Predictors of Mortality in Elderly and Very Elderly Emergency Patients with Sepsis: A Retrospective Study

Boonmee, Phetsinee; Ruangsomboon, Onlak; Limsuwat, Chok; Chakorn, Tipa

doi:10.5811/westjem.2020.7.47405

Cited by 36 publications

(43 citation statements)

References 27 publications

(31 reference statements)

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“…Therefore, we suggest that lower BT in older sepsis patients is associated with a worse prognosis. Our results are supported by those of previous studies, which showed that hypothermia is a significant predictor of mortality in sepsis patients older than 65 years 25 , 26 .…”

Section: Discussionsupporting

confidence: 92%

Cluster analysis integrating age and body temperature for mortality in patients with sepsis: a multicenter retrospective study

Baek

Kim

Kwon

2022

Sci Rep

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It is not clear whether mortality is associated with body temperature (BT) in older sepsis patients. This study aimed to evaluate the mortality rates in sepsis patients according to age and BT and identify the risk factors for mortality. We investigated the clusters using a machine learning method based on a combination of age and BT, and identified the mortality rates according to these clusters. This retrospective multicenter study was conducted at five hospitals in Korea. Data of sepsis patients aged ≥ 18 years who were admitted to the intensive care unit between January 1, 2011 and April 30, 2021 were collected. BT was divided into three groups (hypothermia < 36 °C, normothermia 36‒38 °C, and hyperthermia > 38 °C), and age groups were divided using a 75-year age threshold. Kaplan‒Meier analysis was performed to assess the cumulative mortality over 90 days. A K-means clustering algorithm using age and BT was used to characterize phenotypes. During the study period, 15,574 sepsis patients were enrolled. Overall, 90-day mortality was 20.5%. Kaplan‒Meier survival analyses demonstrated that 90-day mortality rates were 27.4%, 19.6%, and 11.9% in the hypothermia, normothermia, and hyperthermia groups, respectively, in those ≥ 75 years old (Log-rank p < 0.001). Cluster analysis demonstrated three groups: Cluster A (relatively older age and lower BT), Cluster B (relatively younger age and wide range of BT), and Cluster C (relatively higher BT than Cluster A). Kaplan‒Meier curve analysis showed that the 90-day mortality rates of Cluster A was significantly higher than those of Clusters B and C (24.2%, 17.1%, and 17.0%, respectively; Log-rank p < 0.001). The 90-day mortality rate correlated inversely with BT groups among sepsis patients in either age group (< 75 and ≥ 75 years). Clustering analysis revealed that the mortality rate was higher in the cluster of patients with relatively older age and lower BT.

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Section: Discussionsupporting

confidence: 92%

Cluster analysis integrating age and body temperature for mortality in patients with sepsis: a multicenter retrospective study

Baek

Kim

Kwon

2022

Sci Rep

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“…The current study demonstrated the different predictive performance of the qSOFA score for in-hospital mortality between young and elderly OAPN patients; the qSOFA score predicted in-hospital mortality with high accuracy in young patients (AUC, 0.85), whereas its prognostic accuracy was modest in elderly patients (AUC, 0.61). This trend was also observed in several previous studies, in which the AUC of the qSOFA score was less than 0.70 in elderly patients [ 17 , 18 , 19 ]. The sensitivity and specificity of qSOFA score ≥ 2 for in-hospital mortality were 80% and 80% in young patients, and 50% and 68% in elderly patients, respectively.…”

