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1.
Trials ; 22(1): 420, 2021 Jun 29.
Artigo em Inglês | MEDLINE | ID: mdl-34187527

RESUMO

BACKGROUND: The SAVVY project aims to improve the analyses of adverse events (AEs), whether prespecified or emerging, in clinical trials through the use of survival techniques appropriately dealing with varying follow-up times and competing events (CEs). Although statistical methodologies have advanced, in AE analyses, often the incidence proportion, the incidence density, or a non-parametric Kaplan-Meier estimator are used, which ignore either censoring or CEs. In an empirical study including randomized clinical trials from several sponsor organizations, these potential sources of bias are investigated. The main purpose is to compare the estimators that are typically used to quantify AE risk within trial arms to the non-parametric Aalen-Johansen estimator as the gold-standard for estimating cumulative AE probabilities. A follow-up paper will consider consequences when comparing safety between treatment groups. METHODS: Estimators are compared with descriptive statistics, graphical displays, and a more formal assessment using a random effects meta-analysis. The influence of different factors on the size of deviations from the gold-standard is investigated in a meta-regression. Comparisons are conducted at the maximum follow-up time and at earlier evaluation times. CEs definition does not only include death before AE but also end of follow-up for AEs due to events related to the disease course or safety of the treatment. RESULTS: Ten sponsor organizations provided 17 clinical trials including 186 types of investigated AEs. The one minus Kaplan-Meier estimator was on average about 1.2-fold larger than the Aalen-Johansen estimator and the probability transform of the incidence density ignoring CEs was even 2-fold larger. The average bias using the incidence proportion was less than 5%. Assuming constant hazards using incidence densities was hardly an issue provided that CEs were accounted for. The meta-regression showed that the bias depended mainly on the amount of censoring and on the amount of CEs. CONCLUSIONS: The choice of the estimator of the cumulative AE probability and the definition of CEs are crucial. We recommend using the Aalen-Johansen estimator with an appropriate definition of CEs whenever the risk for AEs is to be quantified and to change the guidelines accordingly.


Assuntos
Seguimentos , Humanos , Incidência , Probabilidade , Análise de Sobrevida
2.
Pharm Stat ; 2021 May 18.
Artigo em Inglês | MEDLINE | ID: mdl-34002935

RESUMO

Safety analyses of adverse events (AEs) are important in assessing benefit-risk of therapies but are often rather simplistic compared to efficacy analyses. AE probabilities are typically estimated by incidence proportions, sometimes incidence densities or Kaplan-Meier estimation are proposed. These analyses either do not account for censoring, rely on a too restrictive parametric model, or ignore competing events. With the non-parametric Aalen-Johansen estimator as the "gold standard", that is, reference estimator, potential sources of bias are investigated in an example from oncology and in simulations, for both one-sample and two-sample scenarios. The Aalen-Johansen estimator serves as a reference, because it is the proper non-parametric generalization of the Kaplan-Meier estimator to multiple outcomes. Because of potential large variances at the end of follow-up, comparisons also consider further quantiles of the observed times. To date, consequences for safety comparisons have hardly been investigated, the impact of using different estimators for group comparisons being unclear. For example, the ratio of two both underestimating or overestimating estimators may not be comparable to the ratio of the reference, and our investigation also considers the ratio of AE probabilities. We find that ignoring competing events is more of a problem than falsely assuming constant hazards by the use of the incidence density and that the choice of the AE probability estimator is crucial for group comparisons.

