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. Author manuscript; available in PMC: 2022 Jan 1.
Published in final edited form as: Pediatr Crit Care Med. 2021 Jan 1;22(1):27–39. doi: 10.1097/PCC.0000000000002590

Long-Term Outcome of PICU Patients Discharged with New, Functional Status Morbidity

Murray M Pollack 1, Russell Banks 2, Richard Holubkov 3, Kathleen L Meert 4; Eunice Kennedy Shriver National Institute of Child Health and Human Development Collaborative Pediatric Critical Care Research Network
PMCID: PMC7790876  NIHMSID: NIHMS1619747  PMID: 33027242

Abstract

Objective:

To determine the long-term (>6 months) functional status of PICU patients with significant new functional morbidities at hospital discharge.

Design:

Longitudinal cohort followed-up using structured chart reviews of electronic health records.

Setting:

Electronic health records of former PICU patients at seven sites.

Patients:

Randomly selected patients from the TOPICC study discharged from the hospital with new functional status morbidity who had sufficient electronic health record data to determine functional status.

Interventions:

None.

Measurements and Main Results:

Long-term functional status was measured with the Functional Status Scale (FSS) and categorized by comparison to hospital discharge FSS. Improvement or new morbidity was based on a change in FSS of ≥ 2 in a single domain. Overall, 56% (n=71) improved, 15% (n=19) did not change, 9% (n=11) developed a new morbidity, and 21% (n=26) died. The shortest median follow-up time from PICU discharge was 1.4 years for those who died and the longest was 4.0 years for those improved. Functional status at baseline (pre-acute illness) was different among the outcome groups with those that improved having the highest incidence of baseline normal status or only mild dysfunction. Of the long-term survivors with improvement, 82% (n = 58) improved to normal status or mild dysfunction, 11% (n = 8) improved to moderate dysfunction, and 7% (n = 5) improved to severe dysfunction. Trauma patients improved and cancer patients died more frequently than other diagnoses. The long-term outcome groups were not associated with hospital discharge functional status.

Conclusions:

A majority of PICU survivors discharged with significant new functional morbidity with follow-up after 6 or more months improved, many to normal status or only mild dysfunction, while 29% died or developed new morbidity. Of the long-term survivors, 70% had significant improvement after a median follow-up time of 4.0 years.

Keywords: mortality, morbidity, pediatric critical care, pediatrics, outcomes, long-term outcome, follow-up

Tweet:

Long-term outcome of children discharged with significant functional status morbidity after PICU care is better than expected.

INTRODUCTION

Critical illness is often a life-altering event for surviving children and their families.1,2 Children may leave the hospital with significant physical and cognitive dysfunction that persists, potentially for their lifetime, deteriorates, or improves.3–7 Population studies of pediatric intensive care unit (PICU) survivors with follow-up times of 6 months and longer indicate that the incidence of morbidities persists and may even increase.8–11 One prospective single site study found that the incidence of morbidities and deaths increased by approximately 200% after 3 years.10 While there are long-term numerous outcome studies focused on patients with specific diseases or conditions who were cared for, in part, in the PICU,12–18 there are no long term outcome studies focused on PICU survivors leaving the hospital with significant morbidities that developed during their hospitalization. Some have suggested that the declining PICU mortalities are being replaced with morbidities because significant new morbidity rates currently approximately twice the mortality rates in contemporary studies.19,20

The increasing incidence of morbidities associated with PICU illness renders the long-term outcome of these morbidities important in evaluating the consequences of PICU care. What happens to these PICU survivors discharged with new significant dysfunction? Do they improve, stabilize, get worse, or die? The primary aim of this study was to determine the long-term functional status of PICU patients discharged with significant new functional morbidities that developed during their hospitalization. Secondary aims included the association of the long-term functional status changes with a) the baseline functional status prior to the PICU illness, b) the characteristics of the PICU illness, and c) the pathophysiological etiologies of the morbidities responsible for the morbidity.

METHODS

The data for this analysis originated in the Trichotomous Outcome Prediction in Critical Care (TOPICC) study of 7 funded sties, one being composed of two institutions.. Data collection methods and institutional characteristics have been previously described.21 In brief, general medical and cardiac-cardiovascular PICU patients aged from newborn to less than 18 years were randomly selected and stratified by hospital from December 4, 2011 to April 7, 2013. Only the first PICU admission during a hospitalization was included.

Eligible patients at each clinical site were randomized by the data coordinating center and reviewed in the randomization sequence until 25 or more patients per site were evaluated. For this analysis, the first inclusion criterion consisted of the presence of significant new functional status morbidity on hospital discharge and random selection for structured chart review. New functional status morbidity was defined by the Functional Status Scale (FSS) score22 with an increase of at least 2 in a single domain from pre-illness baseline assuring that the decrement in function was clinically substantial.23 A previous definition of a significant functional status change was a total FSS change of 3 or more. Since 95% of those patients had an increase of at least 2 in a single domain,20 we adopted that simpler and more conservative definition for this analysis since the data was being obtained by a different method. In addition, the CPCCRN steering committee determined a comprehensive set of pathophysiological processes for use in characterizing the causes of morbidity.23,24

