Hasil untuk "Internal medicine"

Justin Ren, PhD, Colin Royse, MBBS, MD, David H. Tian, MD, PhD et al.

Zhi Liu, Tao Yang, Jing Wang et al.

Natural medicines, particularly Traditional Chinese Medicine (TCM), are gaining global recognition for their therapeutic potential in addressing human symptoms and diseases. TCM, with its systematic theories and extensive practical experience, provides abundant resources for healthcare. However, the effective application of TCM requires precise syndrome diagnosis, determination of treatment principles, and prescription formulation, which demand decades of clinical expertise. Despite advancements in TCM-based decision systems, machine learning, and deep learning research, limitations in data and single-objective constraints hinder their practical application. In recent years, large language models (LLMs) have demonstrated potential in complex tasks, but lack specialization in TCM and face significant challenges, such as too big model scale to deploy and issues with hallucination. To address these challenges, we introduce Tianyi with 7.6-billion-parameter LLM, a model scale proper and specifically designed for TCM, pre-trained and fine-tuned on diverse TCM corpora, including classical texts, expert treatises, clinical records, and knowledge graphs. Tianyi is designed to assimilate interconnected and systematic TCM knowledge through a progressive learning manner. Additionally, we establish TCMEval, a comprehensive evaluation benchmark, to assess LLMs in TCM examinations, clinical tasks, domain-specific question-answering, and real-world trials. The extensive evaluations demonstrate the significant potential of Tianyi as an AI assistant in TCM clinical practice and research, bridging the gap between TCM knowledge and practical application.

Zihan Xu, Haotian Ma, Gongbo Zhang et al.

Evidence-based medicine (EBM) is at the forefront of modern healthcare, emphasizing the use of the best available scientific evidence to guide clinical decisions. Due to the sheer volume and rapid growth of medical literature and the high cost of curation, there is a critical need to investigate Natural Language Processing (NLP) methods to identify, appraise, synthesize, summarize, and disseminate evidence in EBM. This survey presents an in-depth review of 129 research studies on leveraging NLP for EBM, illustrating its pivotal role in enhancing clinical decision-making processes. The paper systematically explores how NLP supports the five fundamental steps of EBM -- Ask, Acquire, Appraise, Apply, and Assess. The review not only identifies current limitations within the field but also proposes directions for future research, emphasizing the potential for NLP to revolutionize EBM by refining evidence extraction, evidence synthesis, appraisal, summarization, enhancing data comprehensibility, and facilitating a more efficient clinical workflow.

Tribikram Choudhury, Yacine Haddad, Michael Doser

Infrared quantum dots, operating in the near-infrared (NIR, 700-1400 nm), short-wavelength infrared (SWIR, 1400-3000 nm), mid-infrared (MIR, 3000-8000 nm) and long-wavelength infrared (LWIR, 8000-15000 nm) regions, have promising potential in optoelectronics, nanotechnology and military surveillance applications. The properties of infrared quantum dots exhibit quantum confinement effects, unlike bulk semiconductors, where their bandgap energy and emission wavelength can be precisely tuned by controlling particle size, composition, and surface chemistry. The wide tunability and unique quantum confinement effects in these infrared-emitting materials also make them attractive for both fundamental research, health and space technology. This paper focuses on the synthesis, fabrication and characterisation of polymer-based infrared quantum dots and explores the possible applications of infrared quantum dots in high-energy physics, medicine and astrophysics.

Nanjun Zhang, Bowen Li, Yu Yan et al.

Abstract Background The occurrence of arrhythmias as a complication of Kawasaki disease (KD) is extremely rare. Moreover, previous literature showed a low incidence of arrhythmias during the acute phase of KD, and the majority occurred in the subacute and chronic phases. To date, we have found only 17 sporadically reported global cases in the available literature. Case presentation We present the first documented case of an infant with KD complicated with supraventricular tachycardia (Atrioventricular reentrant tachycardia) during the acute phase. The arrhythmia resolved promptly after the combination therapy of intravenous Immunoglobulin (IVIG) and steroids during the acute phase since the inflammation subsided. Additionally, we conducted a review and summary of cases involving KD-related arrhythmias. Conclusions KD rarely causes arrhythmias, which might be associated with myocarditis and myocardial ischemia attributed to scar formation and/or excessive inflammatory factors damaging the conduction system. Strengthening the early identification and management of complications in patients with KD and personalized follow-up strategies for high-risk children during the chronic phase can enhance patients’ prognosis.

