Surgical adjunctive procedures for accelerating orthodontic treatment

BACKGROUND A range of surgical and non-surgical techniques have received increasing attention in recent years in an effort to reduce the duration of a course of orthodontic treatment. Various surgical techniques have been used; however, uncertainty exists in relation to the effectiveness of these procedures and the possible adverse effects related to them. OBJECTIVES To assess the effects of surgically assisted orthodontics on the duration and outcome of orthodontic treatment. SEARCH METHODS We searched the following electronic databases: the Cochrane Oral Health Group's Trials Register (to 10 September 2014), the Cochrane Central Register of Controlled Trials (CENTRAL) (The Cochrane Library 2014, Issue 8), MEDLINE via OVID (1946 to 10 September 2014), EMBASE via OVID (1980 to 10 September 2014), LILACS via BIREME (1980 to 10 September 2014), metaRegister of Controlled Trials (to 10 September 2014), ClinicalTrials.gov (to 10 September 2014), and the World Health Organization (WHO) International Clinical Trials Registry Platform (to 10 September 2014). We checked the reference lists of all trials identified for further studies. There were no restrictions regarding language or date of publication in the electronic searches. SELECTION CRITERIA Randomised controlled trials (RCTs) evaluating the effect of surgical adjunctive procedures for accelerating tooth movement compared with conventional treatment (no surgical adjunctive procedure). DATA COLLECTION AND ANALYSIS At least two review authors independently assessed the risk of bias in the trials and extracted data. We used the fixed-effect model and expressed results as mean differences (MD) with 95% confidence intervals (CI). We investigated heterogeneity with reference to both clinical and methodological factors. MAIN RESULTS We included four RCTs involving a total of 57 participants ranging in age from 11 to 33 years. The interventions evaluated were corticotomies to facilitate orthodontic space closure or alignment of an ectopic maxillary canine, with the effect of repeated surgical procedures assessed in one of these studies. The studies did not report directly on the primary outcome as prespecified in our protocol: duration of orthodontic treatment, number of visits during active treatment (scheduled and unscheduled) and duration of visits. The main outcome assessed within the trials was the rate of tooth movement, with periodontal effects assessed in one trial and pain assessed in one trial. A maximum of just three trials with small sample sizes were available for each comparison and outcome. We assessed all of the studies as being at unclear risk of bias.Tooth movement was found to be slightly quicker with surgically assisted orthodontics in comparison with conventional treatment over periods of one month (MD 0.61 mm; 95% CI 0.49 to 0.72; P value < 0.001) and three months (MD 2.03 mm, 95% CI 1.52 to 2.54; P value < 0.001). Our results and conclusions should be interpreted with caution given the small number of included studies. Information on adverse events was sought; however, no data were reported in the included studies. AUTHORS' CONCLUSIONS This review found that there is limited research concerning the effectiveness of surgical interventions to accelerate orthodontic treatment, with no studies directly assessing our prespecified primary outcome. The available evidence is of low quality, which indicates that further research is likely to change the estimate of the effect. Based on measured outcomes in the short-term, these procedures do appear to show promise as a means of accelerating tooth movement. It is therefore possible that these procedures may prove useful; however, further prospective research comprising assessment of the entirety of treatment with longer follow-up is required to confirm any possible benefit.

Managing atypical and typical herpetic central nervous system infections: results of a multinational study

There have been many studies pertaining to the management of herpetic meningoencephalitis (HME), but the majority of them have focussed on virologically unconfirmed cases or included only small sample sizes. We have conducted a multicentre study aimed at providing management strategies for HME. Overall, 501 adult patients with PCR-proven HME were included retrospectively from 35 referral centres in 10 countries; 496 patients were found to be eligible for the analysis. Cerebrospinal fluid (CSF) analysis using a PCR assay yielded herpes simplex virus (HSV)-1 DNA in 351 patients (70.8%), HSV-2 DNA in 83 patients (16.7%) and undefined HSV DNA type in 62 patients (12.5%). A total of 379 patients (76.4%) had at least one of the specified characteristics of encephalitis, and we placed these patients into the encephalitis presentation group. The remaining 117 patients (23.6%) had none of these findings, and these patients were placed in the nonencephalitis presentation group. Abnormalities suggestive of encephalitis were detected in magnetic resonance imaging (MRI) in 83.9% of the patients and in electroencephalography (EEG) in 91.0% of patients in the encephalitis presentation group. In the nonencephalitis presentation group, MRI and EEG data were suggestive of encephalitis in 33.3 and 61.9% of patients, respectively. However, the concomitant use of MRI and EEG indicated encephalitis in 96.3 and 87.5% of the cases with and without encephalitic clinical presentation, respectively. Considering the subtle nature of HME, CSF HSV PCR, EEG and MRI data should be collected for all patients with a central nervous system infection.