The second inclusion criterion was our ability to confirm the hospital discharge FSS and determine a FSS at least 6 months following hospital discharge from the electronic health record. The details and assessment of the structured chart review have been published.25 The last date of follow-up was September 1, 2016, allowing for over 3 years of follow-up data from the latest enrollments in the TOPICC study. Six months was chosen at a minimum follow-up time because other follow-up studies have determined the recovery plateau begins at this time.11,26 Reviewers used all available outpatient and hospitalization electronic records. The longest follow-up period in the electronic record was used for functional status determination. If a single follow-up encounter had insufficient information to determine the FSS, we used other care encounters within 2 months of the longest follow-up but all sources needed to have a follow-up period of at least 6 months. If the longest follow-up was a hospitalization, the pre-hospitalization functional status determined from the admission data was used. Data collected from this review included survival or death, the FSS status by domain, date(s) of the medical care episode(s) utilized for the FSS determination, and care location(s) for the medical episode(s) utilized for the assessment of the FSS (hospitalization, emergency department visit, general outpatient care, and specialty care). Overall functional status was categorized by FSS scores as normal or mild (FSS 6-8), moderate dysfunction (FSS 9 – 13), severe dysfunction (FSS 14 – 20), and very severe dysfunction (FSS > 20).27

Outcome groups were categorized as died, new morbidity, no change, or improved. New morbidity was defined as an increase of 2 or more in a single FSS domain from hospital discharge and improvement was defined as a decrease of 2 or more in a single domain. Other data from the PICU admission included age, ethnicity, race, payer, system of primary dysfunction, diagnostic risk categories used in the updated PRISM score,28 PICU type (medical/surgical, cardiac), length of PICU and hospital stays, baseline (pre-illness) and hospital discharge FSS for the TOPICC admission, and use of selected ICU therapies. The process for assignment of cardiac diagnoses has been described.29

The index hospitalization and follow-up data were summarized using counts and percentages for categorical variables and the median and interquartile range (IQR) for continuous variables. Associations with hospitalization data and long-term FSS status were investigated using Fisher’s exact test for categorical variables with few classifications while larger tables employ a Monte Carlo approximation. The Kruskal-Wallis test was used to evaluate associations for continuous variables. All analyses were performed using SAS 9.4 (SAS Institute; Cary, NC). Our statistical approach to this analysis was that of a “hypothesis-generating” study of a small cohort. Due to the small subgroup sizes and multiple comparisons, observations and statistical analyses are intended to inform future studies rather than provide definitive conclusions. Consistent with this approach, two-sided p-values are reported at the 0.05 level for all comparisons without adjustment for multiple comparisons.

RESULTS

A total of 127 patients met inclusion criteria for analysis (Figure 1). Of the 10,078 TOPICC study patients, 327 met review criteria and 292 had hospital discharge FSS scores confirmed during the structured review process. Of these patients, 117 died during the TOPICC hospitalization and 48 of the 175 patients with morbidities did not have adequate follow-up documentation in the EHR leaving a sample of 127 patients (Table 1). The median age at ICU admission for this sample was 2.4 years, 47% (n = 59) were Caucasian and 28% (n = 36) were African-American, and 57% (n = 72) of the cohort had government insurance while 38% (n = 48) had commercial insurance. A total of 83% (n = 105) were cared in medical/surgical PICUs and 17% (n = 22) were cared for in cardiac PICUs. The most common physiological systems of primary dysfunction requiring PICU admission were respiratory (37%, n = 47), neurologic (27%, n = 34), and cardiovascular (22%, n = 28). Cancer (acute or chronic) was present in 14% (n = 18), traumatic illness in 12% (n = 15), and congenital heart disease in 24% (n = 30). Therapeutic interventions during their PICU admission included mechanical ventilation (72%, n = 91), neuromuscular blockade (52%, n = 66), and vasoactive agent infusions (40%, n = 51) while ECMO, renal replacement therapies, and cardiopulmonary resuscitation for cardiac arrest all occurred in less than 7% each. The median FSS on hospital admission was 6 (IQR 6, 8), and the median FSS on hospital discharge was 12 (IQR 9, 15). Median PICU and hospital lengths of stay were 13.0 (IQR 3.9, 28.9) days and 27.9 (IQR 16.8, 52.4) days, respectively. There were no differences between the groups with known and unknown follow-up status except those with unknown follow-up status had a higher PRISM score for the neurological variables (Table 1).

Figure 1.

Figure 1.

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Flowchart of Patient Selection.

Table 1.

Patient Characteristics of New Hospital Morbidities With and Without Long-Term Follow-up.

Characteristic Follow-up Status
Known Unknown P-value
(N = 127) (N = 48)
Age at PICU Admission (years) 2.4 [0.4, 10.0] 3.1 [0.6, 9.5] 0.7141
Ethnicity 0.6162
 Hispanic or Latino 21 (17%) 7 (15%)
 Not Hispanic or Latino 92 (72%) 33 (69%)
 Unknown or not reported 14 (11%) 8 (17%)
Race 0.2162
 American Indian or Alaska Native 0 (0%) 2 (4%)
 Asian 4 (3%) 1 (2%)
 Black or African American 36 (28%) 11 (23%)
 White 59 (47%) 27 (56%)
 Multiracial 1 (1%) 0 (0%)
 Unknown or not reported 27 (21%) 7 (15%)
Payer 0.0972
 Commercial 48 (38%) 20 (42%)
 Government 72 (57%) 21 (44%)
 Other 7 (6%) 7 (15%)
System of Primary Dysfunction 0.2202
 Respiratory 47 (37%) 10 (21%)
 Cardiovascular disease 28 (22%) 14 (29%)
 Neurologic 34 (27%) 16 (33%)
 Miscellaneous 18 (14%) 8 (17%)
ICU Diagnostic Risk Category3 0.0972
 Low risk (DKA, hematologic, musculoskeletal, renal) 1 (1%) 4 (8%)
 Cardiac/Respiratory 75 (59%) 24 (50%)
 Cancer 8 (6%) 2 (4%)
 Neurologic 34 (27%) 16 (33%)
 Other miscellaneous 9 (7%) 2 (4%)
Primary or Secondary Diagnosis of Trauma 15 (12%) 10 (21%) 0.1482
Acute or Chronic Cancer Diagnosis 18 (14%) 4 (8%) 0.4442
Congenital Heart Disease 30 (24%) 12 (25%) 0.8452
Functional Status
 Baseline FSS score 6.[6, 8] 6 [6, 8] 0.7141
 Hospital discharge FSS 12 [9, 15] 12 [10, 15] 0.6191
PRISM Score 3 [0, 10] 4 [0, 8] 0.6301
 PRISM neurological 0 [0, 0] 0 [0, 5. 0.0371
 PRISM non-neurological 3 [0, 7] 2.0 [0, 7] 0.9361
PICU Length of Stay 13.0 [3.9, 28.9] 12.3 [6.6, 31.6] 0.6491
Hospital Length of Stay 27.9 [16.8, 52.4] 25.4 [13.5, 55.0] 0.2631
Therapies
 Mechanical ventilation 91 (72%) 40 (83%) 0.1232
 Vasoactive infusions 51 (40%) 25 (52%) 0.1742
 Neuromuscular blockade 66 (52%) 28 (58%) 0.4992
 Extracorporeal support (ECMO or VAD) 6 (5%) 2 (4%) 1.0002
 Renal replacement therapy (hemofiltration or dialysis) 8 (6%) 3 (6%) 1.0002
 Cardiac Arrest 6 (5%) 2 (4%) 1.0002
PICU type 0.8272
 Cardiac 22 (17%) 13 (21%)
 Medical/Surgical/Other 105 (83%) 48 (79%)
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1

