Observational study:efficacy of aspirin and low-molecular-weight heparin in the management of recurrent miscarriage

In the present study,we aimed to assess the comparative efficacy of low-molecular-weight heparin(LMWH)in combination with low-dose aspirin for the management of recurrent miscarriage and scrutinize alterations in coagulation function following such treatment.A retrospective analysis was conducted on clinical data obtained from 97 patients with recurrent miscarriage treated at our institution from January 2019 to June 2020.Patients were categorized into either the study or control groups based on the administration of LMWH.The control group comprised 48 patients treated solely with aspirin,while the study group included 49 patients treated with both LMWH and aspirin.Comparative evaluations between the two groups encompassed pregnancy outcomes,coagulation function,adverse reactions,and blood loss during delivery.Results revealed a higher term birth rate in the study group(83.67%)compared to the control group(50%).Post-treatment,the study group exhibited lower prothrombin time,plasminogen activator inhibitor,and D-dimer levels than the control group.Moreover,the study group experienced fewer adverse reactions and reduced blood loss during delivery in comparison to the control group,demonstrating statistical significance(P<0.05).The combination of LMWH and low-dose aspirin exhibited noteworthy application in the management of recurrent miscarriage.This therapeutic approach not only fostered the enhancement of coagulation function conducive to pregnancy but also diminished the incidence of adverse reactions observed with aspirin alone.

Voxel modeling and association of ubiquitous spatiotemporal information in natural language texts

The ubiquitous spatiotemporal information extracted from Internet texts limits its application in spatiotemporal association and analysis due to its unstructured nature and uncertainty.This study uses ST-Voxel modeling to solve the problem of structured modeling and the association of ubiquitous spatiotemporal information in natural language texts.It provides a new solution for associating ubiquitous spatiotemporal information on the Internet and discovering public opinion.The main contributions of this paper include:(1)It proposes a convolved method for ST-Voxel,which solves the voxel modeling problem of unstructured and uncertain spatiotemporal objects and spatiotemporal relation in natural language texts.Experiments show that this method can effectively model 5 types of spatiotemporal objects and 16 types of uncertain spatiotemporal relation founded in texts;(2)It realizes the unknown event discovery based on voxelized spatiotemporal information association.Experiments show that this method can effectively solve the aggregation of ubiquitous spatiotemporal information in multi-natural language texts,which is conducive to discovering spatiotemporal events.The selection of convolution parameters in voxel modeling is also discussed.A parameter selection method for balancing the discovery capability and discovery accuracy of spatiotemporal events is given.