Multimodal Assessment of Peripheral Perfusion for the Early Diagnosis of Sepsis in Critically Ill Patients (MAP-SEPS): A Protocol for an Observational Study
Chalkias, A.; Thivaios, I.; Karapiperis, G.; Papagiannakis, N.; Koufaki, F.; Katsifa, K.; Prekates, A.; Tselioti, P.
Show abstract
IntroductionSepsis-induced organ failure is caused by a dysregulated host response characterized by mitochondrial and microcirculatory abnormalities. Early detection of perfusion deficits is critical to preventing progression to shock and organ failure. While capillary refill time (CRT) and other single-parameter assessments are used, a comprehensive, multimodal evaluation of peripheral perfusion has not yet been applied in clinical settings. The purpose of the MAP-SEPS trial is to ascertain whether such a multimodal approach can enhance early identification of sepsis and organ dysfunction in critically ill ICU patients. Methods and analysisMAP-SEPS is a prospective observational study enrolling a minimum of 50 adult ICU patients without sepsis on admission. Patients will be monitored over 72 hours using a multimodal protocol that includes clinical (CRT, skin temperature, mottling score, urine output), biochemical (lactate, ScvO{square}, Pv- aCO{square}, arterial/interstitial glucose), and near-infrared spectroscopy assessments. Standardized macrohemodynamic monitoring and echocardiography will be performed, along with advanced calculations of venous return dynamics, cardiac efficiency, and arterial/venous resistance. Data will be collected at predefined intervals and analyzed using mixed-effects linear regression models. The primary objective is to assess the predictive value of these hemodynamic and perfusion parameters for early detection of sepsis and organ failure. Secondary outcomes include ICU and hospital length of stay, mechanical ventilation duration, and mortality at 28 and 90 days. Ethics and disseminationThe study has been approved by the Ethics Committee of the General Hospital Tzaneio and complies with the Declaration of Helsinki. Peer-reviewed papers, conference presentations, and clinical seminars will all be used to disseminate the findings, contributing to better bedside evaluation techniques for septic patients.
Matching journals
The top 2 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- A Multicenter Evaluation of Blood Purification with Seraph 100 Microbind Affinity Blood Filter for the Treatment of Severe COVID-19: A Preliminary Report 94%
- Utility of skin tone on pulse oximetry in critically ill patients: a prospective cohort study 94%
- Changes in non-linear and time-domain heart rate variability indices between critically ill COVID-19 and all-cause sepsis patients -a retrospective study 94%
Similar papers in this journal
- Performance of digital Early Warning Score (NEWS2) in a cardiac specialist setting: retrospective cohort study 94%
- The COVID-19 Critical Care Consortium observational study: Design and rationale of a prospective, international, multicenter, observational study 93%
- The Diagnostic Accuracy of Subjective Dyspnea in Detecting Hypoxemia Among Outpatients with COVID-19 92%
Similar papers in this journal
- Hemodynamic profiles by non-invasive monitoring of cardiac index and vascular tone in acute heart failure patients in the emergency department: external validation and clinical outcomes 95%
- Altered kinetics of circulating progenitor cells in cardiopulmonary bypass (CPB) associated vasoplegic patients: A pilot study 95%
- Identifying predictors and determining mortality rates of septic cardiomyopathy and sepsis-related cardiogenic shock: A retrospective, observational study 94%
Similar papers in this journal
- Imputation of PaO2 from SpO2 values from the MIMIC-III Critical Care Database Using Machine-Learning Based Algorithms 94%
- Hemodynamics with Mechanical Circulatory Support Devices Using a Cardiogenic Shock Model 94%
- AKI Risk Score (AKI-RiSc): Developing an Interpretable Clinical Score for Early Identification of Acute Kidney Injury for Patients Presenting to the Emergency Department 94%
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.