Time Of Discovery Research Articles

Conceptosphere of the basic concept “winter” in Yu. Shestalov’s lyrical poetry

The article presents a description of the conceptual sphere with the basic concept of “winter”, based on the lyrical poetry of the famous Mansi poet Yuvan Shestalov. The article develops philological regionalism as a current trend in literary criticism. Based on a conceptual analysis of two volumes of the poet’s poems from his complete works, the article suggests this conceptual sphere, proving the objective choice of the nearest periphery concepts by providing examples from the texts. The immediate periphery includes such concepts and their variants as “snow” (ice, blizzard, snowstorm, snow squall); “sleep”; “night” (stars, moon); “road” (skis, sleds, deer, movement, path); “fire” (bonfire, flame, hearth heat, hot tea, ray of sunshine, northern lights). The key conclusion is that winter for the lyrical hero is a time of discovery, a time of learning new things, moving forward, a time of love and creativity. This perception of winter and Ugra as a whole is at odds with the generally accepted perception of the northern region. We believe the presented analysis will help visualize the mental space of the peoples from the North and the “winter” concept functions in the poet’s lyrical poetry to better understand his individual works, at the same time evaluating his work as an integral, mobile and developing system.

Analysis of cases of cervical cystic lymph node metastasis with an unknown primary misdiagnosed as branchial cleft carcinoma

Objectives: To analyze the location, discovery time and possible causes of cases of cervical cystic lymph node metastasis with an unknown primary misdiagnosed as branchial cleft carcinoma. Methods: A retrospective analysis was performed on clinical and pathological data of 15 patients misdiagnosed as branchiogenic carcinoma at Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College between January 2000 and December 2020. Results: Among the 15 patients, 6 were nasopharyngeal squamous cell carcinoma, 4 tonsil squamous cell carcinoma, 2 tongue root squamous cell carcinoma, 2 hypopharyngeal squamous cell carcinoma and 1 thyroid papillary carcinoma. The median time from the diagnosis of branchial cleft carcinoma to the discovery of primary lesions was 3.58 months (0-76 months). The causes of misdiagnosis might be the lack of experience in the diagnosis and treatment of branchial cleft carcinoma, and not enough attention to comprehensive examination and close follow-up. Conclusions: Different from oropharyngeal cancer reported internationally, the proportion of misdiagnosed cases with nasopharyngeal carcinoma as the primary site in the current article is higher. As a country with a high incidence of nasopharyngeal carcinoma, the examination of nasopharynx should not be taken lightly. Most hidden cases can be found in the comprehensive examination in a short time, while a few cases need long-term follow-up. Finding the primary sites should not rely too much on imaging examination, and we cannot ignore the importance of clinical physical examination.

Adrenal tumors in patients with neuroendocrine neoplasms

PurposeTo study the prevalence of primary adrenal tumors and adrenal metastases in patients with neuroendocrine neoplasms (NENs) and describe these in detail. NENs can be further divided into neuroendocrine tumor (NET) and neuroendocrine carcinoma (NEC).MethodsA review of medical files was conducted for all patients who underwent a 68Gallium-DOTATOC-PET/CT during 2010−2023 or adrenalectomy during 1999-2023 at the Karolinska University Hospital.ResultsIn total, 68Gallium-DOTATOC-PET/CT was performed on 1750 individuals with NEN, among whom 12 (0.69%) had adrenal tumors. Of these, 9 (0.51%) were NEN metastases. Out of 1072 adrenalectomies, 4 (0.37%) showed evidence of NEN metastases. Thus, 16 patients with NEN exhibited adrenal tumors. The adrenal tumors were found on average 5 years after the NEN diagnosis and 19% of the adrenal tumors with simultaneous NEN were benign. Few had all adrenal hormones measured. None had an adrenal insufficiency nor an adrenal biopsy. Another synchronous metastasis was found in 69% at the time of the adrenal tumor discovery. During the median 2-year follow-up, 38% of the subjects had deceased (with the exclusion of individuals presenting supposedly benign adrenal tumors 31%) all due to tumor complications. A comparison between individuals identified through 68Gallium-DOTATOC-PET/CT and those who underwent adrenalectomy revealed a higher prevalence of NETs in the former group and NECs in the latter group.ConclusionAdrenal primary tumors and adrenal metastases are infrequent occurrences in patients with NEN. Most cases involved the presence of NEN metastasis upon the initial discovery of adrenal tumors. The overall prognosis was found to be favorable.

