Relation between the time of the transport team in reaching the bedside of children and the 30-day mortality rate after admission
Highlight box
Key findings
• There was no correlation between the arrival time of the transport team at the bedside and the prognosis of the children in the less developed areas of central China.
What is known and what is new?
• European specialists in pediatrics reported that under their transport mode, the arrival time does not affect the prognosis of children.
• There are currently no studies on the prognosis of pediatric transport in China, especially no national unified quality control standards related to transport. This study referred to relevant Pediatric Intensive Care Society standards. The transport situation of children in Anhui Province was analyzed.
What is the implication, and what should change now?
• Our transport time was not associated with the prognosis of the children. In the future, there will be more long-distance transport, and we can also try to transport the patients.
Introduction
With the update of medical equipment and the continuous improvement of treatment level, critically ill children can get better treatment. Nonetheless, due to the uneven distribution of medical resources, in particular the relatively weak treatment level of critically ill patients in primary hospitals, it is of crucial importance to transport critically ill children from primary hospitals (1). According to the census data released by the statistical bureau of Anhui Province in 2021, the number of children aged <14 years in this Anhui province has reached 11 million, accounting for about 20% of the total population. Anhui Children’s Hospital, which is the only pediatric tertiary specialty hospital in the Anhui province, has been undertaking most of the treatment tasks for critically ill children in the Anhui province. To improve the treatment of critically ill children, we took the lead in establishing an intensive care transport team in 2013 to undertake the task of transporting critically ill children in the province. Our transport team consists of an attending physician and a lead nurse in the intensive care unit (ICU). Meanwhile, our transport mode is a ground ambulance equipped with ventilators, infusion pumps, defibrillators, and electrocardiogram (ECG) monitors. In 2013, neonatologists released the Guidelines for Neonatal Transport in China, but the mode and function of pediatric intensive care transport are not yet unified in China (2). According to the National Quality Standards of the Pediatric Intensive Care Society (PICS), our transport team should reach the bedside of the pediatric patient within 3 h after agreement to accept the pediatric intensive care transport request (3). In the International Benchmarking Initiatives (4,5), a similar target is also adopted as a quality control index. It may be necessary for the critically ill children to obtain treatment from the transport team, and some research suggests that providing early and high-quality critical diagnosis and treatment can improve the prognosis of children with sepsis and head injury (6,7). A study in England and Wales reported that under their transport mode, the arrival time does not affect the prognosis of children (8). With reference to related research, this study aimed to analyze the effect of the time taken by the transport team in our center to reach the bedside of children on the prognosis of children after transport request has been received. We present this article in accordance with the STROBE reporting checklist (available at https://tp.amegroups.com/article/view/10.21037/tp-24-164/rc).
Methods
The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by ethics board of Anhui Children’s Hospital (No. EYLL-2024-041). Individual consent for this retrospective analysis was waived. Altogether, data on 307 critically ill children aged <16 years receiving long-distance transport from Anhui Children’s Hospital between March 2020 and February 2022 were collected. After excluding children with unavailable data on the time taken by the transport team to reach their bedside (n=6) and those with unavailable data regarding ventilation at the time of transfer (n=3), a total of 298 critically ill patients were included into this study. With reference to the PICS quality control standards, the time taken by the transport team to reach the bedside of children after receiving a transport request should be within 3 min. Combined with the specific distance, a short-range trip was generally reached within 1 h, a medium-long-range trip was fulfilled within 3 h, while some distant area was reached after 3 h. Correspondingly, the children were divided into three groups: the ≤60, >60 to ≤180, and >180 min groups (Table 1). The cases collected in this study were retrospectively analyzed in terms of their general data and clinical data. All the transported children had severe dysfunction in one, two, or three systems including the respiratory, circulatory, or nervous systems. The patient critical rating was determined using the Transport Pediatric Early Warning Score (TPEWS). This score includes the respiratory, circulatory, and nervous systems, with 0–3 points scored for each system. The total score (n=9 points) was obtained through adding up the scores of these three systems, with a greater score representing a more severe condition (9).
