Sepsis Infozentrale – Aktuelles Wissen rund um Sepsis
Unsere Sepsis Infozentrale bietet fundierte und unabhängige Informationen zur Prävention, Diagnostik, Behandlung und Nachsorge von Sepsis und auf die Versorgungsforschung rund um das Thema: Wie häufig ist Sepsis? Wie wird sie versorgt? Wie sind die Ergebnisse? Was erleben Patientinnen und Patienten?.
Ein zentrales Element ist unsere Literaturdatenbank, die eine qualifizierte Auswahl aktueller wissenschaftlicher Erkenntnisse aus renommierten Quellen bereitstellt. Durch regelmäßige, systematische Recherchen in der Medline-Datenbank der National Library of Medicine wird sie wöchentlich aktualisiert und erweitert – für stets aktuelle, evidenzbasierte Informationen.
Bleiben Sie informiert und vertiefen Sie Ihr Wissen rund um Sepsis!
Unsere Wissens- und Literatur-Datenbank richtet sich an Ärztinnen und Ärzte, die in die Prävention, Diagnostik, Behandlung und Nachsorge der Sepsis eingebunden sind, an medizinische Fachkräfte, Patientinnen und Patienten sowie Selbsthilfegruppen. Sie dient auch zur Information anderer Organisationen des Gesundheitswesens und der interessierten Fachöffentlichkeit.
Informationen zur Literaturdatenbank
Die Datenbank bietet eine qualifizierte Auswahl aktueller, unabhängiger Informationen zur Prävention, Diagnostik, Behandlung und Nachsorge von Sepsis. Auf Grund der äußerst engen pathophysiologischen Verknüpfungen der COVID-19-Erkrankung und der Sepsis werden auch diesbezügliche Publikationen unabhängig von einem septischen Verlauf der SARS-CoV-2-Infektion eingeschlossen. Die vorliegende Liste berücksichtigt Publikationen, die aus Literaturverzeichnissen von Leitlinien, internationalen Fachgesellschaften und Organisationen, sowie aus systematischen Reviews ausgewählt wurden, ergänzt durch Expertenempfehlungen. Die Datenbank wird wöchentlich durch systematische Literatursuche in der Medline-Datenbank der National Library of Medicine aktualisiert und die Ergebnisse vom Redaktionsteam hinsichtlich der Relevanz bewertet. Die gelisteten Publikationen werden nach wissenschaftlicher Qualität und Evidenz ausgewählt, jedoch ohne systematische Quantifizierung der Evidenz. Die Datenbank erhebt nicht den Anspruch auf Vollständigkeit. Der wissenschaftliche Beirat der Sepsis-Stiftung überprüft die Auswahl jährlich. Ein Klick auf den im Pfeil integrierten DOI-Link öffnet das jeweilige Abstract oder den Volltext der entsprechenden Publikation in einem neuen Tab.
Predicting sepsis using deep learning across international sites: a retrospective development and validation study
Bastian Rieck, Drago Plečko, Karsten Borgwardt, Max Horn, Michael Moor, Nicolai Meinshausen, Nicolas Bennett, Peter Bühlmann — EClinicalMedicine
★★★☆☆
2023
Abstract
Background: When sepsis is detected, organ damage may have progressed to
irreversible stages, leading to poor prognosis. The use of machine learning for
predicting sepsis early has shown promise, however international validations are
missing. Methods: This was a retrospective, observational, multi-centre cohort
study. We developed and externally validated a deep learning system for the
prediction…
Background: When sepsis is detected, organ damage may have progressed to
irreversible stages, leading to poor prognosis. The use of machine learning for
predicting sepsis early has shown promise, however international validations are
missing. Methods: This was a retrospective, observational, multi-centre cohort
study. We developed and externally validated a deep learning system for the
prediction of sepsis in the intensive care unit (ICU). Our analysis represents
the first international, multi-centre in-ICU cohort study for sepsis prediction
using deep learning to our knowledge. Our dataset contains 136,478 unique ICU
admissions, representing a refined and harmonised subset of four large ICU
databases comprising data collected from ICUs in the US, the Netherlands, and
Switzerland between 2001 and 2016. Using the international consensus definition
Sepsis-3, we derived hourly-resolved sepsis annotations, amounting to 25,694
(18.8%) patient stays with sepsis. We compared our approach to clinical
baselines as well as machine learning baselines and performed an extensive
internal and external statistical validation within and across databases,
reporting area under the receiver-operating-characteristic curve (AUC).
