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Erschienen in: Neurocritical Care 2/2021

10.07.2020 | Original Work

Early Determinants of Neurocritical Care Unit Length of Stay in Patients with Spontaneous Intracerebral Hemorrhage

verfasst von: Andrea Loggini, Ali Mansour, Faten El Ammar, Christos Lazaridis, Christopher L. Kramer, Zachary Bulwa, Faddi Saleh Velez, Cedric McCoy, Fernando D. Goldenberg

Erschienen in: Neurocritical Care | Ausgabe 2/2021

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Abstract

Background

The present study considers patients with spontaneous intracerebral hemorrhage (ICH) admitted to the neurocritical care unit (NCCU) through the Emergency Department (ED). It aims to identify patient-specific clinical variables that can be assessed on presentation and that are associated with prolonged NCCU length of stay (LOS).

Methods

A cross-sectional, single-center, retrospective analysis of ICH patients directly admitted from the ED to the NCCU over an 8-year period was performed. Patients’ demographics, clinical exam characteristics, serum laboratory values, intubation status, and neurosurgical procedures at presentation were recorded. Head computed tomography scans obtained on presentation were reviewed. LOS was calculated based on the number of midnights spent in the NCCU. Prolonged LOS was determined using a change point analysis, adopting the method of Taylor which utilizes CUMSUM charts and bootstrap analysis. A decision tree model was trained and validated to identify reliable variables associated with prolonged LOS.

Results

Two hundred and five patients with ICH were analyzed. Prolonged LOS was calculated to be a stay that exceeds 8 days; 68 patients (33%) had a prolonged LOS in NCCU. Median LOS did not differ between survivors and patients who died in hospital. Clinical variables explored through the decision tree model were intubation status, neurosurgical intervention (EVD, decompression or evacuation within 24 h from presentation), and components of the ICH score: age, GCS, hematoma volume, the presence of intraventricular hemorrhage (IVH), and infratentorial location. The model accuracy was 0.8 and AUC was 0.83 (95% CI 0.78–0.89).