Gossypiboma: A Surgeon’s Nightmare: A Systematic Review and Case Report

Objective: To assess the trends in Gossypiboma over 1975-2023 and the impact on the career of a surgeon. Background: Gossypibomas are the most feared and undesired complication of surgery. Despite numerous guidelines, they still exist in our modern society. Here, we examine worldwide data along with a case report. Patient: A 46-year-old diabetic anaemic female with a 6-month earlier history of operative management for cancer of the cervix (stage IA2) presented with features suggesting acute intestinal obstruction. She was managed by emergency laparotomy and removal of the retained foreign body. Methods: A literature search was performed on PubMed for gossypiboma and was limited to case reports from 1975-2023. Analysis using Excel and Python. Results: In a study of 289 total gossypiboma cases, analysis revealed that Asia had the highest incidence (53.53%, n=269), and the most common symptom was pain (36.5%, n=287). Additionally, age and time of discovery exhibited an upward trend, with thoracic cases taking the longest to discover. Conclusion: Surgeon accountability for unintentional mistakes, akin to random errors, sparks debate. Gossypibomas emphasize the need to follow rigorous safety standards and team work endorsed by WHO.

Medical findings and congenital anomalies in Vermeer's paintings.

The 17th century was a time of scientific discovery in Europe. Leading academic centers provided the general population with an opportunity to view anatomic dissections of human bodies. Rather than portray idealized versions of individuals, Dutch painters were committed to accurately representing their models. This was true for Johannes Vermeer. The 2023 exhibition of Vermeer's paintings at the Rijksmuseum in Amsterdam provided an unprecedented opportunity to observe 28 of his 37 existing paintings simultaneously in person. Here the authors suggest that in at least eight paintings a visibly pregnant woman is present. Vermeer's wife was pregnant or lactating most of the time during their 22-year marriage. Further, evidence of specific medical findings and congenital anomalies such as polydactyly, ectrodactyly, alopecia, kyphosis, and hyperthyroidism were observed in the paintings. These have not been previously reported in the medical or art history literature.

Science’s greatest discoverers: a shift towards greater interdisciplinarity, top universities and older age

What are the unique features and characteristics of the scientists who have made the greatest discoveries in science? To address this question, we assess all major scientific discoverers, defined as all nobel-prize and major non-nobel-prize discoverers, and their demographic, institutional and economic traits. What emerges is a general profile of the scientists who have driven over 750 of science’s greatest advances. We find that interdisciplinary scientists who completed two or more degrees in different academic fields by the time of discovery made about half—54%—of all nobel-prize discoveries and 42% of major non-nobel-prize discoveries over the same period; this enables greater interdisciplinary methodological training for making new scientific achievements. Science is also becoming increasingly elitist, with scientists at the top 25 ranked universities accounting for 30% of both all nobel-prize and non-nobel-prize discoveries. Scientists over the age of 50 made only 7% of all nobel-prize discoveries and 15% of non-nobel-prize discoveries and those over the age of 60 made only 1% and 3%, respectively. The gap in years between making nobel-prize discoveries and receiving the award is also increasing over time across scientific fields—illustrating that it is taking longer to recognise and select major breakthroughs. Overall, we find that those who make major discoveries are increasingly interdisciplinary, older and at top universities. We also assess here the role and distribution of factors like geographic location, gender, religious affiliation and country conditions of these leading scientists, and how these factors vary across time and scientific fields. The findings suggest that more discoveries could be made if science agencies and research institutions provide greater incentives for researchers to work against the common trend of narrow specialisation and instead foster interdisciplinary research that combines novel methods across fields.

A Review on Repurposing of Drug

Background: For discovering novel drugs and to gain market acceptance process of conventional drug discovery is used in which various stages are involved. Aim: To innovate new approaches for minimizing the cost and time of drug discovery. Method: Several attempts were made for the building of plans based on computational tools and on bio-informatics to strengthen the repurposing method off-late. Various approaches used to invent novel signs for FDA accepted drugs are discussed in this review. Results: The repurposing of the drugs has obtained significance in identifying novel therapeutic uses for existing drugs. It is a productive strategy for the discovery of drugs also time and cost-effective.It fills the gap for the absence of efficiency of conventional drug development. Implications: In drug repurposing, selection and decision of suitable repurposing technique depend on previous knowledge and accessible data from particular studies. The best advantage of the drug repurposing technique is that for approved drugs all the required data is available. Conclusion: This technique is currently appearing to overcome the restriction faced during conventional drug discovery in the form of resources, timeline, and financial support . The feasibility of repurposing technique is improved by its systematic application. Some examples of repurposed drugs are also reviewed here. This review also covers the skill of repurposing survival drugs for use against microbes. Keywords: Conventional drug, drug repurposing, repurposing approaches, docking, proteinopathy.

