Skip to main content

The potential role of ICU capacity strain in COVID-19 mortality: comparison between first and second waves in Pavia, Italy

To the Editor,

In novel coronavirus disease (COVID-19) pandemic, a high mortality rate was reported during wave 1, particularly when COVID-19 load exceeded 100% ICU capacity [1]. With better knowledge of the disease [2, 3], a lower mortality was expected in wave 2; however, similar mortalities were reported for hospital/ICU populations [4]. Within the same wave, in-hospital mortality was lower once past the peak of hospital affluence [1, 5], suggesting a role of ICU facilities’ availability. However, their actual role remains unclear since mortality was high also in non-overwhelmed healthcare systems [6].

To test if disproportion between ICU facilities and hospitalized patients impact COVID-19 mortality, we compared the first 8 weeks of waves 1 vs. 2 in Pavia (Lombardy, Italy). ICU-timing (time from hospital to ICU admission), percentage of COVID-19 hospitalized patients admitted to ICU, and percentage of intubated patients in ICU were considered ICU capacity strain’s markers. All patients during wave 2 received steroids as appropriate [3]. Local ethic committee approved the study.

Patients’ characteristics are in Table 1. In wave 1, a steep increase of ICU COVID-19 patients reached a peak of 64 on day 34 (Fig. 1A); a plateau phase lasted 14/56 days (25.0%); thereafter, a reduction was observed. In wave 2 (Fig. 1B), a slower increase achieved a lower peak (54 patients) on day 40 and lasted 4/56 days (7.1%; p=0.010).

Table 1 Features of the patients admitted to general ward and to ICU during the first and the second COVID-19 waves in Pavia
Fig. 1
figure1

The first 8 weeks of the two pandemic waves in ICU and in the wards: this timeframe was representative of the critical phase for our healthcare system, including rapid increase of ICU patients up to a peak (red arrows), plateau phase, and initial decline (green arrows). A Wave 1 in ICU. A steep increase of ICU COVID-19 patients was observed until a peak of 64; pre-pandemic capacity was 32 beds. The peak was reached on day 34; a plateau phase persisted until day 48; thereafter, a reduction was observed. After 8 weeks, 139 patients had been admitted to ICU (13.1% of hospital admissions) with 55 (39.6%) patients still in ICU, 30 (21.6%) discharged and 54 (38.8%) deceased. At this time, mortality was 54/84 (64.3%) in ICU patients. B Wave 2 in ICU. The initial increase was slower, and a lower peak (54 ICU patients) was achieved on day 40; a plateau phase lasted until day 44, when the decline started. After 8 weeks, 119 patients had been admitted to ICU (17.7% of hospital admissions, p=0.0104 vs. wave 1) with 45 (37.8%) patients still in ICU, 56 (47.1%) discharged, and 18 (15.1%) cumulative deaths (p<0.0001 vs. wave 1). At this time, mortality was 18/74 (24.3%) in ICU patients (p<0.0001 vs. wave 1). C Wave 1 in the wards. After 8 weeks, 923 patients had been admitted (86.9% of hospital admissions) with 175 (19.0%) patients still in the ward, 475 (51.5%) discharged, and 273 (29.6%) deceased. At this time, mortality was 273/748 (36.5%) in ward patients. D Wave 2 in the wards. After 8 weeks, 555 patients had been admitted (82.3% of hospital admissions, p=0.0104 vs. wave 1) with 134 (24.1%) patients still in the ward, 334 (60.2%) discharged and 87 (15.7%) deceased (p<0.0001 vs. wave 1). At this time, mortality was 87/421 (20.7%) in ward patients (p<0.0001 vs. wave 1)

At day 56 of wave 1, patients admitted to ICU were 139, ICU mortality was 54/84 (64.3%), patients still in ICU were 55 (39.6%), and their follow-up ICU mortality was 14/55 (25.5%), lower than in the beginning of the same wave (p<0.0001).

At day 56 of wave 2, patients admitted to ICU were 119, ICU mortality was 18/74 (24.3%; p<0.0001 vs. wave 1), patients still in ICU were 45 (37.8%), and their follow-up ICU mortality was 16/45 (35.6%), similar to the first 8 weeks (p=0.2133). Findings in ward patients are displayed in Fig. 1C, D.

In waves 1 and 2, hospital mortality was in overall ICU patients 48.9% and 30.3% (p=0.0033), in intubated patients 50.7 and 36.7% (p=0.0410), in ward patients 33.3% and 19.6% (p<0.0001), respectively.

Wave 2 determined a lower ICU strain: patients that could be treated in ICU were 17.7 vs. 13.1% (relative increase 35.1%; p=0.0104); ICU-timing was shorter (57±92 vs. 90±91 h; p=0.0047), with patients admitted to ICU within 48 h 58.0 vs. 40.3% (p=0.0059); and intubation was less frequent (75.6 vs. 96.4%; p<0.0001).

ICU-timing was resulted in an independent risk factor for hospital mortality when adjusted for age, gender, and need of invasive ventilation (p<0.0001).

The improvement of ICU and ward patients’ outcome exceeded what expected from steroids’ introduction [3], supporting that other factor may have a role [5]. ICU strain was significantly higher during wave 1. Moreover, patients were admitted to ICU later, when intubation was almost unavoidable, which may increase mortality [5]. ICU-timing was an independent predictor of mortality, suggesting intensive care should be considered a time-dependent treatment for COVID-19 patients.

In conclusion, COVID-19 mortality notably decreased in wave 2 at our institution; beyond the benefits of a deeper knowledge of the disease, lower ICU capacity strain and timelier ICU admission may have played a role.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

COVID-19:

Novel coronavirus disease

ICU:

Intensive care unit

References

  1. 1.

