scholarly journals The level of postoperative care influences mortality prediction by the POSPOM score: A retrospective cohort analysis

PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0257829
Author(s):  
Jan Menzenbach ◽  
Yannik C. Layer ◽  
Yonah L. Layer ◽  
Andreas Mayr ◽  
Mark Coburn ◽  
...  
Keyword(s):  
Postoperative Care ◽  
Cohort Analysis ◽  
Postoperative Mortality ◽  
Scoring Systems ◽  
Mortality Prediction ◽  
University Hospital ◽  
Study Endpoint ◽  
Individual Risk ◽  
Coding System ◽  
Icu Admission

Background The Preoperative Score to Predict Postoperative Mortality (POSPOM) assesses the patients’ individual risk for postsurgical intrahospital death based on preoperative parameters. We hypothesized that mortality predicted by the POSPOM varies depending on the level of postoperative care. Methods All patients age over 18 years undergoing inpatient surgery or interventions involving anesthesia at a German university hospital between January 2006, and December 2017, were assessed for eligibility for this retrospective study. Endpoint was death in hospital following surgery. Adaptation of the POSPOM to the German coding system was performed as previously described. The whole cohort was divided according to the level of postoperative care (normal ward vs. intensive care unit (ICU) admission within 24 h vs. later than 24 h, respectively). Results 199,258 patients were finally included. Observed intrahospital mortality was 2.0% (4,053 deaths). 9.6% of patients were transferred to ICU following surgery, and mortality of those patients was increased already at low POSPOM values of 15. 17,165 patients were admitted to ICU within 24 h, and these patients were older, had more comorbidities, or underwent more invasive surgery, reflected by a higher median POSPOM score compared to the normal-ward group (29 vs. 17, p <0.001). Mortality in that cohort was significantly increased to 8.7% (p <0.001). 2,043 patients were admitted to ICU later than 24 h following surgery (therefore denoted unscheduled admission), and the median POSPOM value of that group was 23. Observed mortality in this cohort was highest (13.5%, p <0.001 vs. ICU admission <24 h cohort). Conclusion Increased mortality in patients transferred to high-care wards reflects the significance of, e.g., intra- or early postoperative events for the patients’ outcome. Therefore, scoring systems considering only preoperative variables such as the POSPOM reveal limitations to predict the individual benefit of postoperative ICU admission.

Prognosis of Allogeneic Haematopoietic Stem Cell Recipients Admitted to the Intensive Care Unit: A Retrospective, Single-Centre Study

2015 ◽  
Vol 135 (2) ◽  
pp. 72-78 ◽  
Author(s):  
Sidsel Christy Lindgaard ◽  
Jonas Nielsen ◽  
Anders Lindmark ◽  
Henrik Sengeløv
Keyword(s):  
Intensive Care Unit ◽  
Mechanical Ventilation ◽  
Stem Cell ◽  
Intensive Care ◽  
Renal Replacement Therapy ◽  
Replacement Therapy ◽  
Scoring Systems ◽  
University Hospital ◽  
Haematopoietic Stem Cell ◽  
Icu Admission

Background: Allogeneic haematopoietic stem cell transplantation (HSCT) is a procedure with inherent complications and intensive care may be necessary. We evaluated the short- and long-term outcomes of the HSCT recipients requiring admission to the intensive care unit (ICU). Methods: We retrospectively examined the outcome of 54 adult haematological HSCT recipients admitted to the ICU at the University Hospital Rigshospitalet between January 2007 and March 2012. Results: The overall in-ICU, in-hospital, 6-month and 1-year mortality rates were 46.3, 75.9, 79.6 and 86.5%, respectively. Mechanical ventilation had a statistically significant effect on in-ICU (p = 0.02), 6-month (p = 0.049) and 1-year (p = 0.014) mortality. Renal replacement therapy also had a statistically significant effect on in-hospital (p = 0.038) and 6-month (p = 0.026) mortality. Short ICU admissions, i.e. <10 days, had a statistically significant positive effect on in-hospital, 6-month and 1-year mortality (all p < 0.001). The SAPS II, APACHE II and SOFA scoring systems grossly underestimated the actual in-hospital mortality observed for these patients. Conclusion: The poor prognosis of critically ill HSCT recipients admitted to the ICU was confirmed in our study. Mechanical ventilation, renal replacement therapy and an ICU admission of ≥10 days were each risk factors for mortality in the first year after ICU admission.

scholarly journals Markers of NETosis and DAMPs are altered in critically ill COVID-19 patients