A comprehensive review of molecular optimization in artificial intelligence‐based drug discovery

AbstractDrug discovery is aimed to design novel molecules with specific chemical properties for the treatment of targeting diseases. Generally, molecular optimization is one important step in drug discovery, which optimizes the physical and chemical properties of a molecule. Currently, artificial intelligence techniques have shown excellent success in drug discovery, which has emerged as a new strategy to address the challenges of drug design including molecular optimization, and drastically reduce the costs and time for drug discovery. We review the latest advances of molecular optimization in artificial intelligence‐based drug discovery, including data resources, molecular properties, optimization methodologies, and assessment criteria for molecular optimization. Specifically, we classify the optimization methodologies into molecular mapping‐based, molecular distribution matching‐based, and guided search‐based methods, respectively, and discuss the principles of these methods as well as their pros and cons. Moreover, we highlight the current challenges in molecular optimization and offer a variety of perspectives, including interpretability, multidimensional optimization, and model generalization, on potential new lines of research to pursue in future. This study provides a comprehensive review of molecular optimization in artificial intelligence‐based drug discovery, which points out the challenges as well as the new prospects. This review will guide researchers who are interested in artificial intelligence molecular optimization.

Abstract TP58: Stroke Recognition Task Force: Increasing Early Activation of Inpatient Stroke Codes

Background: 1 in 5 strokes occur in the hospital. Patients with in-hospital stroke have increased vascular risk factors, delayed time to recognition, and increased mortality compared to patients with community-onset stroke. All staff should be able to recognize and initiate management of patients with a suspected acute stroke. Purpose The goals of this project were to increase early activation of inpatient stroke codes and confidence levels related to the recognition of stroke and management of patients during a code. Methods: An education program, providing unit specific information, was provided to each inpatient unit at an academic medical center. A survey was created for learners to take before and after the education session; including questions regarding symptom recognition, how to activate a stroke code, and tasks required following activation. Additional questions included self-assessment of the learner’s confidence level in different aspects of stroke care, including stroke recognition and management. To assess time to activation, data related to inpatient stroke code activations was analyzed pre- and post-intervention. Data included symptom discovery and stroke team activation time gathered from the electronic medical record. Results: Data from 119 codes was reviewed. Prior to intervention, only 50% of inpatient stroke codes were activated within 10 minutes of symptom discovery. Following intervention, 75% of inpatient stroke codes were activated within 10 minutes of symptom discovery. There were 61 pre-session survey responses and 39 post-session. Before the session, 56.1% of participants were slightly or moderately confident in identifying stroke, but after the session, 80.5% of participants were very or extremely confident in identifying stroke. Before the session, 81.8% of participants did not feel comfortable managing a patient during a code, but after the session, 95% of participants felt comfortable. Conclusion: An education session for hospital staff can increase knowledge and confidence level in the recognition of stroke and their management of patients. This curriculum has potential to be used nationally to reduce delays to diagnosis, increase usage of acute therapies and reduce mortality associated with in-hospital stroke.

Abstract WP45: A Collaborative Approach to Improving Inpatient Stroke Code Time Target Metrics