3.
J Oral Rehabil ; 48(8): 891-900, 2021 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-33983634

RESUMO

BACKGROUND: Passive mandibular advancement with functional appliances is commonly used to treat juvenile patients with mandibular retrognathism. OBJECTIVE: The aim of this study was to investigate whether active repetitive training of the mandible into an anterior position would result in a shift of the habitual mandibular position (HMP). METHODS: Twenty adult healthy subjects were randomly assigned to one of two groups: a training group receiving six supervised functional training sessions of 10 min each and a control group without training. Bonded lateral biteplates disengaged occlusion among both groups throughout the 15-day experiment. Customised registration-training appliances consisted of a maxillary component with an anterior plane and a mandibular component with an attached metal sphere. Training sessions consisted of repeated mouth-opening/closing cycles (frequency: 30/min) to hit an anteriorly positioned hemispherical target notch with this metal sphere. The HMP was registered at defined times during the experiment. RESULTS: The HMP in the training group showed a statistically significant anterior shift of 1.6 mm (interquartile range [IQR]: 1.2 mm), compared with a significant posterior shift of -0.8 mm (IQR: 2.8 mm) in the control group (p < .05). Although the anterior shift among the training group showed a partial relapse 4 days after the first training block, it then advanced slightly in the 4-day interval after the second training block, which might indicate neuroplasticity of the masticatory motor system. CONCLUSIONS: Motor learning by repetitive training of the mandible into an anterior position might help to improve the results of functional appliance therapy among patients with mandibular retrognathism.


Assuntos
Má Oclusão , Avanço Mandibular , Adulto , Cefalometria , Oclusão Dentária , Humanos , Mandíbula
4.
BMJ Evid Based Med ; 26(3): 121-126, 2021 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-31988195

RESUMO

When analysing and presenting results of randomised clinical trials, trialists rarely report if or how underlying statistical assumptions were validated. To avoid data-driven biased trial results, it should be common practice to prospectively describe the assessments of underlying assumptions. In existing literature, there is no consensus on how trialists should assess and report underlying assumptions for the analyses of randomised clinical trials. With this study, we developed suggestions on how to test and validate underlying assumptions behind logistic regression, linear regression, and Cox regression when analysing results of randomised clinical trials.Two investigators compiled an initial draftbased on a review of the literature. Experienced statisticians and trialists from eight different research centres and trial units then participated in a anonymised consensus process, where we reached agreement on the suggestions presented in this paper.This paper provides detailed suggestions on 1) which underlying statistical assumptions behind logistic regression, multiple linear regression and Cox regression each should be assessed; 2) how these underlying assumptions may be assessed; and 3) what to do if these assumptions are violated.We believe that the validity of randomised clinical trial results will increase if our recommendations for assessing and dealing with violations of the underlying statistical assumptions are followed.

5.
Biom J ; 63(3): 650-670, 2021 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-33145854

RESUMO

The assessment of safety is an important aspect of the evaluation of new therapies in clinical trials, with analyses of adverse events being an essential part of this. Standard methods for the analysis of adverse events such as the incidence proportion, that is the number of patients with a specific adverse event out of all patients in the treatment groups, do not account for both varying follow-up times and competing risks. Alternative approaches such as the Aalen-Johansen estimator of the cumulative incidence function have been suggested. Theoretical arguments and numerical evaluations support the application of these more advanced methodology, but as yet there is to our knowledge only insufficient empirical evidence whether these methods would lead to different conclusions in safety evaluations. The Survival analysis for AdVerse events with VarYing follow-up times (SAVVY) project strives to close this gap in evidence by conducting a meta-analytical study to assess the impact of the methodology on the conclusion of the safety assessment empirically. Here we present the rationale and statistical concept of the empirical study conducted as part of the SAVVY project. The statistical methods are presented in unified notation, and examples of their implementation in R and SAS are provided.

