scholarly journals Assessing the Predictive Value of TRIPS in Newborns

2021 ◽  
Vol 18 (4) ◽  
pp. 73-79
Author(s):  
R. F. Mukhametshin ◽  
N. S. Davydova ◽  
S. V. Kinzhalova
Keyword(s):  
Cohort Study ◽  
Intensive Care ◽  
Correlation Analysis ◽  
Hospital Mortality ◽  
Predictive Value ◽  
Quantitative Data ◽  
Hospital Treatment ◽  
Binary Outcomes ◽  
Risk Of Death ◽  
Occlusive Hydrocephalus

The objective: to determine the predictive value of TRIPS at the stage of pre-transport preparation in relation to treatment outcomes of newborns.Subjects: The cohort study included data from 604 visits of the team of the intensive case and consultation center. The TRIPS score was assessed, and the outcomes of the hospital phase of treatment were studied. The AUC ROC curve of the TRIPS score was calculated in relation to the binary outcomes of hospital treatment. The correlation analysis of the quantitative data was performed by Spearman's criterion.Results. AUC was greater than 0.8 only for the risk of death (AUC 0.827 (0.764-0.891)), the formation of severe IVH (AUC 0.831 (0.786-0.877)) and the development of occlusive hydrocephalus (AUC 0.839 (0.764-0.915)). For other binary outcomes, the score shows AUC below 0.8. A weak but significant correlation was found between the TRIPS score and the duration of intensive care (r = 0.478,p < 0.0001).Conclusion: TRIPS demonstrated an acceptable level of accuracy (AUC>0.8) in predicting hospital mortality, severe IVH, and the formation of occlusive hydrocephalus. A weak but significant correlation was found with the quantitative outcomes.

scholarly journals Assessment of the predictive value of the NTISS scale for neonatal outcomes

2021 ◽  
Vol 20 (5) ◽  
pp. 11-20
Author(s):  
O. P. Kovtun ◽  
R. F. Mukhametshin ◽  
N. S. Davidova
Keyword(s):  
Intensive Care ◽  
Bronchopulmonary Dysplasia ◽  
Predictive Value ◽  
Intraventricular Hemorrhage ◽  
Neonatal Intensive Care ◽  
Late Onset ◽  
Scoring Systems ◽  
Binary Outcomes ◽  
Risk Of Death ◽  
Duration Of Hospitalization

Introduction. Improving the disease severity scoring systems at the stages of inter-hospital transportation remains an actual in neonatal intensive care. Therapeutic scales remain poorly studied and their predictive value and practical applicability. The aim of the work is to determine the predictive value of the NTISS scale at the stage of pre-transport preparation in relation to the treatment outcomes of newborns.Materials and methods. The cohort study included data from 604 visits of the resuscitation and consultation center transport team. The evaluation was performed on the NTISS scale, and the outcomes were studied. The AUC ROC curve of the NTISS scale was calculated in relation to the binary outcomes. The correlation analysis of the quantitative data was performed by Spearman's criterion.Results. AUC greater than 0.8 was observed for the risk of death (AUC=0,823 (0,758-0,888)), 7-day mortality (AUC=0,827 (0,752-0,901)), late onset sepsis (AUC=0,808 (0,737-0,879)), bronchopulmonary dysplasia (AUC=0,810 (0,763-0,856)), severe intraventricular hemorrhage (AUC=0,847 (0,804-0,889)) иocclusivehydrocephalus(AUC=0,830 (0,757-0,904)). Similarresultswereobtained analyzing the outcomes among the surviving patients. For other binary outcomes, the scale shows an AUC of less than 0.8. The analysis of outcomes among the surviving patients showed a weak correlation between the NTISS score and the duration of intensive care, r=0.492, p<0.0001, and the duration of hospitalization, r=0.498, p<0.0001.Discussion. The NTISS scale demonstrated an acceptable level of accuracy (AUC>0.8) in predicting hospital mortality, late neonatal sepsis, bronchopulmonary dysplasia, severe intraventricular hemorrhage, and the formation of occlusive hydrocephalus, among both surviving patients and general sample. The observed results are comparable with the information content of other neonatal scales of various types.Conclusion. The predictive value of NTISS in relation to the outcomes of the hospital stage is comparable to the physiological scales described in the literature.

