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Survival after PICU admission: The impact of multiple admissions and complex chronic conditions.

ABSTRACT: Factors predicting survival over time after pediatric intensive care unit (PICU) admissions are not fully understood. The primary aim of the current study was to investigate whether multiple admissions (MADM) compared to single PICU admissions (SADM) were associated with poor survival over time after being admitted to PICU facilities. Our secondary aim was to investigate if the presence of a complex chronic condition (CCC) would further impair prognosis.A closed cohort of all children up to 16 years of age admitted to the three PICUs in Sweden between 2008 and 2010 was prospectively collected and followed until 2012, providing survival data for at least one but up to four years of follow-up.Three Swedish tertiary referral centers for pediatric intensive care and extracorporeal membrane oxygenation (ECMO) care were used.In total, 3,688 Swedish children with 5,019 PICU admissions were included.No interventions were conducted.An extensive data set was recorded, including up to four-year survival information following first PICU admission. The patients were assigned to seven admission diagnostic groups, which were then divided into SADM or MADM groups. The difference in survival over time and mortality rates (MR) and mortality rate ratios (MRR) were calculated. SADM and MADM groups with and without an existing CCC were formed. The difference in survival over time between groups was calculated.A highly significant difference in survival over time was noted between SADM and MADM patients (p<0.0001), which was intensified by the presence of a CCC. MADM patients with a CCC had the worst outcome, while SADM patients without a CCC had the best outcome. MADM patients with no CCC demonstrated decreased survival over time compared to SADM patients with a CCC. Survival over time was statistically worsened for patients with MADM compared to SADM for the following admission diagnostic groups: Cardiovascular, Gastrointestinal/Renal, Respiratory, Neurological, and Miscellaneous. The mortality rate (deaths/patient year of follow-up) during the time of follow-up was 0.023 for SADM and 0.062 for MADM patients. The mortality rate ratio (MRR) between these groups was 2.69.Compared to single admissions, multiple admissions to PICU were associated with a significant decrease in survival over time in some but not all diagnostic groups. Regarding our secondary aim, we found that when the presence of a CCC is factored into the survival analysis, survival over time is further impaired.

SUBMITTER: Kalzen H

PROVIDER: S-EPMC5886395 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Survival after PICU admission: The impact of multiple admissions and complex chronic conditions.

Kalzén Håkan H Larsson Björn B Eksborg Staffan S Lindberg Lars L Edberg Karl Erik KE Frostell Claes C

PloS one 20180405 4

<h4>Objective</h4>Factors predicting survival over time after pediatric intensive care unit (PICU) admissions are not fully understood. The primary aim of the current study was to investigate whether multiple admissions (MADM) compared to single PICU admissions (SADM) were associated with poor survival over time after being admitted to PICU facilities. Our secondary aim was to investigate if the presence of a complex chronic condition (CCC) would further impair prognosis.<h4>Design</h4>A closed ...[more]

PMID: 29621235

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Project description:OBJECTIVE:To derive and validate clinical prediction models to identify children at low risk of clinically significant intoxications for whom intensive care admission is unnecessary. DESIGN:Retrospective review of data in the National Poison Data Systems from 2011 to 2014 and Georgia Poison Center cases from July to December 2016. SETTING:United States PICUs and poison centers participating in the American Association of Poison Control Centers from 2011 to 2016. PATIENTS:Children 18 years and younger admitted to a United States PICU following an acute intoxication. INTERVENTIONS:None. MEASUREMENTS AND MAIN RESULTS:The primary study outcome was the occurrence of clinically significant intoxications defined a priori as organ system-based clinical effects that require intensive care monitoring and interventions. We analyzed 70,364 cases. Derivation (n = 42,240; 60%) and validation cohorts (n = 28,124; 40%) were randomly selected from the eligible population and had similar distributions of clinical effects and PICU interventions. PICU interventions were performed in 1,835 children (14.1%) younger than 6 years, in 374 children (15.4%) 6-12 years, and in 4,446 children (16.5%) 13 years and older. We developed highly predictive models with an area under the receiver operating characteristic curve of 0.834 (< 6 yr), 0.771 (6-12 yr), and 0.786 (?13 yr), respectively. For predicted probabilities of less than or equal to 0.10 in the validation cohorts, the negative predictive values were 95.4% (< 6 yr), 94.9% (6-12 yr), and 95.1% (? 13 yr). An additional 700 patients from the Georgia Poison Center were used to validate the model and would have reduced PICU admission by 31.4% (n = 110). CONCLUSIONS:These validated models identified children at very low risk of clinically significant intoxications for whom pediatric intensive care admission can be avoided. Application of this model using Georgia Poison Center data could have resulted in a 30% reduction in PICU admissions following intoxication.

