (stages III–IV vs I–II; 3·45, 2·43–4·90), bodyweight (≥60 kg vs <45 kg; 0·23, 0·18–0·30), and anaemia status (none vs severe: 0·27, 0·20–0·36). Other independent risk factors for mortality were low total lymphocyte count, advanced age, and male sex. Probability of death at 1 year ranged from 0·9% (95% CI 0·6–1·4) to 52·5% (43·8–61·7) with the CD4 model, and from 0·9% (0·5–1·4) to 59·6% (48·2–71·4) with the total lymphocyte and haemoglobin model. Both models accurately predict early mortality in patients starting ART in sub-Saharan Africa compared with observed data. Interpretation Prognostic models should be used to counsel patients, plan health services, and predict outcomes for patients with HIV-1 infection in sub-Saharan Africa.

The pulmonary artery catheter: in medio virtus

OBJECTIVE: To clarify the role of the pulmonary artery catheter in the intensive care unit. DATA SOURCES: Recent and relevant literature from MEDLINE and authors' personal databases. STUDY SELECTION: Studies on pulmonary artery catheter use and use of other monitoring devices in critically ill patients. DATA EXTRACTION: Based largely on clinical experience and assessment of the relevant published literature and in response to recent articles attacking the pulmonary artery catheter, we propose that the pulmonary artery catheter is still a valuable tool for the hemodynamic monitoring of patients with complex disease processes in whom the information obtained from the pulmonary artery catheter may influence management. We suggest that there is a need to revisit the basics of hemodynamic management and reassess the way in which the pulmonary artery catheter is used, applying three key principles: correct measurement, correct data interpretation, and correct application. CONCLUSION: The pulmonary artery catheter is still a valuable tool for hemodynamic monitoring when used in selected patients and by physicians adequately trained to correctly interpret and apply the data provided.

Resolving diffusion in clay minerals at different time scales: Combination of experimental and modeling approaches

Since no single experimental or modeling technique provides data that allow a description of transport processes in clays and clay minerals at all relevant scales, several complementary approaches have to be combined to understand and explain the interplay between transport relevant phenomena. In this paper molecular dynamics simulations (MD) were used to investigate the mobility of water in the interlayer of montmorillonite (Mt), and to estimate the influence of mineral surfaces and interlayer ions on the water diffusion. Random Walk (RW) simulations based on a simplified representation of pore space in Mt were used to estimate and understand the effect of the arrangement of Mt particles on the meso- to macroscopic diffusivity of water. These theoretical calculations were complemented with quasielastic neutron scattering (QENS) measurements of aqueous diffusion in Mt with two pseudo-layers of water performed at four significantly different energy resolutions (i.e. observation times). The size of the interlayer and the size of Mt particles are two characteristic dimensions which determine the time dependent behavior of water diffusion in Mt. MD simulations show that at very short time scales water dynamics has the characteristic features of an oscillatory motion in the cage formed by neighbors in the first coordination shell. At longer time scales, the interaction of water with the surface determines the water dynamics, and the effect of confinement on the overall water mobility within the interlayer becomes evident. At time scales corresponding to an average water displacement equivalent to the average size of Mt particles, the effects of tortuosity are observed in the meso- to macroscopic pore scale simulations. Consistent with the picture obtained in the simulations, the QENS data can be described using a (local) 3D diffusion at short observation times, whereas at sufficiently long observation times a 2D diffusive motion is clearly observed. The effects of tortuosity measured in macroscopic tracer diffusion experiments are in qualitative agreement with RW simulations. By using experimental data to calibrate molecular and mesoscopic theoretical models, a consistent description of water mobility in clay minerals from the molecular to the macroscopic scale can be achieved. In turn, simulations help in choosing optimal conditions for the experimental measurements and the data interpretation. (C) 2014 Elsevier B.V. All rights reserved.

