scholarly journals Understanding the Abrupt Effect of Spousal Bereavement on Mortality: an Application of Complex Dynamic Systems Theory

2021 ◽  
Author(s):  
Alexandros Katsiferis ◽  
Pernille Yde Nielsen ◽  
Majken K. Jensen ◽  
Rudi G.J Westendorp
Keyword(s):  
Systems Theory ◽  
Mean Squared Error ◽  
Characteristic Curve ◽  
Adverse Outcomes ◽  
Added Value ◽  
Event Analysis ◽  
Spousal Bereavement ◽  
P Values ◽  
Healthcare Consumption ◽  
Dynamic Indicators

Abstract BackgroundThe process of aging renders older people susceptible for adverse outcomes upon stress. Various indicators derived from complex systems theory have been proposed for quantifying resilience in living organisms, including humans. We investigated the ability of system-based indicators in capturing the dynamics of resilience in humans who suffer the adversity of spousal bereavement and tested their predictive power in mortality as a finite health transition.MethodsUsing longitudinal register data on weekly healthcare consumption of all Danish citizens over the age of 65 from January 1st, 2011, throughout December 31st, 2016, we performed statistical comparisons of the indicators ‘average’, ‘slope’, ‘mean squared error’, and ‘lag-1 autocorrelation’ one year before and after spousal bereavement, stratified for age and sex. The relation between levels of these indicators before bereavement and mortality hazards thereafter was determined by time to event analysis and the added value for mortality prediction was estimated by the time dependent area under the receiver operating characteristic curve.ResultsThe study included 934,003 citizens of whom 51,890 experienced spousal bereavement and 2862 died in the first year thereafter. Values of all dynamic indicators were significantly higher with increasing age, in men compared to women, and except lag-1 autocorrelation, higher in the year after bereavement (all p-values < 0.001). All dynamic indicators before bereavement were positively related with mortality hazards thereafter (all p-values < 0.001). The area under the curve of the final model to predict mortality, including all relevant indicators, was 77.7% for males and it was 81.8% for females.ConclusionsIt is concluded that healthcare consumption is increased, more volatile and accelerating with aging and in men compared to women. High values of these dynamic indicators before bereavement indicate loss of resilience as manifested by their predictive value to predict mortality when mourning after spousal loss.

scholarly journals Predictive value of the neutrophil to lymphocyte ratio for disease deterioration and serious adverse outcomes in patients with COVID-19: a prospective cohort study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Zhi-Yong Zeng ◽  
Shao-Dan Feng ◽  
Gong-Ping Chen ◽  
Jiang-Nan Wu
Keyword(s):  
Cohort Study ◽  
Hospital Admission ◽  
Clinical Outcomes ◽  
Prospective Cohort Study ◽  
Prospective Cohort ◽  
Characteristic Curve ◽  
Adverse Outcomes ◽  
Neutrophil To Lymphocyte Ratio ◽  
Predictive Values ◽  
Lymphocyte Ratio

