Toric Intraocular Lenses in the Correction of Astigmatism During Cataract Surgery A Systematic Review and Meta-analysis

TopicWe performed a systematic review and meta-analysis to evaluate the benefit and harms associated with implantation of toric intraocular lenses (IOLs) during cataract surgery. Outcomes were postoperative uncorrected distance visual acuity (UCDVA) and distance spectacle independence. Harms were evaluated as surgical complications and residual astigmatism.Clinical RelevancePostoperative astigmatism is an important cause of suboptimal UCDVA and need for distance spectacles. Toric IOLs may correct for preexisting corneal astigmatism at the time of surgery.MethodsWe performed a systematic literature search in the Embase, PubMed, and CENTRAL databases within the Cochrane Library. We included randomized clinical trials (RCTs) if they compared toric with non-toric IOL implantation (± relaxing incision) in patients with regular corneal astigmatism and age-related cataracts. We assessed the risk of bias using the Cochrane Risk of Bias tool. We assessed the quality of evidence across studies using the GRADE profiler software (available at: www.gradeworkinggroup.org).ResultsWe included 13 RCTs with 707 eyes randomized to toric IOLs and 706 eyes randomized to non-toric IOLs; 225 eyes had a relaxing incision. We found high-quality evidence that UCDVA was better in the toric IOL group (logarithm of the minimum angle of resolution [logMAR] mean difference, −0.07; 95% confidence interval [CI], −0.10 to −0.04) and provided greater spectacle independence (risk ratio [RR], 0.51; 95% CI, 0.36–0.71) and moderate quality evidence that toric IOL implantation was not associated with an increased risk of complications (RR, 1.73; 95% CI, 0.60–5.04). Residual astigmatism was lower in the toric IOL group than in the non-toric IOL plus relaxing incision group (mean difference, 0.37 diopter [D]; 95% CI, −0.55 to −0.19).ConclusionsWe found that toric IOLs provided better UCDVA, greater spectacle independence, and lower amounts of residual astigmatism than non-toric IOLs even when relaxing incisions were used

Pain relief that matters to patients: systematic review of empirical studies assessing the minimum clinically important difference in acute pain

BACKGROUND: The minimum clinically important difference (MCID) is used to interpret the clinical relevance of results reported by trials and meta-analyses as well as to plan sample sizes in new studies. However, there is a lack of consensus about the size of MCID in acute pain, which is a core symptom affecting patients across many clinical conditions. METHODS: We identified and systematically reviewed empirical studies of MCID in acute pain. We searched PubMed, EMBASE and Cochrane Library, and included prospective studies determining MCID using a patient-reported anchor and a one-dimensional pain scale (e.g. 100 mm visual analogue scale). We summarised results and explored reasons for heterogeneity applying meta-regression, subgroup analyses and individual patient data meta-analyses. RESULTS: We included 37 studies (8479 patients). Thirty-five studies used a mean change approach, i.e. MCID was assessed as the mean difference in pain score among patients who reported a minimum degree of improvement, while seven studies used a threshold approach, i.e. MCID was assessed as the threshold in pain reduction associated with the best accuracy (sensitivity and specificity) for identifying improved patients. Meta-analyses found considerable heterogeneity between studies (absolute MCID: I(2) = 93%, relative MCID: I(2) = 75%) and results were therefore presented qualitatively, while analyses focused on exploring reasons for heterogeneity. The reported absolute MCID values ranged widely from 8 to 40 mm (standardised to a 100 mm scale) and the relative MCID values from 13% to 85%. From analyses of individual patient data (seven studies, 918 patients), we found baseline pain strongly associated with absolute, but not relative, MCID as patients with higher baseline pain needed larger pain reduction to perceive relief. Subgroup analyses showed that the definition of improved patients (one or several categories improvement or meaningful change) and the design of studies (single or multiple measurements) also influenced MCID values. CONCLUSIONS: The MCID in acute pain varied greatly between studies and was influenced by baseline pain, definitions of improved patients and study design. MCID is context-specific and potentially misguiding if determined, applied or interpreted inappropriately. Explicit and conscientious reflections on the choice of a reference value are required when using MCID to classify research results as clinically important or trivial

Effects of glucosamine, chondroitin, or placebo in patients with osteoarthritis of hip or knee: network meta-analysis

Objective To determine the effect of glucosamine, chondroitin, or the two in combination on joint pain and on radiological progression of disease in osteoarthritis of the hip or knee

Industry-supported meta-analyses compared with meta-analyses with non-profit or no support: Differences in methodological quality and conclusions

