Publications by authors named "Jian Jun Zou"

Background: Despite endovascular coiling as a valid modality in treatment of aneurysmal subarachnoid hemorrhage (aSAH), there is a risk of poor prognosis. However, the clinical utility of previously proposed early prediction tools remains limited. We aimed to develop a clinically generalizable machine learning (ML) models for accurately predicting unfavorable outcomes in aSAH patients after endovascular coiling.

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Objective: Aneurysmal subarachnoid hemorrhage (aSAH) is an aggressive disease with higher mortality rate in the elderly population. Unfortunately, the previous models for predicting clinical prognosis are still not accurate enough. Therefore, we aimed to construct and validate a visualized nomogram model to predict online the 3-month mortality in elderly aSAH patients undergoing endovascular coiling.

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Article Synopsis
  • Aneurysmal subarachnoid hemorrhage (aSAH) can lead to serious health consequences, especially in elderly patients, and this study aimed to create a dynamic nomogram to predict their 6-month outcomes after treatment.
  • The researchers analyzed data from 209 elderly aSAH patients to identify factors influencing unfavorable outcomes, using statistical methods to develop and validate the nomogram.
  • The resulting tool, which accurately predicts risks based on factors like age and health status, can help clinicians tailor interventions to improve patient care.
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  • The study aimed to create a visual nomogram model to help identify patients with basilar artery occlusion (BAO) who are at high risk of having futile recanalization after endovascular thrombectomy (EVT).
  • Researchers analyzed data from 84 BAO patients treated with EVT, finding that 50% experienced futile recanalization.
  • The resulting nomogram model demonstrated strong predictive capability, with a high accuracy score (AUC of 0.866) and is available online for clinicians to use in patient assessment.
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Estimating whether to treat the rupture risk of small intracranial aneurysms (IAs) with size ≤ 7 mm in diameter is difficult but crucial. We aimed to construct and externally validate a convenient machine learning (ML) model for assessing the rupture risk of small IAs. One thousand four patients with small IAs recruited from two hospitals were included in our retrospective research.

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The decision-making of how to treat urinary infection stones was complicated by the difficulty in preoperative diagnosis of these stones. Hence, we developed machine learning (ML) models that can be leveraged to discriminate between infection and noninfection stones in urolithiasis patients before treatment. We enrolled 462 patients with urinary stones and randomly stratified them into training (80%) and testing sets (20%).

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Background: Immune checkpoint inhibitors had a great effect in triple-negative breast cancer (TNBC); however, they benefited only a subset of patients, underscoring the need to co-target alternative pathways and select optimal patients. Herein, we investigated patient subpopulations more likely to benefit from immunotherapy and inform more effective combination regimens for TNBC patients.

Methods: We conducted exploratory analyses in the FUSCC cohort to characterize a novel patient selection method and actionable targets for TNBC immunotherapy.

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Purpose: Camrelizumab, an mAb against programmed cell death protein 1 (PD-1), plus nab-paclitaxel exhibited promising antitumor activity in refractory metastatic immunomodulatory triple-negative breast cancer (TNBC). Famitinib is a tyrosine kinase inhibitor targeting VEGFR2, PDGFR, and c-kit. We aimed to assess the efficacy and safety of a novel combination of famitinib, camrelizumab, and nab-paclitaxel in advanced immunomodulatory TNBC.

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Background And Purpose: About 20.1% of intracranial aneurysms (IAs) carriers are multiple intracranial aneurysms (MIAs) patients with higher rupture risk and worse prognosis. A prediction model may bring some potential benefits.

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Background: It is not a rare clinical scenario to have patients presenting with coexisting malignant tumor and tuberculosis. Whether it is feasible to conduct programmed death-(ligand) 1 [PD-(L)1] inhibitors to these patients, especially those with active tuberculosis treated with concurrent anti-tuberculosis, is still unknown.

Methods: This study enrolled patients with coexisting malignancy and tuberculosis and treated with anti-PD-(L)1 from Jan 2018 to July 2021 in 2 institutions.

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Article Synopsis
  • Intracranial aneurysms (IAs) are a significant health issue, and while endovascular treatment (EVT) is a common management strategy, there's a notable risk of recurrence leading to serious complications.
  • The study aimed to create and evaluate machine learning (ML) models to predict the recurrence risk of IAs within 6 months after EVT, utilizing data from patients treated at Hunan Provincial People's Hospital from 2016 to 2019.
  • Among five developed ML models, the gradient boosting decision tree (GBDT) model outperformed the others, achieving an area under the curve (AUC) of 0.842, indicating it can effectively predict the risk of recurrence in this patient population.
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Purpose: Henagliflozin is a highly selective and effective sodium glucose co-transporter (SGLT)-2 inhibitor developed for the treatment of patients with type 2 diabetes mellitus (T2DM). This study aimed to investigate the effects of meal intake on the pharmacokinetic properties of henagliflozin, and to understand the excretion pathways of henagliflozin in humans.