Multinomial goodness-of-fit: large sample tests with survey design correction and exact tests for small samples

I introduce the new mgof command to compute distributional tests for discrete (categorical, multinomial) variables. The command supports largesample tests for complex survey designs and exact tests for small samples as well as classic large-sample x2-approximation tests based on Pearson’s X2, the likelihood ratio, or any other statistic from the power-divergence family (Cressie and Read, 1984, Journal of the Royal Statistical Society, Series B (Methodological) 46: 440–464). The complex survey correction is based on the approach by Rao and Scott (1981, Journal of the American Statistical Association 76: 221–230) and parallels the survey design correction used for independence tests in svy: tabulate. mgof computes the exact tests by using Monte Carlo methods or exhaustive enumeration. mgof also provides an exact one-sample Kolmogorov–Smirnov test for discrete data.

Multinomial goodness-of-fit: large sample tests with survey design correction and exact tests for small samples

A new Stata command called -mgof- is introduced. The command is used to compute distributional tests for discrete (categorical, multinomial) variables. Apart from classic large sample $\chi^2$-approximation tests based on Pearson's $X^2$, the likelihood ratio, or any other statistic from the power-divergence family (Cressie and Read 1984), large sample tests for complex survey designs and exact tests for small samples are supported. The complex survey correction is based on the approach by Rao and Scott (1981) and parallels the survey design correction used for independence tests in -svy:tabulate-. The exact tests are computed using Monte Carlo methods or exhaustive enumeration. An exact Kolmogorov-Smirnov test for discrete data is also provided.

Small study effects in meta-analyses of osteoarthritis trials: meta-epidemiological study

Objective To examine the presence and extent of small study effects in clinical osteoarthritis research. Design Meta-epidemiological study. Data sources 13 meta-analyses including 153 randomised trials (41 605 patients) that compared therapeutic interventions with placebo or non-intervention control in patients with osteoarthritis of the hip or knee and used patients’ reported pain as an outcome. Methods We compared estimated benefits of treatment between large trials (at least 100 patients per arm) and small trials, explored funnel plots supplemented with lines of predicted effects and contours of significance, and used three approaches to estimate treatment effects: meta-analyses including all trials irrespective of sample size, meta-analyses restricted to large trials, and treatment effects predicted for large trials. Results On average, treatment effects were more beneficial in small than in large trials (difference in effect sizes −0.21, 95% confidence interval −0.34 to −0.08, P=0.001). Depending on criteria used, six to eight funnel plots indicated small study effects. In six of 13 meta-analyses, the overall pooled estimate suggested a clinically relevant, significant benefit of treatment, whereas analyses restricted to large trials and predicted effects in large trials yielded smaller non-significant estimates. Conclusions Small study effects can often distort results of meta-analyses. The influence of small trials on estimated treatment effects should be routinely assessed.

Vulnerability to risk among small farmers in Tajikistan: results of a 2011 survey

Tajikistan is judged to be highly vulnerable to risk, including food insecurity risks and climate change risks. By some vulnerability measures it is the most vulnerable among all 28 countries in the World Bank’s Europe and Central Asia Region – ECA (World Bank 2009). The rural population, with its relatively high incidence of poverty, is particularly vulnerable. The Pilot Program for Climate Resilience (PPCR) in Tajikistan (2011) provided an opportunity to conduct a farm-level survey with the objective of assessing various dimensions of rural population’s vulnerability to risk and their perception of constraints to farming operations and livelihoods. The survey should be accordingly referred to as the 2011 PPCR survey. The rural population in Tajikistan is highly agrarian, with about 50% of family income deriving from agriculture (see Figure 4.1; also LSMS 2007 – own calculations). Tajikistan’s agriculture basically consists of two groups of producers: small household plots – the successors of Soviet “private agriculture” – and dehkan (or “peasant”) farms – new family farming structures that began to be created under relevant legislation passed after 1992 (Lerman and Sedik, 2008). The household plots manage 20% of arable land and produce 65% of gross agricultural output (GAO). Dehkan farms manage 65% of arable land and produce close to 30% of GAO. The remaining 15% of arable land is held in agricultural enterprises – the rapidly shrinking sector of corporate farms that succeeded the Soviet kolkhozes and sovkhozes and today produces less than 10% of GAO (TajStat 2011) The survey conducted in May 2011 focused on dehkan farms, as budgetary constraints precluded the inclusion of household plots. A total of 142 dehkan farms were surveyed in face-to-face interviews. They were sampled from 17 districts across all four regions – Sughd, Khatlon, RRP, and GBAO. The districts were selected so as to represent different agro-climatic zones, different vulnerability zones (based on the World Bank (2011) vulnerability assessment), and different food-insecurity zones (based on WFP/IPC assessments). Within each district, 3-4 jamoats were chosen at random and 2-3 farms were selected in each jamoat from lists provided by jamoat administration so as to maximize the variability by farm characteristics. The sample design by region/district is presented in Table A, which also shows the agro-climatic zone and the food security phase for each district. The sample districts are superimposed on a map of food security phases based on IPC April 2011.