2020 ◽  
Author(s):  
Joram Huckriede ◽  
Sara Bülow Anderberg ◽  
Albert Morales ◽  
Femke de Vries ◽  
Michael Hultström ◽  
...  
Keyword(s):  
Critically Ill ◽  
Scoring Systems ◽  
Tertiary Hospital ◽  
Blood Parameters ◽  
Severe Form ◽  
University Hospital ◽  
Cellular Damage ◽  
Plasma Parameters ◽  
Immune Modulators ◽  
Icu Admission

Abstract Background Coronavirus disease 19 (COVID-19) is known to present with disease severities of varying degree. In its most severe form, infection may lead to respiratory failure and multi-organ dysfunction. Here we study the levels of extracellular histone H3 (H3), neutrophil elastase (NE) and cfDNA in relation to other plasma parameters, including the immune modulators GAS6 and AXL, ICU scoring systems and mortality in patients with severe COVID-19.Methods We measured plasma H3, NE, cfDNA, GAS6 and AXL concentration in plasma of 83 COVID-19-positive and 11 COVID-19-negative patients at admission to the Intensive Care Unit (ICU) at the Uppsala University hospital, a tertiary hospital in Sweden and a total of 333 samples obtained from these patients during the ICU-stay. We determined their correlation with disease severity, organ failure, mortality and other blood parameters.Results H3, NE, cfDNA, GAS6 and AXL were increased in plasma of COVID-19 patients compared to controls. cfDNA and GAS6 decreased in time in in patients surviving to 30 days post ICU admission. Plasma H3 was a common feature of COVID-19 patients, detected in 40% of the patients at ICU admission. Although these measures were not predictive of the final outcome of the disease, they correlated well with parameters of tissue damage (H3 and cfDNA) and neutrophil counts (NE). A subset of samples displayed H3 processing, possibly due to proteolysis.Conclusions Elevated H3 and cfDNA levels in COVID-19 patients illustrate the severity of the cellular damage observed in critically ill COVID-19 patients. The increase in NE indicates the important role of neutrophil response and the process of NETosis in the disease. GAS6 appears as part of an early activated mechanism of response in Covid-19.

scholarly journals Validation of the Preoperative Score to Predict Postoperative Mortality (POSPOM) in Germany

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0245841
Author(s):  
Yannik C. Layer ◽  
Jan Menzenbach ◽  
Yonah L. Layer ◽  
Andreas Mayr ◽  
Tobias Hilbert ◽  
...  
Keyword(s):  
Hospital Mortality ◽  
Postoperative Mortality ◽  
University Hospital ◽  
Brier Score ◽  
Calibration Plot ◽  
Coding System ◽  
C Statistic ◽  
Using Data ◽  
Previous Demonstration ◽  
Preoperative Score

Background The Preoperative Score to Predict Postoperative Mortality (POSPOM) based on preoperatively available data was presented by Le Manach et al. in 2016. This prognostic model considers the kind of surgical procedure, patients' age and 15 defined comorbidities to predict the risk of postoperative in-hospital mortality. Objective of the present study was to validate POSPOM for the German healthcare coding system (G-POSPOM). Methods and findings All cases involving anaesthesia performed at the University Hospital Bonn between 2006 and 2017 were analysed retrospectively. Procedures codified according to the French Groupes Homogènes de Malades (GHM) were translated and adapted to the German Operationen- und Prozedurenschlüssel (OPS). Comorbidities were identified by the documented International Statistical Classification of Diseases (ICD-10) coding. POSPOM was calculated for the analysed patient collective using these data according to the method described by Le Manach et al. Performance of thereby adapted POSPOM was tested using c-statistic, Brier score and a calibration plot. Validation was performed using data from 199,780 surgical cases. With a mean age of 56.33 years (SD 18.59) and a proportion of 49.24% females, the overall cohort had a mean POSPOM value of 18.18 (SD 8.11). There were 4,066 in-hospital deaths, corresponding to an in-hospital mortality rate of 2.04% (95% CI 1.97 to 2.09%) in our sample. POSPOM showed a good performance with a c-statistic of 0.771 and a Brier score of 0.021. Conclusions After adapting POSPOM to the German coding system, we were able to validate the score using patient data of a German university hospital. According to previous demonstration for French patient cohorts, we observed a good correlation of POSPOM with in-hospital mortality. Therefore, further adjustments of POSPOM considering also multicentre and transnational validation should be pursued based on this proof of concept.