Much effort and education has been placed on pre-hospital and emergency departments to recognize signs and symptoms of acute stroke and time metrics such as door-to-CT, door-to-needle, and door-to-device. For admitted patients with acute onset of stroke symptoms, our data analysis identified a gap in the timeliness of stroke code activation upon symptoms discovery and subsequent delays in CT initiation and treatment. We evaluated our current process and implemented action plans to enhance the current inpatient stroke code process through focused education and training of staff to improve their recognition of acute stroke, timely activation of stroke code and improved CT initiation and treatment times. In 2021, several cardiology pilot units were selected and neuroscience nurse specialists conducted staff education which focused on recognition of stroke signs and symptoms, code activation criteria and response time targets. A resource binder and checklist were created to guide staff in putting together pertinent elements for communication and documentation. Data was collected on stroke code response times and individual feedback was provided. The group meets quarterly to evaluate progress, discuss opportunities for improvement and highlight best practices and outcomes. The checklist was a useful tool in reminding staff of pertinent information to communicate to the stroke team although form completion is not consistent. In 2021-2022, 54% of stroke codes were called within 10 minutes of symptoms discovery. CTH initiation time within 25 minutes of symptoms discovery was achieved in 16.2% of patients. Data analysis showed an opportunity to improve documentation of symptoms discovery time which were missing in 13.8% of cases. This collaborative approach with the pilot units has increased awareness and focus to the inpatient stroke code process. Opportunities exist to improve time target achievements in CTH initiation, treatment, and documentation of symptoms discovery time. Communication between the stroke team and the patient’s primary team has been identified as an essential factor for continued improvement along with on-going staff education.

Abstract NS9: Nurse-Led Quality Improvement Initiative: Advancing Stroke Awareness in Communities Experiencing Racial and Ethnic Disparities

Background and Purpose: As a Joint Commission Comprehensive Stroke Center, the provision of community education is a priority goal of our program. The majority of our existing community education program takes place in locations where we receive requests to provide these sessions. Analysis of our Get With the Guidelines (GWTG) data reveals gaps in early arrival to the hospital and Emergency Medical Service (EMS) utilization among African American and Hispanic populations. Providing educational resources within these populations may help to close these gaps and foster trust in the healthcare system. The aim of this proposed nurse-led quality improvement project is to improve hospital arrival times of African American and Hispanic stroke patients living in zip codes where GWTG data have identified gaps, through provision of targeted community education. Methods: The top zip codes associated with our target outcomes for improvement will be identified using GWTG pre-data from 2022 and 2023. We will partner with our Community Outreach department. We will identify educational venues and stakeholders among African American and Hispanic populations in these zip codes. We will provide education tailored to our identified populations including early recognition of stroke signs and symptoms, activation of EMS, stroke risk factors, and opportunities for treatment. Post implementation, GWTG data will be reviewed for any changes. Results: Using GWTG data, arrival mode, last known well time, and symptom discovery time to Emergency Department arrival as it pertains to zip codes, race and ethnicity will be reviewed and analyzed. The target zip codes’ data will be compared pre- versus post-implementation of community education efforts. Discussion: Through community education and partnership with the Community Outreach department we hope to improve timeliness of arrival to hospital among disproportionately affected racial minorities in our community for early stroke evaluation and treatment consideration.

Resource discoveries and the political survival of dictators

We study the effect of resource discoveries on dictator failure. We extend existing conflict literature by developing a dynamic stochastic model where timing of attack and probability of success are endogenous. Incumbent and opposition invest in military arsenals which determine success probability, while opposition also chooses when to stage a coup. A resource discovery delays the attack and reduces the probability of overthrow. We test these hypotheses using duration models and timing of giant oil and gas discoveries, finding that large discoveries more than double remaining time until failure and reduce hazard faced by an autocrat by 30%–50%.

Government responses to oilfield discoveries: Impact of resource wealth on non-resource tax revenues

It has often been argued that countries that produce natural resources mobilize less non-resource tax revenues than other countries. In this paper, we exploit the exogenous variation in the timing of giant oilfield discoveries to estimate the causal impact of natural resources on taxation. The timing of giant oilfield discoveries is arguably exogenous and thus renders them appealing to empirically examine this argument. This allows us to examine the performance of non-resource tax revenue effort before and immediately after discovery as well as the period corresponding to the inflow of revenues from the production. We find that non-resource tax revenues tend to increase in the period following the discovery before the onset of production and after production commences. This effect is due to an increase in non-resource indirect tax revenues. Further analysis shows that both the total and indirect non-resource tax revenues, experience an increase in only low- -middle income countries, and largely driven by an increase in the consumption of goods and services.

Integrative approach for predicting drug-target interactions via matrix factorization and broad learning systems.

