No abstract

The cost for SILC did not differ significantly from that for LC when standard materials were used and the duration of the procedure was considered. Converted cases were significantly more expensive than completed SILC and LC cases.

Aims Mitral valve prolapse (MVP) is a common valvular heart disease with a prevalence of >2% in the general adult population. Despite this high incidence, there is a limited understanding of the molecular mechanism of this disease, and no medical therapy is available for this disease. We aimed to elucidate the genetic basis of MVP in order to better understand this complex disorder. Methods and results We performed a meta-analysis of six genome-wide association studies that included 4884 cases and 434 649 controls. We identified 14 loci associated with MVP in our primary analysis and 2 additional loci associated with a subset of the samples that additionally underwent mitral valve surgery. Integration of epigenetic, transcriptional, and proteomic data identified candidate MVP genes including LMCD1, SPTBN1, LTBP2, TGFB2, NMB, and ALPK3. We created a polygenic risk score (PRS) for MVP and showed an improved MVP risk prediction beyond age, sex, and clinical risk factors. Conclusion We identified 14 genetic loci that are associated with MVP. Multiple analyses identified candidate genes including two transforming growth factor-β signalling molecules and spectrin β. We present the first PRS for MVP that could eventually aid risk stratification of patients for MVP screening in a clinical setting. These findings advance our understanding of this common valvular heart disease and may reveal novel therapeutic targets for intervention. Key question Expand our understanding of the genetic basis for mitral valve prolapse (MVP). Uncover relevant pathways and target genes for MVP pathophysiology. Leverage genetic data for MVP risk prediction. Key finding Sixteen genetic loci were significantly associated with MVP, including 13 novel loci. Interesting target genes at these loci included LTBP2, TGFB2, ALKP3, BAG3, RBM20, and SPTBN1. A risk score including clinical factors and a polygenic risk score, performed best at predicting MVP, with an area under the receiver operating characteristics curve of 0.677. Take-home message Mitral valve prolapse has a polygenic basis: many genetic variants cumulatively influence pre-disposition for disease. Disease risk may be modulated via changes to transforming growth factor-β signalling, the cytoskeleton, as well as cardiomyopathy pathways. Polygenic risk scores could enhance the MVP risk prediction.

Early recognition of massive transfusion (MT) requirement in geriatric trauma patients presents a challenge, as older patients present with vital signs outside of traditional thresholds for hypotension and tachycardia. Although many systems exist to predict MT need in trauma patients, none have specifically evaluated the geriatric population. We sought to evaluate the predictive value of presenting vital signs in geriatric trauma patients for prediction of MT. We retrospectively reviewed geriatric trauma patients presenting to our Level I trauma center from 2010 to 2013 requiring full trauma team activation. The area under the receiver operating characteristic curve was calculated to assess discrimination of arrival vital signs for MT prediction. Ideal cutoffs with high sensitivity and specificity were identified. A total of 194 patients with complete data were analyzed. Of these, 16 patients received MT. There was no difference between the MT and non-MT groups in sex, age, or mechanism. Systolic blood pressure, pulse pressure, diastolic blood pressure, and shock index all were strongly predictive of MT need. Interestingly, we found that heart rate does not predict MT. MT in geriatric trauma patients can be reliably and simply predicted by arrival vital signs. Heart rate may not reflect serious hemorrhage in this population.