6.
Sci Rep ; 10(1): 14388, 2020 09 01.
Artigo em Inglês | MEDLINE | ID: mdl-32873877

RESUMO

To describe the 5 years' trajectories in functionality and pain of patients with hip or knee osteoarthritis and arthroplasty and analyze the association of these with long-term patients survival. Patients with OA receiving total hip or knee arthroplasty were recruited and completed two sets of standardized questionnaires for functionality and pain 6, 12, and 60 months postoperatively. Multivariate mixed models were conducted to assess trajectories over time and the resulting improvement per month during the last time period was included in a landmark-model to estimate adjusted hazard ratios for mortality. In total 809 patients with joint replacement were included (mean age 65.0 years, 62.2% female), 407 patients died (median follow-up 18.4 years). Both instruments of functionality and pain showed extensive improvement during the first 6 months. Baseline and change in functionality (both p < 0.001) and pain (p = 0.02) during the first 6 months were associated with mortality. Better values in functionality corresponded with improved survival whereas the association with the pain scores was inverse. In patients with hip and knee OA, an explicit improvement in function is seen within the first 6 months after arthroplasty. In addition, especially the functionality scores at baseline as well as their improvement showed an association with long-term patient survival.


Assuntos
Artroplastia de Quadril/efeitos adversos , Artroplastia de Quadril/mortalidade , Artroplastia do Joelho/efeitos adversos , Artroplastia do Joelho/mortalidade , Osteoartrite do Quadril/cirurgia , Osteoartrite do Joelho/cirurgia , Dor Pós-Operatória/etiologia , Idoso , Idoso de 80 Anos ou mais , Feminino , Seguimentos , Humanos , Masculino , Pessoa de Meia-Idade , Medição da Dor , Estudos Prospectivos , Inquéritos e Questionários , Resultado do Tratamento , Escala Visual Analógica
8.
Biol Blood Marrow Transplant ; 26(5): 992-997, 2020 05.
Artigo em Inglês | MEDLINE | ID: mdl-31927103

RESUMO

In most clinical oncology trials, time-to-first-event analyses are used for efficacy assessment, which often do not capture the entire disease process. Instead, the focus may be on more complex time-to-event endpoints, such as the course of disease after the first event or endpoints occurring after randomization. We propose "relapse- and immunosuppression-free survival" (RIFS) as an innovative and clinically relevant outcome measure for assessing treatment success after hematopoietic stem cell transplant (SCT). To capture the time-dynamic relationship of multiple episodes of immunosuppressive therapy during follow-up, relapse, and nonrelapse mortality, a multistate model was developed. The statistical complexity is that the probability of RIFS is nonmonotonic over time; thus, standard time-to-first-event methodology is inappropriate for formal treatment comparisons. Instead, a generalization of the Kaplan-Meier method was used for probability estimation, and simulation-based resampling was suggested as a strategy for statistical inference. We reanalyzed data from a recently published phase III trial in 201 leukemia patients after SCT. The study evaluated long-term treatment success of standard graft-versus-host disease prophylaxis plus a pretransplant antihuman T-lymphocyte immunoglobulin compared with standard prophylaxis alone. Results suggested that treatment increased the long-term probability of RIFS by approximately 30% during the entire follow-up period, which complements the original findings. This article highlights the importance of complex endpoints in oncology, which provide deeper insight into the treatment and disease process over time. Multistate models combined with resampling are highlighted as a promising tool to evaluate treatment success beyond standard endpoints. An example code is provided in the Supplementary Materials.


Assuntos
Doença Enxerto-Hospedeiro , Transplante de Células-Tronco Hematopoéticas , Soro Antilinfocitário , Intervalo Livre de Doença , Doença Enxerto-Hospedeiro/prevenção & controle , Humanos , Recidiva , Condicionamento Pré-Transplante , Resultado do Tratamento
9.
Pharm Stat ; 19(3): 262-275, 2020 05.
Artigo em Inglês | MEDLINE | ID: mdl-31820541

RESUMO

A clinical hold order by the Food and Drug Administration (FDA) to the sponsor of a clinical trial is a measure to delay a proposed or to suspend an ongoing clinical investigation. The phase III clinical trial START serves as motivating data example to explore implications and potential statistical approaches for a trial continuing after a clinical hold is lifted. In spite of a modified intention-to-treat (ITT) analysis introduced to account for the clinical hold by excluding patients potentially affected most by the clinical hold, results of the trial did not show a significant improvement of overall survival duration, and the question remains whether the negative result was an effect of the clinical hold. In this paper, we propose a multistate model incorporating the clinical hold as well as disease progression as intermediate events to investigate the impact of the clinical hold on the treatment effect. Moreover, we consider a simple counterfactual censoring approach as alternative strategy to the modified ITT analysis to deal with a clinical hold. Using a realistic simulation study informed by the START data and with a design based on our multistate model, we show that the modified ITT analysis used in the START trial was reasonable. However, the censoring approach will be shown to have some benefits in terms of power and flexibility.


Assuntos
Ensaios Clínicos Fase III como Assunto/estatística & dados numéricos , Modelos Estatísticos , Ensaios Clínicos Controlados Aleatórios como Assunto/estatística & dados numéricos , Projetos de Pesquisa/estatística & dados numéricos , Carcinoma Pulmonar de Células não Pequenas/imunologia , Carcinoma Pulmonar de Células não Pequenas/mortalidade , Carcinoma Pulmonar de Células não Pequenas/terapia , Interpretação Estatística de Dados , Progressão da Doença , Humanos , Imunoterapia , Análise de Intenção de Tratamento/estatística & dados numéricos , Neoplasias Pulmonares/imunologia , Neoplasias Pulmonares/mortalidade , Neoplasias Pulmonares/terapia , Fatores de Tempo , Resultado do Tratamento
10.
Lifetime Data Anal ; 26(1): 21-44, 2020 01.
Artigo em Inglês | MEDLINE | ID: mdl-30426275

RESUMO

For large cohort studies with rare outcomes, the nested case-control design only requires data collection of small subsets of the individuals at risk. These are typically randomly sampled at the observed event times and a weighted, stratified analysis takes over the role of the full cohort analysis. Motivated by observational studies on the impact of hospital-acquired infection on hospital stay outcome, we are interested in situations, where not necessarily the outcome is rare, but time-dependent exposure such as the occurrence of an adverse event or disease progression is. Using the counting process formulation of general nested case-control designs, we propose three sampling schemes where not all commonly observed outcomes need to be included in the analysis. Rather, inclusion probabilities may be time-dependent and may even depend on the past sampling and exposure history. A bootstrap analysis of a full cohort data set from hospital epidemiology allows us to investigate the practical utility of the proposed sampling schemes in comparison to a full cohort analysis and a too simple application of the nested case-control design, if the outcome is not rare.

11.
Stat Med ; 39(4): 481-493, 2020 02 20.
Artigo em Inglês | MEDLINE | ID: mdl-31788835

RESUMO

Both delayed study entry (left-truncation) and competing risks are common phenomena in observational time-to-event studies. For example, in studies conducted by Teratology Information Services (TIS) on adverse drug reactions during pregnancy, the natural time scale is gestational age, but women enter the study after time origin and upon contact with the service. Competing risks are present, because an elective termination may be precluded by a spontaneous abortion. If left-truncation is entirely random, the Aalen-Johansen estimator is the canonical estimator of the cumulative incidence functions of the competing events. If the assumption of random left-truncation is in doubt, we propose a new semiparametric estimator of the cumulative incidence function. The dependence between entry time and time-to-event is modeled using a cause-specific Cox proportional hazards model and the marginal (unconditional) estimates are derived via inverse probability weighting arguments. We apply the new estimator to data about coumarin usage during pregnancy. Here, the concern is that the cause-specific hazard of experiencing an induced abortion may depend on the time when seeking advice by a TIS, which also is the time of left-truncation or study entry. While the aims of counseling by a TIS are to reduce the rate of elective terminations based on irrational overestimation of drug risks and to lead to better and safer medical treatment of maternal disease, it is conceivable that women considering an induced abortion are more likely to seek counseling. The new estimator is also evaluated in extensive simulation studies and found preferable compared to the Aalen-Johansen estimator in non-misspecified scenarios and to at least provide for a sensitivity analysis otherwise.


