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| Name | Class |
|---|---|
| Capital Medical University | OTHER |
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After neurosurgery, many patients need to stay in the intensive care unit (ICU) and use a breathing machine (mechanical ventilation) because of issues like decreased consciousness, weak breathing, or poor airway protection. During this period, the natural balance of bacteria in the lungs-known as the lung microbiota-can be disturbed by surgery, antibiotics, and airway procedures. This may reduce healthy bacteria and allow harmful bacteria to grow, increasing the risk of lung infections such as ventilator-associated pneumonia (VAP).
This study will follow 220 postoperative neurosurgical ICU patients at three centers: Beijing Tiantan Hospital, Beijing Shijitan Hospital, and Beijing Anzhen Hospital from August 2025 to August 2026. These patients will include those undergoing surgery for brain tumors, brain hemorrhage, or traumatic brain injury. Airway secretion samples (tracheal aspirates) will be collected shortly after surgery and at several subsequent time points to assess how lung bacteria change over time while patients are using a breathing machine.
Using advanced laboratory methods, the investigators will measure both the amount and types of bacteria in the lungs. The aim is to determine how these changes are related to patient outcomes, such as the occurrence of lung infections.
The results of this study may contribute to earlier detection of lung infections and the development of personalized treatment plans to improve recovery in ICU patients after neurosurgery.
Postoperative neurosurgical patients represent a unique and high-risk population in the ICU, often requiring prolonged invasive mechanical ventilation due to impaired consciousness and respiratory function. During this critical period, multiple factors-including surgical trauma, antibiotic administration, and airway manipulation-can disrupt the pulmonary microbiota, potentially leading to dysbiosis characterized by reduced microbial diversity and overgrowth of opportunistic pathogens.
Emerging evidence suggests that alterations in the lung microbiota may play a key role in the development of respiratory infections, such as ventilator-associated pneumonia (VAP), and could influence the overall clinical trajectory of ICU patients. However, current knowledge regarding the temporal dynamics of the lung microbiome in neurosurgical patients is limited, and its potential as a predictive biomarker for infection risk or recovery remains unexplored.
This prospective observational cohort study is designed to systematically characterize the succession patterns of the pulmonary microbiota in adult neurosurgical patients requiring mechanical ventilation. By integrating microbial profiling with clinical data, the study aims to elucidate the relationship between microbiota changes and patient outcomes, including infection incidence, length of ICU stay, and duration of ventilation.
High-resolution microbial analysis using 16S rRNA gene sequencing and quantitative techniques (e.g., droplet digital PCR) will allow for precise tracking of microbial shifts over time. These findings may provide new perspectives on host-microbiota interactions under ICU conditions and support the development of early warning indicators for infection, as well as inform personalized antimicrobial and ventilation strategies in postoperative care.
Ultimately, the study seeks to improve understanding of lung microbiome evolution in response to surgical and critical care interventions and to identify clinically relevant microbial patterns that may serve as novel prognostic tools in neurosurgical ICU populations.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Postoperative Neurosurgical ICU Patients | This cohort includes adult patients admitted to the ICU for the first time following neurosurgical procedures (including brain tumor surgery, subarachnoid hemorrhage surgery, and traumatic brain injury surgery) and expected to receive invasive mechanical ventilation for more than 24 hours. Patients will undergo serial collection of tracheal aspirate samples to assess the dynamic changes in the pulmonary microbiota. No therapeutic intervention is applied; this is a prospective observational cohort study. |
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| Measure | Description | Time Frame |
|---|---|---|
| Incidence of Hospital-Acquired Pneumonia (HAP) Within 28 Days of ICU Admission | Hospital-acquired pneumonia (HAP) will be diagnosed according to the 2016 IDSA/ATS guidelines. The number of HAP cases occurring within 28 days of ICU admission will be recorded. This outcome will be used to evaluate whether alterations in the pulmonary microbiota are associated with the risk of nosocomial pneumonia and may inform empiric antibiotic strategies in the ICU setting. | Within 28 days of ICU admission |
| Measure | Description | Time Frame |
|---|---|---|
| Association Between Pulmonary Microbiota Alterations and Risk of Hospital-Acquired Pneumonia | Changes in pulmonary microbiota composition and diversity, assessed using 16S rRNA gene sequencing and quantitative analysis, will be evaluated for their association with the occurrence of hospital-acquired pneumonia (HAP) during the ICU stay. Statistical models will be applied to determine correlations between microbiota alterations and HAP risk. |
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Inclusion Criteria:
Patients must meet all of the following conditions to be eligible for inclusion:
Exclusion Criteria:
Patients meeting any of the following criteria will be excluded:
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This study will include 220 adult (≥18 years) postoperative neurosurgical patients admitted for the first time to the ICUs of three centers: Beijing Tiantan Hospital, Beijing Shijitan Hospital, and Beijing Anzhen Hospital between August 2025 and August 2026. Eligible patients will have undergone brain tumor surgery, subarachnoid hemorrhage surgery, or traumatic brain injury surgery and be expected to require artificial airway support for more than 24 hours. Inclusion and exclusion criteria will be applied to ensure a consistent, well-defined high-risk ICU population for evaluating clinical outcomes and associated factors.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Jian-Xin Zhou, Professor | Contact | 8610 6392 6666 | zhoujx.cn@icloud.com | |
| Yi-Ran Li, MD | Contact | 8613621234800 | liuyirandou@163.com |
| Name | Affiliation | Role |
|---|---|---|
| Jian-Xin Zhou, MD, PhD | Capital Medical University | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Beijing Shijitan Hospital | Recruiting | Beijing | Beijing Municipality | 100038 | China |
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| ID | Term |
|---|---|
| D053717 | Pneumonia, Ventilator-Associated |
| ID | Term |
|---|---|
| D000077299 | Healthcare-Associated Pneumonia |
| D003428 | Cross Infection |
| D007239 | Infections |
| D011014 | Pneumonia |
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| Within 28 days of ICU admission |
| Incidence of Ventilator-Associated Pneumonia (VAP) Within 28 Days of ICU Admission | Ventilator-associated pneumonia (VAP) will be diagnosed according to the 2016 IDSA/ATS guidelines as pneumonia occurring 48 hours or more after endotracheal intubation or tracheostomy. The number and proportion of VAP cases occurring within 28 days of ICU admission will be calculated. | Within 28 days of ICU admission |
| Association Between Pulmonary Microbiota Alterations and Risk of Ventilator-Associated Pneumonia | Changes in pulmonary microbiota composition and diversity, assessed using 16S rRNA gene sequencing and quantitative analysis, will be evaluated for their association with the occurrence of ventilator-associated pneumonia (VAP) during the ICU stay. Statistical models will be applied to determine correlations between microbiota alterations and VAP risk. | Within 28 days of ICU admission |
| Beijing Tiantan Hospital, Capital Medical University | Recruiting | Beijing | Beijing Municipality | 100050 | China |
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| Beijing Anzhen Hospital, Capital Medical University | Recruiting | Beijing | Beijing Municipality | 101100 | China |
|
| D012141 |
| Respiratory Tract Infections |
| D008171 | Lung Diseases |
| D012140 | Respiratory Tract Diseases |
| D007049 | Iatrogenic Disease |
| D020969 | Disease Attributes |
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |