Efectividad del moxifloxacino intracameral profiláctico para reducir la endoftalmitis posterior a cirugía de cataratas en población chilena

Background: Endophthalmitis is a serious infectious complication of cataract surgery, which may lead to vision loss. Aim: To evaluate the effectiveness of intracameral moxifloxacin in reducing endophthalmitis after cataract surgery in Chilean patients. Material and Methods: We reviewed all phacoemulsification surgeries performed between 2012 and 2020 at a public hospital. The use of intraoperative intracameral moxifloxacin and possible surgical complications were recorded. In patients with postoperative endophthalmitis, we reviewed their risk factors and clinical characteristics. Results: In the study, 22,869 phacoemulsification surgeries were registered, with an annual average of 2,541. The use of prophylactic intracameral moxifloxacin started progressively in 2014. In 2018 it was used in 88% of the surgeries. Fifteen eyes evolved with postoperative endophthalmitis, but none of these surgeries used intracameral moxifloxacin. Five and seven cases occurred in 2012 and 2013, respectively. There was a trend favoring moxifloxacin use, as a preventive measure for endophthalmitis, but the difference between groups was not significant (p = 0.56). In the group with endophthalmitis, 33.3% of the eyes were from patients with type 2 diabetes mellitus, in 13.3% there was rupture of the posterior capsule and 60% of the eyes corresponded to female patients. Since 2018 there is no record of endophthalmitis after cataract surgery performed in this center. Conclusions: Intracameral moxifloxacin showed a tendency to reduce the frequency of endophthalmitis after phacoemulsification surgery, but a longer observation period is required to reach statistical significance, due to the low frequency of this complication.

Exactitud de tamizaje de retinopatía diabética: inteligencia artificial versus tecnólogos médicos entrenados / Accuracy of artificial intelligence compared to trained medical technologists in diabetic retinopathy screening

Background: The early detection of retinopathy among diabetics is of utmost importance. Aim: To estimate the diagnostic accuracy of two diabetic retinopathy (DR) screening strategies currently used in the Chilean public health system. Material and Methods: Cross-sectional observational study of 371 diabetic patients aged 61 ± 14 years (61% women) who underwent DR screening at a public Hospital between July 1 and August 31, 2019. The mydriatic retinal photographs of all participants were classified using artificial intelligence software (DART) and trained medical technologists, independently. The precision of both strategies was compared with the reference standard, namely the evaluation of the fundus by an ophthalmologist with a slit lamp. Participants with severe non-proliferative DR or worse were considered as positive cases. The ophthalmologist was blind to the results of the screening tests. Results: Twenty four percent of participants had DR, including 34 (9.2%) who had sight threatening DR in at least one eye. The sensitivity and specificity of DART were 100% (95% confidence intervals (CI): 90-100%) and 55,4% (95% CI: 50-61%), respectively. Medical technologists had a sensitivity of 97,1% (95% CI: 85-100%) and a specificity of 91,7% (95% CI: 88-94%). The only case missed by medical technologists was a patient with unilateral panphotocoagulated DR. Conclusions: Both strategies had a similar sensitivity to detect cases of sight-threatening DR. However, the specificity of DART was significantly lower compared to medical technologists, which would greatly increase the burden on the health system, a very important aspect to consider in a screening strategy.

Multiple imputation procedures allow the rescue of missing data: An application to determine serum tumor necrosis factor (TNF) concentration values during the treatment of rheumatoid arthritis patients with anti-TNF therapy

Longitudinal studies aimed at evaluating patients clinical response to specific therapeutic treatments are frequently summarized in incomplete datasets due to missing data. Multivariate statistical procedures use only complete cases, deleting any case with missing data. MI and MIANALYZE procedures of the SAS software perform multiple imputations based on the Markov Chain Monte Carlo method to replace each missing value with a plausible value and to evaluate the efficiency of such missing data treatment. The objective of this work was to compare the evaluation of differences in the increase of serum TNF concentrations depending on the ¡308 TNF promoter genotype of rheumatoid arthritis (RA) patients receiving anti-TNF therapy with and without multiple imputations of missing data based on mixed models for repeated measures. Our results indicate that the relative efficiency of our multiple imputation model is greater than 98 percent and that the related inference was significant (p-value < 0.001). We established that under both approaches serum TNF levels in RA patients bearing the G/A ¡308 TNF promoter genotype displayed a significantly (p-value < 0.0001) increased ability to produce TNF over time than the G/G patient group, as they received successively doses of anti-TNF therapy.