Table 1
| Characteristics | Total (n=298) | Arrived at the bedside in ≤60 min (n=16) | Arrived at the bedside in >60 to ≤180 min (n=232) | Arrived at the bedside in >180 min (n=50) |
|---|---|---|---|---|
| Age (years), n (%) | ||||
| <1 | 147 (49.3) | 11 (3.7) | 115 (38.6) | 21 (7.0) |
| 1 to <5 | 90 (30.2) | 2 (0.7) | 71 (23.8) | 17 (5.7) |
| 5 to <11 | 46 (15.4) | 2 (0.7) | 34 (11.4) | 10 (3.4) |
| 11 to <16 | 15 (5.0) | 1 (0.3) | 12 (4.0) | 2 (0.7) |
| Sex of child, n (%) | ||||
| Male | 186 (62.4) | 13 (4.4) | 140 (47.0) | 33 (11.1) |
| Female | 112 (37.6) | 3 (1.0) | 92 (30.9) | 17 (5.7) |
| TPEWS, n (%) | ||||
| ≤1 | 44 (14.8) | 1 (0.3) | 41 (13.8) | 2 (0.7) |
| 2 to 3 | 139 (46.6) | 10 (3.4) | 107 (35.9) | 22 (7.4) |
| 4 to 6 | 74 (24.8) | 2 (0.7) | 59 (19.8) | 13 (4.4) |
| >6 | 41 (13.8) | 3 (1.0) | 25 (8.4) | 13 (4.4) |
| The presence or absence of ICU treatment before transport, n (%) | ||||
| Yes | 197 (66.1) | 6 (2.0) | 145 (48.7) | 46 (15.4) |
| No | 101 (33.9) | 10 (3.4) | 87 (29.2) | 4 (1.3) |
| Diagnostic group, n (%) | ||||
| Respiratory | 112 (37.6) | 7 (2.3) | 86 (28.9) | 19 (6.4) |
| Infection | 11 (3.7) | 1 (0.3) | 10 (3.4) | 0 |
| Neurological | 64 (21.5) | 2 (0.7) | 51 (17.1) | 11 (3.7) |
| Endocrine | 12 (4.0) | 1 (0.3) | 10 (3.4) | 1 (0.3) |
| Hematology/oncology | 9 (3.0) | 1 (0.3) | 8 (2.7) | 0 |
| Surgery | 20 (6.7) | 0 | 13 (4.4) | 7 (2.3) |
| Trauma & accidents | 51 (17.1) | 2 (0.7) | 38 (12.8) | 11 (3.7) |
| Cardiovascular | 14 (4.7) | 2 (0.7) | 11 (3.7) | 1 (0.3) |
| Other | 5 (1.7) | 0 | 5 (1.7) | 0 |
| Ventilated at time of referral call, n (%) | ||||
| Yes | 123 (41.3) | 8 (2.7) | 88 (29.5) | 27 (9.1) |
| No | 175 (58.7) | 8 (2.7) | 144 (48.3) | 23 (7.7) |
| Use of vasoactive drugs, n (%) | ||||
| Yes | 105 (35.2) | 8 (2.7) | 76 (25.5) | 21 (7.0) |
| No | 193 (64.8) | 8 (2.7) | 156 (52.3) | 29 (9.7) |
| Time from onset to transit (days), n (%) | ||||
| ≤1 | 90 (30.2) | 6 (2.0) | 69 (23.2) | 15 (5.0) |
| 2 to 3 | 68 (22.8) | 3 (1.0) | 53 (17.8) | 12 (4.0) |
| 4 to 7 | 85 (28.5) | 3 (1.0) | 70 (23.5) | 12 (4.0) |
| >7 | 55 (18.5) | 4 (1.3) | 40 (13.4) | 11 (3.7) |
| Death, n (%) | ||||
| Yes | 50 (16.8) | 2 (0.7) | 42 (14.1) | 6 (2.0) |
| No | 248 (83.2) | 14 (4.7) | 190 (63.8) | 44 (14.8) |
TPEWS, Transport Pediatric Early Warning Score; ICU, intensive care unit.
