11 research outputs found
Generalisability of deep learning-based early warning in the intensive care unit: a retrospective empirical evaluation
Deep learning (DL) can aid doctors in detecting worsening patient states
early, affording them time to react and prevent bad outcomes. While DL-based
early warning models usually work well in the hospitals they were trained for,
they tend to be less reliable when applied at new hospitals. This makes it
difficult to deploy them at scale. Using carefully harmonised intensive care
data from four data sources across Europe and the US (totalling 334,812 stays),
we systematically assessed the reliability of DL models for three common
adverse events: death, acute kidney injury (AKI), and sepsis. We tested whether
using more than one data source and/or explicitly optimising for
generalisability during training improves model performance at new hospitals.
We found that models achieved high AUROC for mortality (0.838-0.869), AKI
(0.823-0.866), and sepsis (0.749-0.824) at the training hospital. As expected,
performance dropped at new hospitals, sometimes by as much as -0.200. Using
more than one data source for training mitigated the performance drop, with
multi-source models performing roughly on par with the best single-source
model. This suggests that as data from more hospitals become available for
training, model robustness is likely to increase, lower-bounding robustness
with the performance of the most applicable data source in the training data.
Dedicated methods promoting generalisability did not noticeably improve
performance in our experiments
Predicting lethal courses in critically ill COVID-19 patients using a machine learning model trained on patients with non-COVID-19 viral pneumonia
In a pandemic with a novel disease, disease-specific prognosis models are available only with a delay. To bridge the critical early phase, models built for similar diseases might be applied. To test the accuracy of such a knowledge transfer, we investigated how precise lethal courses in critically ill COVID-19 patients can be predicted by a model trained on critically ill non-COVID-19 viral pneumonia patients. We trained gradient boosted decision tree models on 718 (245 deceased) non-COVID-19 viral pneumonia patients to predict individual ICU mortality and applied it to 1054 (369 deceased) COVID-19 patients. Our model showed a significantly better predictive performance (AUROC 0.86 [95% CI 0.86-0.87]) than the clinical scores APACHE2 (0.63 [95% CI 0.61-0.65]), SAPS2 (0.72 [95% CI 0.71-0.74]) and SOFA (0.76 [95% CI 0.75-0.77]), the COVID-19-specific mortality prediction models of Zhou (0.76 [95% CI 0.73-0.78]) and Wang (laboratory: 0.62 [95% CI 0.59-0.65]; clinical: 0.56 [95% CI 0.55-0.58]) and the 4C COVID-19 Mortality score (0.71 [95% CI 0.70-0.72]). We conclude that lethal courses in critically ill COVID-19 patients can be predicted by a machine learning model trained on non-COVID-19 patients. Our results suggest that in a pandemic with a novel disease, prognosis models built for similar diseases can be applied, even when the diseases differ in time courses and in rates of critical and lethal courses
The nociceptive flexion reflex as a measure of antinociception under general anesthesia
Neben der Bewusstlosigkeit ist die UnterdrĂŒckung von Nozizeption, also die
UnterdrĂŒckung der Sinneswahrnehmung von Schmerz, einer der essentiellen
Bestandteile der AllgemeinanÀsthesie. Da sowohl unzureichende, wie auch
ĂŒberschieĂende Gaben von Analgetika im Rahmen der AllgemeinanĂ€sthesie das
perioperative Outcome negativ beeinflussen könnten, ist deren optimale
Dosierung ein zentrales klinisches Ziel. Im Rahmen der hier zusammengefassten
Studien stellen wir ein Verfahren vor, welches im Sinne eines âAnalgesie-
Indexâ eine optimale Dosierung von antinozizeptiven Medikamenten im Rahmen der
