RESUMEN
Optimal rehabilitation of asymmetric dentofacial deformity secondary to unilateral temporomandibular joint (TMJ) ankylosis is often a challenge. The purpose of this case series is to present an insight into esthetic, occlusal and functional rehabilitation of two patients with varying degree of asymmetric Class II dentofacial deformities secondary to long-standing unilateral TMJ ankylosis. The patients were treated with one-stage surgical protocol employing simultaneous dual distraction technique along with interpositional arthroplasty. Dual distraction technique entailed the simultaneous use of two distractors which allowed for proper control of proximal condylar segment during the course of distraction and lowering the risk of ankylosis recurrence. Thereafter, comprehensive fixed orthodontic mechanotherapy involving the use of temporary anchorage devices was instituted to align and level the compensated dentition. Post-treatment records showed significant improvements in skeletal disharmony and functional stability with good functional occlusion. At the three-year follow-up, the morphological and functionally acceptable results were reasonably well-maintained, with no signs of relapse. Through the two cases reported here, we would like to highlight that one-stage concurrent arthroplasty and dual distraction technique is a safe, stable, and reliable approach for surgical and functional rehabilitation of an adult asymmetric dentofacial deformity secondary to unilateral TMJ ankylosis. Meticulously executed comprehensive orthodontic manipulations involving use of acrylic bite-blocks, elastic traction, and temporary skeletal anchorage device play a crucial role in enhancing the final occlusal outcomes.
Asunto(s)
Anquilosis , Deformidades Dentofaciales , Ortodoncia , Adulto , Humanos , Estudios de Seguimiento , Anquilosis/etiología , Anquilosis/cirugía , Articulación Temporomandibular/cirugíaRESUMEN
Individual participant data meta-analysis (IPDMA) projects obtain, check, harmonise and synthesise raw data from multiple studies. When undertaking the meta-analysis, researchers must decide between a two-stage or a one-stage approach. In a two-stage approach, the IPD are first analysed separately within each study to obtain aggregate data (e.g., treatment effect estimates and standard errors); then, in the second stage, these aggregate data are combined in a standard meta-analysis model (e.g., common-effect or random-effects). In a one-stage approach, the IPD from all studies are analysed in a single step using an appropriate model that accounts for clustering of participants within studies and, potentially, between-study heterogeneity (e.g., a general or generalised linear mixed model). The best approach to take is debated in the literature, and so here we provide clearer guidance for a broad audience. Both approaches are important tools for IPDMA researchers and neither are a panacea. If most studies in the IPDMA are small (few participants or events), a one-stage approach is recommended due to using a more exact likelihood. However, in other situations, researchers can choose either approach, carefully following best practice. Some previous claims recommending to always use a one-stage approach are misleading, and the two-stage approach will often suffice for most researchers. When differences do arise between the two approaches, often it is caused by researchers using different modelling assumptions or estimation methods, rather than using one or two stages per se.
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Investigación , Humanos , Modelos Lineales , Análisis por ConglomeradosRESUMEN
BACKGROUND: Trials with binary outcomes can be synthesised using within-trial exact likelihood or approximate normal likelihood in one-stage or two-stage approaches, respectively. The performance of the one-stage and the two-stage approaches has been documented extensively in the literature. However, little is known about how these approaches behave in the presence of missing outcome data (MOD), which are ubiquitous in clinical trials. In this work, we compare the one-stage versus two-stage approach via a pattern-mixture model in the network meta-analysis using Bayesian methods to handle MOD appropriately. METHODS: We used 29 published networks to empirically compare the two approaches concerning the relative treatment effects of several competing interventions and the between-trial variance (τ2), while considering the extent and level of balance of MOD in the included trials. We additionally conducted a simulation study to compare the competing approaches regarding the bias and width of the 95% credible interval of the (summary) log odds ratios (OR) and τ2 in the presence of moderate and large MOD. RESULTS: The empirical study did not reveal any systematic bias between the compared approaches regarding the log OR, but showed systematically larger uncertainty around the log OR under the one-stage approach for networks with at least one small trial or low event risk and moderate MOD. For these networks, the simulation study revealed that the bias in log OR for comparisons with the reference intervention in the network was relatively higher in the two-stage approach. Contrariwise, the bias in log OR for the remaining comparisons was relatively higher in the one-stage approach. Overall, bias increased for large MOD. For these networks, the empirical results revealed slightly higher τ2 estimates under the one-stage approach irrespective of the extent of MOD. The one-stage approach also led to less precise log OR and τ2 when compared with the two-stage approach for large MOD. CONCLUSIONS: Due to considerable bias in the log ORs overall, especially for large MOD, none of the competing approaches was superior. Until a more competent model is developed, the researchers may prefer the one-stage approach to handle MOD, while acknowledging its limitations.