Predicting mortality in bronchiectasis using bronchiectasis severity index and FACED scores: a 19-year cohort study

2015 ◽  
Vol 47 (2) ◽  
pp. 482-489 ◽  
Author(s):  
Huw C. Ellis ◽  
Steven Cowman ◽  
Michele Fernandes ◽  
Robert Wilson ◽  
Michael R. Loebinger
Keyword(s):  
Predictive Power ◽  
Characteristic Curve ◽  
Cohort Analysis ◽  
Scoring Systems ◽  
Severity Index ◽  
Receiver Operator Characteristic Curve ◽  
Mortality Prediction ◽  
Prediction Of Mortality ◽  
Long Term Mortality

The clinical course of bronchiectasis is unpredictable, posing a challenge both in clinical practice and in research. Two mortality prediction scores, the bronchiectasis severity index (BSI) and FACED scores, have recently been developed. The aim of this study was to assess the ability of these scores to predict long-term mortality and to compare the two scores.The study was a single-centre retrospective cohort analysis consisting of 91 subjects originally recruited in 1994. BSI and FACED scores were calculated at the time of enrolment and long-term mortality ascertained. Data was available for 74 patients with a median of 18.8 years of follow-up.Both scoring systems had similar predictive power for 5-year mortality (area under receiver operator characteristic curve (AUC) 0.79 for BSI and 0.8 for FACED). Both scores were able to predict 15-year mortality with the FACED score showing slightly superior predictive power (AUC 0.82 versus 0.69, p=0.0495).This study provides further validation of the FACED and BSI scores for the prediction of mortality in bronchiectasis and demonstrates their utility over a longer period than originally described. Whilst both scores had excellent predictive power, the FACED score was superior for 15-year mortality.

scholarly journals SARS-CoV-2 Renal Impairment in Critical Care: An Observational Study of 42 Cases (Kidney COVID)

2021 ◽  
Vol 10 (8) ◽  
pp. 1571
Author(s):  
Antoine-Marie Molina Barragan ◽  
Emmanuel Pardo ◽  
Pierre Galichon ◽  
Nicolas Hantala ◽  
Anne-Charlotte Gianinazzi ◽  
...  
Keyword(s):  
Renal Impairment ◽  
Renal Injury ◽  
Kidney Injury ◽  
Critical Factor ◽  
University Hospital ◽  
Co2 Partial Pressure ◽  
Icu Admission ◽  
Icu Stay ◽  
Arterial Blood ◽  
Mixed Pattern

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection leads to 5% to 16% hospitalization in intensive care units (ICU) and is associated with 23% to 75% of kidney impairments, including acute kidney injury (AKI). The current work aims to precisely characterize the renal impairment associated to SARS-CoV-2 in ICU patients. Forty-two patients consecutively admitted to the ICU of a French university hospital who tested positive for SARS-CoV-2 between 25 March 2020, and 29 April 2020, were included and classified in categories according to their renal function. Complete renal profiles and evolution during ICU stay were fully characterized in 34 patients. Univariate analyses were performed to determine risk factors associated with AKI. In a second step, we conducted a logistic regression model with inverse probability of treatment weighting (IPTW) analyses to assess major comorbidities as predictors of AKI. Thirty-two patients (94.1%) met diagnostic criteria for intrinsic renal injury with a mixed pattern of tubular and glomerular injuries within the first week of ICU admission, which lasted upon discharge. During their ICU stay, 24 patients (57.1%) presented AKI which was associated with increased mortality (p = 0.007), hemodynamic failure (p = 0.022), and more altered clearance at hospital discharge (p = 0.001). AKI occurrence was associated with lower pH (p = 0.024), higher PaCO2 (CO2 partial pressure in the arterial blood) (p = 0.027), PEEP (positive end-expiratory pressure) (p = 0.027), procalcitonin (p = 0.015), and CRP (C-reactive protein) (p = 0.045) on ICU admission. AKI was found to be independently associated with chronic kidney disease (adjusted OR (odd ratio) 5.97 (2.1–19.69), p = 0.00149). Critical SARS-CoV-2 infection is associated with persistent intrinsic renal injury and AKI, which is a risk factor of mortality. Mechanical ventilation settings seem to be a critical factor of kidney impairment.

scholarly journals Cigarette smoking may accelerate the progression of IgA nephropathy

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Siqing Wang ◽  
Aiya Qin ◽  
Gaiqin Pei ◽  
Zheng Jiang ◽  
Lingqiu Dong ◽  
...  
Keyword(s):  
Risk Factor ◽  
Propensity Score ◽  
Cigarette Smoking ◽  
Independent Risk Factor ◽  
Cox Regression ◽  
Cohort Analysis ◽  
Cox Proportional Hazards ◽  
Study Endpoint ◽  
Cox Regression Analysis ◽  
Ckd Stage

