Predictors of Length of Stay in the Pediatric Intensive Care Unit at Palembang BARI Regional General Hospital

Ahmad Bayu Alfarizi

Abstract


Paediatric intensive care unit (PICU) care is resource intensive, and length of stay (LOS) is widely used to reflect bed utilization and care complexity. This study aimed to identify factors associated with LOS >3 days among PICU patients at Palembang Bari General Hospital. We conducted a retrospective observational study using the PICU admission database from January 1, 2019 to December 31, 2025. Variables included age, sex, primary diagnosis category, Glasgow Coma Scale (GCS), white blood cell count, and platelet count. The outcome was LOS >3 days. Multivariable logistic regression was performed. Among 1,034 admissions, median age was 6 months (IQR 2–12 months) and 58.8% were male. Median LOS was 3 days (IQR 2–4) and 30.7% had LOS >3 days. The most frequent diagnosis categories were respiratory (28.1%), neurologic (19.8%), and dengue (13.1%). In the multivariable model (n=716), neurologic diagnosis was associated with LOS >3 days versus respiratory diagnoses (OR 1.58; 95% CI 1.01–2.47), and GCS ?8 increased the odds of LOS >3 days (OR 2.67; 95% CI 1.33–5.36). Non-dengue shock was associated with lower odds of LOS >3 days and should be interpreted cautiously (OR 0.39; 95% CI 0.20–0.78). In conclusion, neurologic involvement at admission (neurologic diagnosis and low GCS) is a key marker of prolonged PICU stay in this setting.

 


Keywords


picu; length of stay; glasgow coma scale; neurology; dengue

Full Text:

PDF

References


Pollack MM, Holubkov R, Reeder R, Dean JM, Meert KL, Berg RA, et al. PICU length of stay: factors associated with bed utilization and development of a benchmarking model. Pediatr Crit Care Med. 2018;19(3):196-203.

Polito A, Combescure C, Levy-Jamet Y, Rimensberger P; Swiss Society of Intensive Care Medicine. Long-stay patients in pediatric intensive care unit: diagnostic-specific definition and predictors. PLoSOne. 2019;14(10):e0223369.

Miura S, Fukushima M, Kurosawa H, Kimura S. Epidemiology of long-stay patients in the pediatric intensive care unit: prevalence, characteristics, resource consumption and complications. J Public Health (Berl). 2022;30(1):111-9.

Al-Eyadhy AA, Al-Sohime FM, Hassounah MM, Almazyad MA, Hasan GM, Jamal AA, et al. Long-stay patients in pediatric intensive care units. Saudi Med J. 2020;41(11):1187-96.

Boerman GH, Haspels HN, De Hoog M, Joosten KF. Characteristics of long-stay patients in a PICU and healthcare resource utilization after discharge. Crit Care Explor. 2023;5(9):e0971.

Alshaikh R, AlKhalifah A, Fayed A, AlYousef S. Factors influencing the length of stay among patients admitted to a tertiary pediatric intensive care unit in Saudi Arabia. Front Pediatr. 2022;10:1093160.

Kapileshwarkar Y, Floess KE, Astle M, Tripathi S. Risk factors for longer pediatric intensive care unit length of stay among children who required escalation of care within 24 hours of admission. Pediatr Emerg Care. 2022;38(12):678-85.

Brandi S, Troster EJ, Cunha ML. Length of stay in pediatric intensive care unit: prediction model. Einstein (Sao Paulo).2020;18:eAO5476.

Arafah YF, Murni IK, Rusmawatiningtyas D. Predictors of prolonged stay in the pediatric intensive care unit. Paediatr Indones. 2020;60(1):37-41.

Assa NP, Wati DK, Subanada IB, Soetjiningsih S, Kardana M, Sukmawati M. Full outline of unresponsiveness score as a predictor of outcomes in critically ill pediatric patients. Paediatr Indones. 2020;60(2):77-82.

Ganatra HA, Latifi SQ, Baloglu O. Pediatric intensive care unit length of stay prediction by machine learning. Bioengineering (Basel). 2024;11(10):962.

Armenda S, Rusmawatiningtyas D, Makrufardi F, Arguni E. Factors associated with clinical outcomes of pediatric dengue shock syndrome admitted to pediatric intensive care unit: a retrospective cohort study. Ann Med Surg (Lond).2021;66:102472.

Preeprem N, Phumeetham S. Paediatric dengue shock syndrome and acute respiratory failure: a single-centre retrospective study. BMJ Paediatr Open. 2022;6(1):e001578.

Thanh NT, Luan VT, Viet DC, Tung TH, Thien V. A machine learning-based risk score for prediction of mechanical ventilation in children with dengue shock syndrome: a retrospective cohort study. PLoS One. 2024;19(12):e0315281.




DOI: https://doi.org/10.32502/msj.v6i2.11049

Refbacks

  • There are currently no refbacks.


Copyright (c) 2026 Ahmad Bayu Alfarizi

 

Medical Scientific Journal (MESINA) indexed by :

 

Creative Commons License

Medical Scientific Journal (MESINA) Published by Faculty of Medicine, University of Muhammadiyah, Palembang, South Sumatra. This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

________________________________________________

Medical Scientific Journal (MESINA)

Faculty of Medicine, University of Muhammadiyah Palembang
Jl. KH. Balqi Jl. Banten II, 13 Ulu, Kec. Seberang Ulu II, Palembang City, South Sumatera 30263
E-Mail: mesina@um-palembang.ac.id