Methods: In this Phase I, randomized, open-label, single-dose, two-period crossover study, 12 healthy male Chinese volunteers were randomized to receive either henagliflozin 10 mg in the fasted condition followed by henagliflozin 10 mg in the fed condition, or the reverse schedule, with the two administrations separated by a washout period of at least 7 days.

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Clopidogrel (CLOP) is commonly used in coronary artery disease (CAD) patients with or without diabetes (DM), but these patients often suffer CLOP resistance, especially those with diabetes. This study was aimed to develop a physiologically-based pharmacokinetic-pharmacodynamic (PBPK-PD) model to describe the pharmacokinetics and pharmacodynamics of clopidogrel active metabolite (CLOP-AM) in CAD patients with or without DM. The PBPK-PD model was first established and validated in healthy subjects and then in CAD patients with or without DM.

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Background: Henagliflozin, a novel selective inhibitor of sodium-glucose cotransporter 2, is under development as a treatment for type 2 diabetes mellitus.

Purpose: To evaluate the tolerability, pharmacokinetic (PK), and pharmacodynamic (PD) profiles of henagliflozin in healthy Chinese volunteers.

Methods: Two clinical studies were conducted.

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Article Synopsis
  • * Researchers evaluated five different machine learning models and found similar predictive performance among them, significantly outperforming existing clinical prediction tools like the HIAT, THRIVE score, and NADE nomogram.
  • * Out of 1,735 AIS patients studied, 31.2% experienced unfavorable outcomes, and incorporating specific patient data helped improve prediction accuracy, particularly with the Random Forest Classifier (RFC) model.
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The optimal duration of dual antiplatelet therapy (DAPT) as a routine treatment in stroke patients is still controversial. The efficacy and safety of DAPT may vary with different regiments, initiating treatment time and race. Our study assessed the efficacy and safety of DAPT in patients with stroke and to determine the factors influencing the efficacy and safety of DAPT.

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Background: This retrospective study evaluated the safety and efficacy of concurrent anti-tuberculosis (TB) and chemotherapy treatment in patients with advanced lung cancer and active TB.

Methods: We retrospectively analyzed patients who were first diagnosed with advanced lung cancer and received first-line chemotherapy in Guangzhou Chest Hospital from 2015 to 2017. Patients were categorized into two groups (2:1): lung cancer patients without active TB (Group A), and lung cancer patients with active TB (Group B).

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Aims: Voriconazole is a broad-spectrum antifungal agent for the treatment of invasive fungal infections. There is limited information about the pharmacokinetics and appropriate dosage of voriconazole in patients with liver dysfunction. This study aimed to explore the relationship between voriconazole trough concentration (C ) and toxicity, identify the factors significantly associated with voriconazole pharmacokinetic parameters and propose an optimised voriconazole dosing regimen for patients with liver dysfunction.

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Introduction: Little is known about the relationship between smoking and clinical outcomes in acute ischemic stroke (AIS) patients undergoing mechanical thrombectomy (MT). The outcomes could depend on different stroke subtypes. The aim of this study was to investigate whether smoking affected differently the outcomes in patients with different stroke subtypes who received MT.

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Background And Purpose: Mechanical thrombectomy (MT) is a standard care for most acute ischemic stroke (AIS) patients. For AIS patients underwent MT, predicting the patients at high risk of unfavorable outcome and adjusting therapeutic strategies accordingly can greatly improve patient outcomes. We aimed to develop and validate a nomogram for individualized prediction of Chinese AIS patients underwent MT.

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Purpose: Studies on genetic alterations of the heterogenous small cell lung cancer (SCLC) are rare. We carried out the present study to clarify the genomic alterations and TMB levels of Chinese SCLC patients by whole-exome sequencing.

Materials And Methods: Whole-exome sequencing by next-generation sequencing technique was implemented on twenty SCLC samples.

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Article Synopsis
  • Endovascular treatment (ET) is effective for acute ischemic stroke, but early reocclusion is a common issue, raising questions about the role of early antiplatelet therapy in these cases.
  • A meta-analysis of seven studies (1251 patients) found that early antiplatelet therapy did not significantly increase risks of intracranial hemorrhage, symptomatic intracranial hemorrhage, or mortality.
  • The study suggests that while early antiplatelet therapy appears safe for acute ischemic stroke patients, further research is necessary to determine its true efficacy.
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Background: Recently, the NIHSS STroke Scale score, Age, pre-stroke mRS score, onset-to-treatment Time (START nomogram) predicts 3-month functional outcome after intravenous thrombolysis in ischemic stroke patients. However, this model has not yet been an external validation. We aim to validate the performance of START nomogram.

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Background: Accurate prognostication of unfavorable outcome made at the early onset of stroke is important to both the clinician and the patient management. This study was aimed to develop a nomogram based on the integration of parameters to predict the probability of 3-month unfavorable functional outcome in Chinese acute ischemic stroke patients.

Methods: We retrospectively collected patients who underwent acute ischemic stroke at Stroke Center of the Nanjing First Hospital (China) between May 2013 and May 2018.

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