Pedro Zuidberg Dos Martires, Vincent Derkinderen, Luc De Raedt et al.

Recent developments in AI have reinvigorated pursuits to advance the (life) sciences using AI techniques, thereby creating a renewed opportunity to bridge different fields and find synergies. Headlines for AI and the life sciences have been dominated by data-driven techniques, for instance, to solve protein folding with next to no expert knowledge. In contrast to this, we argue for the necessity of a formal representation of expert knowledge - either to develop explicit scientific theories or to compensate for the lack of data. Specifically, we argue that the fields of knowledge representation (KR) and systems biology (SysBio) exhibit important overlaps that have been largely ignored so far. This, in turn, means that relevant scientific questions are ready to be answered using the right domain knowledge (SysBio), encoded in the right way (SysBio/KR), and by combining it with modern automated reasoning tools (KR). Hence, the formal representation of domain knowledge is a natural meeting place for SysBio and KR. On the one hand, we argue that such an interdisciplinary approach will advance the field SysBio by exposing it to industrial-grade reasoning tools and thereby allowing novel scientific questions to be tackled. On the other hand, we see ample opportunities to move the state-of-the-art in KR by tailoring KR methods to the field of SysBio, which comes with challenging problem characteristics, e.g. scale, partial knowledge, noise, or sub-symbolic data. We stipulate that this proposed interdisciplinary research is necessary to attain a prominent long-term goal in the health sciences: precision medicine.

Yixuan Wu, Kaiyuan Hu, Danny Z. Chen et al.

With the rapid advance of computer graphics and artificial intelligence technologies, the ways we interact with the world have undergone a transformative shift. Virtual Reality (VR) technology, aided by artificial intelligence (AI), has emerged as a dominant interaction media in multiple application areas, thanks to its advantage of providing users with immersive experiences. Among those applications, medicine is considered one of the most promising areas. In this paper, we present a comprehensive examination of the burgeoning field of AI-enhanced VR applications in medical care and services. By introducing a systematic taxonomy, we meticulously classify the pertinent techniques and applications into three well-defined categories based on different phases of medical diagnosis and treatment: Visualization Enhancement, VR-related Medical Data Processing, and VR-assisted Intervention. This categorization enables a structured exploration of the diverse roles that AI-powered VR plays in the medical domain, providing a framework for a more comprehensive understanding and evaluation of these technologies. To our best knowledge, this is the first systematic survey of AI-powered VR systems in medical settings, laying a foundation for future research in this interdisciplinary domain.

Jonathan Du, Bryan Li, Shaohuan Zhang

In this paper, we investigate the internal (finite) sum of submonoids of rank-$1$ torsion-free abelian groups. These submonoids, when not groups, are isomorphic to nontrivial submonoids of the nonnegative cone of $\mathbb Q$, known as Puiseux monoids, and have been actively studied during the last few years. Here we study how the atomicity and arithmetic of Puiseux monoids behave under their internal (finite) sum inside the abelian group $\mathbb Q$. We study the factorization properties of such internal sums, giving priority to Cohn's notion of atomicity and the classical bounded and finite factorization properties introduced and studied in 1990 by Anderson, Anderson, and Zafrullah in the setting of integral domains, and then generalized by Halter-Koch to commutative monoids. We pay special attention to how each of the considered properties behaves under the internal sum of a Puiseux monoid with a finitely generated Puiseux monoid. Throughout the paper, we also discuss examples showing that our primary results do not hold for submonoids of torsion-free abelian groups with rank larger than $1$.

Tongyue Shi, Jun Ma, Zihan Yu et al.

With the rapid development of artificial intelligence (AI), large language models (LLMs) have shown strong capabilities in natural language understanding, reasoning, and generation, attracting amounts of research interest in applying LLMs to health and medicine. Critical care medicine (CCM) provides diagnosis and treatment for critically ill patients who often require intensive monitoring and interventions in intensive care units (ICUs). Can LLMs be applied to CCM? Are LLMs just like stochastic parrots or ICU experts in assisting clinical decision-making? This scoping review aims to provide a panoramic portrait of the application of LLMs in CCM. Literature in seven databases, including PubMed, Embase, Scopus, Web of Science, CINAHL, IEEE Xplore, and ACM Digital Library, were searched from January 1, 2019, to June 10, 2024. Peer-reviewed journal and conference articles that discussed the application of LLMs in critical care settings were included. From an initial 619 articles, 24 were selected for final review. This review grouped applications of LLMs in CCM into three categories: clinical decision support, medical documentation and reporting, and medical education and doctor-patient communication. LLMs have advantages in handling unstructured data and do not require manual feature engineering. Meanwhile, applying LLMs to CCM faces challenges, including hallucinations, poor interpretability, bias and alignment challenges, and privacy and ethics issues. Future research should enhance model reliability and interpretability, integrate up-to-date medical knowledge, and strengthen privacy and ethical guidelines. As LLMs evolve, they could become key tools in CCM to help improve patient outcomes and optimize healthcare delivery. This study is the first review of LLMs in CCM, aiding researchers, clinicians, and policymakers to understand the current status and future potentials of LLMs in CCM.

