BackgroundLung cancer remains the leading cause of cancer-related deaths worldwide. The recurrence rate ranges from 35–50% among early stage non-small cell lung cancer patients. To date, there is no fully-validated and clinically applied prognostic gene signature for personalized treatment.Methodology/Principal FindingsFrom genome-wide mRNA expression profiles generated on 256 lung adenocarcinoma patients, a 12-gene signature was identified using combinatorial gene selection methods, and a risk score algorithm was developed with Naïve Bayes. The 12-gene model generates significant patient stratification in the training cohort HLM & UM (n = 256; log-rank P = 6.96e-7) and two independent validation sets, MSK (n = 104; log-rank P = 9.88e-4) and DFCI (n = 82; log-rank P = 2.57e-4), using Kaplan-Meier analyses. This gene signature also stratifies stage I and IB lung adenocarcinoma patients into two distinct survival groups (log-rank P<0.04). The 12-gene risk score is more significant (hazard ratio = 4.19, 95% CI: [2.08, 8.46]) than other commonly used clinical factors except tumor stage (III vs. I) in multivariate Cox analyses. The 12-gene model is more accurate than previously published lung cancer gene signatures on the same datasets. Furthermore, this signature accurately predicts chemoresistance/chemosensitivity to Cisplatin, Carboplatin, Paclitaxel, Etoposide, Erlotinib, and Gefitinib in NCI-60 cancer cell lines (P<0.017). The identified 12 genes exhibit curated interactions with major lung cancer signaling hallmarks in functional pathway analysis. The expression patterns of the signature genes have been confirmed in RT-PCR analyses of independent tumor samples.Conclusions/SignificanceThe results demonstrate the clinical utility of the identified gene signature in prognostic categorization. With this 12-gene risk score algorithm, early stage patients at high risk for tumor recurrence could be identified for adjuvant chemotherapy; whereas stage I and II patients at low risk could be spared the toxic side effects of chemotherapeutic drugs.

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The underlying pathology in IST is yet to be completely understood. However, it is thought that the causes of IST can be broadly classified into two groups; either as an intrinsic increase in sinus node automaticity or an extrinsic cause. Among extrinsic causes, there is evolving evidence that IgG anti-β receptor antibodies are found in IST causing tachycardia. Managing patients with IST includes lifestyle modification, non-pharmacological and pharmacological interventions. Ivabradine has recently emerged as an effective treatment of IST and was shown to be superior to beta-blockers.

Background The prognostic value of echocardiographic evaluation of right ventricular (RV) function in patients undergoing left‐sided valvular surgery has not been well described. The objective of this study is to determine the role of broad echocardiographic assessment of RV function in predicting short‐term outcomes after valvular surgery. Methods and Results Preoperative echocardiographic data, perioperative adverse outcomes, and 30‐day mortality were analyzed in patients who underwent left‐sided valvular surgery from 2006 to 2014. Echocardiographic parameters used to evaluate RV function include RV fractional area change, tricuspid annular plane systolic excursion, systolic movement of the RV lateral wall using tissue Doppler imaging (S'), RV myocardial performance index, and RV dP/dt. Subjects with at least 3 abnormal parameters out of the 5 aforementioned indices were defined as having significant RV dysfunction. The study included 269 patients with valvular surgery (average age: 67±15, 60.6% male, 148 aortic, and 121 mitral). RV dysfunction was found in 53 (19.7%) patients; 30‐day mortality occurred in 20 patients (7.5%). Compared with normal RV function, patients with RV dysfunction had higher 30‐day mortality (22.6% versus 3.8%; P =0.01) and were at risk for developing multisystem failure/shock (13.2% versus 3.2%; P =0.01). Multivariate analyses showed that preexisting RV dysfunction was the strongest predictor of increased 30‐day mortality (odds ratio: 3.5; 95% CI, 1.1–11.1; P <0.05). Conclusions Preoperative RV dysfunction identified by comprehensive echocardiographic assessment is a strong predictor of adverse outcomes following left‐sided valvular surgery.

The number of patients with implantable electronic cardiac devices is continuously increasing. As more pacemakers and implantable cardioverter-defibrillators (ICDs) are being placed, a basic understanding of some troubleshooting for devices is becoming essential. Loss of capture can be an emergent presentation for an unstable patient and can be encountered intermittently in hospitalized patients. There are many causes for a loss of capture, with the timing of the implant having a high correlation with certain causes over others. The most common acute cause just after the insertion procedure is lead dislodgement or malposition. In comparison, an increase in the required threshold promoting a loss of capture can happen after months to years of insertion of the pacemaker or ICD. This change can be due to a cardiomyopathy, fibrosis medications, metabolic imbalance, lead fracture, or an exit block. Loss of capture can also occur from external electrical stimuli and inappropriate pacemaker or ICD settings. Further, there are also potential noncardiac causes, such as medications, electrolyte imbalance, and acidemia. A knowledge of these factors is essential for health care providers, given the morbidity and mortality that can potentially be associated with device-related issues, especially in patients who are dependent on the included pacing function.