Conclusion

We propose an ICH-LOS model based on neurosurgical intervention, intubation status and GCS at presentation to predict prolonged LOS in the NCCU in patients with ICH. This simple clinical tool, if prospectively validated, could help with medical planning, contribute to patient care-directed conversations, assist in optimizing hospital resource utilization, and, more importantly, motivating patient-specific interventions aimed at optimizing outcomes and decreasing LOS.
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Literatur
1.
Zurück zum Zitat McConnell KJ, Richards CF, Daya M, Bernell SL, Weathers CC, Lowe RA. Effect of increased ICU capacity on emergency department length of stay and ambulance diversion. Ann Emerg Med. 2005;45:471–8.CrossRef McConnell KJ, Richards CF, Daya M, Bernell SL, Weathers CC, Lowe RA. Effect of increased ICU capacity on emergency department length of stay and ambulance diversion. Ann Emerg Med. 2005;45:471–8.CrossRef
2.
Zurück zum Zitat Sun BC, Hsia RY, Weiss RE, Zingmond D, Liang LJ, Han W, et al. Effect of emergency department crowding on outcomes of admitted patients. Ann Emerg Med. 2013;61:605.e6–611.e6.CrossRef Sun BC, Hsia RY, Weiss RE, Zingmond D, Liang LJ, Han W, et al. Effect of emergency department crowding on outcomes of admitted patients. Ann Emerg Med. 2013;61:605.e6–611.e6.CrossRef
3.
Zurück zum Zitat Gruenberg DA, Shelton W, Rose SL, Rutter AE, Socaris S, McGee G. Factors influencing length of stay in the intensive care unit. Am J Crit Care. 2006;15:502–9.CrossRef Gruenberg DA, Shelton W, Rose SL, Rutter AE, Socaris S, McGee G. Factors influencing length of stay in the intensive care unit. Am J Crit Care. 2006;15:502–9.CrossRef
4.
Zurück zum Zitat Toptas M, Samanci NS, Akkoc E, Yucetas E, Cebeci E, Sen O, et al. Factors affecting the length of stay in the intensive care unit: our clinical experience. Biomed Res Int. 2018;2018:9438046.PubMedPubMedCentral Toptas M, Samanci NS, Akkoc E, Yucetas E, Cebeci E, Sen O, et al. Factors affecting the length of stay in the intensive care unit: our clinical experience. Biomed Res Int. 2018;2018:9438046.PubMedPubMedCentral
5.
Zurück zum Zitat Verburg IWM, Holman R, Dongelmans D, de Jonge E, de Keizer NF. Is patient length of stay associated with intensive care unit characteristics? J Crit Care. 2018;43:114–21.CrossRef Verburg IWM, Holman R, Dongelmans D, de Jonge E, de Keizer NF. Is patient length of stay associated with intensive care unit characteristics? J Crit Care. 2018;43:114–21.CrossRef
6.
Zurück zum Zitat Higgins TL, McGee WT, Steingrub JS, Rapoport J, Lemeshow S, Teres D. Early indicators of prolonged intensive care unit stay: impact of illness severity, physician staffing, and pre-intensive care unit length of stay. Crit Care Med. 2003;31:45–51.CrossRef Higgins TL, McGee WT, Steingrub JS, Rapoport J, Lemeshow S, Teres D. Early indicators of prolonged intensive care unit stay: impact of illness severity, physician staffing, and pre-intensive care unit length of stay. Crit Care Med. 2003;31:45–51.CrossRef
7.
Zurück zum Zitat Russell MW, Joshi AV, Neumann PJ, Boulanger L, Menzin J. Predictors of hospital length of stay and cost in patients with intracerebral hemorrhage. Neurology. 2006;67:1279–81.CrossRef Russell MW, Joshi AV, Neumann PJ, Boulanger L, Menzin J. Predictors of hospital length of stay and cost in patients with intracerebral hemorrhage. Neurology. 2006;67:1279–81.CrossRef
8.
Zurück zum Zitat Naidech AM, Bendok BR, Tamul P, Bassin SL, Watts CM, Batjer HH, et al. Medical complications drive length of stay after brain hemorrhage: a cohort study. Neurocrit Care. 2009;10:11–9.CrossRef Naidech AM, Bendok BR, Tamul P, Bassin SL, Watts CM, Batjer HH, et al. Medical complications drive length of stay after brain hemorrhage: a cohort study. Neurocrit Care. 2009;10:11–9.CrossRef
