Dynamic Prognosis Prediction for Patients on DAPT After Drug-Eluting Stent Implantation: Model Development and Validation

BACKGROUND

The rapid evolution of artificial intelligence (AI) in conjunction with recent updates in dual antiplatelet therapy (DAPT) management guidelines emphasizes the necessity for innovative models to predict ischemic or bleeding events after drug-eluting stent implantation. Leveraging AI for dynamic prediction has the potential to revolutionize risk stratification and provide personalized decision support for DAPT management.

METHODS AND RESULTS

We developed and validated a new AI-based pipeline using retrospective data of drug-eluting stent-treated patients, sourced from the Cerner Health Facts data set (n=98 236) and Optum's de-identified Clinformatics Data Mart Database (n=9978). The 36 months following drug-eluting stent implantation were designated as our primary forecasting interval, further segmented into 6 sequential prediction windows. We evaluated 5 distinct AI algorithms for their precision in predicting ischemic and bleeding risks. Model discriminative accuracy was assessed using the area under the receiver operating characteristic curve, among other metrics. The weighted light gradient boosting machine stood out as the preeminent model, thus earning its place as our AI-DAPT model. The AI-DAPT demonstrated peak accuracy in the 30 to 36 months window, charting an area under the receiver operating characteristic curve of 90% [95% CI, 88%-92%] for ischemia and 84% [95% CI, 82%-87%] for bleeding predictions.

CONCLUSIONS

Our AI-DAPT excels in formulating iterative, refined dynamic predictions by assimilating ongoing updates from patients' clinical profiles, holding value as a novel smart clinical tool to facilitate optimal DAPT duration management with high accuracy and adaptability.

Novel substituted 1,8-naphthyridines: Design, synthesis, radiolabeling, and evaluation of apoptosis and topoisomerase II inhibition

A series of seventeen 1,8-naphthyridine derivatives (5a-5q) conjugated at N₁ to various substituted phenyl rings were designed and synthesized as potential topoisomerase II (Topo II) inhibitors. The antiproliferative activity of the target compounds against three cancer cell lines showed that compounds 5g and 5p had the highest antiproliferative activity. In addition, 5p and 5g displayed a high selectivity index (SI) for cancer cells when tested on WI38 normal cells, whereby compound 5p showed the highest SI. Furthermore, 5g and 5p induced cell cycle arrest at the S and G1/S phases, respectively, triggering apoptosis in HepG-2 cells. The in vitro Topo II inhibitory effect (plasmid-based) of both compounds revealed that 5p had better inhibition of Topo II. In addition, 5p displayed potent topoisomerase IIβ inhibitory effect when compared to known topoisomerase inhibitors (doxorubicin and topotecan). Molecular docking proposed a unique binding pattern of 5p in the etoposide binding pocket of topoisomerase IIβ, endorsing its potential role as a Topo II poison. Accordingly, 5p was chosen for radioiodination to study the degree of tumor localization following administration in solid tumor-bearing mice. The radioiodinated 5p showed a selective localization at the tumor site, which further confirmed the value of 5p as a lead 1,8-naphthyridine anticancer agent.

Synthesis and Antileishmanial Evaluation of Arylimidamide-Azole Hybrids Containing a Phenoxyalkyl Linker

Due to the limitations of existing medications, there is a critical need for new drugs to treat visceral leishmaniasis. Since arylimidamides and antifungal azoles both show oral activity in murine visceral leishmaniasis models, a molecular hybridization approach was employed where arylimidamide and azole groups were separated by phenoxyalkyl linkers in an attempt to capitalize on the favorable antileishmanial properties of both series. Among the target compounds synthesized, a greater antileishmanial potency against intracellular Leishmania donovani was observed as the linker length increased from two to eight carbons and when an imidazole ring was employed as the terminal group compared to a 1,2,4-triazole group. Compound 24c (N-(4-((8-(1H-imidazol-1-yl)octyl)oxy)-2-isopropoxyphenyl) picolinimidamide) displayed activity against L. donovani intracellular amastigotes with an IC₅₀ value of 0.53 μM. When tested in a murine visceral leishmaniasis model, compound 24c at a dose of 75 mg/kg/day p.o. for five consecutive days resulted in a modest 33% decrease in liver parasitemia compared to the control group, indicating that further optimization of these molecules is needed. While potent hybrid compounds bearing an imidazole terminal group were also strong inhibitors of recombinant CYP51 from L. donovani, as assessed by a fluorescence-based assay, additional targets are likely to play an important role in the antileishmanial action of these compounds.

