Our Experience of Comparison of Hearing Outcomes in Patients Undergoing Type-1 Tympanoplasty with Different Graft Materials.

The present study was undertaken to compare the results of various autogenous tissues: temporalis fascia, sliced tragal cartilage and fascia lata as graft materials for type I tympanoplasty in terms of hearing improvement in safe type of chronic suppurative otitis media. A total of 75 cases with central perforation were considered in the study. Of the 75 cases, temporalis fascia graft was used in 25 cases (Group-A), fascia lata graft in 25 cases (Group-B), and sliced tragal cartilage graft in 25 cases (Group-C). The results were evaluated in the form of hearing improvement with respect to the graft materials. A significant association was observed between the groups, that is, temporalis fascia (Group-A), fascia lata (Group-B), and sliced tragal cartilage (Group-C) in terms of improvement in AB gap (P = 0.047). Improvement in AB gap was statistically significant between groups B and A, but not between the other groups. In the present study, fascia lata showed better graft uptake as compared to temporalis fascia and sliced tragal cartilage. The hearing assessment at post-operative 3rd month showed statistically significant hearing improvement with fascia lata when compared to temporalis fascia.

Association of Insurance Status With Emergent Versus Nonemergent Hospital Encounters Among Adults With Congenital Heart Disease.

Background Although the number of hospital visits has exponentially increased for adults with congenital heart disease (CHD) over the past few decades, the relationship between insurance status and hospital encounter type remains unknown. The purpose of this study was to evaluate the association between insurance status and emergent versus nonemergent encounters among adults with CHD ≥18 years old. Methods and Results We used California Office of Statewide Health Planning and Development Database from January 2005 to December 2015 to determine the trends of insurance status and encounters and the association of insurance status on encounter type among adults with CHD. A total 58 359 nonpregnancy encounters were identified in 6077 patients with CHD. From 2005 to 2015, the number of uninsured encounters decreased by 38%, whereas government insured encounters increased by 124% and private by 79%. Overall, there was a significantly higher proportion of emergent than nonemergent encounters associated with uninsured status (13.0% versus 1.8%; P<0.0001), whereas the proportion of nonemergent encounters associated with private insurance was higher than emergent encounters (35.8% versus 62.4%; P<0.0001). When individual patients with CHD became uninsured, they were ≈5 times more likely to experience an emergent encounter (P<0.0001); upon changing from uninsured to insured, they were significantly less likely to have an emergent encounter (P<0.001). After multivariate adjustment, uninsured status exhibited the highest odds of an emergent rather than nonemergent encounter compared with all other covariates (adjusted odds ratio, 9.20; 95% CI, 7.83-10.8; P<0.0001). Conclusions Efforts to enhance the ability to obtain and maintain insurance throughout the lifetime of patients with CHD might result in meaningful reductions in emergent encounters and a more efficient use of resources.

Predicting Unplanned Readmissions Following a Hip or Knee Arthroplasty: Retrospective Observational Study.

BACKGROUND: Total joint replacements are high-volume and high-cost procedures that should be monitored for cost and quality control. Models that can identify patients at high risk of readmission might help reduce costs by suggesting who should be enrolled in preventive care programs. Previous models for risk prediction have relied on structured data of patients rather than clinical notes in electronic health records (EHRs). The former approach requires manual feature extraction by domain experts, which may limit the applicability of these models. OBJECTIVE: This study aims to develop and evaluate a machine learning model for predicting the risk of 30-day readmission following knee and hip arthroplasty procedures. The input data for these models come from raw EHRs. We empirically demonstrate that unstructured free-text notes contain a reasonably predictive signal for this task. METHODS: We performed a retrospective analysis of data from 7174 patients at Partners Healthcare collected between 2006 and 2016. These data were split into train, validation, and test sets. These data sets were used to build, validate, and test models to predict unplanned readmission within 30 days of hospital discharge. The proposed models made predictions on the basis of clinical notes, obviating the need for performing manual feature extraction by domain and machine learning experts. The notes that served as model inputs were written by physicians, nurses, pathologists, and others who diagnose and treat patients and may have their own predictions, even if these are not recorded. RESULTS: The proposed models output readmission risk scores (propensities) for each patient. The best models (as selected on a development set) yielded an area under the receiver operating characteristic curve of 0.846 (95% CI 82.75-87.11) for hip and 0.822 (95% CI 80.94-86.22) for knee surgery, indicating reasonable discriminative ability. CONCLUSIONS: Machine learning models can predict which patients are at a high risk of readmission within 30 days following hip and knee arthroplasty procedures on the basis of notes in EHRs with reasonable discriminative power. Following further validation and empirical demonstration that the models realize predictive performance above that which clinical judgment may provide, such models may be used to build an automated decision support tool to help caretakers identify at-risk patients.