scholarly journals Disparities in Intensive Care Unit Admission and Mortality Among Patients With Schizophrenia and COVID-19: A National Cohort Study

2020 ◽  
Author(s):  
Guillaume Fond ◽  
Vanessa Pauly ◽  
Marc Leone ◽  
Pierre-Michel Llorca ◽  
Veronica Orleans ◽  
...  
Keyword(s):  
Health Care ◽  
Intensive Care Unit ◽  
Mental Illness ◽  
Cohort Study ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Severe Mental Illness ◽  
Vulnerable Population ◽  
Icu Admission ◽  
Risk Of Death

Abstract Patients with schizophrenia (SCZ) represent a vulnerable population who have been understudied in COVID-19 research. We aimed to establish whether health outcomes and care differed between patients with SCZ and patients without a diagnosis of severe mental illness. We conducted a population-based cohort study of all patients with identified COVID-19 and respiratory symptoms who were hospitalized in France between February and June 2020. Cases were patients who had a diagnosis of SCZ. Controls were patients who did not have a diagnosis of severe mental illness. The outcomes were in-hospital mortality and intensive care unit (ICU) admission. A total of 50 750 patients were included, of whom 823 were SCZ patients (1.6%). The SCZ patients had an increased in-hospital mortality (25.6% vs 21.7%; adjusted OR 1.30 [95% CI, 1.08–1.56], P = .0093) and a decreased ICU admission rate (23.7% vs 28.4%; adjusted OR, 0.75 [95% CI, 0.62–0.91], P = .0062) compared with controls. Significant interactions between SCZ and age for mortality and ICU admission were observed (P = .0006 and P &lt; .0001). SCZ patients between 65 and 80 years had a significantly higher risk of death than controls of the same age (+7.89%). SCZ patients younger than 55 years had more ICU admissions (+13.93%) and SCZ patients between 65 and 80 years and older than 80 years had less ICU admissions than controls of the same age (−15.44% and −5.93%, respectively). Our findings report the existence of disparities in health and health care between SCZ patients and patients without a diagnosis of severe mental illness. These disparities differed according to the age and clinical profile of SCZ patients, suggesting the importance of personalized COVID-19 clinical management and health care strategies before, during, and after hospitalization for reducing health disparities in this vulnerable population.

scholarly journals Prognostic value of Modified Early Warning Score generated in a Chinese emergency department: a prospective cohort study

BMJ Open ◽  
2018 ◽  
Vol 8 (12) ◽  
pp. e024120 ◽  
Author(s):  
Xiaohua Xie ◽  
Wenlong Huang ◽  
Qiongling Liu ◽  
Wei Tan ◽  
Lu Pan ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Emergency Department ◽  
Cohort Study ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Early Warning ◽  
Predictive Value ◽  
Mortality Prediction ◽  
Early Warning Score ◽  
Secondary Outcome

ObjectivesThis study aimed to validate the performance of the Modified Early Warning Score (MEWS) in a Chinese emergency department and to determine the best cut-off value for in-hospital mortality prediction.DesignA prospective, single-centred observational cohort study.SettingThis study was conducted at a tertiary hospital in South China.ParticipantsA total of 383 patients aged 18 years or older who presented to the emergency department from 17 May 2017 through 27 September 2017, triaged as category 1, 2 or 3, were enrolled.OutcomesThe primary outcome was a composite of in-hospital mortality and admission to the intensive care unit. The secondary outcome was using MEWS to predict hospitalised and discharged patients.ResultsA total of 383 patients were included in this study. In-hospital mortality was 13.6% (52/383), and transfer to the intensive care unit was 21.7% (83/383). The area under the receiver operating characteristic curve of MEWS for in-hospital mortality prediction was 0.83 (95% CI 0.786 to 0.881). When predicting in-hospital mortality with the cut-off point defined as 3.5, 158 patients had MEWS >3.5, with a specificity of 66%, a sensitivity of 87%, an accuracy of 69%, a positive predictive value of 28% and a negative predictive value of 97%, respectively.ConclusionOur findings support the use of MEWS for in-hospital mortality prediction in patients who were triaged category 1, 2 or 3 in a Chinese emergency department. The cut-off value for in-hospital mortality prediction defined in this study was different from that seen in many other studies.