Abstract Background Early identification of patients who are at high risk of poor clinical outcomes is of great importance in saving the lives of patients with novel coronavirus disease 2019 (COVID-19) in the context of limited medical resources. Objective To evaluate the value of the neutrophil to lymphocyte ratio (NLR), calculated at hospital admission and in isolation, for the prediction of the subsequent presence of disease progression and serious clinical outcomes (e.g., shock, death). Methods We designed a prospective cohort study of 352 hospitalized patients with COVID-19 between January 9 and February 26, 2020, in Yichang City, Hubei Province. Patients with an NLR equal to or higher than the cutoff value derived from the receiver operating characteristic curve method were classified as the exposed group. The primary outcome was disease deterioration, defined as an increase of the clinical disease severity classification during hospitalization (e.g., moderate to severe/critical; severe to critical). The secondary outcomes were shock and death during the treatment. Results During the follow-up period, 51 (14.5%) patients’ conditions deteriorated, 15 patients (4.3%) had complicated septic shock, and 15 patients (4.3%) died. The NLR was higher in patients with deterioration than in those without deterioration (median: 5.33 vs. 2.14, P < 0.001), and higher in patients with serious clinical outcomes than in those without serious clinical outcomes (shock vs. no shock: 6.19 vs. 2.25, P < 0.001; death vs. survival: 7.19 vs. 2.25, P < 0.001). The NLR measured at hospital admission had high value in predicting subsequent disease deterioration, shock and death (all the areas under the curve > 0.80). The sensitivity of an NLR ≥ 2.6937 for predicting subsequent disease deterioration, shock and death was 82.0% (95% confidence interval, 69.0 to 91.0), 93.3% (68.0 to 100), and 92.9% (66.0 to 100), and the corresponding negative predictive values were 95.7% (93.0 to 99.2), 99.5% (98.6 to 100) and 99.5% (98.6 to 100), respectively. Conclusions The NLR measured at admission and in isolation can be used to effectively predict the subsequent presence of disease deterioration and serious clinical outcomes in patients with COVID-19.

Abstract 2422: Short Term Effects of Milrinone on Biomarkers in Severe Heart Failure

Circulation ◽  
2008 ◽  
Vol 118 (suppl_18) ◽  
Author(s):  
David Lanfear ◽  
Ramesh C Gupta ◽  
Rasha N Bazari ◽  
Reema Hasan ◽  
Celeste Williams ◽  
...  
Keyword(s):  
Heart Failure ◽  
Myocardial Injury ◽  
Fas Ligand ◽  
Troponin I ◽  
Severe Heart Failure ◽  
Myocardial Necrosis ◽  
Adverse Outcomes ◽  
P Values ◽  
Damage Initiation ◽  
Tnf Α

Introduction: Inotrope use is associated with adverse outcomes in heart failure (HF), raising concern that it may cause or accelerate myocardial injury/damage. Whether biomarkers of myocardial necrosis, stretch, inflammation and apoptosis change in response to inotrope initiation is not known. Methods: Ten patients with severe HF and cardiac index < 2.0 L/m/M2 who were planned to receive intravenous milrinone were studied. All patients were at bed rest in cardiac intensive care unit. Blood was drawn immediately before initiation of milrinone and after 24 hours of continuous infusion. Milrinone dosing was at the discretion of the patient’s attending physician (0.375 –0.5 mcg/kg/min were used). Blood samples were immediately centrifuged, plasma aliquoted, and frozen at -70°C. Troponin I (TnI), Myoglobin, N-terminal pro-BNP (NTproBNP), interleukin 6 (IL6), Tumor Necrosis Factor α (TNF α), soluble Fas (sFas), and Fas ligand (FasL) levels were measured. TnI levels were replicated to assess precision of measurement, yielding a correlation coefficient > 0.995 and power > 90% to detect a mean difference as small as 0.02 ng/ml. Statistical comparisons were made between baseline levels and 24 hour levels using the paired t-test. P values < 0.05 were considered significant. Results: Baseline mean biomarker levels, 24 hour levels, absolute change, percent change, and associated p-values are shown in the Table . Troponin I was elevated at baseline in all patients (range 0.0205– 0.56 ng/ml). There was no significant change in TnI after 24 hours of milrinone compared to baseline. There were significant improvements in NTproBNP, IL6, TNF α, sFas, and FasL. Conclusions: In this sample of patients with severe HF and reduced cardiac output, all had elevated troponin at baseline, consistent with ongoing myocardial damage. Initiation of milrinone therapy did not result in changes indicative of accelerated myocardial injury, and was associated with salutary effects on other markers. This research has received full or partial funding support from the American Heart Association, Midwest Affiliate (Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, South Dakota & Wisconsin). Change in Biomarker Levels at 24 hours of Milrinone Therapy

scholarly journals 2409. External Validation and Comparison of Clostridioides difficile Severity Scoring Systems