Learning to Identify Patients at Risk of Uncontrolled Hypertension Using Electronic Health Records Data.

Hypertension is a major risk factor for stroke, cardiovascular disease, and end-stage renal disease, and its prevalence is expected to rise dramatically. Effective hypertension management is thus critical. A particular priority is decreasing the incidence of uncontrolled hypertension. Early identification of patients at risk for uncontrolled hypertension would allow targeted use of personalized, proactive treatments. We develop machine learning models (logistic regression and recurrent neural networks) to stratify patients with respect to the risk of exhibiting uncontrolled hypertension within the coming three-month period. We trained and tested models using EHR data from 14,407 and 3,009 patients, respectively. The best model achieved an AUROC of 0.719, outperforming the simple, competitive baseline of relying prediction based on the last BP measure alone (0.634). Perhaps surprisingly, recurrent neural networks did not outperform a simple logistic regression for this task, suggesting that linear models should be included as strong baselines for predictive tasks using EHR.

Learning Disentangled Representations of Texts with Application to Biomedical Abstracts.

We propose a method for learning disentangled representations of texts that code for distinct and complementary aspects, with the aim of affording efficient model transfer and interpretability. To induce disentangled embeddings, we propose an adversarial objective based on the (dis)similarity between triplets of documents with respect to specific aspects. Our motivating application is embedding biomedical abstracts describing clinical trials in a manner that disentangles the populations, interventions, and outcomes in a given trial. We show that our method learns representations that encode these clinically salient aspects, and that these can be effectively used to perform aspect-specific retrieval. We demonstrate that the approach generalizes beyond our motivating application in experiments on two multi-aspect review corpora.

Tetrazine-Responsive Self-immolative Linkers.

Molecules that undergo activation or modulation following the addition of benign external small-molecule chemical stimuli have numerous applications. Here, we report the highly efficient "decaging" of a variety of moieties by activation of a "self-immolative" linker, by application of water-soluble and stable tetrazine, including the controlled delivery of doxorubicin in a cellular context.

Nanoparticle "switch-on" by tetrazine triggering.

This work describes how a small-molecule chemical trigger, reacting through the mediatory of an inverse electron demand Diels-Alder reaction, results in enhanced cellular uptake and selective nanoparticle disintegration and cargo liberation, via gross polymeric morphological alterations. The power of these responsive nanoparticles is demonstrated through encapsulation of the anti-cancer agent doxorubicin and its triggered release, allowing controlled cell death in response to a small-molecule chemical trigger.

Synthesis and chemical and biological comparison of nitroxyl- and nitric oxide-releasing diazeniumdiolate-based aspirin derivatives.

Structural modifications of nonsteroidal anti-inflammatory drugs (NSAIDs) have successfully reduced the side effect of gastrointestinal ulceration without affecting anti-inflammatory activity, but they may increase the risk of myocardial infarction with chronic use. The fact that nitroxyl (HNO) reduces platelet aggregation, preconditions against myocardial infarction, and enhances contractility led us to synthesize a diazeniumdiolate-based HNO-releasing aspirin and to compare it to an NO-releasing analogue. Here, the decomposition mechanisms are described for these compounds. In addition to protection against stomach ulceration, these prodrugs exhibited significantly enhanced cytotoxcity compared to either aspirin or the parent diazeniumdiolate toward nonsmall cell lung carcinoma cells (A549), but they were not appreciably toxic toward endothelial cells (HUVECs). The HNO-NSAID prodrug inhibited cylcooxgenase-2 and glyceraldehyde 3-phosphate dehydrogenase activity and triggered significant sarcomere shortening on murine ventricular myocytes compared to control. Together, these anti-inflammatory, antineoplasic, and contractile properties suggest the potential of HNO-NSAIDs in the treatment of inflammation, cancer, or heart failure.

Synthesis and biological evaluation of isoxazolo[4,5-d]pyridazin-4-(5H)-one analogues as potent anti-inflammatory agents.