scholarly journals Use of albumin as a risk factor for hospital mortality among burn patients in Brazil: non-concurrent cohort study

2010 ◽  
Vol 128 (5) ◽  
pp. 289-295 ◽  
Author(s):  
Gilson Caleman ◽  
José Fausto de Morais ◽  
Maria Eduarda dos Santos Puga ◽  
Rachel Riera ◽  
Álvaro Nagib Atallah
Keyword(s):  
Cohort Study ◽  
Hospital Mortality ◽  
Primary Outcome ◽  
Statistical Significance ◽  
Burn Patients ◽  
Burnt Area ◽  
Historical Cohort ◽  
Risk Of Death ◽  
Crystalloid Solutions ◽  
De Medicina

CONTEXT AND OBJECTIVE: Among burn patients, it is common to use colloidal substances under the justification that it is necessary to correct the oncotic pressure of the plasma, thereby reducing the edema in the burnt area and the hypotension. The aim here was to assess the risk of hospital mortality, comparing the use of albumin and crystalloid solutions for these patients. DESIGN AND SETTING: Non-concurrent historical cohort study at Faculdade de Medicina de Marília; within the Postgraduate program on Internal and Therapeutic Medicine, Universidade Federal de São Paulo; and at the Brazilian Cochrane Center. METHODS: Burn patients hospitalized between 2000 and 2001, with registration in the Hospital Information System, who received albumin, were compared with those who received other types of volume replacement. The primary outcome was the hospital mortality rate. The data were collected from files within the Datasus software. RESULTS: 39,684 patients were included: 24,116 patients with moderate burns and 15,566 patients with major burns. Among the men treated with albumin, the odds ratio for the risk of death was 20.58 (95% confidence interval, CI: 11.28-37.54) for moderate burns and 6.24 (CI 5.22-7.45) for major burns. Among the women, this risk was 40.97 for moderate burns (CI 21.71-77.30) and 7.35 for major burns (CI 5.99-9.01). The strength of the association between the use of albumin and the risk of death was maintained for the other characteristics studied, with statistical significance. CONCLUSION: The use of albumin among patients with moderate and major burns was associated with considerably increased mortality.

scholarly journals Association Between Oxygen Partial Pressure Trajectories and Short-Term Outcomes in Patients With Hemorrhagic Brain Injury

2021 ◽  
Vol 8 ◽  
Author(s):  
Guolong Cai ◽  
Weizhe Ru ◽  
Qianghong Xu ◽  
Jiong Wu ◽  
Shijin Gong ◽  
...  
Keyword(s):  
Intensive Care ◽  
Brain Injury ◽  
Hospital Mortality ◽  
Oxygen Partial Pressure ◽  
Partial Pressure ◽  
Medical Information ◽  
Logistic Models ◽  
Neurological Outcomes ◽  
Risk Of Death ◽  
Logistic Analysis