In the drug discovery process, time and costs are the most typical problems resulting from the experimental screening of drug-target interactions (DTIs). To address these limitations, many computational methods have been developed to achieve more accurate predictions. However, identifying DTIs mostly rely on separate learning tasks with drug and target features that neglect interaction representation between drugs and target. In addition, the lack of these relationships may lead to a greatly impaired performance on the prediction of DTIs. Aiming at capturing comprehensive drug-target representations and simplifying the network structure, we propose an integrative approach with a convolution broad learning system for the DTI prediction (ConvBLS-DTI) to reduce the impact of the data sparsity and incompleteness. First, given the lack of known interactions for the drug and target, the weighted K-nearest known neighbors (WKNKN) method was used as a preprocessing strategy for unknown drug-target pairs. Second, a neighborhood regularized logistic matrix factorization (NRLMF) was applied to extract features of updated drug-target interaction information, which focused more on the known interaction pair parties. Then, a broad learning network incorporating a convolutional neural network was established to predict DTIs, which can make classification more effective using a different perspective. Finally, based on the four benchmark datasets in three scenarios, the ConvBLS-DTI's overall performance out-performed some mainstream methods. The test results demonstrate that our model achieves improved prediction effect on the area under the receiver operating characteristic curve and the precision-recall curve.

간호사 근무시간대별 입원아동의 투약오류 관련 요인

This is a secondary data analysis study to determine the effect of nurses’ shift time on medication errors in hospitalised children. The Korean Patient Safety Reporting & Learning System (KOPS) reported from July 2016 to December 2020 was used, and the collected data were subjected to multinomial logistic regression analysis using R 4.2.0 version program. The results showed that the risk of medication errors according to nurses' shift time increased when the gender was male compared to female (OR=1.97, p=.042), the medical institution class was general hospital compared to senior general hospital(OR=2.92, p=.002). On the first shift, adverse events and red flag events increased when the time of discovery was less than 1 hour after the incident compared to immediately(OR=4.71, p=.003), and increased significantly when the time of discovery was more than 1 hour(OR=5.79, p=.001). Therefore, it is suggested that improved communication between healthcare workers, supplementation of nursing staff, and preparation of medication-related policies are necessary to prevent medication errors in hospitalised children.

Re-examining the Key Issues Concerning the Craftworks Uncovered from Tonggung Palace and Wŏlchi Pond in Kyŏngju

The excavation of Wŏlchi pond in Kyŏngju has yielded numerous craftworks that offer crucial information about Silla’s crafts. However, due to damage or missing parts, it is difficult to fully understand the nature of some items. Additionally, there are some findings whose appearance and conditions at the time of discovery remain unidentifiable. Therefore, over 50 years since the initial excavation in 1975, it is necessary to re-examine the current key issues and discuss the future directions of studies concerning the discoveries from Tonggung Palace and Wŏlchi pond. Firstly, I examined specific shapes and production techniques that are only observed in the findings from Wŏlchi pond. Further, I investigated the usage, and manufacture and decorative techniques of crystals and various objects made of bone and horn produced in Kyŏngju. I proposed the correct function of the <i>Lacquered Flower-shaped Ornament</i> as a portable shrine and additionally presented the <i>Gilt-Bronze Wick Trimmer</i>, suitably made for its role, as evidence of the new culture involving candles. When further research is conducted into the uses, production techniques, and decorative designs of the items found in incomplete form, such as <i>Bamboo-shaped Ornament, Bone Fragment with Flower and Bird Design</i>, and <i>Lacquered Plate with Flower and Foliage Design</i>, we may be able to understand more aspects of the craft culture of Unified Silla. Furthermore, the recovered items from Wŏlchi pond exhibiting various designs, such as birds holding flowers in their beaks (<i>hamjomun</i>), flower medallions (<i>bosanghwamun</i>), and rows of beads (<i>yeonjumun</i>), provide evidence that Unified Silla shared a common decorative trend with Tang China and Nara Japan. Tonggung palace and Wŏlchi pond are valuable resources for the history of decorative patterns in Korea.

FOTF-CPI: A compound-protein interaction prediction transformer based on the fusion of optimal transport fragments

Compound-protein interaction (CPI) affinity prediction plays an important role in reducing the cost and time of drug discovery. However, the interpretability of how fragments function in CPI is impacted by the fact that current methods ignore the affinity relationships between fragments of compounds and fragments of proteins in CPI modeling. This article introduces an improved Transformer called FOTF-CPI (aFusion of Optimal Transport Fragments compound-protein interaction prediction model). We use an optimal transport-based fragmentation approach to improve the model's understanding of compound and protein sequences. Additionally, a fused attention mechanism is employed, which combines the features of fragments to capture full affinity information. This fused attention redistributes higher attention scores to fragments with higher affinity. Experimental results show FOTF-CPI achieves an average 2% higher performance than other models on all three datasets. Furthermore, the visualization confirms the potential of FOTF-CPI for drug discovery applications.