<p>Abstract</p> <p>Background</p> <p>Studies have shown that industry-sponsored meta-analyses of drugs lack scientific rigour and have biased conclusions. However, these studies have been restricted to certain medical specialities. We compared all industry-supported meta-analyses of drug-drug comparisons with those without industry support.</p> <p>Methods</p> <p>We searched PubMed for all meta-analyses that compared different drugs or classes of drugs published in 2004. Two authors assessed the meta-analyses and independently extracted data. We used a validated scale for judging the methodological quality and a binary scale for judging conclusions. We divided the meta-analyses according to the type of support in 3 categories: industry-supported, non-profit support or no support, and undeclared support.</p> <p>Results</p> <p>We included 39 meta-analyses. Ten had industry support, 18 non-profit or no support, and 11 undeclared support. On a 0–7 scale, the median quality score was 6 for meta-analyses with non-profit or no support and 2.5 for the industry-supported meta-analyses (P < 0.01). Compared with industry-supported meta-analyses, more meta-analyses with non-profit or no support avoided bias in the selection of studies (P = 0.01), more often stated the search methods used to find studies (P = 0.02), searched comprehensively (P < 0.01), reported criteria for assessing the validity of the studies (P = 0.02), used appropriate criteria (P = 0.04), described methods of allocation concealment (P = 0.05), described methods of blinding (P = 0.05), and described excluded patients (P = 0.08) and studies (P = 0.15). Forty percent of the industry-supported meta-analyses recommended the experimental drug without reservations, compared with 22% of the meta-analyses with non-profit or no support (P = 0.57).</p> <p>In a sensitivity analysis, we contacted the authors of the meta-analyses with undeclared support. Eight who replied that they had not received industry funding were added to those with non-profit or no support, and 3 who did not reply were added to those with industry support. This analysis did not change the results much.</p> <p>Conclusion</p> <p>Transparency is essential for readers to make their own judgment about medical interventions guided by the results of meta-analyses. We found that industry-supported meta-analyses are less transparent than meta-analyses with non-profit support or no support.</p

536Systematic Review and Meta-Analysis of Randomized Controlled Trials (RCTs) Comparing Initial Non-Nucleoside Reverse-Transcriptase Inhibitor (NNRTI)- versus Ritonavir Boosted Protease Inhibitor (PI/r)-based Anti-Retroviral Therapy (ART)

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Clinical care of pregnant and postpartum women with COVID-19: Living recommendations from the National COVID-19 Clinical Evidence Taskforce

To date, 18 living recommendations for the clinical care of pregnant and postpartum women with COVID-19 have been issued by the National COVID-19 Clinical Evidence Taskforce. This includes recommendations on mode of birth, delayed umbilical cord clamping, skin-to-skin contact, breastfeeding, rooming-in, antenatal corticosteroids, angiotensin-converting enzyme inhibitors, disease-modifying treatments (including dexamethasone, remdesivir and hydroxychloroquine), venous thromboembolism prophylaxis and advanced respiratory support interventions (prone positioning and extracorporeal membrane oxygenation). Through continuous evidence surveillance, these living recommendations are updated in near real-time to ensure clinicians in Australia have reliable, evidence-based guidelines for clinical decision-making. Please visit https://covid19evidence.net.au/ for the latest recommendation updates

Multiplicity of data in trial reports and the reliability of meta-analyses: empirical study.

OBJECTIVES: To examine the extent of multiplicity of data in trial reports and to assess the impact of multiplicity on meta-analysis results. DESIGN: Empirical study on a cohort of Cochrane systematic reviews. DATA SOURCES: All Cochrane systematic reviews published from issue 3 in 2006 to issue 2 in 2007 that presented a result as a standardised mean difference (SMD). We retrieved trial reports contributing to the first SMD result in each review, and downloaded review protocols. We used these SMDs to identify a specific outcome for each meta-analysis from its protocol. Review methods Reviews were eligible if SMD results were based on two to ten randomised trials and if protocols described the outcome. We excluded reviews if they only presented results of subgroup analyses. Based on review protocols and index outcomes, two observers independently extracted the data necessary to calculate SMDs from the original trial reports for any intervention group, time point, or outcome measure compatible with the protocol. From the extracted data, we used Monte Carlo simulations to calculate all possible SMDs for every meta-analysis. RESULTS: We identified 19 eligible meta-analyses (including 83 trials). Published review protocols often lacked information about which data to choose. Twenty-four (29%) trials reported data for multiple intervention groups, 30 (36%) reported data for multiple time points, and 29 (35%) reported the index outcome measured on multiple scales. In 18 meta-analyses, we found multiplicity of data in at least one trial report; the median difference between the smallest and largest SMD results within a meta-analysis was 0.40 standard deviation units (range 0.04 to 0.91). CONCLUSIONS: Multiplicity of data can affect the findings of systematic reviews and meta-analyses. To reduce the risk of bias, reviews and meta-analyses should comply with prespecified protocols that clearly identify time points, intervention groups, and scales of interest