Objectives: Arterial hyperoxia is reportedly a risk factor for poor outcomes in patients with hemorrhagic brain injury (HBI). However, most previous studies have only evaluated the effects of hyperoxia using static oxygen partial pressure (PaO2) values. This study aimed to investigate the association between overall dynamic oxygenation status and HBI outcomes, using longitudinal PaO2 data.Methods: Data were extracted from the Medical Information Mart for Intensive Care III database. Longitudinal PaO2 data obtained within 72 h of admission to an intensive care unit were analyzed, using a group-based trajectory approach. In-hospital mortality was used as the primary outcomes. Multivariable logistic models were used to explore the association between PaO2 trajectory and outcomes.Results: Data of 2,028 patients with HBI were analyzed. Three PaO2 trajectory types were identified: Traj-1 (mild hyperoxia), Traj-2 (transient severe hyperoxia), and Traj-3 (persistent severe hyperoxia). The initial and maximum PaO2 of patients with Traj-2 and Traj-3 were similar and significantly higher than those of patients with Traj-1. However, PaO2 in patients with Traj-2 decreased more rapidly than in patients with Traj-3. The crude in-hospital mortality was the lowest for patients with Traj-1 and highest for patients with Traj-3 (365/1,303, 209/640, and 43/85 for Traj-1, Traj-2, and Traj-3, respectively; p &lt; 0.001), and the mean Glasgow Coma Scale score at discharge (GCSdis) was highest for patients with Traj-1 and lowest in patients with Traj-3 (13 [7–15], 11 [6–15], and 7 [3–14] for Traj-1, Traj-2, and Traj-3, respectively; p &lt; 0.001). The multivariable model revealed that the risk of death was higher in patients with Traj-3 than in patients with Traj-1 (odds ratio [OR]: 3.3, 95% confidence interval [CI]: 1.9–5.8) but similar for patients with Traj-1 and Traj-2. Similarly, the logistic analysis indicated the worst neurological outcomes in patients with Traj-3 (OR: 3.6, 95% CI: 2.0–6.4, relative to Traj-1), but similar neurological outcomes for patients in Traj-1 and Traj-2.Conclusion: Persistent, but not transient severe arterial hyperoxia, was associated with poor outcome in patients with HBI.

scholarly journals The influence of volume and intensive care unit organization on hospital mortality in patients admitted with severe sepsis: a retrospective multicentre cohort study

Critical Care ◽  
2007 ◽  
Vol 11 (2) ◽  
pp. R40 ◽  
Author(s):  
Linda Peelen ◽  
Nicolette F de Keizer ◽  
Niels Peek ◽  
Gert Scheffer ◽  
Peter HJ van der Voort ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Severe Sepsis ◽  
Cohort Study ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Multicentre Cohort Study ◽  
Unit Organization ◽  
Multicentre Cohort

scholarly journals Prediction of in-hospital mortality of Clostriodiodes difficile infection using critical care database: a big data-driven, machine learning approach

2021 ◽  
Vol 8 (1) ◽  
pp. e000761
Author(s):  
Hao Du ◽  
Kewin Tien Ho Siah ◽  
Valencia Zhang Ru-Yan ◽  
Readon Teh ◽  
Christopher Yu En Tan ◽  
...  
Keyword(s):  
Machine Learning ◽  
Critical Care ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Receiver Operating Curve ◽  
Study Cohort ◽  
Risk Of Death ◽  
Severity Scores ◽  
Mimic Iii ◽  
Care Database

Research objectivesClostriodiodes difficile infection (CDI) is a major cause of healthcare-associated diarrhoea with high mortality. There is a lack of validated predictors for severe outcomes in CDI. The aim of this study is to derive and validate a clinical prediction tool for CDI in-hospital mortality using a large critical care database.MethodologyThe demographics, clinical parameters, laboratory results and mortality of CDI were extracted from the Medical Information Mart for Intensive Care-III (MIMIC-III) database. We subsequently trained three machine learning models: logistic regression (LR), random forest (RF) and gradient boosting machine (GBM) to predict in-hospital mortality. The individual performances of the models were compared against current severity scores (Clostridiodes difficile Associated Risk of Death Score (CARDS) and ATLAS (Age, Treatment with systemic antibiotics, leukocyte count, Albumin and Serum creatinine as a measure of renal function) by calculating area under receiver operating curve (AUROC). We identified factors associated with higher mortality risk in each model.Summary of resultsFrom 61 532 intensive care unit stays in the MIMIC-III database, there were 1315 CDI cases. The mortality rate for CDI in the study cohort was 18.33%. AUROC was 0.69 (95% CI, 0.60 to 0.76) for LR, 0.71 (95% CI, 0.62 to 0.77) for RF and 0.72 (95% CI, 0.64 to 0.78) for GBM, while previously AUROC was 0.57 (95% CI, 0.51 to 0.65) for CARDS and 0.63 (95% CI, 0.54 to 0.70) for ATLAS. Albumin, lactate and bicarbonate were significant mortality factors for all the models. Free calcium, potassium, white blood cell, urea, platelet and mean blood pressure were present in at least two of the three models.ConclusionOur machine learning derived CDI in-hospital mortality prediction model identified pertinent factors that can assist critical care clinicians in identifying patients at high risk of dying from CDI.