Ferenc Sztanek, László Imre Tóth, Attila Pető et al.

Guidelines for the management of obesity and type 2 diabetes (T2DM) emphasize the importance of lifestyle changes, including a reduced-calorie diet and increased physical activity. However, for many people, these changes can be difficult to maintain over the long term. Medication options are already available to treat obesity, which can help reduce appetite and/or reduce caloric intake. Incretin-based peptides exert their effect through G-protein-coupled receptors, the receptors for glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP), and glucagon peptide hormones are important regulators of insulin secretion and energy metabolism. Understanding the role of intercellular signaling pathways and inflammatory processes is essential for the development of effective pharmacological agents in obesity. GLP-1 receptor agonists have been successfully used, but it is assumed that their effectiveness may be limited by desensitization and downregulation of the target receptor. A growing number of new agents acting on incretin hormones are becoming available for everyday clinical practice, including oral GLP-1 receptor agonists, the dual GLP-1/GIP receptor agonist tirzepatide, and other dual and triple GLP-1/GIP/glucagon receptor agonists, which may show further significant therapeutic potential. This narrative review summarizes the therapeutic effects of different incretin hormones and presents future prospects in the treatment of T2DM and obesity.

Ryuya Hora

One of the most fundamental facts in topos theory is the internal parameterization of subtoposes: the bijective correspondence between subtoposes and Lawvere-Tierney topologies. In this paper, we introduce a new but elementary concept, "a local state classifier," and give an analogous internal parameterization of hyperconnected quotients (i.e., hyperconnected geometric morphisms from a topos). As a corollary, we obtain a solution to the Boolean case of the first problem of Lawvere's open problems.

Amirreza Hashemi, Yuemeng Feng, Arman Rahmim et al.

This work investigates use of equivariant neural networks as efficient and high-performance frameworks for image reconstruction and denoising in nuclear medicine. Our work aims to tackle limitations of conventional Convolutional Neural Networks (CNNs), which require significant training. We investigated equivariant networks, aiming to reduce CNN's dependency on specific training sets. Specifically, we implemented and evaluated equivariant spherical CNNs (SCNNs) for 2- and 3-dimensional medical imaging problems. Our results demonstrate superior quality and computational efficiency of SCNNs in both image reconstruction and denoising benchmark problems. Furthermore, we propose a novel approach to employ SCNNs as a complement to conventional image reconstruction tools, enhancing the outcomes while reducing reliance on the training set. Across all cases, we observed significant decrease in computational cost by leveraging the inherent inclusion of equivariant representatives while achieving the same or higher quality of image processing using SCNNs compared to CNNs. Additionally, we explore the potential of SCNNs for broader tomography applications, particularly those requiring rotationally variant representation.

Bojana Femić, Enrico Ghiorzi

We introduce categories $\M$ and $§$ internal in the tricategory $\Bicat_3$ of bicategories, pseudofunctors, pseudonatural transformations and modifications, for matrices and spans in a 1-strict tricategory $V$. Their horizontal tricategories are the tricategories of matrices and spans in $V$. Both the internal and the enriched constructions are tricategorifications of the corresponding constructions in 1-categories. Following \cite{FGK} we introduce monads and their vertical morphisms in categories internal in tricategories. We prove an equivalent condition for when the internal categories for matrices $\M$ and spans $§$ in a 1-strict tricategory $V$ are equivalent, and deduce that in that case their corresponding categories of (strict) monads and vertical monad morphisms are equivalent, too. We prove that the latter categories are isomorphic to those of categories enriched and discretely internal in $V$, respectively. As a byproduct of our tricategorical constructions we recover some results from \cite{Fem}. Truncating to 1-categories we recover results from \cite{CFP} and \cite{Ehr} on the equivalence of enriched and discretely internal 1-categories.

