Post–intensive care syndrome and health-related quality of life in long-term survivors of intensive care unit

Kim, Seung Jun; Park, Kyung-Sook; Kim, Kisook

doi:10.1016/j.aucc.2022.06.002

Cited by 15 publications

(6 citation statements)

References 46 publications

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“…In our study, educational level rarely explained differences in QoL apart from a number of issues within the domains of physical health and ADL. This is in line with a recent study showing a correlation between educational level and in particular the ADL component of PICS in impaired health‐related QoL after intensive care 30 . The structure and reasons for these findings need to be further studied.…”

Section: Discussionsupporting

confidence: 88%

“…This is in line with a recent study showing a correlation between educational level and in particular the ADL component of PICS in impaired health-related QoL after intensive care. 30 The structure and reasons for these findings need to be further studied. Our results within the domain of Cognition differ from studies correlating a low educational level with cognitive impairment after intensive care.…”

Section: Discussionmentioning

confidence: 99%

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The relationship between ICU survivorship, comorbidity and educational level in quality of life after intensive care

Malmgren

Johannesson

Waldenström

et al. 2023

Acta Anaesthesiol Scand

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BackgroundICU survivors have lower quality of life (QoL) compared to a non‐ICU‐treated population. The reason for this is not fully understood, but differences in baseline characteristics may be an important factor. This study evaluates the roles of comorbidity and educational level as possible explanatory factors for differences in QoL in ICU survivors compared to a non‐ICU‐treated population.MethodsUsing a provisional questionnaire with 218 questions in 13 domains on QoL after intensive care, we compared the responses from 395 adult ICU survivors and 195 non‐ICU‐treated controls. An initial bivariable linear correlation analysis compared the responses from the two groups. Two secondary multivariable regression analyses tested for effect modification by comorbidity and educational level, respectively, on the effect on QoL from belonging to the ICU survivor group compared to the control group.ResultsThere was a significant difference in QoL between the two groups in 170 of 218 (78%) questions. In the multivariable analyses, associations between group belonging and QoL remained in 139 questions. In 59 of these, both belonging to the ICU survivor group and comorbidity was associated to QoL, in parallel to each other. Comorbidity moderated the association between group belonging and QoL in six questions, with the highest proportion of questions within the domains of cognition and urinary functions, and the lowest proportion within appetite and alcohol, physical health, and fatigue. In 26 questions, both belonging to the ICU survivor group and educational level were associated to QoL, in parallel to each other. Educational level moderated the association between group belonging and QoL in 34 questions, with the highest proportion of questions within the domains of urinary functions, ADL and physical health, and the lowest proportion within the domains of cognition, appetite and alcohol, pain, sensory functions, and fatigue.ConclusionsLower QoL seen in ICU survivors compared to non‐ICU‐treated controls, as measured by our provisional questionnaire, cannot be explained only by a higher burden of comorbidity, and rarely by only educational level. In issues where comorbidity or educational level was associated to QoL, it often was so in parallel to an association from belonging to the ICU survivor group. Comparing QoL in ICU survivors to that of a non‐ICU‐treated population may be adequate despite differences in baseline characteristics.

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Section: Discussionsupporting

confidence: 88%

Section: Discussionmentioning

confidence: 99%

The relationship between ICU survivorship, comorbidity and educational level in quality of life after intensive care

Malmgren

Johannesson

Waldenström

et al. 2023

Acta Anaesthesiol Scand

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“…The cluster of mid-term mortality (31 to 180 days) and long-term mortality (181 to 365 days) has been under-studied in the scientific literature but, in terms of mortality rate, was very comparable to the cumulative 1-year mortality of surviving patients admitted to an ICU [ 14 ], or to the 31–365-day mortality cluster in the aforementioned Finnish study [ 7 ]. The observed excess mortality in patients following acute life-threatening illness and after ICU admission could result from post-intensive care syndrome (PICS), characterized by a combination of physical, cognitive, and mental symptoms involving a post-discharge deterioration in quality of life and correlated with poorer long-term outcomes [ 15 ]. A comparable pathophysiological mechanism may be observed in patients managed by EMS in critical condition who require prehospital critical care [ 9 , 16 , 17 ].…”

