Literature DB >> 28705790

Children with life-limiting conditions in paediatric intensive care units: a national cohort, data linkage study.

Lorna K Fraser1, Roger Parslow2.   

Abstract

OBJECTIVE: To determine how many children are admitted to paediatric intensive care unit (PICU) with life-limiting conditions (LLCs) and their outcomes.
DESIGN: National cohort, data-linkage study.
SETTING: PICUs in England. PATIENTS: Children admitted to a UK PICU (1 January 2004 and 31 March 2015) were identified in the Paediatric Intensive Care Audit Network dataset. Linkage to hospital episodes statistics enabled identification of children with a LLC using an International Classification of Diseases (ICD10) code list. MAIN OUTCOME MEASURES: Random-effects logistic regression was undertaken to assess risk of death in PICU. Flexible parametric survival modelling was used to assess survival in the year after discharge.
RESULTS: Overall, 57.6% (n=89 127) of PICU admissions and 72.90% (n=4821) of deaths in PICU were for an individual with a LLC.The crude mortality rate in PICU was 5.4% for those with a LLC and 2.7% of those without a LLC. In the fully adjusted model, children with a LLC were 75% more likely than those without a LLC to die in PICU (OR 1.75 (95% CI 1.64 to 1.87)).Although overall survival to 1 year postdischarge was 96%, children with a LLC were 2.5 times more likely to die in that year than children without a LLC (OR 2.59 (95% CI 2.47 to 2.71)).
CONCLUSIONS: Children with a LLC accounted for a large proportion of the PICU population. There is an opportunity to integrate specialist paediatric palliative care services with paediatric critical care to enable choice around place of care for these children and families. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Entities:  

Keywords:  Child; Life-Limiting Conditions; PICU; Palliative Care; Survival

Mesh:

Year:  2017        PMID: 28705790      PMCID: PMC5965357          DOI: 10.1136/archdischild-2017-312638

Source DB:  PubMed          Journal:  Arch Dis Child        ISSN: 0003-9888            Impact factor:   3.791


The prevalence of children and young people with life-limiting conditions (LLCs) or life-threatening conditions is rising. Overall mortality in paediatric intensive care unit (PICU) is decreasing. Children with a LLC accounted for the majority of admissions, bed-days and deaths in PICU. Children with a LLC were75% more likely to die in PICU than those without a LLC. There was 93% survival at 1 year for children with a LLC.

Introduction

Life-limiting conditions (LLCs) are those for which there is no reasonable hope of cure and from which children will ultimately die, for example, Duchenne muscular dystrophy or neurodegenerative disease. Life-threatening conditions (LTCs) are those for which curative treatment may be feasible but can fail, for example, cancer. LLC will be used to include life-limiting conditions and LTCs. The prevalence of children and young people with a LLC is increasing1 partly due to more aggressive treatment of complications and the use of medical technologies, including paediatric intensive care unit (PICU). These children often have repeated hospital admissions2 and use increasing amounts of hospital resources.3–5 Many of these children also die on PICU6 when treatment fails or is withdrawn. This study aims to ascertain what proportion of admissions to PICUs are for children with a LLC and their outcomes in PICU and up to 1 year postdischarge.

Methods

Datasets

The Paediatric Intensive Care Audit Network (PICANet) collects data on all children admitted to PICUs in the UK and Ireland. All admissions to a PICU in the UK between 1 January 2004 and 31 March 2015 were identified in the PICANet dataset.7 Only children resident in England were included as only their inpatient hospital data (Hospital Episodes Statistics (HES)) were available for linkage.8 Hospital data for the other nations of the UK were not available. The Office for National Statistics (ONS) death record data in England were available with a censor date of 1 November 2015.9 Linkage of the PICANet dataset to the HES and ONS data was undertaken by the NHS Digital.10 The standard deterministic linkage algorithm using National Health Service (NHS) number, date of birth, sex and postcode was used.