Ruifeng Sun, Xiaoling Li, Ziman Zhu et al.

BackgroundEvidence for the efficacy of cognitive-motor dual-task (CMDT) training in patients with post-stroke cognitive impairment (PSCI) and no dementia is still lacking. More importantly, although some studies on the cognitive effect of CMDT training show an improvement in cognitive performance, the results are still controversial, and the intervention mechanism of CMDT training on cognitive function improvement is not clear. The main purpose of this study was to analyze the effects of CMDT training on cognitive function, neuron electrophysiology, and frontal lobe hemodynamics in patients with PSCI.MethodsHere we tested the effects of CMDT training on cognitive function in PSCI patients. Forty subjects who met the criteria of PSCI were randomly assigned to control and experimental groups. CMDT training or cognitive task (CT) training was administered to each patient in the experimental and control groups, respectively. All subjects performed Mini-mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scale before and after the intervention, and the event-related potentials (ERP) and functional near-infrared spectroscopy (fNIRS) were used to evaluate the changes in neuron electrophysiology and hemodynamics.ResultsForty patients were randomized across Beijing Rehabilitation Hospital Capital Medical University in Beijing. At the end of the intervention, 33 subjects completed the experimental process. The CMDT group showed significant improvement in the MMSE (P = 0.01) and MoCA (P = 0.024) relative to the CT group. The results of ERP and fNIRS showed that CMDT training could shorten the latency of P300 (P = 0.001) and the peak time of oxygenated hemoglobin (P = 0.004). The results showed that CMDT training shortened the response time of central neurons and significantly increased the rate of oxygen supply to the frontal lobe.ConclusionCMDT training in patients with PSCI improved global cognitive function, which was supported by the improved neural efficiency of associated brain areas.Clinical trial registrationhttp://www.chictr.org.cn, identifier ChiCTR2000034862.

Michel Friedrich, Ezequiel Farrher, Svenja Caspers et al.

BackgroundIn glioma patients, multimodality therapy and recurrent tumor can lead to structural brain tissue damage characterized by pathologic findings in MR and PET imaging. However, little is known about the impact of different types of damage on the fiber architecture of the affected white matter.Patients and methodsThis study included 121 pretreated patients (median age, 52 years; ECOG performance score, 0 in 48%, 1-2 in 51%) with histomolecularly characterized glioma (WHO grade IV glioblastoma, n=81; WHO grade III anaplastic astrocytoma, n=28; WHO grade III anaplastic oligodendroglioma, n=12), who had a resection, radiotherapy, alkylating chemotherapy, or combinations thereof. After a median follow-up time of 14 months (range, 1-214 months), anatomic MR and O-(2-[18F]fluoroethyl)-L-tyrosine (FET) PET images were acquired on a 3T hybrid PET/MR scanner. Post-therapeutic findings comprised resection cavities, regions with contrast enhancement or increased FET uptake and T2/FLAIR hyperintensities. Local fiber density was determined from high angular-resolution diffusion-weighted imaging and advanced tractography methods. A cohort of 121 healthy subjects selected from the 1000BRAINS study matched for age, gender and education served as a control group.ResultsLesion types differed in both affected tissue volumes and relative fiber densities compared to control values (resection cavities: median volume 20.9 mL, fiber density 16% of controls; contrast-enhanced lesions: 7.9 mL, 43%; FET uptake areas: 30.3 mL, 49%; T2/FLAIR hyperintensities: 53.4 mL, 57%, p<0.001). In T2/FLAIR-hyperintense lesions caused by peritumoral edema due to recurrent glioma (n=27), relative fiber density was as low as in lesions associated with radiation-induced gliosis (n=13, 48% vs. 53%, p=0.17). In regions with pathologically increased FET uptake, local fiber density was inversely related (p=0.005) to the extent of uptake. Total fiber loss associated with contrast-enhanced lesions (p=0.006) and T2/FLAIR hyperintense lesions (p=0.013) had a significant impact on overall ECOG score.ConclusionsThese results suggest that apart from resection cavities, reduction in local fiber density is greatest in contrast-enhancing recurrent tumors, but total fiber loss induced by edema or gliosis has an equal detrimental effect on the patients’ performance status due to the larger volume affected.

Lin J, Xue Y, Su W et al.

