Incidence, Risk Factors and Outcomes of Sepsis in Critically Ill Post-craniotomy Patients: A Single-Center Prospective Cohort Study

Zhou, Jialing; Luo, Xu‐Ying; Chen, Guang-Qiang; Li, Hongliang; Xu, Min; Liu, Shuai; Yang, Yanlin; Shi, Guangzhi; Jian-xin, Zhou; Zhang, Linlin

doi:10.3389/fpubh.2022.895991

Cited by 3 publications

(3 citation statements)

References 60 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Lower GCS scores are also associated with the incidence of VAP in TBI patients [32,38], which may be related to the fact that patients with moderate and severe TBI require open surgery, and respiratory support, and are susceptible to urinary tract infection. A single-center prospective cohort study including 900 patients found that lower GCS scores and higher APACHE (Acute Physiology and Chronic Health Evaluation) II scores are independent risk factors for secondary sepsis in TBI patients after operation [39].…”

Section: Discussionmentioning

confidence: 99%

A predictive model for the risk of sepsis within 30 days of admission in patients with traumatic brain injury in the intensive care unit: a retrospective analysis based on MIMIC-IV database

Hu,

Zhu,

Zhang

et al. 2023

Eur J Med Res

View full text Add to dashboard Cite

Purpose Traumatic brain injury (TBI) patients admitted to the intensive care unit (ICU) are at a high risk of infection and sepsis. However, there are few studies on predicting secondary sepsis in TBI patients in the ICU. This study aimed to build a prediction model for the risk of secondary sepsis in TBI patients in the ICU, and provide effective information for clinical diagnosis and treatment. Methods Using the MIMIC IV database version 2.0 (Medical Information Mart for Intensive Care IV), we searched data on TBI patients admitted to ICU and considered them as a study cohort. The extracted data included patient demographic information, laboratory indicators, complications, and other clinical data. The study cohort was divided into a training cohort and a validation cohort. In the training cohort, variables were screened by LASSO (Least absolute shrinkage and selection operator) regression and stepwise Logistic regression to assess the predictive ability of each feature on the incidence of patients. The screened variables were included in the final Logistic regression model. Finally, the decision curve, calibration curve, and receiver operating character (ROC) were used to test the performance of the model. Results Finally, a total of 1167 patients were included in the study, and these patients were randomly divided into the training (N = 817) and validation (N = 350) cohorts at a ratio of 7:3. In the training cohort, seven features were identified as key predictors of secondary sepsis in TBI patients in the ICU, including acute kidney injury (AKI), anemia, invasive ventilation, GCS (Glasgow Coma Scale) score, lactic acid, and blood calcium level, which were included in the final model. The areas under the ROC curve in the training cohort and the validation cohort were 0.756 and 0.711, respectively. The calibration curve and ROC curve show that the model has favorable predictive accuracy, while the decision curve shows that the model has favorable clinical benefits with good and robust predictive efficiency. Conclusion We have developed a nomogram model for predicting secondary sepsis in TBI patients admitted to the ICU, which can provide useful predictive information for clinical decision-making.

show abstract

Section: Discussionmentioning

confidence: 99%

A predictive model for the risk of sepsis within 30 days of admission in patients with traumatic brain injury in the intensive care unit: a retrospective analysis based on MIMIC-IV database

Hu,

Zhu,

Zhang

et al. 2023

Eur J Med Res

View full text Add to dashboard Cite

show abstract

“…34 In a higher risk neurosurgical cohort of postcraniotomy patients (all admitted to the ICU), cumulative incidence of sepsis was 33.3% (95% CI: 30.2–36.4), and the mortality rate in those with sepsis was 13.7 versus 8.3% for those without sepsis. 53…”

Section: Sepsis In Specific Patient Populationsmentioning

confidence: 99%

“…34 In a higher risk neurosurgical cohort of postcraniotomy patients (all admitted to the ICU), cumulative incidence of sepsis was 33.3% (95% CI: 30.2-36.4), and the mortality rate in those with sepsis was 13.7 versus 8.3% for those without sepsis. 53 A single-center study of patients admitted to a cardiac intensive care unit after cardiac surgery utilized physician review and Sepsis-3 definitions; the authors reported a much higher incidence of sepsis (9.5%), of whom half had proven infections (4.8%) and half had suspected infection alone (4.7%). The adjusted odds ratio for 30-day mortality for patients with sepsis versus without was 6.6 (95% CI: 2.6-1.7) for confirmed infection and 3.7 (95% CI: 1.1-10.2) for suspected infection.…”

Section: Sepsis In Surgical and Postprocedural Patientsmentioning

confidence: 99%

Update on Sepsis Epidemiology in the Era of COVID-19

Shappell

Rhee

2023

Semin Respir Crit Care Med

View full text Add to dashboard Cite

Timely and accurate data on the epidemiology of sepsis is essential to inform public policy, clinical practice, and research priorities. Recent studies have illuminated several ongoing questions about sepsis epidemiology, including the incidence and outcomes of sepsis in non-Western countries and in specialized populations such as surgical patients, patients with cancer, and the elderly. There have also been new insights into the limitations of current surveillance methods using administrative data and increasing experience tracking sepsis incidence and outcomes using “big data” approaches that take advantage of detailed electronic health record data. The COVID-19 pandemic, however, has fundamentally changed the landscape of sepsis epidemiology. It has increased sepsis rates, helped highlight ongoing controversies about how to define sepsis, and intensified debate about the possible unintended consequences of overly rigid sepsis care bundles. Despite these controversies, there is a growing consensus that severe COVID-19 causing organ dysfunction is appropriate to label as sepsis, even though it is treated very differently from bacterial sepsis, and that surveillance strategies need to be modified to reliably identify these cases to fully capture and delineate the current burden of sepsis. This review will summarize recent insights into the epidemiology of sepsis and highlight several urgent questions and priorities catalyzed by COVID-19.

show abstract

Impact of Metabolic Syndrome on Post-Operative Infection in Patients Undergoing Flexible Ureteroscopy Lithotripsy

Hao,

Du,

et al. 2024

Surgical Infections

View full text Add to dashboard Cite

Incidence, Risk Factors and Outcomes of Sepsis in Critically Ill Post-craniotomy Patients: A Single-Center Prospective Cohort Study

Cited by 3 publications

References 60 publications

A predictive model for the risk of sepsis within 30 days of admission in patients with traumatic brain injury in the intensive care unit: a retrospective analysis based on MIMIC-IV database

A predictive model for the risk of sepsis within 30 days of admission in patients with traumatic brain injury in the intensive care unit: a retrospective analysis based on MIMIC-IV database

Update on Sepsis Epidemiology in the Era of COVID-19

Impact of Metabolic Syndrome on Post-Operative Infection in Patients Undergoing Flexible Ureteroscopy Lithotripsy

Contact Info

Product

Resources

About