Assuntos
Aborto Espontâneo , Simulação por Computador , Feminino , Humanos , Incidência , Modelos Estatísticos , Gravidez , Probabilidade , Modelos de Riscos Proporcionais
12.
Biostatistics ; 21(3): 449-466, 2020 07 01.
Artigo em Inglês | MEDLINE | ID: mdl-30418529

RESUMO

A popular modeling approach for competing risks analysis in longitudinal studies is the proportional subdistribution hazards model by Fine and Gray (1999. A proportional hazards model for the subdistribution of a competing risk. Journal of the American Statistical Association94, 496-509). This model is widely used for the analysis of continuous event times in clinical and epidemiological studies. However, it does not apply when event times are measured on a discrete time scale, which is a likely scenario when events occur between pairs of consecutive points in time (e.g., between two follow-up visits of an epidemiological study) and when the exact lengths of the continuous time spans are not known. To adapt the Fine and Gray approach to this situation, we propose a technique for modeling subdistribution hazards in discrete time. Our method, which results in consistent and asymptotically normal estimators of the model parameters, is based on a weighted ML estimation scheme for binary regression. We illustrate the modeling approach by an analysis of nosocomial pneumonia in patients treated in hospitals.


Assuntos
Pesquisa Biomédica/métodos , Bioestatística/métodos , Modelos Estatísticos , Pneumonia Associada a Assistência à Saúde/epidemiologia , Humanos , Unidades de Terapia Intensiva/estatística & dados numéricos , Modelos de Riscos Proporcionais
13.
Stat Med ; 38(22): 4270-4289, 2019 09 30.
Artigo em Inglês | MEDLINE | ID: mdl-31273817

RESUMO

In this paper, we derive the joint distribution of progression-free and overall survival as a function of transition probabilities in a multistate model. No assumptions on copulae or latent event times are needed and the model is allowed to be non-Markov. From the joint distribution, statistics of interest can then be computed. As an example, we provide closed formulas and statistical inference for Pearson's correlation coefficient between progression-free and overall survival in a parametric framework. The example is inspired by recent approaches to quantify the dependence between progression-free survival, a common primary outcome in Phase 3 trials in oncology and overall survival. We complement these approaches by providing methods of statistical inference while at the same time working within a much more parsimonious modeling framework. Our approach is completely general and can be applied to other measures of dependence. We also discuss extensions to nonparametric inference. Our analytical results are illustrated using a large randomized clinical trial in breast cancer.


Assuntos
Intervalo Livre de Doença , Modelos Estatísticos , Intervalo Livre de Progressão , Simulação por Computador , Humanos , Funções Verossimilhança , Cadeias de Markov , Probabilidade , Análise de Sobrevida
14.
Stat Med ; 38(22): 4390-4403, 2019 09 30.
Artigo em Inglês | MEDLINE | ID: mdl-31313337

RESUMO

Estimating the potential risk associated with an exposure occurring over time requires complex statistical techniques, since ignoring the time from study entry until the exposure leads to potentially seriously biased effect estimates. A prominent example is estimating the effect of hospital-acquired infections on adverse outcomes in patients admitted to the intensive care unit. Exposure density sampling has been proposed as an approach to dynamic matching with respect to a time-dependent exposure. Firstly, exposure density sampling can be useful to reduce the workload of study follow up, as it includes all exposed but only a subset of the not yet exposed individuals. Secondly, it can help to obtain a comparable control group by including propensity score matching. In the present article, we provide the theoretical justification that data obtained by exposure density sampling can be analyzed as a left-truncated cohort. It is shown that exposure density sampling allows estimation of the effect of a time-dependent exposure as well as further baseline covariates on a subsequent event, with only minor loss in precision as compared with a full cohort analysis. The sampling is applied to a real data example (hospital-acquired infections in intensive care units) and in a simulation study. We also provide an estimate of the loss in precision in terms of an increased standard error in the reduced data set after exposure density sampling as compared with the full cohort.