Jie Lin,1,2,* Yanlong Xue,1,2,* Wenyan Su,1,2,* Zan Zhang,1,2 Qiu Wei,1,2 Tianxia Huang1,2 1Department of Respiratory and Critical Care, The Fifth Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, 530022, People’s Republic of China; 2Department of Respiratory and Critical Care, The First People’s Hospital of Nanning, Nanning, Guangxi, 530022, People’s Republic of China*These authors contributed equally to this workCorrespondence: Qiu Wei; Tianxia Huang, Department of Respiratory and Critical Care, The Fifth Affiliated Hospital of Guangxi Medical University, 89 Qixing Road, Nanning, Guangxi, 530022, People’s Republic of China, Tel +86 7712636163, Fax +86 7712617892, Email weiqiu2017@163.com; nntianxia620@sina.comPurpose: This study aimed to identify candidate gene markers that may facilitate chronic obstructive pulmonary disease (COPD) diagnosis and treatment.Methods: The GSE47460 and GSE151052 datasets were analyzed to identify differentially expressed mRNAs (DEmRs) between COPD patients and controls. DEmRs that were differentially expressed in the same direction in both datasets were analyzed for functional enrichment and for coexpression. Genes from the largest three modules were tested for their ability to diagnose COPD based on the area under the receiver operating characteristic curve (AUC). Genes with AUC > 0.7 in both datasets were used to perform regression based on the “least absolute shrinkage and selection operator” in order to identify feature genes. We also identified differentially expressed miRNAs (DEmiRs) between COPD patients and controls using the GSE38974 dataset, then constructed a regulatory network. We also examined associations between feature genes and immune cell infiltration in COPD, and we identified methylation markers of COPD using the GSE63704 dataset.Results: A total of 1350 genes differentially regulated in the same direction in the GSE47460 and GSE151052 datasets were found. The genes were significantly enriched in immune-related biological functions. Of 186 modules identified using MEGENA, the largest were C1_ 6, C1_ 3, and C1_ 2. Of the 22 candidate genes screened based on AUC, 11 feature genes emerged from analysis of a subset of GSE47460 data, which we validated using another subset of GSE47460 data as well as the independent GSE151052 dataset. Feature genes correlated significantly with infiltration by immune cells. The feature genes GPC4 and RS1 were predicted to be regulated by miR-374a-3p. We identified 117 candidate methylation markers of COPD, including PRRG4.Conclusion: The feature genes we identified may be potential diagnostic markers and therapeutic targets in COPD. These findings provide new leads for exploring disease mechanisms and targeted treatments.Keywords: chronic obstructive pulmonary disease, bioinformatics analysis, miRNAs, immune response, feature genes

Fei Wang, Fei Wang, Min Fei et al.

BackgroundConstipation and dementia have similar epidemiological characteristics. Changes in intestinal flora and characteristics of the brain-gut axis play roles in the pathogeneses of the two diseases, suggesting that there may be a close connection between the two. Most of the studies on constipation in dementia patients have focused on the population with α-synucleinopathies [Parkinson’s disease dementia (PDD), dementia with Lewy bodies (DLB)]. Few studies have reported the prevalence of constipation in all-cause dementia and mild cognitive impairment (MCI) populations.ObjectiveTo assess the prevalence of constipation in patients with all-cause dementia and MCI subtypes and to explore the association between constipation with dementia and MCI subtypes.MethodsFrom May 2019 to December 2019, we conducted a population-based cross-sectional survey. A total of 11,743 participants aged 65 or older from nine cities in China were surveyed. Participants underwent a series of clinical examinations and neuropsychological measurements. Constipation, dementia, MCI and MCI subtype were diagnosed according to established criteria through standard diagnostic procedures.ResultsThe overall age- and sex-adjusted prevalence of constipation in individuals aged 65 years and older was 14.8% (95% CI, 14.6–15.0). The prevalence rates of constipation were19.2% (95% CI, 17.3–21.0), 19.1% (95% CI, 16.8–21.5), 14.4% (95% CI, 12.8–15.9), and 13.8% (95% CI, 13.0–14.6) in the dementia, non-amnestic (na)-MCI, amnestic (a)-MCI and normal cognition populations, respectively. Multivariate logistic regression analysis showed that higher prevalence of constipation was associated with dementia (p = 0.0.032, OR = 1.18, 95% CI: 1.02–1.38) and na-MCI (p = 0.003, OR = 1.30, 95% CI: 1.09–1.54).ConclusionThe present study found a high prevalence of constipation in elderly individuals in China, and higher in patients with dementia and na-MCI.