Clinical variables

Inpatient HES data

The PICANet data are of high quality and validated, but some of the non-mandatory fields, including comorbidities, are incomplete. Therefore, it is not possible to identify children with a LLC using the PICANet dataset alone. Linkage to the inpatient HES data (1 April 1997 to 31 March 2015) enabled the use of a previously developed International Classification of Diseases (ICD10) coding framework1 to identify individuals with a LLC (see online supplementary table 1). A PICU admission was categorised with a LLC if one of the LLC codes were recorded within the HES data for that individual before the date of PICU discharge. For the analyses for survival in the year after PICU discharge, LLC codes up to the censor date were included.

PICANet data

Clinical diagnoses were coded using clinical terms 3 and aggregated into 12 primary diagnostic groups.11 Risk adjustment for mortality used the log odds of mortality based on the Paediatric Index of Mortality 2 (PIM2) with recalibrated coefficients calculated using data from 2011 to 2013.12 PIM2 was categorised into five categories of risk: <1%, 1 to <5%, 5% to <15%, 15% to <30% and 30%+. Length of stay was categorised into <1, 1 to <3, 3 to <7, 7 to <14, 14 to <28 and ≥28 days. The total number of bed-days for each individual was calculated for all their PICU admissions. The number of PICU admissions were categorised as single admission, two admissions, three admissions and four or more admissions. The type of admission was defined as planned after surgery, unplanned after surgery, planned other and unplanned.

ONS death data

Date of death was obtained from the ONS data.9

Sociodemographic variables

Age at admission to PICU was categorised as <1, 1–4, 5–10, 11–15 and ≥16 years. Sex was included in the analysis only where it was non-ambiguous. An Index of Multiple Deprivation13 category was assigned to each individual based on their lower super output area (LSOA) of residence. An LSOA is a census geographical area built up of output areas with population of 1000–3000 per LSOA.14 Ethnicity is poorly recorded in all the datasets; therefore, ethnicity was determined using two name analysis programmes which classified children as South Asian (Pakistani, Indian, Bangladeshi): Nam Pehchan15 16 and the South Asian Names and Group Recognition Algorithm.17 The results were corrected manually for known misclassification errors.18 Ethnicity was assessed as South Asian or not, as the South Asian population are the largest minority ethnic group in the UK.19

Statistical analyses

Descriptive statistics were undertaken, and differences between groups were assessed by χ2 or t-test. Random-effects logistic regression was undertaken to account for inter-PICU variation in the outcome, death in PICU. Variables were included via a forced entry method and retained if p<0.05 or if they improved the model fit assessed using the Bayesian information criterion (BIC). Flexible parametric survival modelling was undertaken to assess survival in the year after discharge from PICU rather than traditional Cox regression as the proportional hazards assumption was violated.20 Data from the last PICU admission for each individual discharged alive from PICU were included. Analyses were carried out using STATA V.13, and tests of statistical significance were at p≤0.05.

Ethics approval

Collection of personally identifiable data has been approved by the Patient Information Advisory Group (now the Health Research Authority Confidentiality Advisory Group), and ethics approval was granted by the Trent Medical Research Ethics Committee (ref. 05/MRE04/17 +5).

Results

Cohort and linkage

Nearly 200 000 PICU admissions occurred in the UK in the study period. After excluding non-English residents and those with poor-quality demographic data (denoting missing NHS number and date of birth which are required for linkage), data for 103 374 individuals were sent for linkage. Linkage was successful for 102 722 individuals (99%) who had 154 667 PICU admissions (figure 1).
Figure 1

Study flowchart. HES, Hospital Episodes Statistics; LLC, life-limiting condition; PICU, paediatric intensive care unit.

Study flowchart. HES, Hospital Episodes Statistics; LLC, life-limiting condition; PICU, paediatric intensive care unit. There were no significant differences between those who linked and those in whom linkage was not successful by sex, ethnicity, PIM2 score or length of PICU stay (see online supplementary table 2). Some significant differences were found; linkage improved from 98.0% in 2004 to 99.4% in 2015 (χ2=365, p<0.001), fewer >16-year-olds linked compared with the <1-year-olds (98.9% vs 99.3%) and children with more PICU admissions were more likely to be linked than those with a single admission (99.5% vs 98.9%, χ2=120, p<0.001).

Descriptive statistics

Overall, 57.6% (n=89 127) of PICU admissions were for an individual with a LLC (table 1). Excluding 2015 data which in only part year, the percentage of admissions to PICU for those with a LLC has increased from 51.8% to 61.0%. There was a U-shaped association with age with 58.5% of the <1-year-olds admitted to PICU having a LLC, 50.2% of the children aged 11- to 15 years and 65.4% of the >16-year-olds. More of the admissions from children with a South Asian background had a LLC compared with non-South Asians (62.9% vs 56.9% χ2=233, p<0.001).
Table 1

Descriptive statistics of PICU admissions by LLC status (with row %)

TotalLLC%No LLC%Χ2 p Value
Number154 66789 12757.665 54042.4
Age category556<0.001
 <1 year72 17042 23258.529 93841.5
 1–4 years39 57123 09758.416 47441.6
 5–10 years20 44811 98258.6846641.4
 11–15 years19 003954250.2946149.8
 16+3467226765.4120034.6
 Missing871
Sex3.10.21
 Male87 68650 42257.537 26442.5
 Female66 93338 68257.828 25142.2
 Missing482325
Ethnicity233<0.001
 Non-South Asian1 36 67077 80456.958 86643.1
 South Asian17 99711 32362.9667437.1
Deprivation category74.7<0.001
 Category 1 (least deprived)21 42112 10156.5932043.5
 Category 221 81612 57357.6924342.4
 Category 326 34115 43758.610 90441.4
 Category 434 49819 93557.814 56342.2
 Category 5 (most deprived)49 53828 36157.321 17742.7
 Missing1053720333
Diagnostic group (reason for PICU admission)1300<0.001
 Neurological17 270815447.2911652.8
 Cardiac44 76732 46572.512 30227.5
 Respiratory42 23021 68751.420 54348.6
 Oncology5190466389.852710.2
 Infection8014346843.3454656.7
 Musculoskeletal5736319255.6254444.4
 Gastrointestinal10 019524552.4477447.6
 Other8140455455.9358644.1
 Blood and lymph145675752.069948.0
 Trauma45814058.8417691.2
 Endocrine/metabolic3878213155.0174745.0
 Multisystem42740294.1255.9
 Body wall and cavities2959200467.780832.3
Risk of mortality (PIM2)2001<0.001
 <1%48 95725 58352.323 37447.7
 1% to <5%74 21242 40357.131 80942.9
 5% to <15%24 72716 26165.8846634.2
 15% to <30%4270332177.894922.2
 >30%2501155962.394237.7
LOS PICU (days)5600<0.001
 <145 24622 42049.622 82650.4
 1 to <349 28526 57953.922 70646.1
 3 to <734 12220 38159.713 74140.3
 7 to <1415 95711 34271.1461528.9
 14 to <286603540181.8120218.2
 28+3412298687.542612.5
 Missing421842.92457.1
Type of PICU admission3600<0.001
 Planned, after surgery49 74933 03466.416 71533.6
 Unplanned, after surgery7688398551.8370348.2
 Planned other10 900755169.3334930.7
 Unplanned86 05044 41251.641 63848.4
 Not known280145135
Year of PICU admission574<0.001
 200412 293636651.8592748.2
 200512 326653153.0579547.0
 200612 634711656.3551843.7
 200713 275749256.4578343.6
 200813 462746355.4599944.6
 200914 023799457.0602943.0
 201014 185834158.8584441.2
 201114 006828259.1572440.9
 201214 597890461.0569339.0
 201314 865912661.4573938.6
 201414 973913761.0583639.0
 20154028237559.0165341.0

LLC, life-limiting condition; LOS, length of stay; PICU, paediatric intensive care unit; PIM2, Paediatric Index of Mortality 2.