2019 ◽  
Vol 6 (Supplement_2) ◽  
pp. S831-S832
Author(s):  
Donald A Perry ◽  
Daniel Shirley ◽  
Dejan Micic ◽  
Rosemary K B Putler ◽  
Pratish Patel ◽  
...  
Keyword(s):  
Binary Classification ◽  
Characteristic Curve ◽  
External Validation ◽  
Receiver Operator Characteristic Curve ◽  
Adverse Outcomes ◽  
Risk Scores ◽  
Composite Outcome ◽  
Clostridioides Difficile ◽  
Severity Scores ◽  
Primary Composite Outcome

Abstract Background Annually in the US alone, Clostridioides difficile infection (CDI) afflicts nearly 500,000 patients causing 29,000 deaths. Since early and aggressive interventions could save lives but are not optimally deployed in all patients, numerous studies have published predictive models for adverse outcomes. These models are usually developed at a single institution, and largely are not externally validated. This aim of this study was to validate the predictability for severe CDI with previously published risk scores in a multicenter cohort of patients with CDI. Methods We conducted a retrospective study on four separate inpatient cohorts with CDI from three distinct sites: the Universities of Michigan (2010–2012 and 2016), Chicago (2012), and Wisconsin (2012). The primary composite outcome was admission to an intensive care unit, colectomy, and/or death attributed to CDI within 30 days of positive test. Structured query and manual chart review abstracted data from the medical record at each site. Published CDI severity scores were assessed and compared with each other and the IDSA guideline definition of severe CDI. Sensitivity, specificity, area under the receiver operator characteristic curve (AuROC), precision-recall curves, and net reclassification index (NRI) were calculated to compare models. Results We included 3,775 patients from the four cohorts (Table 1) and evaluated eight severity scores (Table 2). The IDSA (baseline comparator) model showed poor performance across cohorts(Table 3). Of the binary classification models, including those that were most predictive of the primary composite outcome, Jardin, performed poorly with minimal to no NRI improvement compared with IDSA. The continuous score models, Toro and ATLAS, performed better, but the AuROC varied by site by up to 17% (Table 3). The Gujja model varied the most: from most predictive in the University of Michigan 2010–2012 cohort to having no predictive value in the 2016 cohort (Table 3). Conclusion No published CDI severity score showed stable, acceptable predictive ability across multiple cohorts/institutions. To maximize performance and clinical utility, future efforts should focus on a multicenter-derived and validated scoring system, and/or incorporate novel biomarkers. Disclosures All authors: No reported disclosures.

scholarly journals Early identification of severe community-acquired pneumonia: a retrospective observational study

2019 ◽  
Vol 6 (1) ◽  
pp. e000438 ◽  
Author(s):  
Frances S Grudzinska ◽  
Kerrie Aldridge ◽  
Sian Hughes ◽  
Peter Nightingale ◽  
Dhruv Parekh ◽  
...  
Keyword(s):  
Early Warning ◽  
Assessment Tool ◽  
Characteristic Curve ◽  
Community Acquired Pneumonia ◽  
Adverse Outcomes ◽  
Assessment Tools ◽  
Early Warning Score ◽  
News Medium ◽  
Increased Risk ◽  
Early Warning Scores