Yan Tao, Yusuke Murakami, Demetrios G. Vavvas et al.

Necroptosis mediates the chronic inflammatory phenotype in neurodegeneration. Receptor-interacting protein kinase (RIPK) plays a pivotal role in the induction of necroptosis in various cell types, including microglia, and it is implicated in diverse neurodegenerative diseases in the central nervous system and the retina. Targeting RIPK has been proven beneficial for alleviating both neuroinflammation and degeneration in basic/preclinical studies. In this review, we discuss the role of necroptosis in retinal degeneration, including (1) the molecular pathways involving RIPK, (2) RIPK-dependent microglial activation and necroptosis, and (3) the interactions between necroptosis and retinal neuroinflammation/degeneration. This review will contribute to a renewed focus on neuroinflammation induced by necroptosis and to the development of anti-RIPK drugs against retinal degeneration.

Allysson Costa, Gleisson A. P. de Brito

Background. Several studies indicate that celiac disease patients present alterations within anthropometric, metabolic, and inflammatory parameters, while physical exercise and fish oil are known to activate modulatory pathways of such parameters. Objective. To investigate the effects of a 12-week-long protocol of aerobic exercise and its association with fish oil supplementation in nineteen adult celiac disease patients. Material and Methods. The celiacs were divided into 2 groups: (A) FOS: supplementation (n = 11); and (B) EXE: supplementation and exercise (n = 8). The celiac groups were compared to the adult healthy control group (CTR) (n 12). Aerobic exercises were performed weekly, in three sessions of 60 minutes each, with a maximal heart rate intensity of 60–70%. The participants received 2 g/day of fish oil, a daily intake of 420 mg of eicosapentaenoic acid, and 230 mg of docosahexaenoic acid. The following measurements were taken in four phases: (A) anthropometry: body mass, height, body mass index, waist-to-hip ratio, fat mass, and fat-free mass; (B) metabolic profile: total cholesterol, triglycerides, HDL, and LDL; and (C) inflammatory profile: C-reactive protein and interleukin-6. Results. Supplementation associated with aerobic exercise promoted a significant reduction in C-reactive protein (P<0.01) and increased the proportion of individuals in the undetectable range of interleukin-6. Conclusions. The associated interventions showed a corrective and preventive potential in relation to disorders associated with chronic inflammation; however, the experimental design does not allow us to discriminate between the biological effects that are dependent on the association between interventions and those exclusively dependent on aerobic exercise.

Xinmi Liu, Hua Lou, Junwei Zhang et al.

ObjectiveTo investigate the clinical outcomes of Day 7 (D7) frozen-thawed embryo transfer (FET) and to provide a reference value for clinical work.MethodsThis was a retrospective cohort study. Patients undergoing FET cycles in the Reproductive Medicine Center of the Third Affiliated Hospital of Zhengzhou University between December 2015 and January 2021 were included. According to the developmental stage of the embryos at transfer, the embryos were divided into three groups: Day (D) 5, D6 and D7 blastocysts. Group D7 was compared with Groups D5 and D6. Simultaneously, the preimplantation genetic testing (PGT) and non-PGT cycles in Group D7 were analyzed and compared. The main outcomes were the clinical pregnancy, live birth and miscarriage rates. The secondary outcomes were the implantation and euploidy rates.ResultsIn total, 5945, 4094 and 137 FET cycles were included in the D5, D6 and D7 groups, respectively. The clinical pregnancy rate was significantly lower in Group D7 than in Groups D5 (13.9% vs 62.9%, P &lt;0.001) and D6 (13.9% vs 51.4%, P &lt;0.001). Additionally, the live birth rate was significantly lower in Group D7 than in Groups D5 (7.3% vs 50.7%, P &lt;0.001) and D6 (7.3% vs 40.5%, P &lt;0.001). However, the miscarriage rate was significantly higher in Group D7 than in Groups D5 (47.4% vs 18.2%, P =0.001) and D6 (47.4% vs 20.6%, P =0.004). The clinical pregnancy and live birth rates for D7 blastocysts were significantly higher in the PGT group than in the non-PGT group (41.7% vs 13.9%, P=0.012; 33.3% vs 7.3%, P =0.003).ConclusionsD7 blastocyst transfer can yield a live birth rate that is lower than that for D5 and D6 blastocysts but has value for transfer. PGT for D7 blastocysts may reduce the number of ineffective transfers and improve the outcome of D7 blastocyst transfer, which can be performed according to a patient’s situation.