Abstract Background Whether cigarette smoking is associated with the progression of immunoglobulin A nephropathy (IgAN) remains uncertain; therefore, we aimed to evaluate the effect of cigarette smoking on the prognosis of IgAN. Methods We divided 1239 IgAN patients from West China Hospital of Sichuan University who met the inclusion criteria into smoker (current or former) and non-smoker groups. The endpoint was end-stage renal disease (ESRD: eGFR < 15 mL/min/1.73 m2 or undergoing renal replacement treatment) and/or eGFR decreased by > 50%. Kaplan–Meier, correlation, logistic regression and Cox proportional hazards analyses were performed. The association between cigarette smoking and IgAN was further verified by propensity-score-matched cohort analysis. Results During the mean follow-up period of 61 months, 19% (40/209) of the smoker group and 11% (110/1030) of the non-smoker group reached the study endpoint (p < 0.001). Multivariate Cox regression analysis revealed that cigarette smoking (hazard ratio (HR) = 1.58; p = 0.043) was an independent risk factor predicting poor renal progression in IgAN, and that IgAN patients with chronic kidney disease (CKD) stage 3–4 were more susceptible to cigarette smoking (p < 0.001). After propensity score matching (PSM), a significant correlation between cigarette smoking and renal outcomes in IgAN patients was seen. Furthermore, Spearman’s correlation test revealed that smoking dose was negatively correlated with eGFR (r = 0.141; p < 0.001) and positively related with proteinuria (r = 0.096; p = 0.001). Conclusions Cigarette smoking is an independent risk factor for IgAN progression, especially for advanced patients.

scholarly journals Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Espen Jimenez-Solem ◽  
Tonny S. Petersen ◽  
Casper Hansen ◽  
Christian Hansen ◽  
Christina Lioma ◽  
...  
Keyword(s):  
Prediction Models ◽  
Severe Disease ◽  
External Validation ◽  
Area Under The Curve ◽  
Predictive Performance ◽  
Mortality Prediction ◽  
Icu Admission ◽  
Risk Of Death ◽  
Online Risk ◽  
The United Kingdom

AbstractPatients with severe COVID-19 have overwhelmed healthcare systems worldwide. We hypothesized that machine learning (ML) models could be used to predict risks at different stages of management and thereby provide insights into drivers and prognostic markers of disease progression and death. From a cohort of approx. 2.6 million citizens in Denmark, SARS-CoV-2 PCR tests were performed on subjects suspected for COVID-19 disease; 3944 cases had at least one positive test and were subjected to further analysis. SARS-CoV-2 positive cases from the United Kingdom Biobank was used for external validation. The ML models predicted the risk of death (Receiver Operation Characteristics—Area Under the Curve, ROC-AUC) of 0.906 at diagnosis, 0.818, at hospital admission and 0.721 at Intensive Care Unit (ICU) admission. Similar metrics were achieved for predicted risks of hospital and ICU admission and use of mechanical ventilation. Common risk factors, included age, body mass index and hypertension, although the top risk features shifted towards markers of shock and organ dysfunction in ICU patients. The external validation indicated fair predictive performance for mortality prediction, but suboptimal performance for predicting ICU admission. ML may be used to identify drivers of progression to more severe disease and for prognostication patients in patients with COVID-19. We provide access to an online risk calculator based on these findings.

scholarly journals Mortality prediction using a novel combination of biomarkers in the first day of sepsis in intensive care units

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Junkun Liu ◽  
Chengwen Bai ◽  
Binbin Li ◽  
Aijun Shan ◽  
Fei Shi ◽  
...  
Keyword(s):  
Septic Shock ◽  
Scoring Systems ◽  
Predictive Performance ◽  
Serum Levels ◽  
International Normalized Ratio ◽  
Individual Performance ◽  
Mortality Prediction ◽  
New Combination ◽  
Thrombin Time ◽  
Survivor Group

AbstractEarly identification of infection severity and organ dysfunction is crucial in improving outcomes of patients with sepsis. We aimed to develop a new combination of blood-based biomarkers that can early predict 28-day mortality in patients with sepsis or septic shock. We enrolled 66 patients with sepsis or septic shock and compared 14 blood-based biomarkers in the first 24 h after ICU admission. The serum levels of interleukin-6 (IL-6) (median 217.6 vs. 4809.0 pg/ml, P = 0.001), lactate (median 2.4 vs. 6.3 mmol/L, P = 0.014), N-terminal prohormone of brain natriuretic peptide (NT-proBNP) (median 1596.5 vs. 32,905.3 ng/ml, P < 0.001), prothrombin time (PT) (median 15.6 vs. 20.1 s, P = 0.030), activated partial thrombin time (APTT) (median 45.1 vs. 59.0 s, P = 0.026), and international normalized ratio (INR) (median 1.3 vs. 1.8, P < 0.001) were significantly lower in the survivor group. IL-6, NT-proBNP, and INR provided the best individual performance in predicting 28-day mortality of patients with sepsis or septic shock. Furthermore, the combination of these three biomarkers achieved better predictive performance (AUC 0.890, P < 0.001) than conventional scoring systems. In summary, the combination of IL-6, NT-proBNP, and INR may serve as a potential predictor of 28-day mortality in critically ill patients with sepsis or septic shock.