Descriptive statistics of PICU admissions by LLC status (with row %) LLC, life-limiting condition; LOS, length of stay; PICU, paediatric intensive care unit; PIM2, Paediatric Index of Mortality 2. Differences between the two groups existed for the clinical variables with 94.1% of those children whose reason for PICU admission was multisystem having a LLC compared with only 8.8% of trauma cases and 43.3% of infective cases (χ2=1300, p<0.001). The risk of mortality scores varied by LLC status with 52.3% of those with a PIM2 score <1% having a LLC, 77.8% of those with a PIM2 score of 15% to <30% and 62.3% of those with a PIM2 score of >30% (χ2=2300, p<0.001). A linear association with length of PICU stay was shown with 49.6% of those with a PICU stay of <1 day and 87.5% of those staying in PICU >28 days having a LLC (χ2=6000, p<0.001). The median length of stay was 2.6 days (IQR 1.0–6.1) for those with a LLC compared with 1.6 days (IQR 0.8–3.5) for those without a LLC. The total number of PICU bed days for this cohort was 763 664; children with a LLC accounted for 72.6% (554 404). More than 66% of the planned PICU admissions after surgery were for children with a LLC compared with 51.6% of unplanned PICU admissions (χ2=3600, p<0.001).

Deaths

A total of 11 588 children had died at the censor date, with 6612 deaths occurring in PICU. Children with a LLC accounted for 72.9% (n=4821) of PICU deaths and 87.4% (n=4397) of deaths after discharge. The crude PICU mortality rate was 5.4% for those with a LLC and 2.7% for those without a LLC.

Death in PICU

The unadjusted risk of death in PICU for children with a LLC was nearly twice that of those without a LLC (OR 1.94 (95% CI 1.84 to 2.06)). After adjusting for expected risk of mortality and other clinical and demographic variables, children with a LLC were 75% more likely than those without a LLC to die in PICU (OR 1.75 (95% CI 1.64 to 1.87)) (table 2).
Table 2

Random-effects logistic regression model for death in PICU

OR95% CIsp Value
LLC
 NoRef
 Yes1.751.641.87<0.001
Age category
 <1 yearRef
 1–4 years0.810.750.87<0.001
 5–10 years0.940.861.030.20
 11–15 years1.060.961.160.26
 16+1.371.131.66<0.001
Sex
 MaleRef
 Female1.091.031.150.002
Ethnicity
 Non-South AsianRef
 South Asian1.301.201.41<0.001
Deprivation category
 Category 1 (least deprived)Ref
 Category 21.020.911.130.77
 Category 31.030.921.140.64
 Category 41.070.971.180.18
 Category 5 (most deprived)1.070.971.170.17
Diagnostic group (reason for PICU admission)
 Neurological1.391.261.54<0.001
 Cardiac1.231.131.350.001
 RespiratoryRef
 Oncology2.061.752.42<0.001
 Infection1.941.742.17<0.001
 Musculoskeletal0.740.550.990.04
 Gastrointestinal1.391.221.58<0.001
 Other1.261.101.45<0.001
 Blood and lymph2.321.862.91<0.001
 Trauma1.691.432.01<0.001
 Endocrine/metabolic2.181.902.50<0.001
 Multisystem0.670.331.380.28
 Body wall and cavities0.970.761.220.78
Risk of mortality (PIM2)
 <1%Ref
 1% to <5%4.543.915.28<0.001
 5% to <15%12.4610.6514.57<0.001
 15% to <30%32.5627.4438.64<0.001
 >30%201.63169.60239.70<0.001
LOS PICU (days)
 <11.511.391.63<0.001
 1 to <3Ref
 3 to <70.860.790.940.001
 7 to <141.090.991.200.07
 14 to <282.021.812.24<0.001
 >283.983.534.47<0.001
Type of PICU admission
 Planned, after surgeryRef
 Unplanned, after surgery1.201.011.420.04
 Planned other1.321.141.52<0.001
 Unplanned1.531.381.70<0.001
 Not known1.350.632.880.44
Year of admission0.970.960.98<0.001

n=153 513, group=35, Wald χ2=10 213, BIC=40 229, sigma_u=0.30, rho=0.03.