Assuntos
Exposição Ambiental/efeitos adversos , Medição de Risco/métodos , Simulação por Computador , Humanos , Funções Verossimilhança , Pontuação de Propensão , Tempo
15.
Stat Med ; 38(20): 3747-3763, 2019 09 10.
Artigo em Inglês | MEDLINE | ID: mdl-31162707

RESUMO

We consider nonparametric and semiparametric resampling of multistate event histories by simulating multistate trajectories from an empirical multivariate hazard measure. One advantage of our approach is that it does not necessarily require individual patient data, but may be based on published information. This is also attractive for both study planning and simulating realistic real-world event history data in general. The concept extends to left-truncation and right-censoring mechanisms, nondegenerate initial distributions, and nonproportional as well as non-Markov settings. A special focus is on its connection to simulating survival data with time-dependent covariates. For the case of qualitative time-dependent exposures, we demonstrate that our proposal gives a more natural interpretation of how such data evolve over the course of time than many of the competing approaches. The multistate perspective avoids any latent failure time structure and sampling spaces impossible in real life, whereas its parsimony follows the principle of Occam's razor. We also suggest empirical simulation as a novel bootstrap procedure to assess estimation uncertainty in the absence of individual patient data. This is not possible for established procedures such as Efron's bootstrap. A simulation study investigating the effect of liver functionality on survival in patients with liver cirrhosis serves as a proof of concept. Example code is provided.


Assuntos
Análise Multivariada , Análise de Sobrevida , Algoritmos , Simulação por Computador , Humanos , Probabilidade , Tempo
16.
BMC Med Res Methodol ; 19(1): 111, 2019 05 31.
Artigo em Inglês | MEDLINE | ID: mdl-31151418

RESUMO

BACKGROUND: Length of stay evaluations are very common to determine the burden of nosocomial infections. However, there exist fundamentally different methods to quantify the prolonged length of stay associated with nosocomial infections. Previous methodological studies emphasized the need to account for the timing of infection in order to differentiate the length of stay before and after the infection. METHODS: We derive four different approaches in a simple multi-state framework, display their mathematical relationships in a multiplicative as well as additive way and apply them to a real cohort study (n=756 German intensive-care unit patients of whom 124 patients acquired a nosocomial infection). RESULTS: The first approach ignores the timing of infection and quantifies the difference of eventually infected and eventually uninfected; it is 12.31 days in the real data. The second approach compares the average sojourn time with infection with the average sojourn time of being hypothetically uninfected; it is 2.12 days. The third one compares the average length of stay of a population in a world with nosocomial infections with a population in a hypothetical world without nosocomial infections; it is 0.35 days. Finally, approach four compares the mean residual length of stay between currently infected and uninfected patients on a daily basis; the difference is 1.77 days per infected patient. CONCLUSIONS: The first approach should be avoided because it compares the eventually infected with the eventually uninfected, but has no prospective interpretation. The other approaches differ in their interpretation but are suitable because they explicitly distinguish between the pre- and post-time of the nosocomial infection.


Assuntos
Infecção Hospitalar/epidemiologia , Unidades de Terapia Intensiva/estatística & dados numéricos , Tempo de Internação/estatística & dados numéricos , Alemanha/epidemiologia , Humanos
17.
BMJ Evid Based Med ; 24(5): 185-189, 2019 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-30948454

RESUMO

In order to ensure the validity of results of randomised clinical trials and under some circumstances to optimise statistical power, most statistical methods require validation of underlying statistical assumptions. The present paper describes how trialists in major medical journals report tests of underlying statistical assumptions when analysing results of randomised clinical trials. We also consider possible solutions how to improve current practice by adequate reporting of tests of underlying statistical assumptions. We conclude that there is a need to reach consensus on which underlying assumptions should be assessed, how these underlying assumptions should be assessed and what should be done if the underlying assumptions are violated.