9.
Zurück zum Zitat Ohwaki K, Yano E, Nagashima H, Nakagomi T, Tamura A. Impact of infection on length of intensive care unit stay after intracerebral hemorrhage. Neurocrit Care. 2008;8:271–5.CrossRef Ohwaki K, Yano E, Nagashima H, Nakagomi T, Tamura A. Impact of infection on length of intensive care unit stay after intracerebral hemorrhage. Neurocrit Care. 2008;8:271–5.CrossRef
10.
Zurück zum Zitat Luo L, Xu X, Jiang Y, Zhu W. Predicting intracerebral hemorrhage patients’ length-of-stay probability distribution based on demographic, clinical, admission diagnosis, and surgery information. J Healthc Eng. 2019;2019:12.CrossRef Luo L, Xu X, Jiang Y, Zhu W. Predicting intracerebral hemorrhage patients’ length-of-stay probability distribution based on demographic, clinical, admission diagnosis, and surgery information. J Healthc Eng. 2019;2019:12.CrossRef
11.
Zurück zum Zitat Chan CL, Ting HW, Huang HT. The definition of a prolonged intensive care unit stay for spontaneous intracerebral hemorrhage patients: An application with national health insurance research database. Biomed Res Int. 2014;2014:891725.PubMedPubMedCentral Chan CL, Ting HW, Huang HT. The definition of a prolonged intensive care unit stay for spontaneous intracerebral hemorrhage patients: An application with national health insurance research database. Biomed Res Int. 2014;2014:891725.PubMedPubMedCentral
12.
Zurück zum Zitat Stein M, Misselwitz B, Hamann GF, Kolodziej MA, Reinges MHT, Uhl E. defining prolonged length of acute care stay for surgically and conservatively treated patients with spontaneous intracerebral hemorrhage: a population-based analysis. Biomed Res Int. 2016;2016:6.CrossRef Stein M, Misselwitz B, Hamann GF, Kolodziej MA, Reinges MHT, Uhl E. defining prolonged length of acute care stay for surgically and conservatively treated patients with spontaneous intracerebral hemorrhage: a population-based analysis. Biomed Res Int. 2016;2016:6.CrossRef
14.
Zurück zum Zitat Kothari RU, Brott T, Broderick JP, Barsan WG, Sauerbeck LR, Zuccarello M, et al. The ABCs of measuring intracerebral hemorrhage volumes. Stroke. 1996;27:1304–5.CrossRef Kothari RU, Brott T, Broderick JP, Barsan WG, Sauerbeck LR, Zuccarello M, et al. The ABCs of measuring intracerebral hemorrhage volumes. Stroke. 1996;27:1304–5.CrossRef
15.
Zurück zum Zitat Hemphill JC, Bonovich DC, Besmertis L, Manley GT, Johnston SC. The ICH score: A simple, reliable grading scale for intracerebral hemorrhage. Stroke. 2001;32:891–7.CrossRef Hemphill JC, Bonovich DC, Besmertis L, Manley GT, Johnston SC. The ICH score: A simple, reliable grading scale for intracerebral hemorrhage. Stroke. 2001;32:891–7.CrossRef
16.
Zurück zum Zitat Taylor WA (200) Change-point analysis: a powerful new tool for detecting changes. Analysis Taylor WA (200) Change-point analysis: a powerful new tool for detecting changes. Analysis
17.
Zurück zum Zitat Gavit P, Baddour Y, Tholmer R. Use of change-point analysis for process monitoring and control. Biopharm Int. 2009;22(8):46–55. Gavit P, Baddour Y, Tholmer R. Use of change-point analysis for process monitoring and control. Biopharm Int. 2009;22(8):46–55.
18.
Zurück zum Zitat Boulkedid R, Sibony O, Bossu-Salvador C, Oury JF, Alberti C. Monitoring healthcare quality in an obstetrics and gynaecology department using a CUSUM chart. BJOG An Int J Obstet Gynaecol. 2010;117(10):1225–35.CrossRef Boulkedid R, Sibony O, Bossu-Salvador C, Oury JF, Alberti C. Monitoring healthcare quality in an obstetrics and gynaecology department using a CUSUM chart. BJOG An Int J Obstet Gynaecol. 2010;117(10):1225–35.CrossRef
19.
Zurück zum Zitat Nam S, Cha JH, Cho S. A Bayesian change-point analysis for software reliability models. Commun Stat Simul Comput. 2008;37:1855–69.CrossRef Nam S, Cha JH, Cho S. A Bayesian change-point analysis for software reliability models. Commun Stat Simul Comput. 2008;37:1855–69.CrossRef