AllgemeinanĂ€sthesie unterstĂŒtzen könnte. Das Verfahren basiert auf einer
kontinuierlichen Bestimmung der Schwelle des nozizeptiven Flexorenreflexes,
welcher mit Hilfe elektrischer Stimulation am AuĂenknöchel ausgelöst und
mittels Elektromyografie ĂŒber dem Oberschenkel abgeleitet werden kann. Wir
konnten anhand von Probandenstudien zeigen, dass diese Schwelle des
nozizeptiven Flexorenreflexes sowohl unter Mononarkosen mit Propofol und
Sevofluran, sowie auch unter Narkose mit Propofol und Remifentanil in
wechselnden Dosierungen, zuverlÀssig bestimmt werden kann und jeweils
konzentrationsabhÀngig durch die einzelnen Medikamente beeinflusst wird. Des
Weiteren konnten wir zeigen, dass anhand des Reflexes Vorhersagen von
Bewegungen auf einen elektrischen Schmerzreiz getroffen werden können: dabei
ergab sich unter Propofolmononarkose eine Àhnliche PrÀzision wie mittels des
Bispektralindex, und unter Sevofluran und Propofol-Remifentanil jeweils eine
höhere PrĂ€zision. Im Rahmen einer Patientenstudie konnten wir darĂŒber hinaus
zeigen, dass der nozizeptive Flexorenreflex auch im klinischen Umfeld
zuverlÀssig eingesetzt werden kann. Unter Kombinationsnarkose mit Propofol und
Remifentanil erlaubte der nozizeptive Flexorenreflex hierbei eine Vorhersage
sowohl von Bewegungsreaktionen, als auch von Herzfrequenzanstiegen, welche
jeweils nach Einlage der Larynxmaske und nach Hautschnitt auftraten. Die
PrĂ€zision der Vorhersagen ĂŒbertraf dabei alle anderen untersuchten
Monitoringparameter wie Bispektralindex, Composite Variability Index, Noxious
Stimulation Response Index und die Medikamentenkonzentrationen. Der
nozizeptive Flexorenreflex stellt somit einen zuverlÀssigen funktionellen
Surrogatparameter fĂŒr klinische AusdrĂŒcke der Nozizeption dar. Die Korrelation
des Reflexes mit den klinischen Schmerzreaktionen bleibt auch unter
AnÀsthetika mit unterschiedlichen molekularen Wirkmechanismen und unter
Medikamentenkombinationen erhalten.Next to unconsciousness, the suppression of nociception is one of the
essential components of general anesthesia. Since both, too low dosing of
anesthetics as well as too high dosing of anesthetics, can lead to negative
perioperative outcome, optimal dosing of anesthetics is of vital importance.
In the here presented studies we introduced a method which can be used as an
âanalgesia-indexâ during general anesthesia to assist optimal dosing of
anesthetics. The method is based on a continual estimation of the threshold of
the nociceptive flexion reflex, which can be recorded using electromyography
of the biceps femoris muscle while stimulating the sural nerve. We were able
to show that the here presented method allows a reliable estimation of the
threshold of the nociceptive flexion reflex unter mono-anesthesia using
propofol or sevofluran, as well as under anesthesia using propofol and
remifentanil in varying concentrations. The reflex threshold was affected in a
dose-dependant manner by all investigated anesthetics. We also able to
demonstrate, that the reflex threshold allows a prediction of movement
responses following a painful electrical stimulus. The accuracy of the
predictions using the reflex threshold under propofol was similar as the
accuracy of predictions using the eeg-parameter bispectral index. The accuracy
of predictions using the reflex threshold under sevofluran and propofol-
remifentanil combination were higher compared to the bispectral index.
Furthermore, we were able to show in a clinical study on patients, that the
nociceptive flexion reflex can be recorded reliably in the clinical setting.
Under combined anesthesia using propofol and remifentanil, the nociceptive
flexion reflex allowed a prediction of movement responses as well as heart
rate responses after insertion of the laryngeal mask and after skin incision.