Findings: Averaged over sites, our model was able to predict sepsis with an AUC
of 0.846 (95% confidence interval [CI], 0.841-0.852) on a held-out validation
cohort internal to each site, and an AUC of 0.761 (95% CI, 0.746-0.770) when
validating externally across sites. Given access to a small fine-tuning set (10%
per site), the transfer to target sites was improved to an AUC of 0.807 (95% CI,
0.801-0.813). Our model raised 1.4 false alerts per true alert and detected 80%
of the septic patients 3.7 h (95% CI, 3.0-4.3) prior to the onset of sepsis,
opening a vital window for intervention. Interpretation: By monitoring clinical
and laboratory measurements in a retrospective simulation of a real-time
prediction scenario, a deep learning system for the detection of sepsis
generalised to previously unseen ICU cohorts, internationally. Funding: This
study was funded by the Personalized Health and Related Technologies (PHRT)
strategic focus area of the ETH domain.
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Alex J Walker, Alex S F Kwong, Charlotte F Huggins, Claire L Niedzwiedz, Dylan M Williams, Ellen J Thompson, Giorgio Di Gessa, Richard J Silverwood, Ruth E Mitchell, Tiffany C Yang — Nature communications
★★★☆☆
2022
Abstract
The frequency of, and risk factors for, long COVID are unclear among
community-based individuals with a history of COVID-19. To elucidate the burden
and possible causes of long COVID in the community, we coordinated analyses of
survey data from 6907 individuals with self-reported COVID-19 from 10 UK
longitudinal study (LS) samples and 1.1 million…
The frequency of, and risk factors for, long COVID are unclear among
community-based individuals with a history of COVID-19. To elucidate the burden
and possible causes of long COVID in the community, we coordinated analyses of
survey data from 6907 individuals with self-reported COVID-19 from 10 UK
longitudinal study (LS) samples and 1.1 million individuals with COVID-19
diagnostic codes in electronic healthcare records (EHR) collected by spring
2021. Proportions of presumed COVID-19 cases in LS reporting any symptoms for
12+ weeks ranged from 7.8% and 17% (with 1.2 to 4.8% reporting debilitating
symptoms). Increasing age, female sex, white ethnicity, poor pre-pandemic
general and mental health, overweight/obesity, and asthma were associated with
prolonged symptoms in both LS and EHR data, but findings for other factors, such
as cardio-metabolic parameters, were inconclusive.
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A Danielle Iuliano, Benjamin J Silk, Betsy L Cadwell, Charles Rose, Heather E Reese, Ian D Plumb, Mark W Tenforde, Owen J Devine, Quan M Vu, Ryan Threlkel — The Journal of infectious diseases
★★★☆☆
2022
Abstract
Background: Although most adults infected with SARS-CoV-2 fully recover, a
proportion have ongoing symptoms, or post-COVID conditions (PCC), after
infection. The objective of this analysis was to estimate the number of US
adults with activity-limiting PCC on November 1, 2021. Methods: We modeled the
prevalence of PCC using reported infections occurring from February 1,…
Background: Although most adults infected with SARS-CoV-2 fully recover, a
proportion have ongoing symptoms, or post-COVID conditions (PCC), after
infection. The objective of this analysis was to estimate the number of US
adults with activity-limiting PCC on November 1, 2021. Methods: We modeled the
prevalence of PCC using reported infections occurring from February 1, 2020 –
September 30, 2021, and population-based, household survey data on new
activity-limiting symptoms ≥1 month following SARS-CoV-2 infection. From these
data sources, we estimated the number and proportion of US adults with
activity-limiting PCC on November 1, 2021, as 95% uncertainty intervals,
stratified by sex and age. Sensitivity analyses adjusted for under-ascertainment
of infections and uncertainty about symptom duration. Results: On November 1,
2021, at least 3.0-5.0 million US adults were estimated to have
activity-limiting PCC of ≥1 month duration, or 1.2%-1.9% of US adults.
Population prevalence was higher in females (1.4%-2.2%) than males. The
estimated prevalence after adjusting for under-ascertainment of infections was
1.7%-3.8%. Conclusion: Millions of US adults were estimated to have
activity-limiting PCC. These estimates can support future efforts to address the
impact of PCC on the U.S. population.
