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      Predictive model of risk factors for 28-day mortality in patients with sepsis or sepsis-associated delirium based on the MIMIC-IV database

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          Abstract

          Research on the severity and prognosis of sepsis with or without progressive delirium is relatively insufficient. We constructed a prediction model of the risk factors for 28-day mortality in patients who developed sepsis or sepsis-associated delirium. The modeling group of patients diagnosed with Sepsis-3 and patients with progressive delirium of related indicators were selected from the MIMIC-IV database. Relevant independent risk factors were determined and integrated into the prediction model. Receiver operating characteristic (ROC) curves and the Hosmer–Lemeshow (HL) test were used to evaluate the prediction accuracy and goodness-of-fit of the model. Relevant indicators of patients with sepsis or progressive delirium admitted to the intensive care unit (ICU) of a 3A hospital in Xinjiang were collected and included in the verification group for comparative analysis and clinical validation of the prediction model. The total length of stay in the ICU, hemoglobin levels, albumin levels, activated partial thrombin time, and total bilirubin level were the five independent risk factors in constructing a prediction model. The area under the ROC curve of the predictive model (0.904) and the HL test result (χ 2 = 8.518) indicate a good fit. This model is valuable for clinical diagnosis and treatment and auxiliary clinical decision-making.

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          Most cited references30

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          The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3).

          Definitions of sepsis and septic shock were last revised in 2001. Considerable advances have since been made into the pathobiology (changes in organ function, morphology, cell biology, biochemistry, immunology, and circulation), management, and epidemiology of sepsis, suggesting the need for reexamination.
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            MIMIC-III, a freely accessible critical care database

            MIMIC-III (‘Medical Information Mart for Intensive Care’) is a large, single-center database comprising information relating to patients admitted to critical care units at a large tertiary care hospital. Data includes vital signs, medications, laboratory measurements, observations and notes charted by care providers, fluid balance, procedure codes, diagnostic codes, imaging reports, hospital length of stay, survival data, and more. The database supports applications including academic and industrial research, quality improvement initiatives, and higher education coursework.
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              Delirium as a predictor of mortality in mechanically ventilated patients in the intensive care unit.

              In the intensive care unit (ICU), delirium is a common yet underdiagnosed form of organ dysfunction, and its contribution to patient outcomes is unclear. To determine if delirium is an independent predictor of clinical outcomes, including 6-month mortality and length of stay among ICU patients receiving mechanical ventilation. Prospective cohort study enrolling 275 consecutive mechanically ventilated patients admitted to adult medical and coronary ICUs of a US university-based medical center between February 2000 and May 2001. Patients were followed up for development of delirium over 2158 ICU days using the Confusion Assessment Method for the ICU and the Richmond Agitation-Sedation Scale. Primary outcomes included 6-month mortality, overall hospital length of stay, and length of stay in the post-ICU period. Secondary outcomes were ventilator-free days and cognitive impairment at hospital discharge. Of 275 patients, 51 (18.5%) had persistent coma and died in the hospital. Among the remaining 224 patients, 183 (81.7%) developed delirium at some point during the ICU stay. Baseline demographics including age, comorbidity scores, dementia scores, activities of daily living, severity of illness, and admission diagnoses were similar between those with and without delirium (P>.05 for all). Patients who developed delirium had higher 6-month mortality rates (34% vs 15%, P =.03) and spent 10 days longer in the hospital than those who never developed delirium (P<.001). After adjusting for covariates (including age, severity of illness, comorbid conditions, coma, and use of sedatives or analgesic medications), delirium was independently associated with higher 6-month mortality (adjusted hazard ratio [HR], 3.2; 95% confidence interval [CI], 1.4-7.7; P =.008), and longer hospital stay (adjusted HR, 2.0; 95% CI, 1.4-3.0; P<.001). Delirium in the ICU was also independently associated with a longer post-ICU stay (adjusted HR, 1.6; 95% CI, 1.2-2.3; P =.009), fewer median days alive and without mechanical ventilation (19 [interquartile range, 4-23] vs 24 [19-26]; adjusted P =.03), and a higher incidence of cognitive impairment at hospital discharge (adjusted HR, 9.1; 95% CI, 2.3-35.3; P =.002). Delirium was an independent predictor of higher 6-month mortality and longer hospital stay even after adjusting for relevant covariates including coma, sedatives, and analgesics in patients receiving mechanical ventilation.
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                Author and article information

                Contributors
                yu2796@163.com
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                13 August 2024
                13 August 2024
                2024
                : 14
                : 18751
                Affiliations
                [1 ]Xinjiang Medical University, ( https://ror.org/01p455v08) Urumqi, 830000 China
                [2 ]School of Nursing, Xinjiang Medical University, ( https://ror.org/01p455v08) Urumqi, 830000 China
                [3 ]Department of Nursing, the First Affiliated Hospital of Xinjiang Medical University, ( https://ror.org/02qx1ae98) Urumqi, 830054 China
                [4 ]Centre for Critical Care Medicine, The First Affiliated Hospital of Xinjiang Medical University, ( https://ror.org/02qx1ae98) Urumqi, 830054 Xinjiang China
                [5 ]Department of Traumatology and Orthopaedics, the First Affiliated Hospital of Xinjiang Medical University, ( https://ror.org/02qx1ae98) Urumqi, 830054 China
                Article
                69332
                10.1038/s41598-024-69332-4
                11322336
                39138233
                31c29dbe-75bb-4bde-85a5-9371a6319430
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

                History
                : 28 October 2023
                : 2 August 2024
                Funding
                Funded by: This work was supported by the Wu Jieping Medical Foundation Clinical Research Fund [grant number 320.6750.2023-02-3]
                Categories
                Article
                Custom metadata
                © Springer Nature Limited 2024

                Uncategorized
                sepsis with delirium,risk factors,prediction model,mimic- iv database,diseases,neurology
                Uncategorized
                sepsis with delirium, risk factors, prediction model, mimic- iv database, diseases, neurology

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