Kruskal-Wallis test.

2

Fisher’s exact test (Monte Carlo approximation for tables larger than 2X2).

3

Reference 23.

Overall, 56% (n=71) improved, 15% (n=19) did not change their functional status category, 9% (n=11) developed a new morbidity, and 21% (n=13) died (Table 2). The FSS trajectories for individual patients for each outcome category are shown in Supplemental Digital Content 1–5 (Supplemental Figures 2a–2e). The follow-up period from PICU discharge to the final medical episode differed among the outcome groups (p<.001). Those who improved were followed for the longest time period (median 4.0 years) and those that died were followed for the shortest (0.6 years). The ages at the time of outcome determination significantly differed (p = 0.009) with the youngest patients in the group that died and the oldest in the group that did not improve. The most common care location for the follow-up status assessment was a specialty clinic for all groups except those who died where the most common care situation was as a hospital inpatient. Other characteristics including race, payer, ICU type, admission PRISM scores, and diagnostic distributions did not differ among the outcome groups.

Table 2.

Long-Term Outcomes.

Characteristic Follow-up Functional Status
No Change
(N = 19, 15.0%)		 Improved
(N = 71, 55.9%)		 New Morbidity
(N = 11, 8.7%)		 Death
(N = 26, 20.5%)		 P-value
Follow-up Data
 ICU discharge to last medical episode (years)
 (median, 25th, 75th percentiles)		 2.9 [0.8, 4.8] 4.0 [2.9, 4.5] 3.0 [2.5, 3.7] 0.6 [0.1, 1.6] <0.0011
 Type of last medical episode (n (%)) <0.0012
  Emergency department visit 1 (5%) 8 (11%) 0 (0%) 1 (4%)
  General outpatient care 3 (16%) 11 (16%) 4 (36%) 1 (4%)
  Hospitalization 4 (21%) 8 (11%) 1 (9%) 16 (62%)
  Specialty outpatient care 11 (58%) 43 (61%) 5 (46%) 5 (19%)
  Unknown 0 (0%) 1 (1%) 1 (9%) 3 (12%)
 Age at last medical episode (median, 25th, 75th percentiles) 7.3 [4.6, 16.6] 6.7 [4.7, 13.4] 6.5 [2.8, 13.1] 3.7 [0.7, 8.1] 0.0091
Descriptive Data (n (%))
 Gender: Female 10 (53%) 36 (51%) 6 (55%) 8 (31%) 0.2982
 Race 0.8002
  Asian 0 (0%) 4 (6%) 0 (0%) 0 (0%)
  Black of African American 5 (26%) 20 (28%) 4 (36%) 7 (27%)
  White 8 (42%) 34 (48%) 3 (27%) 14 (54%)
  Multiracial 0 (0%) 1 (1%) 0 (0%) 0 (0%)
  Unknown or not reported 6 (32%) 12 (17%) 4 (36%) 5 (19%)
 Payer 0.2422
  Commercial 7 (37%) 28 (39%) 1 (9.%) 12 (46%)
  Government 12 (63%) 38 (54%) 10 (91%) 12 (46%)
  Other 0 (0%) 5 (7.0%) 0 (0%) 2 (8%)
Data From Index Hospitalization
 PICU type (n (%)) 0.5592
  Cardiac 3 (16%) 11 (16%) 1 (9%) 7 (27%)
  Medical/Surgical/Other 16 (84%) 60 (85%) 10 (91%) 19 (73%)
 PICU length of stay (days) (median, 25th, 75th percentiles) 17.8 [2.9, 38.3] 12.7 [3.9, 25.8] 9.5 [5.0, 20.7] 12.1 [3.2, 33.1] 0.6621
 Cardiac arrest prior to PICU admission (n (%)) 1 (5%) 4 (6%) 0 (0%) 1 (4%) 1.0002
 Cardiac arrest (n (%)) 2 (10%) 2 (3%) 0 (0%) 2 (8%) 0.2762
 Admission source (n (%)) 0.5282
  Admitted for postoperative care 4 (21%) 11 (16%) 3 (27%) 7 (27%)
  Inpatient unit from same hospital 6 (32%) 13 (18%) 1 (9%) 7 (27%)
  Direct admission from outside of the study hospital 4 (21%) 18 (25%) 4 (36%) 3 (12%)
   Study hospital emergency department 5 (26%) 29 (41%) 3 (27%) 9 (35%)
 PICU admission status (n (%)) 0.8912
  Elective 4 (21%) 12 (17%) 2 (18%) 6 (23%)
  Emergency 15 (79%) 59 (83%) 9 (82%) 20 (7%)
  PRISM Score (median, 25th, 75th percentiles) 7 [0, 13] 3 [0, 7] 6 [0, 11.0 3.0 [0.0, 8.0] 0.2571
  PRISM neurological 0 [0, 5] 0 [0. 0] 0 [0, 5] 0 [0, 0] 0.1031
  PRISM non-neurological 3 [0, 12] 2.0 [0, 6] 4 [0, 7] 3 [0, 7] 0.6541
 Hospital Discharge FSS Total (n (%)) 0.4102
  Moderate dysfunction 13 (68%) 49 (69%) 4 (36%) 17 (65%)
  Severe dysfunction 4 (21%) 16 (23%) 6 (55%) 6 (23%)
  Very severe dysfunction 2 (11%) 6 (8.9%) 1 (9%) 3 (12%)
 Baseline FSS Score Category (n (%)) 0.0542
  Normal and mild dysfunction (6-8) 13 (68%) 62 (87%) 6 (55%) 19 (73%)
  Moderate dysfunction (9-13) 5 (26%) 7 (10%) 3 (27%) 5 (19%)
  Severe dysfunction (14-20) 1 (5%) 2 (3%) 2 (18%) 2 (8%)
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1