20.
Zurück zum Zitat Jose CT, Ismail B, Jayasekhar S. Trend, growth rate, and change point analysis—a data driven approach. Commun Stat Simul Comput. 2008;37:498–506.CrossRef Jose CT, Ismail B, Jayasekhar S. Trend, growth rate, and change point analysis—a data driven approach. Commun Stat Simul Comput. 2008;37:498–506.CrossRef
21.
Zurück zum Zitat Liu P, Guo S, Xiong L, Chen L. Flood season segmentation based on the probability change-point analysis technique. Hydrol Sci J. 2010;5:540–54.CrossRef Liu P, Guo S, Xiong L, Chen L. Flood season segmentation based on the probability change-point analysis technique. Hydrol Sci J. 2010;5:540–54.CrossRef
22.
Zurück zum Zitat Rudoy D, Yuen SG, Howe RD, Wolfe PJ. Bayesian change-point analysis for atomic force microscopy and soft material indentation. J R Stat Soc Ser C Appl Stat. 2010;59:573–93. Rudoy D, Yuen SG, Howe RD, Wolfe PJ. Bayesian change-point analysis for atomic force microscopy and soft material indentation. J R Stat Soc Ser C Appl Stat. 2010;59:573–93.
23.
Zurück zum Zitat Hanley DF, Thompson RE, Rosenblum M, Yenokyan G, Lane K, McBee N, et al. Efficacy and safety of minimally invasive surgery with thrombolysis in intracerebral haemorrhage evacuation (MISTIE III): a randomised, controlled, open-label, blinded endpoint phase 3 trial. Lancet. 2019;393:1021–32.CrossRef Hanley DF, Thompson RE, Rosenblum M, Yenokyan G, Lane K, McBee N, et al. Efficacy and safety of minimally invasive surgery with thrombolysis in intracerebral haemorrhage evacuation (MISTIE III): a randomised, controlled, open-label, blinded endpoint phase 3 trial. Lancet. 2019;393:1021–32.CrossRef
24.
Zurück zum Zitat Kellner CP, Chartrain AG, Nistal DA, Scaggiante J, Hom D, Ghatan S, et al. The Stereotactic Intracerebral Hemorrhage Underwater Blood Aspiration (SCUBA) technique for minimally invasive endoscopic intracerebral hemorrhage evacuation. J Neurointerv Surg. 2018;10:771–6.CrossRef Kellner CP, Chartrain AG, Nistal DA, Scaggiante J, Hom D, Ghatan S, et al. The Stereotactic Intracerebral Hemorrhage Underwater Blood Aspiration (SCUBA) technique for minimally invasive endoscopic intracerebral hemorrhage evacuation. J Neurointerv Surg. 2018;10:771–6.CrossRef
25.
Zurück zum Zitat Alsherbini K, Goyal N, Metter EJ, Pandhi A, Tsivgoulis G, Huffstatler T, et al. Predictors for Tracheostomy with External Validation of the Stroke-Related Early Tracheostomy Score (SETscore). Neurocrit Care. 2019;30:185–92.CrossRef Alsherbini K, Goyal N, Metter EJ, Pandhi A, Tsivgoulis G, Huffstatler T, et al. Predictors for Tracheostomy with External Validation of the Stroke-Related Early Tracheostomy Score (SETscore). Neurocrit Care. 2019;30:185–92.CrossRef
26.
Zurück zum Zitat McCann MR, Hatton KW, Vsevolozhskaya OA, Fraser JF. Earlier tracheostomy and percutaneous endoscopic gastrostomy in patients with hemorrhagic stroke: associated factors and effects on hospitalization. J Neurosurg. 2019;132(1):1–7. McCann MR, Hatton KW, Vsevolozhskaya OA, Fraser JF. Earlier tracheostomy and percutaneous endoscopic gastrostomy in patients with hemorrhagic stroke: associated factors and effects on hospitalization. J Neurosurg. 2019;132(1):1–7.
Metadaten
Titel
Early Determinants of Neurocritical Care Unit Length of Stay in Patients with Spontaneous Intracerebral Hemorrhage
verfasst von
Andrea Loggini
Ali Mansour
Faten El Ammar
Christos Lazaridis
Christopher L. Kramer
Zachary Bulwa
Faddi Saleh Velez
Cedric McCoy
Fernando D. Goldenberg
Publikationsdatum
10.07.2020
Verlag
Springer US
Erschienen in
Neurocritical Care / Ausgabe 2/2021
Print ISSN: 1541-6933
Elektronische ISSN: 1556-0961
DOI
https://doi.org/10.1007/s12028-020-01046-7

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