Prediction of pharmacokinetics of an anaplastic lymphoma kinase inhibitor in rat and monkey: application of physiologically based pharmacokinetic model as an alternative tool to minimise animal studies

The pharmacokinetic (PK) and toxicokinetic profile of a drug from its preclinical evaluation helps the researcher determine whether the drug should be tested in humans based on its safety and toxicity. Preclinical studies require time and resources and are prone to error. Moreover, according to the United States Food and Drug Administration Modernisation Act 2, animal testing is no longer mandatory for new drug development, and an animal-free alternative, such as cell-based assay and computer models, can be used. Different physiologically based PK models were developed for an anaplastic lymphoma kinase inhibitor in rats and monkeys after intravenous and oral administration using its physicochemical properties and in vitro characterisation data. The developed model was validated against the in vivo data available in the literature, and the validation results were found within the acceptable limit. A parameter sensitivity analysis was performed to identify the properties of the compound influencing the PK profile. This work demonstrates the application of the physiologically based PK model to predict the PKs of a drug, which will eventually assist in reducing the number of animal studies and save time and cost of drug discovery and development.

Vascularized liver-on-a-chip model to investigate nicotine-induced dysfunction.

The development of physiologically relevant in vitro systems for simulating disease onset and progression and predicting drug metabolism holds tremendous value in reducing drug discovery time and cost. However, many of these platforms lack accuracy in replicating the tissue architecture and multicellular interactions. By leveraging three-dimensional cell culture, biomimetic soft hydrogels, and engineered stimuli, in vitro models have continued to progress. Nonetheless, the incorporation of the microvasculature has been met with many challenges, specifically with the addition of parenchymal cell types. Here, a systematic approach to investigating the initial seeding density of endothelial cells and its effects on interconnected networks was taken and combined with hepatic spheroids to form a liver-on-a-chip model. Leveraging this system, nicotine's effects on microvasculature and hepatic function were investigated. The findings indicated that nicotine led to interrupted adherens junctions, decreased guanosine triphosphate cyclohydrolase 1 expression, impaired angiogenesis, and lowered barrier function, all key factors in endothelial dysfunction. With the combination of the optimized microvascular networks, a vascularized liver-on-a-chip was formed, providing functional xenobiotic metabolism and synthesis of both albumin and urea. This system provides insight into potential hepatotoxicity caused by various drugs and allows for assessing vascular dysfunction in a high throughput manner.

Risk factors for immediate and delayed cardiogenic shock in patients with ventricular septal rupture after myocardial infarction

BackgroundVentricular septal rupture (VSR) is a serious complication occurring after myocardial infarction (MI). Cardiogenic shock (CS) is a common complication of VSR and an important factor affecting its prognosis. CS can occur in either an immediate or delayed manner after VSR; however, studies on the risk factors associated with immediate or delayed CS are scarce.MethodsWe retrospectively studied patients diagnosed with VSR after MI and admitted to the West China Hospital between September 2009 and August 2023. Demographic data, medical history, physical examination results, electrocardiograms, and echocardiographic and hematological data were extracted from electronic medical records or archived records. CS was defined as hypotension (<90 mmHg) and/or the requirement for catecholamines, pulmonary congestion, and signs of end-organ failure. The CS onset time was defined as the time at which catecholamines were initiated.ResultsA total of 88 patients with VSR after MI, including 49 males (55.7%), were enrolled. The average age was 70.2 years. Of these patients, 32 (36.4%) who already had CS at the time of VSR discovery were defined as immediate CS, and 28 (31.8%) who developed CS within 2 weeks after VSR discovery were defined as delayed CS. A smaller left ventricular end-diastolic diameter (LVEDD) and VSR discovered after admission were independent risk factors for immediate CS. Elevated heart rate and higher levels of creatine kinase-MB isoenzyme on admission were independent risk factors for delayed CS in patients without immediate CS after VSR.ConclusionsThe occurrence of CS in patients with VSR after MI has an evident time course. Thus, an early identification of patients at risk of immediate or delayed CS and optimization of treatment procedures may help improve the prognosis.