Kruskal-Wallis test.

2

Fisher’s exact test (Monte Carlo approximation)

The diagnostic etiologies for the illnesses requiring PICU care in the outcome groups are shown in Table 3. The incidences of both cancer and trauma differed among the outcome groups. The highest incidence of cancer occurred in those who died (39%, p = 0.002) and the highest incidence of trauma occurred in those who improved (18%) and those with new morbidities (18%, p = 0.013). These diagnostic labels are consistent with the pathophysiological etiologies of the morbidities (Supplemental Digital Content 1: Table 1). Notably, there was no evidence that long-term outcome was associated with congenital heart disease including single or double ventricle physiology, acquired heart disease, or physiological system of dysfunction requiring ICU care.

Table 3.

Diagnoses and Long-Term Outcomes.

Characteristic Long-Term Functional Status
No Change
(N = 19)		 Improved
(N = 71)		 New Morbidity
(N = 11)		 Death
(N = 26)		 P-value
 Primary Diagnosis Category 0.1441
  Respiratory 9 (47%) 24 (34%) 5 (46%) 9 (35%)
  Cardiovascular disease 3 (16%) 14 (20%) 1 (9%) 10 (39%)
  Neurologic 5 (26%) 22 (31%) 5 (46%) 2 (8%)
  Miscellaneous 2 (11%) 11 (16%) 0 (0%) 5 (19%)
 Diagnosis Risk Category 0.2201
  Low risk (DKA, hematologic, musculoskeletal, renal) 0 (0%) 1 (1%) 0 (0%) 0 (0%)
  Cardio/Respiratory 12 (63%) 38 (54%) 6 (55%) 19 (73%)
  Cancer 1 (5%) 3 (4%) 0 (0%) 4 (15%)
  Neurologic 5 (26%) 22 (31%) 5 (46%) 2 (8%)
  Other miscellaneous 1 (5%) 7 (10%) 0 (0%) 1 (4%)
 Primary or Secondary Diagnosis of Trauma 0 (0%) 13 (18%) 2 (18%) 0 (0%) 0.0131
 Acute or Chronic Cancer Diagnosis 1 (5%) 7 (10%) 0 (0%) 10 (39%) 0.0021
 Congenital Heart Disease 4 (21%) 15 (21%) 2 (18%) 9 (35%) 0.5531
 Single or Double Outlet Ventricle 0.4961
  Two ventricles 17 (90%) 64 (90%) 10 (91%) 20 (77%)
  Double outlet ventricle 1 (5%) 4 (6%) 1 (9%) 2 (8%)
  Single ventricle 1 (5%) 3 (4%) 0 (0%) 4 (15%)
 Acquired Heart Disease 2 (11%) 3 (4%) 1 (9%) 2 (8%) 0.5381
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1

Fisher’s exact test (Monte Carlo approximation).

Functional status at baseline (pre-acute illness) was different among the outcome groups (Table 2, p = 0.054). Those who improved had the highest incidence of normal functional status or mild dysfunction at baseline (87%, n = 62), those with a new follow-up morbidity had the highest incidence of moderate or severe dysfunction (46%, n = 5), and those without change or death had intermediate incidences of moderate or severe dysfunction, 32% (n = 6) and 27% (n = 7), respectively. Unlike the relationship of long-term outcome to baseline functional status, the long-term outcome groups were not associated with hospital discharge functional status.

The relationship of changed long-term functional status to hospital discharge functional status is shown in Table 4. Of those who improved, 82% (n = 58) improved to normal status or mild dysfunction, 11% (n = 8) improved to moderate dysfunction, and 7% (n = 5) improved to severe dysfunction. Of those who improved to normal or mild dysfunction, 81% (n = 47) were discharged from the hospital with moderate dysfunction. Of those who improved to moderate dysfunction, only 25% (n = 2) were discharged from the hospital with moderate dysfunction. Of those who improved to severe dysfunction, 60% (n = 3) were discharged with very severe dysfunction. Overall, of the 71 who improved, 45% (n = 32) improved in more than one domain. The domain improvements were feeding (66%, n = 47), motor (47%, n = 33), respiratory (23%, n = 16), mental status (20%, n = 14), communication (13%, n = 9), and sensory (9%, n = 6). Only 36% (n = 4) of those developing new morbidity were discharged with moderate dysfunction. In general, the worst performing FSS domains in the 101 long-term survivors were motor and feeding and the best performing FSS domains were mental and sensory (Supplemental Digital Content 2: Table 2).