Quaternary refugia of the sweet chestnut (Castanea sativa Mill.): an extended palynological approach

Knowledge about the glacial refugia of the thermophilous European Castanea sativa Mill. (sweet chestnut) is still inadequate. Its original range of distribution has been masked by strong human impact. Moreover, under natural conditions the species was probably admixed with other taxa (such as Quercus, Fraxinus, Fagus, Tilia) and thus possibly represented by low percentages in pollen records. In this paper we try to overcome the difficulties related to the scarcity and irregularity of chestnut pollen records by considering 1471 sites and extending the palynological approach to develop a Castanea refugium probability index (IRP), aimed at detecting possible chestnut refugia where chestnuts survived during the last glaciation. The results are in close agreement with the current literature on the refugia of other thermophilous European trees. The few divergences are most probably due to the large amount of new data integrated in this study, rather than to fundamental disagreements about data and data interpretation. The main chestnut refugia are located in the Transcaucasian region, north-western Anatolia, the hinterland of the Tyrrhenian coast from Liguria to Lazio along the Apennine range, the region around Lago di Monticchio (Monte Vulture) in southern Italy, and the Cantabrian coast on the Iberian peninsula. Despite the high likelihood of Castanea refugia in the Balkan Peninsula and north-eastern Italy (Colli Euganei, Monti Berici, Emilia-Romagna) as suggested by the IRP, additional palaeobotanical investigations are needed to assess whether these regions effectively sheltered chestnut during the last glaciation. Other regions, such as the Isère Département in France, the region across north-west Portugal and Galicia, and the hilly region along the Mediterranean coast of Syria and Lebanon were classified as areas of medium refugium probability. Our results reveal an unexpected spatial richness of potential Castanea refugia. It is likely that other European trees had similar distribution ranges during the last glaciation. It is thus conceivable that shelter zones with favourable microclimates were probably more numerous and more widely dispersed across Europe than so far assumed. In the future, more attention should be paid to pollen traces of sporadic taxa thought to have disappeared from a given area during the last glacial and post-glacial period.

Does published orthodontic research account for clustering effects during statistical data analysis?

In orthodontics, multiple site observations within patients or multiple observations collected at consecutive time points are often encountered. Clustered designs require larger sample sizes compared to individual randomized trials and special statistical analyses that account for the fact that observations within clusters are correlated. It is the purpose of this study to assess to what degree clustering effects are considered during design and data analysis in the three major orthodontic journals. The contents of the most recent 24 issues of the American Journal of Orthodontics and Dentofacial Orthopedics (AJODO), Angle Orthodontist (AO), and European Journal of Orthodontics (EJO) from December 2010 backwards were hand searched. Articles with clustering effects and whether the authors accounted for clustering effects were identified. Additionally, information was collected on: involvement of a statistician, single or multicenter study, number of authors in the publication, geographical area, and statistical significance. From the 1584 articles, after exclusions, 1062 were assessed for clustering effects from which 250 (23.5 per cent) were considered to have clustering effects in the design (kappa = 0.92, 95 per cent CI: 0.67-0.99 for inter rater agreement). From the studies with clustering effects only, 63 (25.20 per cent) had indicated accounting for clustering effects. There was evidence that the studies published in the AO have higher odds of accounting for clustering effects [AO versus AJODO: odds ratio (OR) = 2.17, 95 per cent confidence interval (CI): 1.06-4.43, P = 0.03; EJO versus AJODO: OR = 1.90, 95 per cent CI: 0.84-4.24, non-significant; and EJO versus AO: OR = 1.15, 95 per cent CI: 0.57-2.33, non-significant). The results of this study indicate that only about a quarter of the studies with clustering effects account for this in statistical data analysis.