scholarly journals Accuracy of conventional and novel scoring systems in predicting severity and outcomes of acute pancreatitis: a retrospective study

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Qing Wu ◽  
Jie Wang ◽  
Mengbin Qin ◽  
Huiying Yang ◽  
Zhihai Liang ◽  
...  
Keyword(s):  
Acute Pancreatitis ◽  
Organ Failure ◽  
Scoring System ◽  
Characteristic Curve ◽  
Failure Prediction ◽  
Scoring Systems ◽  
Mortality Prediction ◽  
Severity Prediction ◽  
Index Of Severity ◽  
Glasgow Score

Abstract Background Recently, several novel scoring systems have been developed to evaluate the severity and outcomes of acute pancreatitis. This study aimed to compare the effectiveness of novel and conventional scoring systems in predicting the severity and outcomes of acute pancreatitis. Methods Patients treated between January 2003 and August 2020 were reviewed. The Ranson score (RS), Glasgow score (GS), bedside index of severity in acute pancreatitis (BISAP), pancreatic activity scoring system (PASS), and Chinese simple scoring system (CSSS) were determined within 48 h after admission. Multivariate logistic regression was used for severity, mortality, and organ failure prediction. Optimum cutoffs were identified using receiver operating characteristic curve analysis. Results A total of 1848 patients were included. The areas under the curve (AUCs) of RS, GS, BISAP, PASS, and CSSS for severity prediction were 0.861, 0.865, 0.829, 0.778, and 0.816, respectively. The corresponding AUCs for mortality prediction were 0.693, 0.736, 0.789, 0.858, and 0.759. The corresponding AUCs for acute respiratory distress syndrome prediction were 0.745, 0.784, 0.834, 0.936, and 0.820. Finally, the corresponding AUCs for acute renal failure prediction were 0.707, 0.734, 0.781, 0.868, and 0.816. Conclusions RS and GS predicted severity better than they predicted mortality and organ failure, while PASS predicted mortality and organ failure better. BISAP and CSSS performed equally well in severity and outcome predictions.

scholarly journals Glutamine and glutathione at ICU admission in relation to outcome

2012 ◽  
Vol 122 (12) ◽  
pp. 591-597 ◽  
Author(s):  
Paul Castillo Rodas ◽  
Olav Rooyackers ◽  
Christina Hebert ◽  
Åke Norberg ◽  
Jan Wernerman
Keyword(s):  
Risk Factor ◽  
Organ Failure ◽  
Independent Predictor ◽  
Apache Ii ◽  
University Hospital ◽  
Glutathione Depletion ◽  
Glutamine Supplementation ◽  
Limiting Factor ◽  
Icu Patients ◽  
Icu Admission

Glutamine depletion is demonstrated to be an independent predictor of hospital mortality in ICU (intensive care unit) patients. Today glutamine supplementation is recommended to ICU patients on parenteral nutrition. In addition to glutamine, glutathione may be a limiting factor in ICU patients with MOF (multiple organ failure). To study the prevalence of glutamine and glutathione depletion an observational study was performed. The results were analysed in relation to mortality and the conventional predictors of mortality outcome, APACHE II (Acute Physiology and Chronic Health Evaluation II) and SOFA (Sequential Organ Failure Assessment). Consecutive patients admitted to the ICU at Karolinska University Hospital Huddinge were studied. Patient admission scoring of APACHE II and SOFA were registered as well as mortality up to 6 months. Plasma glutamine concentration and whole blood glutathione status at admittance were analysed. The admission plasma glutamine concentrations were totally independent of the conventional risk scoring at admittance, and a subnormal concentration was an independent predictor of mortality. In addition, glutathione redox status was also an independent mortality predictor, but here a normal ratio was the risk factor. In both cases the mortality risk was mainly confined to the post-ICU period. A low plasma concentration of glutamine at ICU admission is an independent risk factor for post-ICU mortality. The possible benefit of extending glutamine supplementation post-ICU should be evaluated prospectively.

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