BIC, Bayesian information criterion; LLC, life-limiting condition; LOS, length of stay; PICU, paediatric intensive care unit; PIM2, Paediatric Index of Mortality 2.

Random-effects logistic regression model for death in PICU n=153 513, group=35, Wald χ2=10 213, BIC=40 229, sigma_u=0.30, rho=0.03. BIC, Bayesian information criterion; LLC, life-limiting condition; LOS, length of stay; PICU, paediatric intensive care unit; PIM2, Paediatric Index of Mortality 2. Stratified analyses by LLC status highlighted some differences between the main variables associated with a higher risk of death in PICU (see online supplementary table 3a and b). For those with a LLC, being older than age 16 years (OR 1.37 (95% CI 1.12 to 1.67)) and of South Asian origin (OR 1.30 (95% CI 1.20 to 1.41)) had a higher risk of death. This was not seen for those without a LLC. The diagnoses with highest risk of death in PICU were blood and lymph (OR 2.54 (95% CI 1.98 to 3.25)) or endocrine/metabolic (OR 2.38 (95% CI 2.05 to 2.76)) for those with a LLC compared with trauma (OR 2.37 (95% CI 1.84 to 3.00)) or neurological conditions (OR 2.19 (95% CI 1.79 to 2.69)) for those without a LLC. The risk of death was highest for stays longer than 7 days in those with a LLC but not until 14 days for those without a LLC. The odds of dying in PICU decreased by 3% each year (OR 0.98 (95% CI 0.97 to 0.99)).

Survival after discharge from PICU

Overall survival rate is >96% at 1 year after PICU (figure 2A). There are differences between these survival functions for children with (figure 2B) and without a LLC (figure 2C). There is a steeper curve in the first 3 months after discharge from PICU for those with a LLC with approximately 93% still alive at 1 year postdischarge. For those without a LLC, the survival curve is much flatter, and >99% are alive at 1 year post-PICU discharge.
Figure 2

Survival curves with 95% CIs. LLC, life-limiting condition; PICU, paediatric intensive care unit.

Survival curves with 95% CIs. LLC, life-limiting condition; PICU, paediatric intensive care unit. A log normal distribution model with 5 df provided the best fit assessed using BIC (table 3). There are some similarities to the death in PICU model: children with a LLC (OR 2.59 (95% CI 2.47 to 2.71)), those from a South Asian background (OR 1.19 (95% CI 1.13 to 1.25)) and those from the most deprived category (OR 1.08 (95% CI 1.02 to 1.14) were more likely to die in the year after discharge from PICU than children without a LLC, non-South Asian and those in the least deprived areas, respectively. All other types of PICU admission had significantly higher odds of death compared with the planned after surgery group and the odds of dying after discharge decreased by 3% with each increasing year of admission (OR 0.97 (95% CI 0.96 to 0.98)). Compared with the reference group of respiratory reasons for PICU admission, those with an oncology (OR 1.83 (95% CI 1.70 to 1.97)) or neurology diagnoses (OR 1.17 (95% CI 1.11 to 1.24)) were more likely to die in the year after discharge from PICU. Those with trauma (OR 0.63 (95% CI 0.53 to 0.77)) or body wall and cavities (OR 0.63 (95% CI 0.54 to 0.72)) diagnoses were significantly less likely to die in the year after discharge from PICU.
Table 3

Results of flexible parametric survival modelling for survival to 365 days after discharge from PICU