Project description:BackgroundIndividuals of low socioeconomic status experience a disproportionate burden of chronic conditions; however it is unclear whether chronic condition burden affects survival differently across socioeconomic strata.MethodsThis retrospective cohort study used health administrative data from all residents of Ontario, Canada aged 65 to 105 with at least one of 16 chronic conditions on April 1, 2009 (n = 1,518,939). Chronic condition burden and unadjusted mortality were compared across neighborhood income quintiles. Multivariable Cox proportional hazards models were used to examine the effect of number of chronic conditions on two-year survival across income quintiles.FindingsPrevalence of five or more chronic conditions was significantly higher among older adults in the poorest neighborhoods (18.2%) than the wealthiest (14.3%) (Standardized difference > 0·1). There was also a socioeconomic gradient in unadjusted mortality over two years: 10.1% of people in the poorest neighborhoods died compared with 7.6% of people in the wealthiest neighborhoods. In adjusted analyses, having more chronic conditions was associated with a statistically significant increase in hazard of death over two years, however the magnitude of this effect was comparable across income quintiles. Individuals in the poorest neighborhoods with four chronic conditions had 2.07 times higher hazard of death (95% CI: 1.97-2.19) than those with one chronic condition, but this was comparable to the hazard associated with four chronic conditions in the wealthiest neighborhoods (HR: 2.29, 95% CI: 2.16-2.43).InterpretationAmong older adults with universal access to health care, the deleterious effect of increasing chronic condition burden on two-year hazard of death was consistent across neighborhood income quintiles once baseline differences in condition burden were accounted for. This may be partly attributable to equal access to, and utilization of, health care. Alternate explanations for these findings, including study limitations, are also discussed.

Project description:BACKGROUND:Survivors of critical illness in childhood commonly display subsequent psychiatric symptoms including emotional and behavioural difficulties, and manifestations of post-traumatic stress disorder (PTSD). Anomalies in inflammatory profiles are an established finding in these childhood psychiatric conditions. OBJECTIVE:This exploratory study aimed to investigate whether abnormal peripheral blood inflammatory markers measured during paediatric intensive care unit (PICU) admission were associated with psychiatric symptoms after discharge. METHODS:We performed a prospective observational cohort study on 71 children with septic illness, meningoencephalitis and other critical disorders admitted to two PICUs between 2007 and 2010. 3-6 months following discharge, subjects were assessed for global psychiatric risk (ie, presence of emotional and behavioural difficulties on the parental Strengths and Difficulties Questionnaire (SDQ)), and for PTSD risk using the child-rated Impact of Events Scale (IES-8). Inflammatory and related biological markers were transcribed from PICU admission notes (white cell count, lymphocytes, neutrophils, C reactive protein (CRP), platelets, fibrinogen and lactate). FINDINGS:Global psychiatric risk at follow-up was associated with abnormal lymphocyte count during admission (?2=6.757, p=0.014, n=48). In children with sepsis, partial correlation analyses controlling for age and gender highlighted associations between (i) SDQ scores and low lymphocyte count (r=-0.712; p=0.009, n=14), and (ii) IES-8 score and high CRP levels (r=0.823; p=0.006, n=11). These associations remained after correction for multiple comparisons. CONCLUSION:These results support the hypothesis that acute inflammation may play a role in determining the development of psychopathology following PICU admission. CLINICAL IMPLICATIONS:If the findings are replicated, they may help to better highlight which children are at risk of post-PICU psychopathology and appropriately target follow-up.