Table 4.

Association of Long-Term Functional Status Changes with Hospital Discharge Functional Status.

Hospital Discharge FSS Improved Long Term Outcome
Normal/Mild
(N = 58)		 Moderate
(N = 8)		 Severe
(N = 5)		 Very severe
(N = 0)		 Overall
(N = 71)
Hospital Discharge FSS
 Moderate dysfunction 47 (81%) 2 (25%) 0 (0%) 0 (0%) 49 (69%)
 Severe dysfunction 9 (16%) 5 (63%) 2 (40%) 0 (0%) 16 (23%)
 Very severe dysfunction 2 (3%) 1 (13%) 3 (60%) 0 (0%) 6 (9%)
New Morbidity Long Term Outcome
Normal/Mild
(N = 0)		 Moderate
(N = 2)		 Severe
(N = 4)		 Very severe
(N = 5)		 Overall
(N = 11)
Hospital Discharge FSS
 Moderate dysfunction 0 (0%) 2 (100%) 2 (50%) 0 (0%) 4 (36%)
 Severe dysfunction 0 (0%) 0 (0%) 2 (50%) 4 (80%) 6 (55%)
 Very severe dysfunction 0 (0%) 0 (0%) 0 (0%) 1 (20%) 1 (9%)
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DISCUSSION

This study is the first multi-center, long-term follow-up of PICU children focused on those discharged from the hospital with new functional status morbidity. Overall, 56% improved, 15% did not change, 9% developed a new morbidity, and 21% died. The shortest median follow-up time was 1.4 years for those who died and the longest was 4.0 years for those who improved. Patient characteristics except age at follow-up, and the diagnoses of trauma and cancer did not differ among the long-term outcome groups. Notably, long-term outcome was not associated with hospital discharge functional status.

Remarkably, 70% of the survivors had significant improvement after a median follow-up time of 4.0 years. Of these, 82% improved to normal or mild dysfunction, 11% improved to moderate dysfunction, and 7% improved to severe dysfunction. There was little to distinguish these patients from the other outcome groups except that their baseline functional status was more frequently normal or mildly dysfunctional and they tended to be patients with traumatic illness. Those improving to normal or mild dysfunction were most likely to be discharged from the hospital with moderate dysfunction rather than severe or very severe dysfunction.

A total of 29% of all patients died or developed worsening functional status at long-term follow-up. For those who developed a new morbidity at long-term follow-up, 82% were severely or very severely dysfunctional. Those who died had the highest incidence of cancer and many of their deaths were likely associated with this underlying condition.

Our study population contrasts with most long-term follow-up PICU studies that focused on general survivor cohorts or relatively small samples of patients with specific diagnoses, or those who received specific therapies.15,30–38 The earliest published study on long term outcome of a general intensive care cohort of children published in 1990 evaluated 976 discharges 3 years after admission. Overall, 80% of children survived and, using a relatively simple qualitative assessment method, 91% of survivors were felt likely to lead an independent life.9 Recently, Ong et al. reviewed the follow-up functional outcome literature for general intensive care cohorts. 39 Rates of acquired functional impairment ranged from 10% to 36% at hospital discharge and 10% to 13% after more than 2 years. Several relatively recent general cohort studies with follow-up periods of at least 6 months have had notably pessimistic results. Utilizing a Health Utilities Index in the United Kingdom, Jones et al. found that only 27.3% were in full health, 5.5% had impairment in all outcome domains and the mortality rate was 11.1.8 A recent 3 year longitudinal follow-up study of PICU survivors from a single site using the FSS found that morbidity and mortality increased by approximately 200%.10

Some limitations to this study are common to PICU follow-up studies and may account for many of the differences between this study and others. A significant limitation is the failure to distinguish between long-term outcome secondary to underlying disease, a complication of the acute illness, or a complication of intensive care. A detailed review of PICU children discharged with morbidity including these cases indicates that aspects of the chronic disease, acute disease, and acute care and PICU care therapies account for hospital discharge morbidity.24 A second substantial limitation to this and similar studies is the inability to directly compare long term outcome studies because the follow-up assessment methods are sufficiently different. For example, pediatric methods suitable for follow-up of relatively large samples have been based on diverse conceptual frameworks including the Glasgow Outcome Scale, adaptive behavior, activities of daily living and health related quality of life.40–43 Finally, a general limitation applicable to all studies is their inability to account for the full spectrum of issues relevant to patients and families following critical illness. This framework recently recognized as the pediatric post intensive care syndrome (PICS-peds) is still evolving. It recognizes that issues concerning the families of survivors are also important and has expanded the outcome framework to include physical health, cognitive health, emotional health, and social health in a developmental and family-centered context.1,2

Several limitations are specific to this study. First, while this study was designed to maximize generalizability, the study sites were all academic PICUs in a research network that might have relatively unique patient populations or follow-up care practices. Second, while this cohort of new-morbidity patients is one of the most substantial examined to date, it is nevertheless of modest size and the lack of statistically significant differences between outcome groups could be a consequence of inadequate power. As a hypothesis-generating study, the findings are intended to inform future studies rather than provide definitive conclusions.

Third, we were not able to assess the impact of rehabilitation services on the long-term outcome.

CONCLUSION

Morbidity following pediatric intensive care occurs frequently and appears to be increasing as mortality decreases. In our study of a comparatively large sample of patients discharged from the hospital with new functional status morbidity, a majority improved, many to normal status or only mild dysfunction, while 29% died or developed new morbidity Of the long-term survivors, 70% had significant improvement after a median follow-up time of 4.0 years.