HR95% CIsp Value
Age category
 <1 yearRef
 1–4 years0.830.800.87<0.001
 5–10 years0.770.730.82<0.001
 11–15 years0.850.800.90<0.001
 16+0.980.891.090.72
Sex
 MaleRef
 Female1.020.991.060.23
Ethnicity
 Non-South AsianRef
 South Asian1.191.131.25<0.001
Deprivation category
 Category 1 (least deprived)Ref
 Category 20.990.921.050.66
 Category 31.030.961.090.41
 Category 41.061.001.130.04
 Category 5 (most deprived)1.081.021.140.01
LLC
 NoRef
 Yes2.592.472.71<0.001
Diagnostic group (reason for PICU admission)
 Neurological1.171.111.24<0.001
 Cardiac0.860.810.90<0.001
 RespiratoryRef
 Oncology1.831.701.97<0.001
 Infection0.870.800.940.001
 Musculoskeletal0.910.811.030.152
 Gastrointestinal1.040.971.120.276
 Other1.040.961.130.339
 Blood and lymph0.980.821.170.79
 Trauma0.630.530.77<0.001
 Endocrine/metabolic1.080.981.200.117
 Multisystem0.970.701.330.831
 Body wall and cavities0.630.540.72<0.001
Risk of mortality (PIM2)
 <1%Ref
 1% to <5%1.281.221.35<0.001
 5% to <15%1.551.451.64<0.001
 15% to <30%2.071.882.28<0.001
 >30%2.462.122.85<0.001
LOS PICU (days)
 <11.141.081.19<0.001
 1 to <3Ref
 3 to <71.061.011.120.01
 7 to <141.291.221.37<0.001
 14 to <281.581.471.71<0.001
 >281.751.571.95<0.001
Type of PICU admission
 Planned, after surgeryRef
 Unplanned, after surgery1.221.121.33<0.001
 Planned other1.651.541.78<0.001
 Unplanned1.371.291.44<0.001
 Not known1.170.761.780.48
Year of admission0.970.960.98<0.001

n=91 614.

HR, hazard ratio; LLC, life-limiting condition; LOS, length of stay; PICU, paediatric intensive care unit; PIM2, Paediatric Index of Mortality 2.

Results of flexible parametric survival modelling for survival to 365 days after discharge from PICU n=91 614. HR, hazard ratio; LLC, life-limiting condition; LOS, length of stay; PICU, paediatric intensive care unit; PIM2, Paediatric Index of Mortality 2. In contrast to the in-PICU death models, all those aged 1–15 years were significantly less likely to die than the <1 age group.

Discussion

Children with a LLC accounted for nearly 58% of all admissions to PICU, 72% of PICU bed-days and 87.5% of all PICU admissions that lasted >28 days. Although the mortality rate continues to decrease in PICU, 73% of all deaths in PICU during this study were in children with a LLC. The survival in the year after PICU discharge was also significantly lower in children with a LLC compared with those without a LLC. The high number and percentage of PICU admissions for children with a LLC is similar to results from a US study in which children with complex chronic conditions (CCCs) accounted for 53% (range 22.4%–70.6%) of PICU admissions.21 The definitions used to identify the populations with CCCs were different to the LLC definition used in the current study. A multicountry prevalence study found that 67% of children had a CCC or disability within PICU or neonatal intensive care unit.22 Previous work has found that children with a CCC had an increased risk of prolonged length of PICU stay (>15 days)21 and children who died in PICU have longer lengths of stay before death.23 This study has shown that the risk of death in PICU is significantly higher for those with a LLC who have been in PICU for longer than 7 days. The higher PICU crude death rate for children with a LLC is not unexpected and confirms the patterns seen in the US study where they found in-PICU mortality of 3.9% for those with a CCC compared with 2.2% for children with no chronic condition and 0.3% for those with non-CCCs.21 However, death in a child with a LLC may be expected, and admissions to PICU are known to be stressful24–27 and parents and siblings of children who died in hospital show more psychological symptoms28 and poorer adjustment29 than if their child had died at home. If the child is likely to die despite PICU admission, then an alternative place of care such as being cared for at home or in a hospice by specialist paediatric palliative care may be more appropriate. Guidance from The European Association of Palliative Care30 and the International Children’s Palliative Care Network31 both state that the family home should, where possible, be the main place of care and that these families should have access to paediatric palliative care services. With in-PICU mortality falling to low levels, it is important that other in-/post-PICU outcomes such as quality of life or functional status are assessed, especially for this group of children with high-care needs. Although the vast majority of children survived their PICU admission, nearly 7% of those with a LLC will die in the year after discharge from PICU with many of these deaths occurring in the first 3 months. PICU staff are highly experienced at caring for a dying child and their family, but given the expansion of specialist paediatric palliative care services and the children’s hospice sector over the last decade, further integration of these services may offer the family more choice over place of care or death for their child and can often offer longer term input, both when the child has died and in the bereavement period than is possible from a PICU.