Sample sizes of studies on diagnostic accuracy: literature survey

OBJECTIVES: To determine sample sizes in studies on diagnostic accuracy and the proportion of studies that report calculations of sample size. DESIGN: Literature survey. DATA SOURCES: All issues of eight leading journals published in 2002. METHODS: Sample sizes, number of subgroup analyses, and how often studies reported calculations of sample size were extracted. RESULTS: 43 of 8999 articles were non-screening studies on diagnostic accuracy. The median sample size was 118 (interquartile range 71-350) and the median prevalence of the target condition was 43% (27-61%). The median number of patients with the target condition--needed to calculate a test's sensitivity--was 49 (28-91). The median number of patients without the target condition--needed to determine a test's specificity--was 76 (27-209). Two of the 43 studies (5%) reported a priori calculations of sample size. Twenty articles (47%) reported results for patient subgroups. The number of subgroups ranged from two to 19 (median four). No studies reported that sample size was calculated on the basis of preplanned analyses of subgroups. CONCLUSION: Few studies on diagnostic accuracy report considerations of sample size. The number of participants in most studies on diagnostic accuracy is probably too small to analyse variability of measures of accuracy across patient subgroups.

Field performance of two rapid screening tests in active surveillance of transmissible spongiform encephalopathies in small ruminants

Recently, screening tests for monitoring the prevalence of transmissible spongiform encephalopathies specifically in sheep and goats became available. Although most countries require comprehensive test validation prior to approval, little is known about their performance under normal operating conditions. Switzerland was one of the first countries to implement 2 of these tests, an enzyme-linked immunosorbent assay (ELISA) and a Western blot, in a 1-year active surveillance program. Slaughtered animals (n = 32,777) were analyzed in either of the 2 tests with immunohistochemistry for confirmation of initial reactive results, and fallen stock samples (n = 3,193) were subjected to both screening tests and immunohistochemistry in parallel. Initial reactive and false-positive rates were recorded over time. Both tests revealed an excellent diagnostic specificity (>99.5%). However, initial reactive rates were elevated at the beginning of the program but dropped to levels below 1% with routine and enhanced staff training. Only those in the ELISA increased again in the second half of the program and correlated with the degree of tissue autolysis in the fallen stock samples. It is noteworthy that the Western blot missed 1 of the 3 atypical scrapie cases in the fallen stock, indicating potential differences in the diagnostic sensitivities between the 2 screening tests. However, an estimation of the diagnostic sensitivity for both tests on field samples remained difficult due to the low disease prevalence. Taken together, these results highlight the importance of staff training, sample quality, and interlaboratory comparison trials when such screening tests are implemented in the field.

Portfolio-optimization models for small investors

Since 2010, the client base of online-trading service providers has grown significantly. Such companies enable small investors to access the stock market at advantageous rates. Because small investors buy and sell stocks in moderate amounts, they should consider fixed transaction costs, integral transaction units, and dividends when selecting their portfolio. In this paper, we consider the small investor’s problem of investing capital in stocks in a way that maximizes the expected portfolio return and guarantees that the portfolio risk does not exceed a prescribed risk level. Portfolio-optimization models known from the literature are in general designed for institutional investors and do not consider the specific constraints of small investors. We therefore extend four well-known portfolio-optimization models to make them applicable for small investors. We consider one nonlinear model that uses variance as a risk measure and three linear models that use the mean absolute deviation from the portfolio return, the maximum loss, and the conditional value-at-risk as risk measures. We extend all models to consider piecewise-constant transaction costs, integral transaction units, and dividends. In an out-of-sample experiment based on Swiss stock-market data and the cost structure of the online-trading service provider Swissquote, we apply both the basic models and the extended models; the former represent the perspective of an institutional investor, and the latter the perspective of a small investor. The basic models compute portfolios that yield on average a slightly higher return than the portfolios computed with the extended models. However, all generated portfolios yield on average a higher return than the Swiss performance index. There are considerable differences between the four risk measures with respect to the mean realized portfolio return and the standard deviation of the realized portfolio return.