Statistical evaluation of time-dependent metabolite concentrations: estimation of post-mortem intervals based on in situ 1H-MRS of the brain

Knowledge of the time interval from death (post-mortem interval, PMI) has an enormous legal, criminological and psychological impact. Aiming to find an objective method for the determination of PMIs in forensic medicine, 1H-MR spectroscopy (1H-MRS) was used in a sheep head model to follow changes in brain metabolite concentrations after death. Following the characterization of newly observed metabolites (Ith et al., Magn. Reson. Med. 2002; 5: 915-920), the full set of acquired spectra was analyzed statistically to provide a quantitative estimation of PMIs with their respective confidence limits. In a first step, analytical mathematical functions are proposed to describe the time courses of 10 metabolites in the decomposing brain up to 3 weeks post-mortem. Subsequently, the inverted functions are used to predict PMIs based on the measured metabolite concentrations. Individual PMIs calculated from five different metabolites are then pooled, being weighted by their inverse variances. The predicted PMIs from all individual examinations in the sheep model are compared with known true times. In addition, four human cases with forensically estimated PMIs are compared with predictions based on single in situ MRS measurements. Interpretation of the individual sheep examinations gave a good correlation up to 250 h post-mortem, demonstrating that the predicted PMIs are consistent with the data used to generate the model. Comparison of the estimated PMIs with the forensically determined PMIs in the four human cases shows an adequate correlation. Current PMI estimations based on forensic methods typically suffer from uncertainties in the order of days to weeks without mathematically defined confidence information. In turn, a single 1H-MRS measurement of brain tissue in situ results in PMIs with defined and favorable confidence intervals in the range of hours, thus offering a quantitative and objective method for the determination of PMIs.

From Statistical Data to Spatial Knowledge - informing decision making in Vietnam

Vietnam has developed rapidly over the past 15 years. However, progress was not uniformly distributed across the country. Availability, adequate visualization and analysis of spatially explicit data on socio-economic and environmental aspects can support both research and policy towards sustainable development. Applying appropriate mapping techniques allows gleaning important information from tabular socio-economic data. Spatial analysis of socio-economic phenomena can yield insights into locally-specifi c patterns and processes that cannot be generated by non-spatial applications. This paper presents techniques and applications that develop and analyze spatially highly disaggregated socioeconomic datasets. A number of examples show how such information can support informed decisionmaking and research in Vietnam.

Statistical analysis of multichannel scalp field data

High density spatial and temporal sampling of EEG data enhances the quality of results of electrophysiological experiments. Because EEG sources typically produce widespread electric fields (see Chapter 3) and operate at frequencies well below the sampling rate, increasing the number of electrodes and time samples will not necessarily increase the number of observed processes, but mainly increase the accuracy of the representation of these processes. This is namely the case when inverse solutions are computed. As a consequence, increasing the sampling in space and time increases the redundancy of the data (in space, because electrodes are correlated due to volume conduction, and time, because neighboring time points are correlated), while the degrees of freedom of the data change only little. This has to be taken into account when statistical inferences are to be made from the data. However, in many ERP studies, the intrinsic correlation structure of the data has been disregarded. Often, some electrodes or groups of electrodes are a priori selected as the analysis entity and considered as repeated (within subject) measures that are analyzed using standard univariate statistics. The increased spatial resolution obtained with more electrodes is thus poorly represented by the resulting statistics. In addition, the assumptions made (e.g. in terms of what constitutes a repeated measure) are not supported by what we know about the properties of EEG data. From the point of view of physics (see Chapter 3), the natural “atomic” analysis entity of EEG and ERP data is the scalp electric field

End-tidal CO2 pressure: an important parameter for a correct interpretation of changes in cerebral hemodynamics and oxygenation measured with functional near infrared spectrophotometry (fNIRS)