Assuntos
Interpretação Estatística de Dados , Ensaios Clínicos Controlados Aleatórios como Assunto/métodos , Humanos , Reprodutibilidade dos Testes , Estatística como Assunto
18.
Pharmacoepidemiol Drug Saf ; 28(5): 616-624, 2019 05.
Artigo em Inglês | MEDLINE | ID: mdl-30828912

RESUMO

PURPOSE: Observational cohort studies are essential to evaluate the risk of adverse pregnancy outcomes associated with drug intake. Besides left truncation and competing events, it is crucial to account for the time-dynamic pattern of drug exposure. In fact, potentially harmful medications are often discontinued, which might affect the outcome. Ignoring these challenges may lead to biased estimation of drug-related risks highlighting the need for adequate statistical techniques. METHODS: We reanalyze updated data of a recently published study provided by the German Embryotox pharmacovigilance institute. The aim of the study was to quantify the effect of discontinuation of vitamin K antagonist phenprocoumon on the risk of spontaneous abortion. RESULTS: We outline multistate methodology as a powerful method removing bias in probability estimation inherent to commonly used crude proportions. We incorporate time-dependent discontinuation and competing pregnancy outcomes as separate states in a multistate model, which enables the formulation of hazard-based Cox proportional hazard models and the application of so-called landmark techniques. Results show that early discontinuation of phenprocoumon substantially reduces the risk of spontaneous abortion, which is of great importance for both pregnant women and treating physicians. CONCLUSIONS: An adequate handling of discontinuation times is essential when analyzing the risk of spontaneous abortion. The proposed concepts are not restricted to pregnancy outcome studies but have broad usage in other fields of epidemiology. Our nontechnical report may provide guidance for the design and analysis of future studies. Example code is provided.


Assuntos
Aborto Espontâneo , Anticoagulantes/administração & dosagem , Anticoagulantes/efeitos adversos , Farmacovigilância , Femprocumona/administração & dosagem , Femprocumona/efeitos adversos , Aborto Espontâneo/induzido quimicamente , Aborto Espontâneo/epidemiologia , Estudos de Coortes , Relação Dose-Resposta a Droga , Esquema de Medicação , Feminino , Humanos , Modelos Logísticos , Modelos Estatísticos , Gravidez , Medição de Risco
19.
JAMA Neurol ; 76(5): 571-579, 2019 05 01.
Artigo em Inglês | MEDLINE | ID: mdl-30657812

RESUMO

Importance: Moderate hypothermia in addition to early decompressive hemicraniectomy has been suggested to further reduce mortality and improve functional outcome in patients with malignant middle cerebral artery (MCA) stroke. Objective: To investigate whether moderate hypothermia vs standard treatment after early hemicraniectomy reduces mortality at day 14 in patients with malignant MCA stroke. Design, Setting, and Participants: This randomized clinical trial recruited patients from August 2011 through September 2015 at 6 German university hospitals with dedicated neurointensive care units. Of the patients treated with hemicraniectomy and assessed for eligibility, patients were randomly assigned to either standard care or moderate hypothermia. Data analysis was completed from December 2016 to June 2018. Interventions: Moderate hypothermia (temperature, 33.0 ± 1.0°C) was maintained for at least 72 hours immediately after hemicraniectomy. Main Outcomes and Measures: The primary outcome was mortality rate at day 14 compared with the Fisher exact test and expressed as odds ratio (ORs) with 95% CIs. Rates of patients with serious adverse events were estimated for the period of the first 14 days after hemicraniectomy and 12 months of follow-up. Secondary outcome measures included functional outcome at 12 months. Results: Of the 50 study participants, 24 were assigned to standard care and 26 to moderate hypothermia. Twenty-eight were male (56%); the mean (SD) patient age was 51.3 (6.6) years. Recruitment was suspended for safety concerns: 12 of 26 patients (46%) in the hypothermia group and 7 of 24 patients (29%) receiving standard care had at least 1 serious adverse event within 14 days (OR, 2.05 [95% CI, 0.56-8.00]; P = .26); after 12 months, rates of serious adverse events were 80% (n = 20 of 25) in the hypothermia group and 43% (n = 10 of 23) in the standard care group (hazard ratio, 2.54 [95% CI, 1.29-5.00]; P = .005). The mortality rate at day 14 was 19% (5 of 26 patients) in the hypothermia group and 13% (3 of 24 patients) in the group receiving standard care (OR, 1.65 [95% CI, 0.28-12.01]; P = .70). There was no significant difference regarding functional outcome after 12 months of follow-up. Interpretation: In patients with malignant MCA stroke, moderate hypothermia early after hemicraniectomy did not improve mortality and functional outcome compared with standard care, but may cause serious harm in this specific setting. Trial Registration: http://www.drks.de, identifier DRKS00000623.