The accuracy of the predictions based on the reflex threshold was higher than
all other investigated monitoring parameters, namely the bispectral index, the
composite variability index, the noxious stimulation response index and the
drug concentrations. We conclude that the nociceptive flexion reflex is a
reliable functional surrogate parameter for clinical expressions of
nociception under general anesthesia. The correlation of the reflex threshold
with clinical pain responses remains unaffected even when anesthetics with
different molecular targets are used
Inhibitory mechanisms of the alpha-motoneuronal excitability of propofol, sevoflurane and nitrous oxide in the human spinal cord
Es wird angenommen, dass die UnterdrĂŒckung motorischer Reaktionen auf
Schmerzreize durch AnĂ€sthetika zumindest teilweise ĂŒber eine Abnahme der
Erregbarkeit von alpha-Motoneuronen vermittelt wird. Diese Abnahme der
Erregbarkeit kann eine Folge von prÀ- und/oder postsynaptischen
Hemmungsmechanismen sein. Zur Bestimmung der relativen Anteile von prÀ- und
postsynaptischen Mechanismen an der jeweiligen Gesamthemmung untersuchten wir
am Menschen unter Einfluss von Propofol, Sevofluran und Lachgas im Vergleich
zu Kontrollbedingungen: i) die Amplitude des maximalen H-Reflexes als einen
direkter Parameter der alpha-motoneuronalen Erregbarkeit, welcher sowohl durch
prÀsynaptische als auch durch postsynaptische Hemmungsmechanismen beeinflusst
wird, und ii) die relative heteronyme Fazilitation des H-Reflexes als einen
anti-proportionalen Parameter der alleinigen prÀsynaptischen Hemmung. WÀhrend
Lachgas kaum prÀsynaptische Hemmung bei deutlicher Abnahme der alpha-
motoneuronalen Erregbarkeit zeigt, ergeben sich fĂŒr Sevofluran und Propofol
starke prÀ- sowie postsynaptische Hemmungsanteile. Die unterschiedlichen
AusmaĂe der prĂ€synaptischen Hemmung lassen sich durch die jeweiligen GABAergen
Wirkungen der einzelnen Medikamente erklĂ€ren: wĂ€hrend fĂŒr Lachgas kaum
GABAerge Effekte bekannt sind, stellen diese ein Hauptziel der spinalen
Wirkung von Sevofluran und Propofol dar. Die GABAergen Wirkungen von
Sevofluran und Propofol scheinen daher fĂŒr ihre Hemmung der alpha-
motoneuronalen Erregbarkeit und somit fĂŒr die UnterdrĂŒckung motorischer
Reaktionen auf Schmerzreize durch diese Stoffe von Bedeutung zu sein.The suppression of movement reactions to noxious stimuli under influence of
anesthetics is mediated at least in part by a reduction of the excitability of
alpha-motoneurons. This reduction of excitability can be a result of pre-
and/or postsynaptic inhibitory mechanisms. To investigate the relative amounts
of contribution of pre- and postsynaptic inhibitory mechanisms to the overall
reduction of motoneuronal excitability, we determined in humans under
influence of propofol, sevoflurane and nitrous oxide in comparison to control
states the following parameters: i) the amplitude of the maximum h-reflex as a
direct parameter of the alpha-motoneuronal excitability, which is susceptible
to both presynaptic and postsynaptic inhibitory mechanisms, and ii) the
relative amount of heteronymous facilitation of the h-reflex as an anti-
proportional parameter of the presynaptic inhibition only. While nitrous oxide
shows only a marginal amount of presynaptic inhibition along with a high
amount of reduction of motoneuronal excitability, sevoflurane and propofol
show both strong pre- and postsynaptic inhibitory fractions. The different
amounts of presynaptic inhibition could be explained by the GABAergic actions
of the different substances: while for nitrous oxide only very marginal
GABAergic effects are known, the GABAergic structures represent a major site
of action for the spinal mechanisms of propofol and sevoflurane. So the
GABAergic actions of sevoflurane and propofol seem to be of importance for
their inhibitory mechanisms of motoneuronal excitability and therefore for
their mechanisms of suppression of movement
Reliability of Subjective Pain Ratings and Nociceptive Flexion Reflex Responses as Measures of Conditioned Pain Modulation
BACKGROUND: The endogenous modulation of pain can be assessed through conditioned pain modulation (CPM), which can be quantified using subjective pain ratings or nociceptive flexion reflexes. However, to date, the test-retest reliability has only been investigated for subjective pain ratings
Technical considerations when using the EEG export of the SEDLine Root device