Supplementary Material

Supplemental Data File (.doc, .tif, pdf, etc.)_1

Supplemental Digital Content 1: Figure 2a. FSS Trajectories for All Patients (n = 127).

Supplemental Data File (.doc, .tif, pdf, etc.)_2

Supplemental Digital Content 2: Figure 2b. FSS Trajectories for Improving Patients (n = 71).

Supplemental Data File (.doc, .tif, pdf, etc.)_3

Supplemental Digital Content 3: Figure 2c. FSS Trajectories for No Change Patients (n = 19).

Supplemental Data File (.doc, .tif, pdf, etc.)_4

Supplemental Digital Content 4: Figure 2d. FSS Trajectories for New Morbidity Patients (n = 11).

Supplemental Data File (.doc, .tif, pdf, etc.)_5

Supplemental Digital Content 5: Figure 2e. FSS Trajectories for Deaths (n = 26).

Supplemental Data File (.doc, .tif, pdf, etc.)_6
Supplemental Data File (.doc, .tif, pdf, etc.)_7

Acknowledgments

Funding Source: Supported, in part, by the following cooperative agreements from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Department of Health and Human Services: U10HD050096, U10HD049981, U10HD049983, U10HD050012, U10HD063108, U10HD063114 and U01HD049934. UG1HD083171, UG1HD083166, and UG1HD083170.

Copyright form disclosure: Drs. Pollack, Carcillo, and Priestley’s institutions received funding from the National Institutes of Child Health and Human Development. Drs. Pollack, Banks, Holubkov, Meert, Bolton, Carcillo, Newth, Priestley, and Siems received support for article research from the National Institutes of Health (NIH). Drs. Banks, Holubkov, Meert, and Siems’ institutions received funding from the NIH. Dr. Holubkov received funding from Pfizer (DSMB), Revance (DSMB), Physicians Committee for Responsible Medicine (Biostatistical consulting), Medimmune (DSMB), and DURECT Corporation (biostatistical consulting). Dr. Newth received funding from Philips Research North America and Hamilton Medical. The remaining authors have disclosed that they do not have any potential conflicts of interest.

Authors from the Eunice Kennedy Shriver National Institute of Child Health and Human Development Collaborative Pediatric Critical Care Research Network.

(alphabetical order)

  • Christian Bauerfeld, MD; Department of Pediatrics, Children’s Hospital of Michigan, Wayne State University, Detroit, MI

  • Melissa M. Bolton, MBA; Department of Pediatrics, University of Utah School of Medicine, Salt Lake City, UT

  • Yonca Bulut, MD; Department of Pediatrics, UCLA Mattel Children’s Hospital, University of California, Los Angeles, CA

  • Joseph Carcillo, MD; Department of Critical Care Medicine, Children’s Hospital of Pittsburgh, Pittsburgh, PA

  • Eleanor Gradidge, MD; Phoenix Children’s Hospital, Phoenix, AZ

  • Christopher J. L. Newth, MD, FRCPC; Department of Anesthesiology and Critical Care Medicine, Children’s Hospital Los Angeles, University of Southern California Keck School of Medicine, Los Angeles, CA

  • Margaret A. Priestley, MD; Department of Anesthesiology and Critical Care , Children’s Hospital of Philadelphia, Philadelphia, PA

  • Ashley Siems, MD; Department of Pediatrics, Children’s National Hospital and the George Washington University School of Medicine and Health Sciences, Washington DC

Contributor Information

Murray M. Pollack, Department of Pediatrics, Children’s National Hospital and the George Washington University School of Medicine and Health Sciences, Washington DC.

Russell Banks, Department of Pediatrics, University of Utah School of Medicine, Salt Lake City, UT.

Richard Holubkov, Department of Pediatrics, University of Utah School of Medicine, Salt Lake City, UT.

Kathleen L. Meert, Department of Pediatrics, Children’s Hospital of Michigan, Detroit, MI.