Assuntos
Craniectomia Descompressiva/métodos , Mortalidade Hospitalar , Hipotermia Induzida/métodos , Infarto da Artéria Cerebral Média/terapia , Adulto , Edema Encefálico , Término Precoce de Ensaios Clínicos , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Mortalidade , Cuidados Pós-Operatórios/métodos , Modelos de Riscos Proporcionais , Índice de Gravidade de Doença , Trombectomia , Terapia Trombolítica , Tempo para o Tratamento , Traqueostomia/estatística & dados numéricos
20.
Eur Heart J ; 40(15): 1226-1232, 2019 04 14.
Artigo em Inglês | MEDLINE | ID: mdl-30689825

RESUMO

AIMS: In the Minimizing Adverse Haemorrhagic Events by TRansradial Access Site and Systemic Implementation of angioX (MATRIX) trial, adults with acute coronary syndrome undergoing coronary intervention who were allocated to radial access had a lower risk of bleeding, acute kidney injury (AKI), and all-cause mortality, as compared with those allocated to femoral access. The mechanism of the mortality benefit of radial access remained unclear. METHODS AND RESULTS: We used multistate and competing risk models to determine the effects of radial and femoral access on bleeding, AKI and all-cause mortality in the MATRIX trial and to disentangle the relationship between these different types of events. There were large relative risk reductions in mortality for radial compared with femoral access for the transition from AKI to death [hazard ratio (HR) 0.55, 95% confidence interval (CI) 0.31-0.97] and for the pathway from coronary intervention to AKI to death (HR 0.49, 95% CI 0.26-0.92). Conversely, there was little evidence for a difference between radial and femoral groups for the transition from bleeding to death (HR 1.05, 95% CI 0.42-2.64) and the pathway from coronary intervention to bleeding to death (HR 0.84, 95% CI 0.28-2.49). CONCLUSION: The prevention of AKI appeared predominantly responsible for the mortality benefit of radial as compared with femoral access in the MATRIX trial. There was little evidence for an equally important, independent role of bleeding.


Assuntos
Síndrome Coronariana Aguda/mortalidade , Síndrome Coronariana Aguda/terapia , Injúria Renal Aguda/prevenção & controle , Hemorragia/prevenção & controle , Intervenção Coronária Percutânea/efeitos adversos , Síndrome Coronariana Aguda/diagnóstico por imagem , Injúria Renal Aguda/etiologia , Estudos de Casos e Controles , Angiografia Coronária/métodos , Artéria Femoral/cirurgia , Hemorragia/etiologia , Humanos , Intervenção Coronária Percutânea/métodos , Artéria Radial/cirurgia , Infarto do Miocárdio com Supradesnível do Segmento ST/fisiopatologia , Resultado do Tratamento
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