Portfolio-optimization models for small investors

Since 2010, the client base of online-trading service providers has grown significantly. Such companies enable small investors to access the stock market at advantageous rates. Because small investors buy and sell stocks in moderate amounts, they should consider fixed transaction costs, integral transaction units, and dividends when selecting their portfolio. In this paper, we consider the small investor’s problem of investing capital in stocks in a way that maximizes the expected portfolio return and guarantees that the portfolio risk does not exceed a prescribed risk level. Portfolio-optimization models known from the literature are in general designed for institutional investors and do not consider the specific constraints of small investors. We therefore extend four well-known portfolio-optimization models to make them applicable for small investors. We consider one nonlinear model that uses variance as a risk measure and three linear models that use the mean absolute deviation from the portfolio return, the maximum loss, and the conditional value-at-risk as risk measures. We extend all models to consider piecewise-constant transaction costs, integral transaction units, and dividends. In an out-of-sample experiment based on Swiss stock-market data and the cost structure of the online-trading service provider Swissquote, we apply both the basic models and the extended models; the former represent the perspective of an institutional investor, and the latter the perspective of a small investor. The basic models compute portfolios that yield on average a slightly higher return than the portfolios computed with the extended models. However, all generated portfolios yield on average a higher return than the Swiss performance index. There are considerable differences between the four risk measures with respect to the mean realized portfolio return and the standard deviation of the realized portfolio return.

Sample size in orthodontic randomized controlled trials: are numbers justified?

Sample size calculations are advocated by the Consolidated Standards of Reporting Trials (CONSORT) group to justify sample sizes in randomized controlled trials (RCTs). This study aimed to analyse the reporting of sample size calculations in trials published as RCTs in orthodontic speciality journals. The performance of sample size calculations was assessed and calculations verified where possible. Related aspects, including number of authors; parallel, split-mouth, or other design; single- or multi-centre study; region of publication; type of data analysis (intention-to-treat or per-protocol basis); and number of participants recruited and lost to follow-up, were considered. Of 139 RCTs identified, complete sample size calculations were reported in 41 studies (29.5 per cent). Parallel designs were typically adopted (n = 113; 81 per cent), with 80 per cent (n = 111) involving two arms and 16 per cent having three arms. Data analysis was conducted on an intention-to-treat (ITT) basis in a small minority of studies (n = 18; 13 per cent). According to the calculations presented, overall, a median of 46 participants were required to demonstrate sufficient power to highlight meaningful differences (typically at a power of 80 per cent). The median number of participants recruited was 60, with a median of 4 participants being lost to follow-up. Our finding indicates good agreement between projected numbers required and those verified (median discrepancy: 5.3 per cent), although only a minority of trials (29.5 per cent) could be examined. Although sample size calculations are often reported in trials published as RCTs in orthodontic speciality journals, presentation is suboptimal and in need of significant improvement.

Sample size considerations using mathematical models: an example with Chlamydia trachomatis infection and its sequelae pelvic inflammatory disease.

BACKGROUND The success of an intervention to prevent the complications of an infection is influenced by the natural history of the infection. Assumptions about the temporal relationship between infection and the development of sequelae can affect the predicted effect size of an intervention and the sample size calculation. This study investigates how a mathematical model can be used to inform sample size calculations for a randomised controlled trial (RCT) using the example of Chlamydia trachomatis infection and pelvic inflammatory disease (PID). METHODS We used a compartmental model to imitate the structure of a published RCT. We considered three different processes for the timing of PID development, in relation to the initial C. trachomatis infection: immediate, constant throughout, or at the end of the infectious period. For each process we assumed that, of all women infected, the same fraction would develop PID in the absence of an intervention. We examined two sets of assumptions used to calculate the sample size in a published RCT that investigated the effect of chlamydia screening on PID incidence. We also investigated the influence of the natural history parameters of chlamydia on the required sample size. RESULTS The assumed event rates and effect sizes used for the sample size calculation implicitly determined the temporal relationship between chlamydia infection and PID in the model. Even small changes in the assumed PID incidence and relative risk (RR) led to considerable differences in the hypothesised mechanism of PID development. The RR and the sample size needed per group also depend on the natural history parameters of chlamydia. CONCLUSIONS Mathematical modelling helps to understand the temporal relationship between an infection and its sequelae and can show how uncertainties about natural history parameters affect sample size calculations when planning a RCT.

Pre-clinical in vivo models for the screening of bone biomaterials for oral/craniofacial indications: focus on small-animal models.