REFERENCES

  • 1.Watson RS, Choong K, Colville G, et al. Life after Critical Illness in Children-Toward an Understanding of Pediatric Post-intensive Care Syndrome. The Journal of pediatrics. 2018;198:16–24. [DOI] [PubMed] [Google Scholar]
  • 2.Manning JC, Pinto NP, Rennick JE, Colville G, Curley MAQ. Conceptualizing Post Intensive Care Syndrome in Children-The PICS-p Framework. Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies. 2018;19(4):298–300. [DOI] [PubMed] [Google Scholar]
  • 3.Hordijk J, Verbruggen S, Vanhorebeek I, et al. Health-related quality of life of children and their parents 6 months after children’s critical illness. Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation. 2019. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Killien EY, Farris RWD, Watson RS, Dervan LA, Zimmerman JJ. Health-Related Quality of Life Among Survivors of Pediatric Sepsis. Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies. 2019;20(6):501–509. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Watson RS, Asaro LA, Hertzog JH, et al. Long-Term Outcomes after Protocolized Sedation versus Usual Care in Ventilated Pediatric Patients. American journal of respiratory and critical care medicine. 2018;197(11):1457–1467. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Choong K, Fraser D, Al-Harbi S, et al. Functional Recovery in Critically Ill Children, the “WeeCover” Multicenter Study. Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies. 2018;19(2):145–154. [DOI] [PubMed] [Google Scholar]
  • 7.Heneghan JA, Pollack MM. Morbidity: Changing the Outcome Paradigm for Pediatric Critical Care. Pediatric clinics of North America. 2017;64(5):1147–1165. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Jones S, Rantell K, Stevens K, et al. Outcome at 6 months after admission for pediatric intensive care: a report of a national study of pediatric intensive care units in the United kingdom. Pediatrics. 2006;118(5):2101–2108. [DOI] [PubMed] [Google Scholar]
  • 9.Butt W, Shann F, Tibballs J, et al. Long-term outcome of children after intensive care. Critical care medicine. 1990;18(9):961–965. [DOI] [PubMed] [Google Scholar]
  • 10.Pinto NP, Rhinesmith EW, Kim TY, Ladner PH, Pollack MM. Long-Term Function After Pediatric Critical Illness: Results From the Survivor Outcomes Study. Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies. 2017;18(3):e122–e130. [DOI] [PubMed] [Google Scholar]
  • 11.Fiser DH, Long N, Roberson PK, Hefley G, Zolten K, Brodie-Fowler M. Relationship of pediatric overall performance category and pediatric cerebral performance category scores at pediatric intensive care unit discharge with outcome measures collected at hospital discharge and 1- and 6-month follow-up assessments. Critical care medicine. 2000;28(7):2616–2620. [DOI] [PubMed] [Google Scholar]
  • 12.Downing TE, Allen KY, Glatz AC, et al. Long-term survival after the Fontan operation: Twenty years of experience at a single center. The Journal of thoracic and cardiovascular surgery. 2017;154(1):243–253.e242. [DOI] [PubMed] [Google Scholar]
  • 13.Overman AE, Liu M, Kurachek SC, et al. Tracheostomy for infants requiring prolonged mechanical ventilation: 10 years’ experience. Pediatrics. 2013;131(5):e1491–1496. [DOI] [PubMed] [Google Scholar]
  • 14.Rao S, Elkon B, Flett KB, et al. Long-Term Outcomes and Risk Factors Associated With Acute Encephalitis in Children. Journal of the Pediatric Infectious Diseases Society. 2017;6(1):20–27. [DOI] [PubMed] [Google Scholar]
  • 15.Buysse CM, Vermunt LC, Raat H, et al. Surviving meningococcal septic shock in childhood: long-term overall outcome and the effect on health-related quality of life. Critical care (London, England). 2010;14(3):R124. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Slovis JC, Gupta N, Li NY, Kernie SG, Miles DK. Assessment of Recovery Following Pediatric Traumatic Brain Injury. Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies. 2018;19(4):353–360. [DOI] [PubMed] [Google Scholar]
  • 17.Namachivayam SP, d’Udekem Y, Millar J, Cheung MM, Butt W. Survival status and functional outcome of children who required prolonged intensive care after cardiac surgery. The Journal of thoracic and cardiovascular surgery. 2016;152(4):1104–1112.e1103. [DOI] [PubMed] [Google Scholar]
  • 18.Zimmerman JJ, Banks R, Berg RA, et al. . Trajectory of Mortality and Health-Related Quality of Life Morbidity Following Community-Acquired Pediatric Septic Shock. . Crit Care Med 2020;48(3):319–328. 2020. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Namachivayam P, Shann F, Shekerdemian L, et al. Three decades of pediatric intensive care: Who was admitted, what happened in intensive care, and what happened afterward. Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies. 2010;11(5):549–555. [DOI] [PubMed] [Google Scholar]
  • 20.Pollack MM, Holubkov R, Funai T, et al. Pediatric intensive care outcomes: development of new morbidities during pediatric critical care. Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies. 2014;15(9):821–827. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Pollack MM, Holubkov R, Funai T, et al. Simultaneous Prediction of New Morbidity, Mortality, and Survival Without New Morbidity From Pediatric Intensive Care: A New Paradigm for Outcomes Assessment. Critical care medicine. 2015;43(8):1699–1709. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Pollack MM, Holubkov R, Glass P, et al. Functional Status Scale: new pediatric outcome measure. Pediatrics. 2009;124(1):e18–28. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Pollack MM BR, Holubkov R, Mauerfield C, Beyda D, Berg RA, Bolton MA, Bulut Y, Burd RS, Carcillo J, Dean JM, Gradidge E, Hall MW, Mourani PM, Newth CJL, Notterman DA, Priestley MA, Siems A, Wessle DL, Yates AR, Meert KL. Morbidity and Mortality in Critically Ill Children. I. Pathophysiologies and Potential Therapeutic Solutions. Critical care medicine. 2020;accepted. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Meert KL BR, Holubkov R, Bauerfield C, Beyda D, Berg RA, Bolton MM, Bolut Y, Burd RS, Carcillo J, Dean JM, Gradidge E, McQuillen PS, Murani PM, Newth CJL, Notterman DA, Priestley MA, Sapru A, Yates AR, Pollack MM. Morbidity and Mortality in Critically Ill Children. II. A Qualitative Patient-Level Analysis of Pathophysiologies and Potential Therapeutic Solutions. Critical care medicine. 2020;accepted. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Siems A, Banks R, Holubkov R, et al. Structured Chart Review: Assessment of a Structured Chart Review Methodology. Hospital pediatrics. 2020;10(1):61–69. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Winthrop AL, Brasel KJ, Stahovic L, Paulson J, Schneeberger B, Kuhn EM. Quality of life and functional outcome after pediatric trauma. The Journal of trauma. 2005;58(3):468–473; discussion 473-464. [DOI] [PubMed] [Google Scholar]
  • 27.Pollack MM, Holubkov R, Funai T, et al. Relationship between the functional status scale and the pediatric overall performance category and pediatric cerebral performance category scales. JAMA pediatrics. 2014;168(7):671–676. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Pollack MM, Holubkov R, Funai T, et al. The Pediatric Risk of Mortality Score: Update 2015. Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies. 2016;17(1):2–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Berger JT, Holubkov R, Reeder R, et al. Morbidity and mortality prediction in pediatric heart surgery: Physiological profiles and surgical complexity. J Thorac Cardiovasc Surg. 2017;154(2):620–628.e626. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.van Zellem L, Utens EM, Legerstee JS, et al. Cardiac Arrest in Children: Long-Term Health Status and Health-Related Quality of Life. Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies. 2015;16(8):693–702. [DOI] [PubMed] [Google Scholar]
  • 31.Smith S, Butt W, Best D, MacLaren G. Long-term survival after extracorporeal life support in children with neutropenic sepsis. Intensive care medicine. 2016;42(5):942–943. [DOI] [PubMed] [Google Scholar]
  • 32.Martinelli J, Habes D, Majed L, et al. Long-term outcome of liver transplantation in childhood: A study of 20-year survivors. American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons. 2018;18(7):1680–1689. [DOI] [PubMed] [Google Scholar]
  • 33.Ward SL, Turpin A, Spicer AC, Treadwell MJ, Church GD, Flori HR. Long-Term Pulmonary Function and Quality of Life in Children After Acute Respiratory Distress Syndrome: A Feasibility Investigation. Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies. 2017;18(1):e48–e55. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Joffe AR, Lequier L, Robertson CM. Pediatric outcomes after extracorporeal membrane oxygenation for cardiac disease and for cardiac arrest: a review. ASAIO journal (American Society for Artificial Internal Organs : 1992). 2012;58(4):297–310. [DOI] [PubMed] [Google Scholar]
  • 35.Reynolds JC, Hartley T, Michiels EA, Quan L. Long-Term Survival After Drowning-Related Cardiac Arrest. The Journal of emergency medicine. 2019;57(2):129–139. [DOI] [PubMed] [Google Scholar]
  • 36.Faber J, Wilde EA, Hanten G, et al. Ten-year outcome of early childhood traumatic brain injury: Diffusion tensor imaging of the ventral striatum in relation to executive functioning. Brain injury. 2016;30(13-14):1635–1641. [DOI] [PubMed] [Google Scholar]
  • 37.Treble-Barna A, Zang H, Zhang N, Taylor HG, Yeates KO, Wade S. Long-Term Neuropsychological Profiles and Their Role as Mediators of Adaptive Functioning after Traumatic Brain Injury in Early Childhood. Journal of neurotrauma. 2017;34(2):353–362. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Kumar SR, Kung G, Noh N, et al. Single-Ventricle Outcomes After Neonatal Palliation of Severe Ebstein Anomaly With Modified Starnes Procedure. Circulation. 2016;134(17):1257–1264. [DOI] [PubMed] [Google Scholar]
  • 39.Ong C, Lee JH, Leow MK, Puthucheary ZA. Functional Outcomes and Physical Impairments in Pediatric Critical Care Survivors: A Scoping Review. Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies. 2016;17(5):e247–259. [DOI] [PubMed] [Google Scholar]
  • 40.Beers SR, Wisniewski SR, Garcia-Filion P, et al. Validity of a pediatric version of the Glasgow Outcome Scale-Extended. Journal of neurotrauma. 2012;29(6):1126–1139. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Farmer C, Adedipe D, Bal VH, Chlebowski C, Thurm A. Concordance of the Vineland Adaptive Behavior Scales, second and third editions. Journal of intellectual disability research : JIDR. 2020;64(1):18–26. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.van der Linde BW, van Netten JJ, Otten E, Postema K, Geuze RH, Schoemaker MM. A systematic review of instruments for assessment of capacity in activities of daily living in children with developmental co-ordination disorder. Child: care, health and development. 2015;41(1):23–34. [DOI] [PubMed] [Google Scholar]
  • 43.Varni JW, Seid M, Knight TS, Uzark K, Szer IS. The PedsQL 4.0 Generic Core Scales: sensitivity, responsiveness, and impact on clinical decision-making. Journal of behavioral medicine. 2002;25(2):175–193. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplemental Data File (.doc, .tif, pdf, etc.)_1