Statistical analysis
The clinical data of 298 children receiving long-distance transport from the pediatric intensive care transport team of Anhui Children’s Hospital from March 2020 to February 2022 were retrospectively analyzed. All statistical data were processed with SPSS 24.0 software (IBM Corp., Armonk, NY, USA). Enumeration data are expressed as numbers with percentages and were analyzed with the chi-square test. The mortality of children within 30 days after admission (0= no, 1= yes) was used as the dependent variable for multivariate logistic regression analysis, and the odds ratio (OR) and 95% confidence interval (CI) indicated the relation between the time taken by the transport team to reach the bedside and the 30-day mortality rate after admission. P<0.05 indicated a statistically significant difference.
Results
After accepting the critical child transport request, our transport team reached the bedside of 248 (83.2%) critically ill children. Among them, 147 (49.3%) cases were younger than 1 year of age. The most common diagnosis was respiratory disease (n=112, 37.6%). At the time of referral, 123 (41.3%) children were mechanically ventilated prior to transport. There were 41 patients with critical scores greater than 6 points, and in 28 (68.3%) of them, the transport team arrived at the bedside of children within 3 h. There were 51 critically injured children, and in 40 of whom, the transport team arrived within 3 h. There was no significant relation between the time taken by the transport team to reach the bedside of children and 30-day mortality (P>0.05); in other words, the time taken by the transport team to reach the bedside of children was not related to the mortality rate within 30 days after admission into the pediatric ICU (PICU) (Table 2). All the CIs of the time to reach the bedside included the points of indifference (dominance ratio of 1). In addition, there was no obvious evidence supporting an increasing or decreasing trend for the mortality rate relative to the time taken by the transport team to reach the bedside of children (Figure 1). There was no statistical relationship between the TPEWS of children and the mortality within 30 days of admission (P>0.05) (Table 3).
Table 2
| Characteristics | OR (mortality in 30 days) | 95% CI (30 days) |
|---|---|---|
| Age (years) | ||
| <1 | Baseline | Baseline |
| 1 to <5 | 0.86 | 0.27–2.77 |
| 5 to <11 | 0.76 | 0.20–2.91 |
| 11 to <16 | 1.75 | 0.32–9.56 |
| TPEWS | ||
| ≤1 | Baseline | Baseline |
| 2 to 3 | 0.51 | 0.04–6.37 |
| 4 to 6 | 0.19 | 0.007–5.16 |
| >6 | 0.67 | 0.02–24.74 |
| Time to arrive at bedside (min) | ||
| ≤60 | Baseline | Baseline |
| >60 to ≤180 | 0.59 | 0.07–5.14 |
| >180 | 2.28 | 0.69–7.50 |
| The presence or absence of ICU treatment before transport | ||
| No | Baseline | Baseline |
| Yes | 1.19 | 0.25–5.61 |
| Ventilated at time of referral call | ||
| No | Baseline | Baseline |
| Yes | 1.22 | 0.13–11.09 |
| Use of vasoactive drugs | ||
| No | Baseline | Baseline |
| Yes | 1.53 | 0.39–6.03 |
| Cardiopulmonary resuscitation | ||
| No | Baseline | Baseline |
| Yes | 0.45 | 0.10–1.96 |
| Use of vasoactive drugs | ||
| No | Baseline | Baseline |
| Yes | 14.31 | 3.90–52.50 |
| Diagnostic group | ||
| Respiratory | Baseline | Baseline |
| Infection | 2.32 | 1.59–3.58 |
| Neurological | 2.68 | 1.79–4.11 |
| Endocrine | 2.56 | 1.26–4.79 |
| Hematology/oncology | 1.68 | 1.24–2.49 |
| Surgery | 1.31 | 0.77–2.21 |
| Trauma & accidents | 1.28 | 0.89–1.84 |
| Cardiovascular | 1.79 | 0.94–2.96 |
| Other | 1.82 | 0.99–3.49 |
OR, odds ratio; CI, confidence interval; TPEWS, Transport Pediatric Early Warning Score; ICU, intensive care unit.