Section: Discussionsupporting

confidence: 88%

Prognostic Accuracy of the qSOFA Score for In-Hospital Mortality in Elderly Patients with Obstructive Acute Pyelonephritis: A Multi-Institutional Study

et al. 2021

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Prognostic accuracy of the quick sequential organ failure assessment (qSOFA) score for mortality may be limited in elderly patients. Using our multi-institutional database, we classified obstructive acute pyelonephritis (OAPN) patients into young and elderly groups, and evaluated predictive performance of the qSOFA score for in-hospital mortality. qSOFA score ≥ 2 was an independent predictor for in-hospital mortality, as was higher age, and Charlson comorbidity index (CCI) ≥ 2. In young patients, the area under the curve (AUC) of the qSOFA score for in-hospital mortality was 0.85, whereas it was 0.61 in elderly patients. The sensitivity and specificity of qSOFA score ≥ 2 for in-hospital mortality was 80% and 80% in young patients, and 50% and 68% in elderly patients, respectively. For elderly patients, we developed the CCI-incorporated qSOFA score, which showed higher prognostic accuracy compared with the qSOFA score (AUC, 0.66 vs. 0.61, p < 0.001). Therefore, the prognostic accuracy of the qSOFA score for in-hospital mortality was high in young OAPN patients, but modest in elderly patients. Although it can work as a screening tool to determine therapeutic management in young patients, for elderly patients, the presence of comorbidities should be considered at the initial assessment.

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“…Given that age is an independent predictor of do not resuscitate (DNR) status, 16 elderly patients may have a higher rate of DNR status 16 and, thus, a higher mortality rate and lower likelihood of undergoing invasive procedures (e.g, intubation). 17 Finally, at the time of this study, certain medications were experimental drugs that adhered to strict inclusion criteria. Elderly patients with more comorbidities may have been more likely to have been excluded in the clinical trials because of underlying conditions.…”

Section: Discussionmentioning

confidence: 99%

Identification of Phenotypes Among COVID-19 Patients in the United States Using Latent Class Analysis

Teng¹,

Thampy²,

Bae³

et al. 2021

IDR

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Background Coronavirus disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 or COVID-19) is a heterogeneous disorder with a complex pathogenesis. Recent studies from Spain and France have indicated that underlying phenotypes may exist among patients admitted to the hospital with COVID-19. Whether those same phenotypes exist in the United States (US) remains unclear. Using latent class analysis (LCA), we sought to determine whether clinical phenotypes exist among patients admitted for COVID-19. Methods We reviewed the charts of adult patients who were hospitalized primarily for COVID-19 at Greenwich Hospital and performed LCA using variables based on patient demographics and comorbidities. To further examine the reliability and replicability of the clustering results, we repeated LCA on the cohort of patients who died during hospitalization for COVID-19. Results Two phenotypes were identified in patients admitted for COVID-19 (N = 483). According to phenotype, patients were designated as cluster 1 (C1) or cluster 2 (C2). C1 (n = 193) consisted of older individuals with more comorbidities and a higher mortality rate (25.4% vs 8.97%, p < 0.001) than patients in C2. C2 (n = 290) consisted of younger individuals who were more likely to be obese, male, and nonwhite, with higher levels of the inflammatory markers C-reactive protein and alanine aminotransferase. When we performed LCA on the cohort of patients who died during hospitalization for COVID-19 (n = 75), we found that the distribution of patient baseline characteristics and comorbidities was similar to that of the entire cohort of patients admitted for COVID-19. Conclusion Using LCA, we identified two clinical phenotypes of patients who were admitted to our hospital for COVID-19. These findings may reflect different pathophysiologic processes that lead to moderate to severe COVID-19 and may be useful for identifying treatment targets and selecting patients with severe COVID-19 disease for future clinical trials.

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Predictors of Mortality in Elderly and Very Elderly Emergency Patients with Sepsis: A Retrospective Study

Cited by 36 publications

References 27 publications

Cluster analysis integrating age and body temperature for mortality in patients with sepsis: a multicenter retrospective study

Cluster analysis integrating age and body temperature for mortality in patients with sepsis: a multicenter retrospective study

Prognostic Accuracy of the qSOFA Score for In-Hospital Mortality in Elderly Patients with Obstructive Acute Pyelonephritis: A Multi-Institutional Study

Identification of Phenotypes Among COVID-19 Patients in the United States Using Latent Class Analysis

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