Preclinical in vivo experimental studies are performed for evaluating proof-of-principle concepts, safety and possible unwanted reactions of candidate bone biomaterials before proceeding to clinical testing. Specifically, models involving small animals have been developed for screening bone biomaterials for their potential to enhance bone formation. No single model can completely recreate the anatomic, physiologic, biomechanic and functional environment of the human mouth and jaws. Relevant aspects regarding physiology, anatomy, dimensions and handling are discussed in this paper to elucidate the advantages and disadvantages of small-animal models. Model selection should be based not on the 'expertise' or capacities of the team, but rather on a scientifically solid rationale, and the animal model selected should reflect the question for which an answer is sought. The rationale for using heterotopic or orthotopic testing sites, and intraosseous, periosseous or extraskeletal defect models, is discussed. The paper also discusses the relevance of critical size defect modeling, with focus on calvarial defects in rodents. In addition, the rabbit sinus model and the capsule model in the rat mandible are presented and discussed in detail. All animal experiments should be designed with care and include sample-size and study-power calculations, thus allowing generation of meaningful data. Moreover, animal experiments are subject to ethical approval by the relevant authority. All procedures and the postoperative handling and care, including postoperative analgesics, should follow best practice.

A Non-Synonymous HMGA2 Variant Decreases Height in Shetland Ponies and Other Small Horses

The identification of quantitative trait loci (QTL) such as height and their underlying causative variants is still challenging and often requires large sample sizes. In humans hundreds of loci with small effects control the heritable portion of height variability. In domestic animals, typically only a few loci with comparatively large effects explain a major fraction of the heritability. We investigated height at withers in Shetland ponies and mapped a QTL to ECA 6 by genome-wide association (GWAS) using a small cohort of only 48 animals and the Illumina equine SNP70 BeadChip. Fine-mapping revealed a shared haplotype block of 793 kb in small Shetland ponies. The HMGA2 gene, known to be associated with height in horses and many other species, was located in the associated haplotype. After closing a gap in the equine reference genome we identified a non-synonymous variant in the first exon of HMGA2 in small Shetland ponies. The variant was predicted to affect the functionally important first AT-hook DNA binding domain of the HMGA2 protein (c.83G>A; p.G28E). We assessed the functional impact and found impaired DNA binding of a peptide with the mutant sequence in an electrophoretic mobility shift assay. This suggests that the HMGA2 variant also affects DNA binding in vivo and thus leads to reduced growth and a smaller stature in Shetland ponies. The identified HMGA2 variant also segregates in several other pony breeds but was not found in regular-sized horse breeds. We therefore conclude that we identified a quantitative trait nucleotide for height in horses.

Reconstruction of in-situ porosity and porewater compositions of low-permeability crystalline rocks: Magnitude of artefacts induced by drilling and sample recovery

Geological site characterisation programmes typically rely on drill cores for direct information on subsurface rocks. However, porosity, transport properties and porewater composition measured on drill cores can deviate from in-situ values due to two main artefacts caused by drilling and sample recovery: (1) mechanical disruption that increases porosity and (2) contamination of the porewater by drilling fluid. We investigated the effect and magnitude of these perturbations on large drill core samples (12–20 cm long, 5 cmdiameter) of high-grade, granitic gneisses obtained from 350 to 600 m depth in a borehole on Olkiluoto Island (SW Finland). The drilling fluid was traced with sodium–iodide. By combining out-diffusion experiments, gravimetry, UV-microscopy and iodide mass balance calculations, we successfully quantified the magnitudes of the artefacts: 2–6% increase in porosity relative to the bulk connected porosity and 0.9 to 8.9 vol.% contamination by drilling fluid. The spatial distribution of the drilling-induced perturbations was revealed by numerical simulations of 2D diffusion matched to the experimental data. This showed that the rims of the samples have a mechanically disrupted zone 0.04 to 0.22 cm wide, characterised by faster transport properties compared to the undisturbed centre (1.8 to 7.7 times higher pore diffusion coefficient). Chemical contamination was shown to affect an even wider zone in all samples, ranging from 0.15 to 0.60 cm, inwhich iodide enrichmentwas up to 180 mg/kgwater, compared to 0.5 mg/kgwater in the uncontaminated centre. For all samples in the present case study, it turned out that the magnitude of the artefacts caused by drilling and sample recovery is so small that no correction is required for their effects. Therefore, the standard laboratory measurements of porosity, transport properties and porewater composition can be taken as valid in-situ estimates. However, it is clear that the magnitudes strongly depend on site- and drilling-specific factors and therefore our results cannot be transferred simply to other locations. We recommend the approach presented in this study as a route to obtain reliable values in future drilling campaigns aimed at characterising in-situ bedrock properties.