Strengths/limitations

This is the first national study providing data on survival following PICU admission in this population of children, and it used linked audit, administrative and hospital data. Identification of children with a LLC in this dataset was via the HES data. This is an administrative dataset in which the coding has improved over time, but its primary aim is not as a research dataset. Lack of agreement on definitions of some complex conditions has been shown previously.32 Having complete data for comorbidities in the PICANet dataset, which is audited for quality, would be preferable.

Conclusions

Children with a LLC accounted for nearly 58% of admissions to PICU, 72% of bed-days, 87.5% of stays greater than 28 days and 73% of deaths in PICU. There is an opportunity, given the recent growth in specialist paediatric palliative care services, to have integration of these services to enable choice around place of care and place of death for these children and families. Future studies collecting high-quality information on changes in functional status and quality of life are vital to further gauge the clinical value of these PICU admissions.
  20 in total

1.  Flexible parametric joint modelling of longitudinal and survival data.

Authors:  Michael J Crowther; Keith R Abrams; Paul C Lambert
Journal:  Stat Med       Date:  2012-10-04       Impact factor: 2.373

2.  How children die: classifying child deaths.

Authors:  G A Pearson; M Ward-Platt; D Kelly
Journal:  Arch Dis Child       Date:  2010-07-23       Impact factor: 3.791

3.  Rising national prevalence of life-limiting conditions in children in England.

Authors:  Lorna K Fraser; Michael Miller; Richard Hain; Paul Norman; Jan Aldridge; Patricia A McKinney; Roger C Parslow
Journal:  Pediatrics       Date:  2012-03-12       Impact factor: 7.124

4.  Characteristics of deaths occurring in hospitalised children: changing trends.

Authors:  Padmanabhan Ramnarayan; Finella Craig; Andy Petros; Christine Pierce
Journal:  J Med Ethics       Date:  2007-05       Impact factor: 2.903

5.  Epidemiology of critically ill children in England and Wales: incidence, mortality, deprivation and ethnicity.

Authors:  R C Parslow; R C Tasker; E S Draper; G J Parry; S Jones; T Chater; K Thiru; P A McKinney
Journal:  Arch Dis Child       Date:  2008-12-23       Impact factor: 3.791

6.  The impact on parents of a child's admission to intensive care: integration of qualitative findings from a cross-sectional study.

Authors:  Gillian Colville; Janet Darkins; Janet Hesketh; Virginia Bennett; John Alcock; Jane Noyes
Journal:  Intensive Crit Care Nurs       Date:  2008-11-18       Impact factor: 3.072

7.  Chronic conditions among children admitted to U.S. pediatric intensive care units: their prevalence and impact on risk for mortality and prolonged length of stay*.

Authors:  Jeffrey D Edwards; Amy J Houtrow; Eduard E Vasilevskis; Roberta S Rehm; Barry P Markovitz; Robert J Graham; R Adams Dudley
Journal:  Crit Care Med       Date:  2012-07       Impact factor: 7.598

8.  Children with chronic conditions in pediatric intensive care units located in predominantly French-speaking regions: Prevalence and implications on rehabilitation care need and utilization.