Supplemental Digital Content 1: Figure 2a. FSS Trajectories for All Patients (n = 127).

NIHMS1619747-supplement-Supplemental_Data_File___doc___tif__pdf__etc___1.pdf (398.5KB, pdf)
Supplemental Data File (.doc, .tif, pdf, etc.)_2

Supplemental Digital Content 2: Figure 2b. FSS Trajectories for Improving Patients (n = 71).

NIHMS1619747-supplement-Supplemental_Data_File___doc___tif__pdf__etc___2.pdf (256.1KB, pdf)
Supplemental Data File (.doc, .tif, pdf, etc.)_3

Supplemental Digital Content 3: Figure 2c. FSS Trajectories for No Change Patients (n = 19).

NIHMS1619747-supplement-Supplemental_Data_File___doc___tif__pdf__etc___3.pdf (67.5KB, pdf)
Supplemental Data File (.doc, .tif, pdf, etc.)_4

Supplemental Digital Content 4: Figure 2d. FSS Trajectories for New Morbidity Patients (n = 11).

NIHMS1619747-supplement-Supplemental_Data_File___doc___tif__pdf__etc___4.pdf (64.9KB, pdf)
Supplemental Data File (.doc, .tif, pdf, etc.)_5

Supplemental Digital Content 5: Figure 2e. FSS Trajectories for Deaths (n = 26).

NIHMS1619747-supplement-Supplemental_Data_File___doc___tif__pdf__etc___5.pdf (95.4KB, pdf)
Supplemental Data File (.doc, .tif, pdf, etc.)_6
NIHMS1619747-supplement-Supplemental_Data_File___doc___tif__pdf__etc___6.docx (25.6KB, docx)
Supplemental Data File (.doc, .tif, pdf, etc.)_7
NIHMS1619747-supplement-Supplemental_Data_File___doc___tif__pdf__etc___7.docx (25.4KB, docx)

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