Biased and unbiased estimation of the average length of stay in intensive care units in the Covid-19 pandemic
BACKGROUND: The average length of stay (LOS) in the intensive care unit (ICU_ALOS) is a helpful parameter summarizing critical bed occupancy. During the outbreak of a novel virus, estimating early a reliable ICU_ALOS estimate of infected patients is critical to accurately parameterize models examining mitigation and preparedness scenarios.
METHODS: Two estimation methods of ICU_ALOS were compared: the average LOS of already discharged patients at the date of estimation (DPE), and a standard parametric method used for analyzing time-to-event data which fits a given distribution to observed data and includes the censored stays of patients still treated in the ICU at the date of estimation (CPE). Methods were compared on a series of all COVID-19 consecutive cases (n = 59) admitted in an ICU devoted to such patients. At the last follow-up date, 99 days after the first admission, all patients but one had been discharged. A simulation study investigated the generalizability of the methods' patterns. CPE and DPE estimates were also compared to COVID-19 estimates reported to date.
RESULTS: LOS ≥ 30 days concerned 14 out of the 59 patients (24%), including 8 of the 21 deaths observed. Two months after the first admission, 38 (64%) patients had been discharged, with corresponding DPE and CPE estimates of ICU_ALOS (95% CI) at 13.0 days (10.4-15.6) and 23.1 days (18.1-29.7), respectively. Series' true ICU_ALOS was greater than 21 days, well above reported estimates to date.
CONCLUSIONS: Discharges of short stays are more likely observed earlier during the course of an outbreak. Cautious unbiased ICU_ALOS estimates suggest parameterizing a higher burden of ICU bed occupancy than that adopted to date in COVID-19 forecasting models.
FUNDING: Support by the National Natural Science Foundation of China (81900097 to Dr. Zhou) and the Emergency Response Project of Hubei Science and Technology Department (2020FCA023 to Pr. Zhao).
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2020 |
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| Erschienen: |
2020 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:10 |
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| Enthalten in: |
Annals of intensive care - 10(2020), 1 vom: 16. Okt., Seite 135 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Lapidus, Nathanael [VerfasserIn] |
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| Links: |
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| Themen: |
COVID-19 |
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| Anmerkungen: |
Date Revised 22.10.2020 published: Electronic Citation Status PubMed-not-MEDLINE |
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| doi: |
10.1186/s13613-020-00749-6 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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NLM316327360 |
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| 245 | 1 | 0 | |a Biased and unbiased estimation of the average length of stay in intensive care units in the Covid-19 pandemic |
| 264 | 1 | |c 2020 | |
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| 500 | |a published: Electronic | ||
| 500 | |a Citation Status PubMed-not-MEDLINE | ||
| 520 | |a BACKGROUND: The average length of stay (LOS) in the intensive care unit (ICU_ALOS) is a helpful parameter summarizing critical bed occupancy. During the outbreak of a novel virus, estimating early a reliable ICU_ALOS estimate of infected patients is critical to accurately parameterize models examining mitigation and preparedness scenarios | ||
| 520 | |a METHODS: Two estimation methods of ICU_ALOS were compared: the average LOS of already discharged patients at the date of estimation (DPE), and a standard parametric method used for analyzing time-to-event data which fits a given distribution to observed data and includes the censored stays of patients still treated in the ICU at the date of estimation (CPE). Methods were compared on a series of all COVID-19 consecutive cases (n = 59) admitted in an ICU devoted to such patients. At the last follow-up date, 99 days after the first admission, all patients but one had been discharged. A simulation study investigated the generalizability of the methods' patterns. CPE and DPE estimates were also compared to COVID-19 estimates reported to date | ||
| 520 | |a RESULTS: LOS ≥ 30 days concerned 14 out of the 59 patients (24%), including 8 of the 21 deaths observed. Two months after the first admission, 38 (64%) patients had been discharged, with corresponding DPE and CPE estimates of ICU_ALOS (95% CI) at 13.0 days (10.4-15.6) and 23.1 days (18.1-29.7), respectively. Series' true ICU_ALOS was greater than 21 days, well above reported estimates to date | ||
| 520 | |a CONCLUSIONS: Discharges of short stays are more likely observed earlier during the course of an outbreak. Cautious unbiased ICU_ALOS estimates suggest parameterizing a higher burden of ICU bed occupancy than that adopted to date in COVID-19 forecasting models | ||
| 520 | |a FUNDING: Support by the National Natural Science Foundation of China (81900097 to Dr. Zhou) and the Emergency Response Project of Hubei Science and Technology Department (2020FCA023 to Pr. Zhao) | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a COVID-19 | |
| 650 | 4 | |a China | |
| 650 | 4 | |a Intensive care units | |
| 650 | 4 | |a Pandemics | |
| 650 | 4 | |a Statistical models | |
| 700 | 1 | |a Zhou, Xianlong |e verfasserin |4 aut | |
| 700 | 1 | |a Carrat, Fabrice |e verfasserin |4 aut | |
| 700 | 1 | |a Riou, Bruno |e verfasserin |4 aut | |
| 700 | 1 | |a Zhao, Yan |e verfasserin |4 aut | |
| 700 | 1 | |a Hejblum, Gilles |e verfasserin |4 aut | |
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