Zero-cell corrections in random-effects meta-analyses

The standard estimator for the log odds ratio (the unconditional maximum likelihood estimator) and the delta-method estimator for its standard error are not defined if the corresponding 2x2 table contains at least one "zero cell". This is also an issue when estimating the overall log odds ratio in a meta-analysis. It is well known that correcting for zero cells by adding a small increment should be avoided. Nevertheless, these zero-cell corrections continue to be used. With this article, we want to warn of a particularly bad zero-cell correction. For this, we conduct a simulation study comparing the following two zero-cell corrections under the ordinary random-effects model: (i) adding 1/2 to all cells of all the individual studies' 2x2 tables independently of any zero-cell occurrences and (ii) adding 1/2 to all cells of only those 2x2 tables containing at least one zero cell. The main finding is that correction (i) performs worse than correction (ii). Thus, we strongly discourage the use of correction (i)

Code and output for "Interval estimation of the overall treatment effect in random-effects meta-analyses: Recommendations from a simulation study comparing frequentist, Bayesian, and bootstrap methods"

This is the code and output corresponding to: Weber F, Knapp G, Glass Ä, Kundt G, and Ickstadt K (2020). "Interval estimation of the overall treatment effect in random-effects meta-analyses: Recommendations from a simulation study comparing frequentist, Bayesian, and bootstrap methods". Research Synthesis Methods, 12(3), 291-315. DOI: 10.1002/jrsm.1471. URL: https://doi.org/10.1002/jrsm.1471; Weber F, Knapp G, Glass Ä, Kundt G, and Ickstadt K (2020). "Interval estimation of the overall treatment effect in random-effects meta-analyses: Recommendations from a simulation study comparing frequentist, Bayesian, and bootstrap methods". OSF Preprints. DOI: 10.31219/osf.io/5zbh6. URL: https://doi.org/10.31219/osf.io/5zbh6

Interval estimation of the overall treatment effect in random-effects meta-analyses: Recommendations from a simulation study comparing frequentist, Bayesian, and bootstrap methods

There exists a variety of interval estimators for the overall treatment effect in a random-effects meta-analysis. A recent literature review summarizing existing methods suggested that in most situations, the Hartung-Knapp/Sidik-Jonkman (HKSJ) method was preferable. However, a quantitative comparison of those methods in a common simulation study is still lacking. Thus, we conduct such a simulation study for continuous and binary outcomes, focusing on the medical field for application. Based on the literature review and some new theoretical considerations, a practicable number of interval estimators is selected for this comparison: the classical normal-approximation interval using the DerSimonian-Laird heterogeneity estimator, the HKSJ interval using either the Paule-Mandel or the Sidik-Jonkman heterogeneity estimator, the Skovgaard higher-order profile likelihood interval, a parametric bootstrap interval, and a Bayesian interval using different priors. We evaluate the performance measures (coverage and interval length) at specific points in the parameter space, i.e. not averaging over a prior distribution. In this sense, our study is conducted from a frequentist point of view. We confirm the main finding of the literature review, the general recommendation of the HKSJ method (here with the Sidik-Jonkman heterogeneity estimator). For meta-analyses including only 2 studies, the high length of the HKSJ interval limits its practical usage. In this case, the Bayesian interval using a weakly informative prior for the heterogeneity may help. Our recommendations are illustrated using a real-world meta-analysis dealing with the efficacy of an intramyocardial bone marrow stem cell transplantation during coronary artery bypass grafting

Prospective data collection and analysis of perforations and tears of latex surgical gloves during primary endoprosthetic surgeries

Introduction: Surgical gloves are used to prevent contamination of the patient and the hospital staff with pathogens. The aim of this study was to examine the actual effectiveness of gloves by examining the damage (perforations, tears) to latex gloves during surgery in the case of primary hip and knee prosthesis implantation. Materials and methods: Latex surgical gloves used by surgeons for primary hip and knee replacement surgeries were collected directly after the surgery and tested using the watertightness test according to ISO EN 455-1:2000.Results: 540 gloves were collected from 104 surgeries. In 32.7% of surgeries at least one glove was damaged. Of all the gloves collected, 10.9% were damaged, mainly on the index finger. The size of the perforations ranged from ≤1 mm to over 5 mm. The surgeon’s glove size was the only factor that significantly influenced the occurrence of glove damage. Surgeon training level, procedure duration, and the use of bone cement had no significant influence.Conclusions: Our results highlight the high failure rate of surgical gloves. This has acute implications for glove production, surgical practice, and hygiene guidelines. Further studies are needed to detect the surgical steps, surface structures, and instruments that pose an increased risk for glove damage

The effects of hydrogen sulfide on platelet–leukocyte aggregation and microvascular thrombolysis

The volatile transmitter hydrogen sulfide (H2S) is known for its various functions in vascular biology. This study evaluates the effect of the H2S-donor GYY4137 (GYY) on thrombus stability and microvascular thrombolysis. Human whole blood served for all in vitro studies and was analyzed in a resting state, after stimulation with thrombin-receptor activating peptide (TRAP) and after incubation with 10 or 30 mM GYY or its vehicle DMSO following TRAP-activation, respectively. As a marker for thrombus stability, platelet–leukocyte aggregation was assessed using flow cytometry after staining of human whole blood against CD62P and CD45, respectively. Furthermore, morphology and quantity of platelet–leukocyte aggregation were studied by means of scanning electron microscopy (scanning EM). Therefore, platelets were stained for CD62P followed by immuno gold labeling. In vivo, the dorsal skinfold chamber preparation was performed for light/dye induction of thrombi in arterioles and venules using intravital fluorescence microscopy. Thrombolysis was assessed 10 and 22 h after thrombus induction and treatment with the vehicle, GYY, or recombinant tissue plasminogen activator (rtPA). Flow cytometry revealed an increase of CD62P/CD45 positive aggregates after TRAP stimulation of human whole blood, which was significantly reduced by preincubation with 30 mM GYY. Scanning EM additionally showed a reduced platelet–leukocyte aggregation and a decreased leukocyte count within the aggregates after preincubation with GYY compared to TRAP stimulation alone. Further on, morphological signs of platelet activation were found markedly reduced upon treatment with GYY. In mice, both GYY and rtPA significantly accelerated arteriolar and venular thrombolysis compared to the vehicle control. In conclusion, GYY impairs thrombus stability by reducing platelet–leukocyte aggregation and thereby facilitates endogenous thrombolysis