Impact of a hospital‐wide sepsis pathway on improved quality of care and clinical outcomes in surgical patients at a comprehensive cancer centre

Hiong, Alison; Thursky, Karin; Venn, Georgina; Teh, Benjamin W; Haeusler, Gabrielle M; Crane, Megan; Slavin, Monica; Worth, Leon J

doi:10.1111/ecc.13018

Cited by 3 publications

(2 citation statements)

References 32 publications

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“…Infection leading to sepsis is a major cause of readmissions and is associated with significantly higher healthcare costs and worse patient outcomes 62 , 63 . However, early detection of infection has been associated with better outcomes; therefore, Fitbit data could lead to better patient outcomes and lower healthcare costs 64 , 65 .…”

Section: Discussionmentioning

confidence: 99%

Applying machine learning to consumer wearable data for the early detection of complications after pediatric appendectomy

Ghomrawi,

O’Brien,

Carter

et al. 2023

npj Digit. Med.

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When children are discharged from the hospital after surgery, their caregivers often rely on subjective assessments (e.g., appetite, fatigue) to monitor postoperative recovery as objective assessment tools are scarce at home. Such imprecise and one-dimensional evaluations can result in unwarranted emergency department visits or delayed care. To address this gap in postoperative monitoring, we evaluated the ability of a consumer-grade wearable device, Fitbit, which records multimodal data about daily physical activity, heart rate, and sleep, in detecting abnormal recovery early in children recovering after appendectomy. One hundred and sixty-two children, ages 3–17 years old, who underwent an appendectomy (86 complicated and 76 simple cases of appendicitis) wore a Fitbit device on their wrist for 21 days postoperatively. Abnormal recovery events (i.e., abnormal symptoms or confirmed postoperative complications) that arose during this period were gathered from medical records and patient reports. Fitbit-derived measures, as well as demographic and clinical characteristics, were used to train machine learning models to retrospectively detect abnormal recovery in the two days leading up to the event for patients with complicated and simple appendicitis. A balanced random forest classifier accurately detected 83% of these abnormal recovery days in complicated appendicitis and 70% of abnormal recovery days in simple appendicitis prior to the true report of a symptom/complication. These results support the development of machine learning algorithms to predict onset of abnormal symptoms and complications in children undergoing surgery, and the use of consumer wearables as monitoring tools for early detection of postoperative events.

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Section: Discussionmentioning

confidence: 99%

Applying machine learning to consumer wearable data for the early detection of complications after pediatric appendectomy

Ghomrawi,

O’Brien,

Carter

et al. 2023

npj Digit. Med.

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show abstract

“…These parameters may have clinical applicability in differentiating patients at high risk of clinical deterioration and poor outcome from those at low risk. Early differentiation allows targeted therapy and appropriate resource allocation, and has been shown to improve outcomes in non‐neutropaenic children, 11 and adults with cancer 12 . Despite the frequency with which these parameters are utilised in the ED to triage and risk stratify the general paediatric population, they have not been specifically evaluated in children with FN.…”

Section: Introductionmentioning

confidence: 99%

Prevalence and predictors of poor outcome in children with febrile neutropaenia presenting to the emergency department

Long

Babl

Phillips

et al. 2022

Emerg Medicine Australasia

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Objective Children with acquired neutropaenia due to cancer chemotherapy are at high risk of severe infection. The present study aims to describe the prevalence and predictors of poor outcomes in children with febrile neutropaenia (FN). Methods This is a multicentre, prospective observational study in tertiary Australian EDs. Cancer patients with FN were included. Fever was defined as a single temperature ≥38°C, and neutropaenia was defined as an absolute neutrophil count <1000/mm3. The primary outcome was the ICU admission for organ support therapy (inotropic support, mechanical ventilation, renal replacement therapy, extracorporeal life support). Secondary outcomes were: ICU admission, ICU length of stay (LOS) ≥3 days, proven or probable bacterial infection, hospital LOS ≥7 days and 28‐day mortality. Initial vital signs, biomarkers (including lactate) and clinical sepsis scores, including Systemic Inflammatory Response Syndrome, quick Sequential Organ Failure Assessment and quick Paediatric Logistic Organ Dysfunction‐2 were evaluated as predictors of poor outcomes. Results Between December 2016 and January 2018, 2124 episodes of fever in children with cancer were screened, 547 episodes in 334 children met inclusion criteria. Four episodes resulted in ICU admission for organ support therapy, nine episodes required ICU admission, ICU LOS was ≥3 days in four, hospital LOS was ≥7 days in 153 and two patients died within 28 days. Vital signs, blood tests and clinical sepsis scores, including Systemic Inflammatory Response Syndrome, quick Sequential Organ Failure Assessment and quick Paediatric Logistic Organ Dysfunction‐2, performed poorly as predictors of these outcomes (area under the receiver operating characteristic curve <0.6). Conclusions Very few patients with FN required ICU‐level care. Vital signs, biomarkers and clinical sepsis scores for the prediction of poor outcomes are of limited utility in children with FN.

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Letter in reply to Carboni F et al

Smibert

Worth

2021

Support Care Cancer

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Impact of a hospital‐wide sepsis pathway on improved quality of care and clinical outcomes in surgical patients at a comprehensive cancer centre

Cited by 3 publications

References 32 publications

Applying machine learning to consumer wearable data for the early detection of complications after pediatric appendectomy

Applying machine learning to consumer wearable data for the early detection of complications after pediatric appendectomy

Prevalence and predictors of poor outcome in children with febrile neutropaenia presenting to the emergency department

Letter in reply to Carboni F et al

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