BackgroundCommunity-acquired pneumonia (CAP) is a leading cause of sepsis worldwide. Prompt identification of those at high risk of adverse outcomes improves survival by enabling early escalation of care. There are multiple severity assessment tools recommended for risk stratification; however, there is no consensus as to which tool should be used for those with CAP. We sought to assess whether pneumonia-specific, generic sepsis or early warning scores were most accurate at predicting adverse outcomes.MethodsWe performed a retrospective analysis of all cases of CAP admitted to a large, adult tertiary hospital in the UK between October 2014 and January 2016. All cases of CAP were eligible for inclusion and were reviewed by a senior respiratory physician to confirm the diagnosis. The association between the CURB65, Lac-CURB-65, quick Sequential (Sepsis-related) Organ Failure Assessment tool (qSOFA) score and National Early Warning Score (NEWS) at the time of admission and outcome measures including intensive care admission, length of hospital stay, in-hospital, 30-day, 90-day and 365-day all-cause mortality was assessed.Results1545 cases were included with 30-day mortality of 19%. Increasing score was significantly associated with increased risk of poor outcomes for all four tools. Overall accuracy assessed by receiver operating characteristic curve analysis was significantly greater for the CURB65 and Lac-CURB-65 scores than qSOFA. At admission, a CURB65 ≥2, Lac-CURB-65 ≥moderate, qSOFA ≥2 and NEWS ≥medium identified 85.0%, 96.4%, 40.3% and 79.0% of those who died within 30 days, respectively. A Lac-CURB-65 ≥moderate had the highest negative predictive value: 95.6%.ConclusionAll four scoring systems can stratify according to increasing risk in CAP; however, when a confident diagnosis of pneumonia can be made, these data support the use of pneumonia-specific tools rather than generic sepsis or early warning scores.

scholarly journals How We Care for an Older Patient With Cancer

2017 ◽  
Vol 13 (2) ◽  
pp. 95-102 ◽  
Author(s):  
Armin Shahrokni ◽  
Soo Jung Kim ◽  
George J. Bosl ◽  
Beatriz Korc-Grodzicki
Keyword(s):  
Predictive Models ◽  
Older Patients ◽  
Process Development ◽  
Adverse Outcomes ◽  
Added Value ◽  
Cancer Center ◽  
Multiple Chronic Conditions ◽  
Older Patient ◽  
Improve Patient Survival ◽  
Patients With Cancer

As the number of older patients with cancer is increasing, oncology disciplines are faced with the challenge of managing patients with multiple chronic conditions who have difficulty maintaining independence, who may have cognitive impairment, and who also may be more vulnerable to adverse outcomes. National and international societies have recommended that all older patients with cancer undergo geriatric assessment (GA) to detect unaddressed problems and introduce interventions to augment functional status to possibly improve patient survival. Several predictive models have been developed, and evidence has shown correlation between information obtained through GA and treatment-related complications. Comprehensive geriatric evaluations and effective interventions on the basis of GA may prove to be challenging for the oncologist because of the lack of the necessary skills, time constraints, and/or limited available resources. In this article, we describe how the Geriatrics Service at Memorial Sloan Kettering Cancer Center approaches an older patient with colon cancer from presentation to the end of life, show the importance of GA at the various stages of cancer treatment, and how predictive models are used to tailor the treatment. The patient’s needs and preferences are at the core of the decision-making process. Development of a plan of care should always include the patient’s preferences, but it is particularly important in the older patient with cancer because a disease-centered approach may neglect noncancer considerations. We will elaborate on the added value of co-management between the oncologist and a geriatric nurse practitioner and on the feasibility of adapting elements of this model into busy oncology practices.

scholarly journals Predicting developmental outcomes in preterm infants

Neurology ◽  
2019 ◽  
Vol 93 (13) ◽  
pp. e1231-e1240 ◽  
Author(s):  
Dalit Cayam-Rand ◽  
Ting Guo ◽  
Ruth E. Grunau ◽  
Isabel Benavente-Fernández ◽  
Anne Synnes ◽  
...  
Keyword(s):  
Characteristic Curve ◽  
Brain Mri ◽  
Adverse Outcomes ◽  
Preschool Age ◽  
Cognitive Outcomes ◽  
White Matter Injury ◽  
Preterm Neonates ◽  
Posterior Commissure ◽  
Neurodevelopmental Outcomes ◽  
Motor Outcomes