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Audai A Hayajneh, Dania Bani Hamad, Mohammad Rababa — PloS one
★★★☆☆
2022
Abstract
Background: Early assessment and management of patients with sepsis can
significantly reduce its high mortality rates and improve patient outcomes and
quality of life. Objectives: The purposes of this review are to: (1) explore
nurses‘ knowledge, attitude, practice, and perceived barriers and facilitators
related to early recognition and management of sepsis, (2) explore different
interventions…
Background: Early assessment and management of patients with sepsis can
significantly reduce its high mortality rates and improve patient outcomes and
quality of life. Objectives: The purposes of this review are to: (1) explore
nurses‘ knowledge, attitude, practice, and perceived barriers and facilitators
related to early recognition and management of sepsis, (2) explore different
interventions directed at nurses to improve sepsis management. Methods: A
systematic review method according to the PRISMA guidelines was used. An
electronic search was conducted in March 2021 on several databases using
combinations of keywords. Two researchers independently selected and screened
the articles according to the eligibility criteria. Results: Nurses reported an
adequate of knowledge in certain areas of sepsis assessment and management in
critically ill adult patients. Also, nurses‘ attitudes toward sepsis assessment
and management were positive in general, but they reported some misconceptions
regarding antibiotic use for patients with sepsis, and that sepsis was
inevitable for critically ill adult patients. Furthermore, nurses reported they
either were not well-prepared or confident enough to effectively recognize and
promptly manage sepsis. Also, there are different kinds of nurses‘ perceived
barriers and facilitators related to sepsis assessment and management: nurse,
patient, physician, and system-related. There are different interventions
directed at nurses to help in improving nurses‘ knowledge, attitudes, and
practice of sepsis assessment and management. These interventions include
education sessions, simulation, decision support or screening tools for sepsis,
and evidence-based treatment protocols/guidelines. Discussion: Our findings
could help hospital managers in developing continuous education and staff
development training programs on assessing and managing sepsis in critical care
patients. Conclusion: Nurses have poor to good knowledge, practices, and
attitudes toward sepsis as well as report many barriers related to sepsis
management in adult critically ill patients. Despite all education
interventions, no study has collectively targeted critical care nurses‘
knowledge, attitudes, and practice of sepsis management.
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Audai A Hayajneh, Dania Bani Hamad, Mohammad Rababa — PloS one
★★★☆☆
2022
Abstract
Background: Early assessment and management of patients with sepsis can
significantly reduce its high mortality rates and improve patient outcomes and
quality of life. Objectives: The purposes of this review are to: (1) explore
nurses‘ knowledge, attitude, practice, and perceived barriers and facilitators
related to early recognition and management of sepsis, (2) explore different
interventions…
Background: Early assessment and management of patients with sepsis can
significantly reduce its high mortality rates and improve patient outcomes and
quality of life. Objectives: The purposes of this review are to: (1) explore
nurses‘ knowledge, attitude, practice, and perceived barriers and facilitators
related to early recognition and management of sepsis, (2) explore different
interventions directed at nurses to improve sepsis management. Methods: A
systematic review method according to the PRISMA guidelines was used. An
electronic search was conducted in March 2021 on several databases using
combinations of keywords. Two researchers independently selected and screened
the articles according to the eligibility criteria. Results: Nurses reported an
adequate of knowledge in certain areas of sepsis assessment and management in
critically ill adult patients. Also, nurses‘ attitudes toward sepsis assessment
and management were positive in general, but they reported some misconceptions
regarding antibiotic use for patients with sepsis, and that sepsis was
inevitable for critically ill adult patients. Furthermore, nurses reported they
either were not well-prepared or confident enough to effectively recognize and
promptly manage sepsis. Also, there are different kinds of nurses‘ perceived
barriers and facilitators related to sepsis assessment and management: nurse,
patient, physician, and system-related. There are different interventions
directed at nurses to help in improving nurses‘ knowledge, attitudes, and
practice of sepsis assessment and management. These interventions include
education sessions, simulation, decision support or screening tools for sepsis,
and evidence-based treatment protocols/guidelines. Discussion: Our findings
could help hospital managers in developing continuous education and staff
development training programs on assessing and managing sepsis in critical care
patients. Conclusion: Nurses have poor to good knowledge, practices, and
attitudes toward sepsis as well as report many barriers related to sepsis
management in adult critically ill patients. Despite all education
interventions, no study has collectively targeted critical care nurses‘
knowledge, attitudes, and practice of sepsis management.