A Deep Learning Approach for Automatic Seizure Detection in Children With Epilepsy

Over the last few decades, electroencephalogram (EEG) has become one of the most vital tools used by physicians to diagnose several neurological disorders of the human brain and, in particular, to detect seizures. Because of its peculiar nature, the consequent impact of epileptic seizures on the quality of life of patients made the precise diagnosis of epilepsy extremely essential. Therefore, this article proposes a novel deep-learning approach for detecting seizures in pediatric patients based on the classification of raw multichannel EEG signal recordings that are minimally pre-processed. The new approach takes advantage of the automatic feature learning capabilities of a two-dimensional deep convolution autoencoder (2D-DCAE) linked to a neural network-based classifier to form a unified system that is trained in a supervised way to achieve the best classification accuracy between the ictal and interictal brain state signals. For testing and evaluating our approach, two models were designed and assessed using three different EEG data segment lengths and a 10-fold cross-validation scheme. Based on five evaluation metrics, the best performing model was a supervised deep convolutional autoencoder (SDCAE) model that uses a bidirectional long short-term memory (Bi-LSTM) – based classifier, and EEG segment length of 4 s. Using the public dataset collected from the Children’s Hospital Boston (CHB) and the Massachusetts Institute of Technology (MIT), this model has obtained 98.79 ± 0.53% accuracy, 98.72 ± 0.77% sensitivity, 98.86 ± 0.53% specificity, 98.86 ± 0.53% precision, and an F1-score of 98.79 ± 0.53%, respectively. Based on these results, our new approach was able to present one of the most effective seizure detection methods compared to other existing state-of-the-art methods applied to the same dataset.

Definitive ureteroscopy and intracorporeal lithotripsy in treatment of ureteral calculi during pregnancy

Objective

To evaluate the outcome of using semi-rigid ureteroscopy with or without intracorporeal pneumatic lithotripsy vs. temporary ureteric JJ stenting in the management of obstructing ureteric calculi in pregnant women.

Patients and methods

This prospective comparative study comprised 43 pregnant women with obstructing ureteric calculi. The diagnosis was based on the acute flank pain as the main symptom, microscopic haematuria, and unilateral hydronephrosis on abdominal ultrasonography (US). The patients were randomly divided into two groups; those in group 1 (22 patients) were treated by temporary ureteric JJ stenting until after delivery, and those in group 2 (21) were treated definitively by ureteroscopic stone extraction with intracorporeal pneumatic lithotripsy. Postoperative complications and the degree of patient satisfaction were reported.

Results

An obstructing ureteric stone was identified by US in 68% and 76% of groups 1 and 2, respectively. In group 1, nine patients had mid-ureteric stones and 13 had stones in the lower ureter. In group 2, seven patients had mid-ureteric stones, whilst the stones were in the distal ureter in 14. No perioperative foetal complications were detected in any group and all patients completed the full term of pregnancy. In group 1, four patients had a postoperative urinary tract infection (UTI), and the JJ stent was exchanged in seven. Two patients in group 2 had a postoperative UTI.

Conclusions

Definitive ureteroscopy, even with intracorporeal pneumatic lithotripsy, is an effective and safe treatment for pregnant women with obstructing ureteric calculi. It has a better outcome and is more satisfactory for the patients than a temporary JJ stent.