ObjectiveTo develop a simple imaging rule to predict neurodevelopmental outcomes at 4.5 years in a cohort of preterm neonates with white matter injury (WMI) based on lesion location and examine whether clinical variables enhance prediction.MethodsSixty-eight preterm neonates born 24–32 weeks' gestation (median 27.7 weeks) were diagnosed with WMI on early brain MRI scans (median 32.3 weeks). 3D T1-weighted images of 60 neonates with 4.5-year outcomes were reformatted and aligned to the posterior commissure–eye plane and WMI was classified by location: anterior or posterior-only to the midventricle line on the reformatted axial plane. Adverse outcomes at 4.5 years were defined as Wechsler Preschool and Primary Scale of Intelligence full-scale IQ <85, cerebral palsy, or Movement Assessment Battery for Children, second edition percentile <5. The prediction of adverse outcome by WMI location, intraventricular hemorrhage (IVH), bronchopulmonary dysplasia (BPD), and retinopathy of prematurity (ROP) was assessed using multivariable logistic regression.ResultsSix children had adverse cognitive outcomes and 17 had adverse motor outcomes. WMI location predicted cognitive outcomes in 90% (area under receiver operating characteristic curve [AUC] 0.80) and motor outcomes in 85% (AUC 0.75). Adding IVH, BPD, and ROP to the model enhances the predictive strength for cognitive and motor outcomes (AUC 0.83 and 0.88, respectively). Rule performance was confirmed in an independent cohort of children with WMI.ConclusionsWMI on early MRI can be classified by location to predict preschool age outcomes in children born preterm. The predictive value of this WMI classification is enhanced by considering clinical factors apparent by term-equivalent age.

scholarly journals Validation and Adaptation of the Multidimensional Prognostic Index in an Older Australian Cohort

2019 ◽  
Vol 8 (11) ◽  
pp. 1820 ◽  
Author(s):  
Kimberley Bryant ◽  
Michael J. Sorich ◽  
Richard J. Woodman ◽  
Arduino A. Mangoni
Keyword(s):  
Operating Characteristic ◽  
Reference Group ◽  
Characteristic Curve ◽  
Prognostic Index ◽  
Adverse Outcomes ◽  
Moderate Risk ◽  
Australian Cohort ◽  
Operating Characteristic Curve ◽  
Simple Logistic ◽  
Discriminatory Performance

Background and aims: The Multidimensional Prognostic Index (MPI), an objective and quantifiable tool based on the Comprehensive Geriatric Assessment, has been shown to predict adverse outcomes in European cohorts. We conducted a validation study of the original MPI, and of adapted versions that accounted for the use of specific drugs and cultural diversity in the assessment of cognition, in older Australians. Methods: The capacity of the MPI to predict 12-month mortality was assessed in 697 patients (median age: 80 years; interquartile range: 72–86) admitted to a metropolitan teaching hospital between September 2015 and February 2017. Results: In simple logistic regression analysis, the MPI was associated with 12-month mortality (Low risk: OR reference group; moderate risk: OR 2.50, 95% CI: 1.67–3.75; high risk: OR 4.24, 95% CI: 2.28–7.88). The area under the receiver operating characteristic curve (AUC) for the unadjusted MPI was 0.61 (0.57–0.65) and 0.64 (95% CI: 0.59–0.68) with age and sex adjusted. The adapted versions of the MPI did not significantly change the AUC of the original MPI. Conclusion: The original and adapted MPI were strongly associated with 12-month mortality in an Australian cohort. However, the discriminatory performance was lower than that reported in European studies.

scholarly journals The natriuretic peptide MR-proANP predicts all-cause mortality and adverse outcome in community patients: a 10-year follow-up study

2017 ◽  
Vol 55 (9) ◽  
Author(s):  
Jonas Odermatt ◽  
Lara Hersberger ◽  
Rebekka Bolliger ◽  
Lena Graedel ◽  
Mirjam Christ-Crain ◽  
...  
Keyword(s):  
Natriuretic Peptide ◽  
Cox Regression ◽  
Adverse Outcome ◽  
Characteristic Curve ◽  
Physiological Role ◽  
Adverse Outcomes ◽  
Community Dwelling ◽  
Blood Levels ◽  
All Cause Mortality