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Eileen M Crimmins, Jennifer A Ailshire, Qiao Wu — Scientific reports
★★★☆☆
2022
Abstract
People who have COVID-19 can experience symptoms for months. Studies on long
COVID in the population lack representative samples and longitudinal data
focusing on new-onset symptoms occurring with COVID while accounting for
pre-infection symptoms. We use a sample representing the U.S. community
population from the Understanding America Study COVID-19 Survey, which surveyed
around 8000 respondents…
People who have COVID-19 can experience symptoms for months. Studies on long
COVID in the population lack representative samples and longitudinal data
focusing on new-onset symptoms occurring with COVID while accounting for
pre-infection symptoms. We use a sample representing the U.S. community
population from the Understanding America Study COVID-19 Survey, which surveyed
around 8000 respondents bi-weekly from March 2020 to March 2021. Our final
sample includes 308 infected individuals who were interviewed one month before,
around the time of, and 12 weeks after infection. About 23% of the sample
experienced new-onset symptoms during infection which lasted for more than 12
weeks, and thus can be considered as having long COVID. The most common
new-onset persistent symptoms among those included in the study were headache
(22%), runny or stuffy nose (19%), abdominal discomfort (18%), fatigue (17%),
and diarrhea (13%). Long COVID was more likely among obese individuals (OR =
5.44, 95% CI 2.12-13.96) and those who experienced hair loss (OR = 6.94, 95% CI
1.03-46.92), headache (OR = 3.37, 95% CI 1.18-9.60), and sore throat (OR = 3.56,
95% CI 1.21-10.46) during infection. There was a lack of evidence relating risk
to age, gender, race/ethnicity, education, current smoking status, or comorbid
chronic conditions. This work provides national estimates of long COVID in a
representative sample after accounting for pre-infection symptoms.
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André Dankert, Christian Zöllner, Christoph Doehn, Clemens Bopp, Janina Bathe, Jochen Kraxner, Linda Krause, Malte Issleib, Martin Petzoldt, Philipp Breitfeld — Journal of clinical medicine
★★★☆☆
2022
Abstract
Background: This study aimed to determine whether prehospital qSOFA (quick
sequential organ failure assessment) assessment was associated with a shortened
‚time to antibiotics‘ and ‚time to intravenous fluid resuscitation‘ compared
with standard assessment. Methods: This retrospective study included patients
who were referred to our Emergency Department between 2014 and 2018 by emergency
medical services, in…
Background: This study aimed to determine whether prehospital qSOFA (quick
sequential organ failure assessment) assessment was associated with a shortened
‚time to antibiotics‘ and ‚time to intravenous fluid resuscitation‘ compared
with standard assessment. Methods: This retrospective study included patients
who were referred to our Emergency Department between 2014 and 2018 by emergency
medical services, in whom sepsis was diagnosed during hospitalization. Two
multivariable regression models were fitted, with and without qSOFA parameters,
for ‚time to antibiotics‘ (primary endpoint) and ‚time to intravenous fluid
resuscitation‘. Results: In total, 702 patients were included. Multiple linear
regression analysis showed that antibiotics and intravenous fluids were
initiated earlier if infections were suspected and emergency medical services
involved emergency physicians. A heart rate above 90/min was associated with a
shortened time to antibiotics. If qSOFA parameters were added to the models, a
respiratory rate ≥ 22/min and altered mentation were independent predictors for
earlier antibiotics. A systolic blood pressure ≤ 100 mmHg and altered mentation
were independent predictors for earlier fluids. When qSOFA parameters were
added, the explained variability of the model increased by 24% and 38%,
respectively (adjusted R² 0.106 versus 0.131 for antibiotics and 0.117 versus
0.162 for fluids). Conclusion: Prehospital assessment of qSOFA parameters was
associated with a shortened time to a targeted sepsis therapy. Keywords:
anti-infective agents, emergency medicine, fluid therapy, organ dysfunction
scores, sepsis, systemic inflammatory response syndrome
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