Acute and Critical Care

Original Articles

Infection
Prognostic value of novel indices combining Shock Index, Reverse Shock Index, age, and oxygen saturation for predicting mortality in COVID-19 patients in Iran at emergency department triage: a cross-sectional study: Mehdi Torabi, Atefe Noroozpour, Neda Naeemi Bafghi, Moghaddameh Mirzaee; Acute Crit Care. 2025;40(3):425-434. Published online August 29, 2025; DOI: https://doi.org/10.4266/acc.005040

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Abstract PDF: Background
The objective of the study was to investigate the role of the Shock Index (SI), the Reverse Shock Index (RSI) along with oxygen saturation in predicting mortality in coronavirus disease 2019 (COVID-19).
Methods
This cross-sectional study was conducted at an academic hospital over a period of 6 months and involved patients over the age of 18 who had been diagnosed with COVID-19 via positive polymerase chain reaction tests. The data were recorded anonymously using a checklist. The study focused on indices such as the SI and RSI, both alone and in conjunction with age and oxygen saturation, to predict hospital mortality. Statistical analysis was conducted using SPSS software.
Results
The study involved 500 COVID-19 patients with a 14.4% mortality rate. Key differences were found between survival and mortality groups in terms of age, vital signs except diastolic blood pressure, length of stay, and a series of laboratory tests. Logistic regression showed gender, oxygen saturation, hemoglobin, direct bilirubin, lactate dehydrogenase, D-dimer, and Age SI/oxygen saturation (SpO2) and RSI×SpO2/Age indices significantly associated with hospital mortality. Receiver operating characteristic analysis indicated Age SI/SpO2 and RSI×SpO2/Age as effective mortality predictors, exhibiting an area under the curve of 0.80 and achieving a sensitivity, specificity, and accuracy of over 70%.
Conclusions
The combination of SI, the RSI along with hypoxia, and age has been identified as a potentially more significant role in ruling out hospital mortality in COVID-19 patients than vital signs alone, given the established role of hypoxia as a major risk factor in such cases.

Pediatrics
A deep learning model for estimating sedation levels using heart rate variability and vital signs: a retrospective cross-sectional study at a center in South Korea: You Sun Kim, Bongjin Lee, Wonjin Jang, Yonghyuk Jeon, June Dong Park; Acute Crit Care. 2024;39(4):621-629. Published online November 25, 2024; DOI: https://doi.org/10.4266/acc.2024.01200; Retraction in: Acute Crit Care 2025;40(3):512

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Epidemiology
Mortality rates among adult critical care patients with unusual or extreme values of vital signs and other physiological parameters: a retrospective study: Charles Harding, Marybeth Pompei, Dmitriy Burmistrov, Francesco Pompei; Acute Crit Care. 2024;39(2):304-311. Published online May 13, 2024; DOI: https://doi.org/10.4266/acc.2023.01361

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3 Web of Science
4 Crossref

Abstract PDF

Background
We evaluated relationships of vital signs and laboratory-tested physiological parameters with in-hospital mortality, focusing on values that are unusual or extreme even in critical care settings.
Methods
We retrospectively studied Philips Healthcare–MIT eICU data (207 U.S. hospitals, 20142015), including 166,959 adult-patient critical care admissions. Analyzing most-deranged (worst) value measured in the first admission day, we investigated vital signs (body temperature, heart rate, mean arterial pressure, and respiratory rate) as well as albumin, bilirubin, blood pH via arterial blood gas (ABG), blood urea nitrogen, creatinine, FiO2 ABG, glucose, hematocrit, PaO2 ABG, PaCO2 ABG, sodium, 24-hour urine output, and white blood cell count (WBC).
Results
In-hospital mortality was ≥50% at extremes of low blood pH, low and high body temperature, low albumin, low glucose, and low heart rate. Near extremes of blood pH, temperature, glucose, heart rate, PaO2 , and WBC, relatively. Small changes in measured values correlated with several-fold mortality rate increases. However, high mortality rates and abrupt mortality increases were often hidden by the common practice of thresholding or binning physiological parameters. The best predictors of in-hospital mortality were blood pH, temperature, and FiO2 (scaled Brier scores: 0.084, 0.063, and 0.049, respectively).
Conclusions
In-hospital mortality is high and sharply increasing at extremes of blood pH, body temperature, and other parameters. Common-practice thresholding obscures these associations. In practice, vital signs are sometimes treated more casually than laboratory-tested parameters. Yet, vitals are easier to obtain and we found they are often the best mortality predictors, supporting perspectives that vitals are undervalued.

Citations

Citations to this article as recorded by

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BMC Medicine.2025;[Epub] CrossRef

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