Project description:ObjectivesEvolution of multiple chronic conditions (MCC) follows a complex stochastic process, influenced by several factors including the inter-relationship of existing conditions, and patient-level risk factors. Nearly 20% of citizens aged 18 years and older are burdened with two or more (multiple) chronic conditions (MCC). Treatment for people living with MCC currently accounts for an estimated 66% of the Nation's healthcare costs. However, it is still not known precisely how MCC emerge and accumulate among individuals or in the general population. This study investigates major patterns of MCC transitions in a diverse population of patients and identifies the risk factors affecting the transition process.MethodsA Latent regression Markov clustering (LRMCL) algorithm is proposed to identify major transitions of four MCC that include hypertension (HTN), depression, Post- Traumatic Stress Disorder (PTSD), and back pain. A cohort of 601,805 individuals randomly selected from the population of Iraq and Afghanistan war Veterans (IAVs) who received VA care during three or more years between 2002-2015, is used for training the proposed LRMCL algorithm.ResultsTwo major clusters of MCC transition patterns with 78% and 22% probability of membership respectively were identified. The primary cluster demonstrated the possibility of improvement when the number of MCC is small and an increase in probability of MCC accumulation as the number of co- morbidities increased. The second cluster showed stability (no change) of MCC overtime as the major pattern. Age was the most significant risk factor associated with the most probable cluster for each IAV.ConclusionsThese findings suggest that our proposed LRMCL algorithm can be used to describe and understand MCC transitions, which may ultimately allow healthcare systems to support optimal clinical decision- making. This method will be used to describe a broader range of MCC transitions in this and non-VA populations, and will add treatment information to see if models including treatments and MCC emergence can be used to support clinical decision-making in patient care.

Project description:BackgroundTelemonitoring is becoming increasingly important for the management of patients with chronic conditions, especially in countries with large distances such as Australia. However, despite large national investments in health information technology, little policy work has been undertaken in Australia in deploying telehealth in the home as a solution to the increasing demands and costs of managing chronic disease.ObjectiveThe objective of this trial was to evaluate the impact of introducing at-home telemonitoring to patients living with chronic conditions on health care expenditure, number of admissions to hospital, and length of stay (LOS).MethodsA before and after control intervention analysis model was adopted whereby at each location patients were selected from a list of eligible patients living with a range of chronic conditions. Each test patient was case matched with at least one control patient. Test patients were supplied with a telehealth vital signs monitor and were remotely managed by a trained clinical care coordinator, while control patients continued to receive usual care. A total of 100 test patients and 137 control patients were analyzed. Primary health care benefits provided to Australian patients were investigated for the trial cohort. Time series data were analyzed using linear regression and analysis of covariance for a period of 3 years before the intervention and 1 year after.ResultsThere were no significant differences between test and control patients at baseline. Test patients were monitored for an average of 276 days with 75% of patients monitored for more than 6 months. Test patients 1 year after the start of their intervention showed a 46.3% reduction in rate of predicted medical expenditure, a 25.5% reduction in the rate of predicted pharmaceutical expenditure, a 53.2% reduction in the rate of predicted unscheduled admission to hospital, a 67.9% reduction in the predicted rate of LOS when admitted to hospital, and a reduction in mortality of between 41.3% and 44.5% relative to control patients. Control patients did not demonstrate any significant change in their predicted trajectory for any of the above variables.ConclusionsAt-home telemonitoring of chronically ill patients showed a statistically robust positive impact increasing over time on health care expenditure, number of admissions to hospital, and LOS as well as a reduction in mortality.Trial registrationRetrospectively registered with the Australian and New Zealand Clinical Trial Registry ACTRN12613000635763; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=364030 (Archived by WebCite at http://www.webcitation.org/6sxqjkJHW).

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Survival after PICU admission: The impact of multiple admissions and complex chronic conditions.

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Survival after PICU admission: The impact of multiple admissions and complex chronic conditions.

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