Electroencephalographic (EEG) patient monitoring during general anesthesia can help to assess the real-time neurophysiology of unconscious states. Some monitoring systems like the SEDLine Root allow export of the EEG to be used for retrospective analysis. We show that changes made to the SEDLine display during recording affected the recorded EEG. These changes can strongly impact retrospective analysis of EEG signals. Real-time changes of the feed speed in the SEDLine Root device display modifies the sampling rate of the exported EEG. We used a patient as well as a simulated EEG recording to highlight the effects of the display settings on the extracted EEG. Therefore, we changed EEG feed and amplitude resolution on the display in a systematic manner. To visualize the effects of these changes, we present raw EEG segments and the density spectral array of the recording. Changing the display's amplitude resolution affects the amplitudes. If the amplitude resolution is too fine, the exported EEG contains clipped amplitudes. If the resolution is too coarse, the EEG resolution becomes too low leading to a low-quality signal making frequency analysis impossible. The proportion of clipped or zero-line data caused by the amplitude setting was >â60% in our sedated patient. Changing the display settings results in undocumented changes in EEG amplitude, sampling rate, and signal quality. The occult nature of these changes could make the analysis of data sets difficult if not invalid. We strongly suggest researchers adequately define and keep the EEG display settings to export good quality EEG and to ensure comparability among patients
Presynaptic and Postsynaptic Effects of the Anesthetics Sevoflurane and Nitrous Oxide in the Human Spinal Cord
Background: Reduced spinal excitability contributes to the suppression of movement responses to noxious stimuli during the anesthetic state. This study examines and compares presynaptic and postsynaptic effects of two anesthetics in the human spinal cord. Methods: The authors tested two parameters during the administration of 0.8 vol% sevoflurane or 40 vol% nitrous oxide compared with control states before and after drug administration: (1) the size of the soleus H reflex (integrating presynaptic and postsynaptic effects) at increasing stimulus intensities (recruitment curve) and (2) the amount of presynaptic inhibition on Ia afferents of the quadriceps femoris, evaluated by the heteronymous facilitation of the soleus H reflex caused by a conditioning stimulation of the femoral nerve. The study was performed in 10 subjects for each drug. Results: At the chosen concentrations, the maximum H reflex was reduced by 26.3 Ű 8.4% (mean Ű SD) during sevoflurane and by 33.5 Ű 15.6% during nitrous oxide administration. The averaged recruitment curves were similarly depressed under the influence of the two drugs. The reduction of H-reflex facilitation was significantly stronger for sevoflurane (28.8 Ű 20.0%) than for nitrous oxide administration (6.2 Ű 26.4%). Conclusions: These results demonstrate in humans presynaptic effects of the volatile anesthetic sevoflurane but not of nitrous oxide. A possible explanation for this difference may be the different potency of the respective drugs in enhancing â„-aminobutyric acid type A receptor-mediated inhibition, because presynaptic inhibition in the spinal cord involves this receptor subtype
Das Gesundheitsdatennutzungsgesetz und was dies fĂŒr die Forschung in der Intensiv- und Notfallmedizin bedeutet : ErlĂ€uterungen und erste Handlungsempfehlungen
The Health Data Utilization Act (GDNG) is the first nationwide legal basis for the use of healthcare data for research. Particularly relevant for intensive care and emergency medicine is the authorization of non-consensual data use (in-house research), including collaborative research by healthcare facilities. Another change is that there is a cultural shift from preventing unauthorised data use to transparency and control. These changes open up new opportunities for research, but are also associated with obligations. In this article, an interdisciplinary and interprofessional working group from three scientific societies explains the GDNG and formulates initial recommendations for action.Das Gesundheitsdatennutzungsgesetz (GDNG) schafft zum ersten Mal eine bundeseinheitliche Rechtsgrundlage fĂŒr die Nutzung von Versorgungsdaten fĂŒr die Forschung. FĂŒr die Intensiv- und Notfallmedizin ist besonders der Erlaubnistatbestand einer einwilligungsfreien Datennutzung (Eigenforschung) relevant, einschlieĂlich der Verbundforschung von Gesundheitseinrichtungen. DarĂŒber hinaus gibt es einen Kulturwechsel von der Verhinderung unerlaubter Datennutzung hin zu Transparenz und Kontrolle. Diese VerĂ€nderungen eröffnen neue Möglichkeiten fĂŒr die Forschung, sind aber auch mit Pflichten verbunden. In einer interdisziplinĂ€ren und interprofessionellen Arbeitsgruppe mit Vertretern von drei Fachgesellschaften wird in diesem Artikel das GDNG erlĂ€utert und erste Handlungsempfehlungen formuliert