Table 3
| TPEWS | Death, n | Mortality (%) | P |
|---|---|---|---|
| ≤1 | 2 | 4.55 | 0.31 |
| 2 to 3 | 13 | 9.35 | 0.60 |
| 4 to 6 | 15 | 20.27 | 0.33 |
| >6 | 20 | 48.78 | 0.83 |
TPEWS, Transport Pediatric Early Warning Score.
Discussion
The optimum balance between the relative concentration of treatment resources for critically ill children and the rapid acquisition of specialized intensive care treatment has long been a source of scrutiny and discussion. For instance, European countries such as England, the PICUs are usually concentrated in several specialized hospitals. In China, professional PICUs are distributed across a number of municipal hospitals in developed provinces. Anhui province is a central underdeveloped area, where no municipal hospitals have an established PICU due to limitations in medical resources and personnel allocation. As mentioned previously, providing early and high-quality intensive care diagnosis and treatment can improve the prognosis of children with sepsis and head injury (8,9). In a single-center study carried out in Canada, critically ill children transported by the non-professional teams from remote hospitals (>350 km) were associated with longer lengths of PICU stay and mechanical ventilation (10). Meanwhile, studies from other countries indicate that in the distance from the PICU does not affect the prognostic outcome, demonstrating that the initiation of intensive care immediately after the transport team reaches the emergency hospital can confer benefit (11,12). Therefore, it is reasonable to conclude that the early arrival of the transport team may be related to the improved survival rate (13,14). In hierarchical diagnosis and treatment, the treatment resources for critically ill children are usually concentrated in major cities, which inevitably makes it difficult for critically ill children in remote areas to gain rapid access to professional specialized treatment. In our single-center, retrospectively study, based on our preliminary analysis, there were differences in the disease severity, disease type, and age among the three groups of children, but the time taken by the transport team to reach the bedside of children was not related to the 30-day mortality, at least for an arrival time <4 h (the longest arrival time was 4 h). However, in this study, only a few critically ill patients with an extremely high TPEWS waited for a long time to be transported. Moreover, we are not sure whether the current transport arrival time can be further broadened because of the relatively low number of children waiting for >3 h to be transported. Such research results are suggested to be related to the following factors. First, some of the municipal hospitals have established small-scale standby ICUs, which allow for treatments such as preliminary organ functional support for critically ill children. Some hospitals also have an emergency room separate from the ordinary wards which is equipped with the relevant emergency equipment. There are also some PICUs affiliated to the neonatology department, which aids substantially in the temporary treatment of critically ill children. Second, before the arrival of the transport team, some patients can still receive assistant treatment from the adult anesthesiology department and the adult ICU team which can perform the bulk of the intensive care intervention measures even if there is no PICU in the referring hospital. Finally, for critically ill children, our transport team provided long-distance treatment suggestions after receiving a transport request, such as drug and ventilator parameter settings. For patients requiring specialty support, such as from the department of cardiology, we asked the corresponding department for help in long-distance treatment.
The limitation of this study was that only the 3-year transport data in the Anhui Children’s Hospital were analyzed. As a result, only the transport data under the medical resource conditions of Anhui Province could be analyzed. A larger, multi-center research is warranted to validate and expand our results.
Conclusions
Although this study suggests that the time taken by the transport team to reach the bedside of children after receiving a transport request is not associated with the mortality rate of children, reaching the bedside of the children in need of treatment as soon as possible has always been a critical objective of our team. Moreover, we are positively exploring the more convenient transport modes, such as high-speed railway and air transport, since the extension of arrival time is a huge challenge for basic treatment (15).
Acknowledgments
Funding: None.
Footnote
Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://tp.amegroups.com/article/view/10.21037/tp-24-164/rc
Data Sharing Statement: Available at https://tp.amegroups.com/article/view/10.21037/tp-24-164/dss
Peer Review File: Available at https://tp.amegroups.com/article/view/10.21037/tp-24-164/prf
Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tp.amegroups.com/article/view/10.21037/tp-24-164/coif). The authors have no conflicts of interest to declare.
Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013).
Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.
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(English Language Editor: J. Gray)