In this study, eighteen new isoxazolo[4,5-d]pyridazin-4(5H)-one derivatives possessing either a 1,3,4-thiadiazole or a 1,2,4-triazole-5-thione moiety were synthesized and tested for anti-inflammatory activity in vitro (COX-1/COX-2, 5-LOX) and in vivo (rat paw edema assay). Compounds 15, 16, 25, 26 and 28-30 showed dual COX-2 (IC(50)'s in the 2.1-10.9 µM range), and 5-LOX (IC(50)'s in the 6.3-63.5 µM range) inhibitory activity. When administered orally to rats, dual COX-2/5-LOX inhibitors showed higher anti-inflammatory activity in vivo (30-45% reduction of the inflammatory response) than the reference drug ibuprofen (18%). Among dual COX-2/5-LOX inhibitors, the most potent compound (28) exhibited the best anti-inflammatory profile by inhibiting both COX-2 (IC(50)=2.1 µM) and 5-LOX (IC(50)=6.3 µM) enzymes. We investigated the binding interactions of compound 28 by an enzyme-ligand molecular modeling (docking) studies, which showed favorable binding interactions in both COX-2 and 5-LOX active sites. Furthermore, the dual acting COX-2/5-LOX compound 28 exhibited a superior gastrointestinal safety profile (ulcer index=0.25) compared to the reference drug ibuprofen (UI=7.0) when administered orally at the same molar dose. These observations suggest that isoxazolo[4,5-d]pyridazin-4(5H)-one analogs represent a new scaffold to design potent, effective, and safe anti-inflammatory agents possessing dual COX-2/5-LOX inhibitory activity.

Nitric oxide release is not required to decrease the ulcerogenic profile of nonsteroidal anti-inflammatory drugs.

The objective of this work was to evaluate the biological properties of a new series of nitric oxide-releasing nonsteroidal anti-inflammatory drugs (NO-NSAIDs) possessing a tyrosol linker between the NSAID and the NO-releasing moiety (PROLI/NO); however, initial screening of ester intermediates without the PROLI/NO group showed the required (desirable) efficacy/safety ratio, which questioned the need for NO in the design. In this regard, NSAID ester intermediates were potent and selective COX-2 inhibitors in vitro, showed equipotent anti-inflammatory activity compared to the corresponding parent NSAID, but showed a markedly reduced gastric toxicity when administered orally. These results provide complementary evidence to challenge the currently accepted notion that hybrid NO-NSAIDs exert their cytoprotective effects by releasing NO. Results obtained in this work constitute a good body of evidence to initiate a debate about the future replacement of NSAID prodrugs for unprotected NSAIDs (possessing a free carboxylic acid group) currently in clinical use.

Improving Long Term Myoelectric Decoding, Using an Adaptive Classifier with Label Correction.

This study presents a novel adaptive myoelectric decoding algorithm for control of upper limb prosthesis. Myoelectric decoding algorithms are inherently subject to decay in decoding accuracy over time, which is caused by the changes occurring in the muscle signals. The proposed algorithm relies on an unsupervised and on demand update of the training set, and has been designed to adapt to both the slow and fast changes that occur in myoelectric signals. An update in the training data is used to counter the slow changes, whereas an update with label correction addresses the fast changes in the signals. We collected myoelectric data from an able bodied user for over four and a half hours, while the user performed repetitions of eight wrist movements. The major benefit of the proposed algorithm is the lower rate of decay in accuracy; it has a decay rate of 0.2 per hour as opposed to 3.3 for the non adaptive classifier. The results show that, long term decoding accuracy in EMG signals can be maintained over time, improving the performance and reliability of myoelectric prosthesis.

Acyclic triaryl olefins possessing a sulfohydroxamic acid pharmacophore: synthesis, nitric oxide/nitroxyl release, cyclooxygenase inhibition, and anti-inflammatory studies.

Nitric oxide (NO) and its reduced form nitroxyl (HNO), effective vasodilation agents that can inhibit platelet aggregation and adhesion, could suppress adverse cardiovascular effects associated with the use of selective COX-2 inhibitors. In this regard, a sulfohydroxamic acid (SO(2)NHOH) substituent, that can act as a dual NO/HNO donor moiety, was inserted at the para-position of the C2 phenyl ring of acyclic 2-alkyl-1,1,2-triaryl olefins previously shown to be potent and highly selective COX-2 inhibitors. Although this new group of 1,1-diaryl-2-(4-hydroxyaminosulfonylphenyl)alk-1-enes exhibited weak inhibition of the constitutive cyclooxygenase-1 (COX-1) and inducible COX-2 isozymes, in vivo studies showed anti-inflammatory potencies that were generally intermediate between that of the reference drugs aspirin and ibuprofen. All compounds released NO (5.6-13.5% range) upon incubation with phosphate buffer which was increased further (8.3-25.6% range) in the presence of the oxidant K(3)(FeCN(6)).The low release of HNO in MeOH-buffer (< 2% at 24 h incubation) was much higher at alkaline pH (11-37% range). The concept of designing better anti-inflammatory drugs possessing either an effective HNO, or dual NO/HNO, donor moiety that are devoid of adverse ulcerogenic and/or cardiovascular side effects warrants further investigation.