The aim of the present study was to investigate the effects of different speech tasks (recitation of prose (PR), alliteration (AR) and hexameter (HR) verses) and a control task (mental arithmetic (MA) with voicing of the result) on endtidal CO2 (ET-CO2), cerebral hemodynamics; i.e. total hemoglobin (tHb) and tissue oxygen saturation (StO2). tHb and StO2 were measured with a frequency domain near infrared spectrophotometer (ISS Inc., USA) and ET-CO2 with a gas analyzer (Nellcor N1000). Measurements were performed in 24 adult volunteers (11 female, 13 male; age range 22 to 64 years) during task performance in a randomized order on 4 different days to avoid potential carry over effects. Statistical analysis was applied to test differences between baseline, 2 recitation and 5 recovery periods. The two brain hemispheres and 4 tasks were tested separately. Data analysis revealed that during the recitation tasks (PR, AR and HR) StO2 decreased statistically significant (p < 0.05) during PR and AR in the right prefrontal cortex (PFC) and during AR and HR in the left PFC. tHb showed a significant decrease during HR in the right PFC and during PR, AR and HR in the left PFC. During the MA task, StO2 increased significantly. A significant decrease in ET-CO2 was found during all 4 tasks with the smallest decrease during the MA task. In conclusion, we hypothesize that the observed changes in tHb and StO2 are mainly caused by an altered breathing during the tasks that led a lowering of the CO2 content in the blood provoked a cerebral CO2 reaction, i.e. a vasoconstriction of blood vessels due to decreased CO2 pressure and thereby decrease in cerebral blood volume. Therefore, breathing changes should be monitored during brain studies involving speech when using functional near infrared spectroscopy (fNIRS) to ensure a correct interpretation of changes in hemodynamics and oxygenation.

Reporting of statistical results in prosthodontic and implantology journals: p values or confidence intervals?

PURPOSE Confidence intervals (CIs) are integral to the interpretation of the precision and clinical relevance of research findings. The aim of this study was to ascertain the frequency of reporting of CIs in leading prosthodontic and dental implantology journals and to explore possible factors associated with improved reporting. MATERIALS AND METHODS Thirty issues of nine journals in prosthodontics and implant dentistry were accessed, covering the years 2005 to 2012: The Journal of Prosthetic Dentistry, Journal of Oral Rehabilitation, The International Journal of Prosthodontics, The International Journal of Periodontics & Restorative Dentistry, Clinical Oral Implants Research, Clinical Implant Dentistry and Related Research, The International Journal of Oral & Maxillofacial Implants, Implant Dentistry, and Journal of Dentistry. Articles were screened and the reporting of CIs and P values recorded. Other information including study design, region of authorship, involvement of methodologists, and ethical approval was also obtained. Univariable and multivariable logistic regression was used to identify characteristics associated with reporting of CIs. RESULTS Interrater agreement for the data extraction performed was excellent (kappa = 0.88; 95% CI: 0.87 to 0.89). CI reporting was limited, with mean reporting across journals of 14%. CI reporting was associated with journal type, study design, and involvement of a methodologist or statistician. CONCLUSIONS Reporting of CI in implant dentistry and prosthodontic journals requires improvement. Improved reporting will aid appraisal of the clinical relevance of research findings by providing a range of values within which the effect size lies, thus giving the end user the opportunity to interpret the results in relation to clinical practice.

A simulation study on the statistical monitoring of condemnation rates from slaughterhouses for syndromic surveillance: an evaluation based on Swiss data

Syndromic surveillance (SyS) systems currently exploit various sources of health-related data, most of which are collected for purposes other than surveillance (e.g. economic). Several European SyS systems use data collected during meat inspection for syndromic surveillance of animal health, as some diseases may be more easily detected post-mortem than at their point of origin or during the ante-mortem inspection upon arrival at the slaughterhouse. In this paper we use simulation to evaluate the performance of a quasi-Poisson regression (also known as an improved Farrington) algorithm for the detection of disease outbreaks during post-mortem inspection of slaughtered animals. When parameterizing the algorithm based on the retrospective analyses of 6 years of historic data, the probability of detection was satisfactory for large (range 83-445 cases) outbreaks but poor for small (range 20-177 cases) outbreaks. Varying the amount of historical data used to fit the algorithm can help increasing the probability of detection for small outbreaks. However, while the use of a 0·975 quantile generated a low false-positive rate, in most cases, more than 50% of outbreak cases had already occurred at the time of detection. High variance observed in the whole carcass condemnations time-series, and lack of flexibility in terms of the temporal distribution of simulated outbreaks resulting from low reporting frequency (monthly), constitute major challenges for early detection of outbreaks in the livestock population based on meat inspection data. Reporting frequency should be increased in the future to improve timeliness of the SyS system while increased sensitivity may be achieved by integrating meat inspection data into a multivariate system simultaneously evaluating multiple sources of data on livestock health.