AbstractBackground:The precursor peptide of atrial natriuretic peptide (MR-proANP) has a physiological role in fluid homeostasis and is associated with mortality and adverse clinical outcomes in heart failure patients. Little is known about the prognostic potential of this peptide for long-term mortality prediction in community-dwelling patients. We evaluated associations of MR-proANP levels with 10-year all-cause mortality in patients visiting their general practitioner for a respiratory tract infection.Methods:In this post-hoc analysis including 359 patients (78.5%) of the original trial, we calculated cox regression models and area under the receiver operating characteristic curve (AUC) to assess associations of MR-proANP blood levels with mortality and adverse outcome including death, pulmonary embolism, and major adverse cardiac or cerebrovascular events.Results:After a median follow-up of 10.0 years, 9.8% of included patients died. Median admission MR-proANP levels were significantly elevated in non-survivors compared to survivors (80.5 pmol/L, IQR 58.6–126.0; vs. 45.6 pmol/L, IQR 34.2–68.3; p<0.001) and associated with 10-year all-cause mortality (age-adjusted HR 2.0 [95% CI 1.3–3.1, p=0.002]; AUC 0.79). Results were similar for day 7 blood levels and also for the prediction of other adverse outcomes.Conclusions:Increased MR-proANP levels were associated with 10-year all-cause mortality and adverse clinical outcome in a sample of community-dwelling patients. If diagnosis-specific cut-offs are confirmed in future studies, this marker may help to direct preventive measures in primary care.

scholarly journals Initial SARS-CoV-2 viral load is associated with disease severity: a retrospective cohort study

2021 ◽  
Author(s):  
Dennis Souverein ◽  
Karlijn van Stralen ◽  
Steven van Lelyveld ◽  
Claudia van Gemeren ◽  
Milly Haverkort ◽  
...  
Keyword(s):  
Viral Load ◽  
Hospital Mortality ◽  
Adverse Outcomes ◽  
Added Value ◽  
Teaching Hospitals ◽  
P Value ◽  
Rt Pcr ◽  
Icu Admission ◽  
Increased Risk ◽  
Viral Load Group

Background: We aimed to assess the association between initial SARS-CoV-2 viral load and the subsequent hospital and intensive care unit (ICU) admission and overall survival. Methods: All persons with a positive SARS-CoV-2 RT-PCR result from a combined nasopharyngeal (NP) and oropharyngeal (OP) swab (first samples from unique persons only) that was collected between March 17, 2020, and March 31, 2021, in Public Health testing facilities in the region Kennemerland, province of North Holland, the Netherlands were included. Data on hospital (and ICU) admission were collected from the two large teaching hospitals in the region Kennemerland. Results: In total, 20,207 SARS-CoV-2 positive persons were included in this study, of whom 310 (1.5%) were hospitalized in a regional hospital within 30 days of their positive SARS-CoV-2 RT-PCR test. When persons were categorized in three SARS-CoV-2 viral load groups, the high viral load group (Cp < 25) was associated with an increased risk of hospitalization as compared to the low viral load group (Cp > 30) (ORadjusted [95%CI]: 1.57 [1.11-2.26], p-value=0.012), adjusted for age and sex. The same association was seen for ICU admission (ORadjusted [95%CI]: 7.06 [2.15-43.57], p-value=0.007). For a subset of 243 of the 310 hospitalized patients, the association of initial SARS-CoV-2 Cp-value with in-hospital mortality was analyzed. The initial SARS-CoV-2 Cp-value of the 17 patients who deceased in the hospital was significantly lower (indicating a higher viral load) compared to the 226 survivors: median Cp-value [IQR]: 22.7 [3.4] vs. 25.0 [5.2], OR[95%CI]: 0.81 [0.68-0.94], p-value = 0.010. Conclusions: Our data show that higher initial SARS-CoV-2 viral load is associated with an increased risk of hospital admission, ICU admission, and in-hospital mortality. We believe that our findings emphasize the added value of reporting SARS-CoV-2 viral load based on Cp-values to identify persons who are at the highest risk of adverse outcomes such as hospital or ICU admission and who therefore may benefit from more intensive monitoring.

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