Authors:  Robin Cremer; Francis Leclerc; Jacques Lacroix; Dominique Ploin
Journal:  Crit Care Med       Date:  2009-04       Impact factor: 7.598

9.  Patterns and costs of health care use of children with medical complexity.

Authors:  Eyal Cohen; Jay G Berry; Ximena Camacho; Geoff Anderson; Walter Wodchis; Astrid Guttmann
Journal:  Pediatrics       Date:  2012-11-26       Impact factor: 7.124

10.  Family-centred care and traumatic symptoms in parents of children admitted to PICU.

Authors:  Jesper Mortensen; Birgitte Olesen Simonsen; Sara Bek Eriksen; Pernille Skovby; Rolf Dall; Ask Elklit
Journal:  Scand J Caring Sci       Date:  2014-09-18
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  20 in total

1.  Doing more of less: what registry data tell us about death in PICU.

Authors:  Thomas Brick; Roger C Parslow
Journal:  Intensive Care Med       Date:  2019-08-16       Impact factor: 17.440

Review 2.  Pediatric palliative care in the intensive care unit and questions of quality: a review of the determinants and mechanisms of high-quality palliative care in the pediatric intensive care unit (PICU).

Authors:  Sara Rhodes Short; Rachel Thienprayoon
Journal:  Transl Pediatr       Date:  2018-10

3.  Epidemiology of childhood death in Australian and New Zealand intensive care units.

Authors:  Katie M Moynihan; Peta M A Alexander; Luregn J Schlapbach; Johnny Millar; Stephen Jacobe; Hari Ravindranathan; Elizabeth J Croston; Steven J Staffa; Jeffrey P Burns; Ben Gelbart
Journal:  Intensive Care Med       Date:  2019-07-03       Impact factor: 17.440

Review 4.  Is this as good as it gets? Implications of an asymptotic mortality decline and approaching the nadir in pediatric intensive care.

Authors:  Katie M Moynihan; Efrat Lelkes; Raman Krishna Kumar; Danielle D DeCourcey
Journal:  Eur J Pediatr       Date:  2021-10-01       Impact factor: 3.183

Review 5.  Palliative and Critical Care: Their Convergence in the Pediatric Intensive Care Unit.

Authors:  Siti Nur Hanim Buang; Sin Wee Loh; Yee Hui Mok; Jan Hau Lee; Yoke Hwee Chan
Journal:  Front Pediatr       Date:  2022-06-10       Impact factor: 3.569

6.  Prospective paediatric intensive care registry in Latvia: one year outcomes.

Authors:  Ivars Veģeris; Iveta Daukšte; Arta Bārzdiņa; Roger C Parslow; Reinis Balmaks
Journal:  Acta Med Litu       Date:  2019

Review 7.  Palliative Care for Children in Hospital: Essential Roles.

Authors:  Ross Drake
Journal:  Children (Basel)       Date:  2018-02-19

8.  Delivering Pediatric Palliative Care: From Denial, Palliphobia, Pallilalia to Palliactive.

Authors:  Stefan J Friedrichsdorf; Eduardo Bruera
Journal:  Children (Basel)       Date:  2018-08-31

9.  Exploring the experiences of parent caregivers of children with chronic medical complexity during pediatric intensive care unit hospitalization: an interpretive descriptive study.

Authors:  Janet E Rennick; Isabelle St-Sauveur; Alyssa M Knox; Margaret Ruddy
Journal:  BMC Pediatr       Date:  2019-08-06       Impact factor: 2.125

10.  Comorbidity patterns and socioeconomic inequalities in children under 15 with medical complexity: a population-based study.

Authors:  Neus Carrilero; Albert Dalmau-Bueno; Anna García-Altés
Journal:  BMC Pediatr       Date:  2020-07-30       Impact factor: 2.567

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