Section: Discussionmentioning

confidence: 99%

A Comparison of the Clinical Characteristics of Short-, Mid-, and Long-Term Mortality in Patients Attended by the Emergency Medical Services: An Observational Study

Enriquez de Salamanca Gambara,

Sanz-García,

del Pozo Vegas

et al. 2024

Diagnostics

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Aim: The development of predictive models for patients treated by emergency medical services (EMS) is on the rise in the emergency field. However, how these models evolve over time has not been studied. The objective of the present work is to compare the characteristics of patients who present mortality in the short, medium and long term, and to derive and validate a predictive model for each mortality time. Methods: A prospective multicenter study was conducted, which included adult patients with unselected acute illness who were treated by EMS. The primary outcome was noncumulative mortality from all causes by time windows including 30-day mortality, 31- to 180-day mortality, and 181- to 365-day mortality. Prehospital predictors included demographic variables, standard vital signs, prehospital laboratory tests, and comorbidities. Results: A total of 4830 patients were enrolled. The noncumulative mortalities at 30, 180, and 365 days were 10.8%, 6.6%, and 3.5%, respectively. The best predictive value was shown for 30-day mortality (AUC = 0.930; 95% CI: 0.919–0.940), followed by 180-day (AUC = 0.852; 95% CI: 0.832–0.871) and 365-day (AUC = 0.806; 95% CI: 0.778–0.833) mortality. Discussion: Rapid characterization of patients at risk of short-, medium-, or long-term mortality could help EMS to improve the treatment of patients suffering from acute illnesses.

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“…The management of care in ICUs is undergoing recent changes, with the current model being replaced by one that aims to reduce mortality and improve the quality of life of survivors (5). It should be noted, however, that a balance needs to be reached between these perspectives and nursing care, based on basic human needs (BHNs), which can enable nurses and patients to become closer, including ICUs, where critically ill patients are present (6).…”

Section: Introductionmentioning

confidence: 99%

Nursing Admission Form for Oncology Intensive Care Unit Patients: Production and Validation

Carvalho,

Lima,

Menezes

et al. 2023

Aquichan

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Introduction: Assistive technology is aimed at improving the quality of nursing care for patients admitted to oncology intensive care units (ICUs). Objective: To develop a nursing admission form for patients admitted to an oncology intensive care unit. Materials and methods: This is a methodological study conducted in three stages: 1) an integrative literature review to compose the content of the research form, 2) content validation, which included the participation and approval of 15 specialists (nurses) using Pasquali’s concordance validation method, and 3) presentation of the final version of the form. Results: A total of 20 articles were included in the review; the first version of the form was structured based on the thematic synthesis; 15 specialists participated in content validation and, after completion of the instrument, it was found that all the items had a content validation index ≥ 0.85; based on the suggestions, the admission form was organized into blocks of items: identification, brief history, admission conditions, and physical examination, with a total of four items. Conclusions: The nursing survey form for patients admitted to oncology ICUs is suitable for use by the nursing team at the time of patient admission, enabling data recording to support the planning and systematization of care in the oncology ICU setting.

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Post–intensive care syndrome and health-related quality of life in long-term survivors of intensive care unit

Cited by 15 publications

References 46 publications

The relationship between ICU survivorship, comorbidity and educational level in quality of life after intensive care

The relationship between ICU survivorship, comorbidity and educational level in quality of life after intensive care

A Comparison of the Clinical Characteristics of Short-, Mid-, and Long-Term Mortality in Patients Attended by the Emergency Medical Services: An Observational Study

Nursing Admission Form for Oncology Intensive Care Unit Patients: Production and Validation

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