scholarly journals Association between Malnutrition and Hospital Mortality and Duration of Intensive Care Unit Admission in the Critically Ill: A Prospective Cohort Study

2017 ◽  
Author(s):  
Charles Chin Han Lew ◽  
Gabriel Jun Yung Wong ◽  
Ka Po Cheung ◽  
Ai Ping Chua ◽  
Mary Foong Fong Chong ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Cohort Study ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Critically Ill ◽  
Prospective Cohort Study ◽  
Critically Ill Patients ◽  
Prospective Cohort ◽  
Unit Length ◽  
Increased Risk

There is limited evidence for the association between malnutrition and hospital mortality as well as Intensive Care Unit length-of-stay (ICU-LOS) in critically ill patients. We aimed to examine the aforementioned associations by conducting a prospective cohort study in an ICU of a Singapore tertiary hospital. Between August 2015 and October 2016, all adult patients with &ge;24 h of ICU-LOS were included. The 7-point Subjective Global Assessment (7-point SGA) was used to determine patients&rsquo; nutritional status within 48 hours of ICU admission. Multivariate analyses were conducted in two ways: 1) presence versus absence of malnutrition, and 2) dose-dependent association for each 1-point decrease in the 7-point SGA. There were 439 patients of which 28.0% were malnourished, and 29.6% died before hospital discharge. Malnutrition was associated with an increased risk of hospital mortality [adjusted-RR 1.39 (95%CI: 1.10&ndash;1.76)], and this risk increased with a greater degree of malnutrition [adjusted-RR 1.09 (95%CI: 1.01&ndash;1.18) for each 1-point decrease in the 7-point SGA]. No significant association was found between malnutrition and ICU-LOS. Conclusion: There was a clear association between malnutrition and higher hospital mortality in critically ill patients. The association between malnutrition and ICU-LOS could not be replicated and hence requires further evaluation.

scholarly journals The Association between Nutritional Status and In-Hospital Mortality of COVID-19 in Critically-Ill Patients in the ICU

Nutrients ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 3302
Author(s):  
Michał Czapla ◽  
Raúl Juárez-Vela ◽  
Vicente Gea-Caballero ◽  
Stanisław Zieliński ◽  
Marzena Zielińska
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Nutritional Status ◽  
Hospital Mortality ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Invasive Mechanical Ventilation ◽  
Nutritional Risk ◽  
Risk Of Death ◽  
The Impact

Background: Coronavirus disease 2019 (COVID-19) has become one of the leading causes of death worldwide. The impact of poor nutritional status on increased mortality and prolonged ICU (intensive care unit) stay in critically ill patients is well-documented. This study aims to assess how nutritional status and BMI (body mass index) affected in-hospital mortality in critically ill COVID-19 patients Methods: We conducted a retrospective study and analysed medical records of 286 COVID-19 patients admitted to the intensive care unit of the University Clinical Hospital in Wroclaw (Poland). Results: A total of 286 patients were analysed. In the sample group, 8% of patients who died had a BMI within the normal range, 46% were overweight, and 46% were obese. There was a statistically significantly higher death rate in men (73%) and those with BMIs between 25.0–29.9 (p = 0.011). Nonsurvivors had a statistically significantly higher HF (Heart Failure) rate (p = 0.037) and HT (hypertension) rate (p < 0.001). Furthermore, nonsurvivors were statistically significantly older (p < 0.001). The risk of death was higher in overweight patients (HR = 2.13; p = 0.038). Mortality was influenced by higher scores in parameters such as age (HR = 1.03; p = 0.001), NRS2002 (nutritional risk score, HR = 1.18; p = 0.019), PCT (procalcitonin, HR = 1.10; p < 0.001) and potassium level (HR = 1.40; p = 0.023). Conclusions: Being overweight in critically ill COVID-19 patients requiring invasive mechanical ventilation increases their risk of death significantly. Additional factors indicating a higher risk of death include the patient’s age, high PCT, potassium levels, and NRS ≥ 3 measured at the time of admission to the ICU.

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