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Metaanálisis en Red , Teorema de Bayes , Sesgo , Simulación por Computador , Humanos , Oportunidad RelativaRESUMEN
BACKGROUND: In meta-analyses of a binary outcome, double zero events in some studies cause a critical methodology problem. The generalized linear mixed model (GLMM) has been proposed as a valid statistical tool for pooling such data. Three parameter estimation methods, including the Laplace approximation (LA), penalized quasi-likelihood (PQL) and adaptive Gauss-Hermite quadrature (AGHQ) were frequently used in the GLMM. However, the performance of GLMM via these estimation methods is unclear in meta-analysis with zero events. METHODS: A simulation study was conducted to compare the performance. We fitted five random-effects GLMMs and estimated the results through the LA, PQL and AGHQ methods, respectively. Each scenario conducted 20,000 simulation iterations. The data from Cochrane Database of Systematic Reviews were collected to form the simulation settings. The estimation methods were compared in terms of the convergence rate, bias, mean square error, and coverage probability. RESULTS: Our results suggested that when the total events were insufficient in either of the arms, the GLMMs did not show good point estimation to pool studies of rare events. The AGHQ method did not show better properties than the LA estimation in terms of convergence rate, bias, coverage, and possibility to produce very large odds ratios. In addition, although the PQL had some advantages, it was not the preferred option due to its low convergence rate in some situations, and the suboptimal point and variance estimation compared to the LA. CONCLUSION: The GLMM is an alternative for meta-analysis of rare events and is especially useful in the presence of zero-events studies, while at least 10 total events in both arms is recommended when employing GLMM for meta-analysis. The penalized quasi-likelihood and adaptive Gauss-Hermite quadrature are not superior to the Laplace approximation for rare events and thus they are not recommended.
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Modelos Estadísticos , Simulación por Computador , Humanos , Funciones de Verosimilitud , Modelos Lineales , Oportunidad Relativa , Revisiones Sistemáticas como AsuntoRESUMEN
INTRODUCTION: The timing and optimal method for common bile duct (CBD) clearance and laparoscopic cholecystectomy remains controversial. Several different approaches are available in clinical practice. The current study presents the experience of two European hospitals of simultaneous laparoscopic cholecystectomy (LC) and intra-operative endoscopic retrograde cholangiopacreatography (IO-ERCP) done by surgeons. METHODS: Retrospective analysis of all consecutive patients subjected to LC + IO-ERCP during their index admission between 4/2014 and 9/2016. Data accrued included patient demographics, laboratory markers, operation time (min) reported as mean (± SD) and hospital length of stay (LOS) reported as median (lower quartile, upper quartile). RESULTS: During the 29-month study, a total of 201 consecutive LC + IO-ERCPs were performed. The mean age of patients was 55 ± 19 years and 67% were female. The mean intervention time was 105 ± 44 min. The total LOS was 4 (3, 7) days and the post-operative LOS was 2 (1, 3) days. A total of 6 (3%) patients experienced post-interventional pancreatitis and two (1%) patients suffered a Strasberg type A bile leak. All patients were successfully discharged. CONCLUSION: Simultaneous LC + IO-ERCP is associated with few complications. Further studies investigating cost-benefit and patient satisfaction are warranted.
Asunto(s)
Colangiopancreatografia Retrógrada Endoscópica , Colecistectomía Laparoscópica/estadística & datos numéricos , Colecistitis/cirugía , Conducto Colédoco/patología , Complicaciones Posoperatorias/diagnóstico por imagen , Adulto , Anciano , Colangiopancreatografia Retrógrada Endoscópica/métodos , Colecistectomía Laparoscópica/efectos adversos , Colecistitis/diagnóstico por imagen , Conducto Colédoco/diagnóstico por imagen , Femenino , Humanos , Tiempo de Internación/estadística & datos numéricos , Masculino , Persona de Mediana Edad , Pancreatitis/diagnóstico por imagen , Pancreatitis/etiología , Estudios Retrospectivos , Resultado del TratamientoRESUMEN
OBJECTIVE: Combining multiple health-care databases (DBs) allows comparing the effects of a wide variety of health-care services. There is a growing interest in methods for combining the results from multiple DBs. We attempted to learn lessons about the performance of one- and two-stage approaches from the reanalysis of data drawn from two studies of pharmacoepidemiology based on multiple DBs. STUDY DESIGN AND SETTING: Two nested case-control studies were carried out for estimating the tricyclic antidepressants (TCAs)-arrhythmia and etoricoxib-heart failure associations, respectively, from the Italian Group for Appropriate Drug Prescription in the Elderly and the European Safety of Non-Steroidal Anti-Inflammatory programs. The associations of interest were modeled by conditional logistic regression for matched case-control sets, fitting fixed-effect and random-effect models with both one- and two-stage approaches. RESULTS: One- and two-stage approaches gave very similar results, showing uncertainty of TCA-arrhythmia association (random-effect odds ratios [ORs], 95% confidence interval [CI], 1.26, 0.71-2.24, and 1.30, 0.66-2.55, respectively) and statistical evidence for etoricoxib-heart failure association (fixed-effect OR, 95% CI, 1.53, 1.41-1.66, and 1.54, 1.42-1.66, respectively). CONCLUSION: Our study offers further evidence that two-stage approach generates estimates very similar as those from one-stage approach, even in the case of between-DB exposure heterogeneity and when several covariates must be concurrently considered. As current rules limit the free movement of electronic health data, our findings open the door of treating data within the country where they are generated and then to apply conventional techniques for summarizing estimates, which is the two-stage approach for meta-analysis using individual participant data.