    Bravata DM, Perkins AJ, Myers LJ et al (2021) Association of intensive care unit patient load and demand with mortality rates in US Department of Veterans Affairs Hospitals during the COVID-19 pandemic. JAMA New Open 4(1):e2034266

    Article  Google Scholar 

  2. 2.

    Vaschetto R, Barone-Adesi F, Racca F et al (2021) Outcomes of COVID-19 patients treated with continuous positive airway pressure outside the intensive care unit. ERJ Open Res 7(1):00541–02020

    Article  Google Scholar 

  3. 3.

    RECOVERY Collaborative Group, Horby P, Lim WS, Emberson JR et al (2021) Dexamethasone in Hospitalized Patients with Covid-19. N Engl J Med 384(8):693–704

    Article  Google Scholar 

  4. 4.

    Contou D, Fraissé M, Pajot O et al (2021) Comparison between first and second wave among critically ill COVID-19 patients admitted to a French ICU: no prognostic improvement during the second wave? Crit Care 25(1):3

    Article  Google Scholar 

  5. 5.

    Docherty AB, Mulholland RH, Lone NI et al (2021) Changes in in-hospital mortality in the first wave of COVID-19: a multicentre prospective observational cohort study using the WHO Clinical Characterisation Protocol UK. Lancet Respir Med S2213-2600(21):00175–00172

    Google Scholar 

  6. 6.

    Karagiannidis C, Mostert C, Hentschker C, Voshaar T, Malzahn J, Schillinger G, Klauber J, Janssens U, Marx G, Weber-Carstens S, Kluge S, Pfeifer M, Grabenhenrich L, Welte T, Busse R (2020) Case characteristics, resource use, and outcomes of 10 021 patients with COVID-19 admitted to 920 German hospitals: an observational study. Lancet Respir Med 8(9):853–862. https://doi.org/10.1016/S2213-2600(20)30316-7

    CAS  Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

The authors would like the names of the individual members of the group COVID-19 Pavia Crisis Unit to be searchable through their individual PubMed records. COVID-19 Pavia Crisis Unit: Carlo Marena, MD (San Matteo Hospital, Pavia, Italy); Monica Calvi, PharmD (San Matteo Hospital, Pavia, Italy); Giuseppina Grugnetti, BSN (San Matteo Hospital, Pavia, Italy); Alba Muzzi, MD (San Matteo Hospital, Pavia, Italy); Raffaele Bruno, MD (San Matteo Hospital, Pavia, Italy); Paolo Lago (San Matteo Hospital, Pavia, Italy); Gianluigi Marseglia, MD (San Matteo Hospital, Pavia, Italy); Stefano Perlini, MD (San Matteo Hospital, Pavia, Italy); Alessandra Palo, MD (San Matteo Hospital, Pavia, Italy); Fausto Baldanti, MD (San Matteo Hospital, Pavia, Italy); Luigi Oltrona Visconti, MD (San Matteo Hospital, Pavia, Italy); Marco Benazzo, MD (San Matteo Hospital, Pavia, Italy); Carlo Nicora, MD (San Matteo Hospital, Pavia, Italy); Antonio Triarico, MD (San Matteo Hospital, Pavia, Italy); Vincenzo Petronella, MD (San Matteo Hospital, Pavia, Italy); Antonio Di Sabatino, MD (San Matteo Hospital, Pavia, Italy); Marco Vincenzo Lenti, MD (San Matteo Hospital, Pavia, Italy); Luca Civardi, MD (Anesthesia and Intensive Care, San Matteo Hospital, Pavia, Italy); Fabio Sciutti, MD (Anesthesia and Intensive Care, San Matteo Hospital, Pavia, Italy); Giuseppe Maggio, MD (Anesthesia and Intensive Care, San Matteo Hospital, Pavia, Italy); Michele Pagani, MD (Anesthesia and Intensive Care, San Matteo Hospital, Pavia, Italy); Giuseppe Sala Gallini, MD (Anesthesia and Intensive Care, San Matteo Hospital, Pavia, Italy); Giuseppe Rodi, MD (Anesthesia and Intensive Care, San Matteo Hospital, Pavia, Italy).

Mail: ca.marena@smatteo.pv.it

Funding

Institutional funding

Author information

Affiliations

Authors

Contributions

FM conceived the research protocol, collected and analysed the data, wrote the draft, and revised it critically before submission. SC collected and analysed the data and revised the draft critically before submission. SM collected and analysed the data, wrote the draft, and revised it critically before submission. RB collected the data and revised the draft critically before submission. AGC collected the data and revised the draft critically before submission. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Silvia Mongodi.

Ethics declarations

Ethics approval and consent to participate

The study was approved by local ethic committee.

Consent for publication

All the patients signed an informed consent for data publication.

Competing interests

FM received fees for lectures from GE Healthcare, Hamilton Medical, SEDA SpA, outside the present work. SM received fees for lectures from GE Healthcare, outside the present work. A research agreement is active between University of Pavia and Hamilton Medical. The other authors declare no conflict of interest.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

On behalf of COVID-19 Pavia Crisis Unit

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Mojoli, F., Cutti, S., Mongodi, S. et al. The potential role of ICU capacity strain in COVID-19 mortality: comparison between first and second waves in Pavia, Italy. J Anesth Analg Crit Care 1, 8 (2021). https://doi.org/10.1186/s44158-021-00007-6

Download citation

Keywords

  • COVID-19 waves
  • ICU organization
  • ICU capacity
  • ICU preparedness
  • COVID-19 mortality