We appreciate the insightful commentary from Li et al. [1]. In our multicentre trial, the median time to loss of consciousness during induction of anaesthesia was 45 s and 25 s, for children aged 3–6 y receiving 0.3 mg.kg-1 remimazolam vs. 2.5 mg.kg-1 propofol, respectively [2]. Although the pharmacokinetic simulation from Li et al. suggests increased drug efficacy, our findings regarding time to loss of consciousness were consistent with previous paediatric research [3]. The use of remimazolam monotherapy for anaesthetic induction did indeed necessitate higher doses [4]. Notably, opioid co-administration can reduce the dose of sedative drugs, and our protocol for anaesthesia induction included intravenous administration of 3 μg.kg-1 fentanyl 3 min before injection of the study drugs. Consequently, we observed a Modified Observer's Assessment of Alertness/Sedation score of 3 or 2 in some patients before injection of the study drugs. This sequential approach was designed specifically to synchronise tracheal intubation with the peak opioid analgesic effect, accounting for known pharmacokinetic variability in paediatric populations.
Regarding the methods, our protocol mandated randomised administration of initial bolus doses; an injection duration < 60 s; and a standardised assessment of loss of consciousness with no response to gentle shoulder shaking. Consequently, establishing robust temporal pharmacokinetic-pharmacodynamic models between sedative drug administration and loss of consciousness through covariate-adjusted analyses (e.g. age, sex and BMI) using both linear and logistic regression approaches is crucial in optimising safe and effective anaesthetic induction in paediatric anaesthesia.
{"title":"Temporal characteristics of remimazolam-induced sedation in paediatric anaesthesia: a reply","authors":"Yu-Bo Fang, Hua-Cheng Liu","doi":"10.1111/anae.16615","DOIUrl":"https://doi.org/10.1111/anae.16615","url":null,"abstract":"<p>We appreciate the insightful commentary from Li et al. [<span>1</span>]. In our multicentre trial, the median time to loss of consciousness during induction of anaesthesia was 45 s and 25 s, for children aged 3–6 y receiving 0.3 mg.kg<sup>-1</sup> remimazolam vs. 2.5 mg.kg<sup>-1</sup> propofol, respectively [<span>2</span>]. Although the pharmacokinetic simulation from Li et al. suggests increased drug efficacy, our findings regarding time to loss of consciousness were consistent with previous paediatric research [<span>3</span>]. The use of remimazolam monotherapy for anaesthetic induction did indeed necessitate higher doses [<span>4</span>]. Notably, opioid co-administration can reduce the dose of sedative drugs, and our protocol for anaesthesia induction included intravenous administration of 3 μg.kg<sup>-1</sup> fentanyl 3 min before injection of the study drugs. Consequently, we observed a Modified Observer's Assessment of Alertness/Sedation score of 3 or 2 in some patients before injection of the study drugs. This sequential approach was designed specifically to synchronise tracheal intubation with the peak opioid analgesic effect, accounting for known pharmacokinetic variability in paediatric populations.</p>\u0000<p>Regarding the methods, our protocol mandated randomised administration of initial bolus doses; an injection duration < 60 s; and a standardised assessment of loss of consciousness with no response to gentle shoulder shaking. Consequently, establishing robust temporal pharmacokinetic-pharmacodynamic models between sedative drug administration and loss of consciousness through covariate-adjusted analyses (e.g. age, sex and BMI) using both linear and logistic regression approaches is crucial in optimising safe and effective anaesthetic induction in paediatric anaesthesia.</p>","PeriodicalId":7742,"journal":{"name":"Anaesthesia","volume":"1 1","pages":""},"PeriodicalIF":10.7,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143857830","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
<p>We read with great interest the article by Buiteman-Kruizinga et al. [<span>1</span>] which investigated the effect of individual components of mechanical ventilation on mechanical power and provided evidence that the respiratory rate may be the most attractive ventilator setting to adjust when targeting a lower mechanical power. The authors utilised data from three randomised clinical trials that involved patients receiving invasive mechanical ventilation in the form of either volume- or pressure-controlled ventilation for reasons other than acute respiratory distress syndrome (ARDS). In addition, the authors grouped the patients by an upper quartile cut-point of 17 J.min<sup>-1</sup> for mechanical power but did not segregate patients based on the mode of mechanical ventilation utilised.</p><p>This exploration aligns well with our study in which we modelled the effects of individual ventilator settings such as tidal volume, respiration rate and positive end-expiratory pressure on mechanical power across various ventilation modes and ARDS severity using a mathematical simulator [<span>2</span>]. Some of our findings align well with those of Buiteman-Kruizinga et al. However, our data showed that tidal volume reduction may be the most effective and consistent strategy for reducing mechanical power to ≤ 17 J.min<sup>-1</sup>, especially under volume-controlled ventilation with constant flow, which yielded the lowest mechanical power compared with pressure-controlled ventilation and descending ramp volume-controlled ventilation.</p><p>Notably, Buiteman-Kruizinga et al. emphasised respiratory rate as a prime target to lower mechanical power in patients without ARDS, whereas our modelling data suggest tidal volume reduction is more efficient in simulated ARDS scenarios. An obvious reason for this divergence is the fact that the patients in the study by Buiteman-Kruizinga et al. did not have ARDS while our study included simulated patients with mild, moderate and severe ARDS. However, we believe another important reason may be the fact that Buiteman-Kruizinga et al. did not segregate patients based on the mode of mechanical ventilation but mixed mechanical power values obtained under volume- and pressure-controlled ventilation despite mechanical power being expressed differently under these two widely used modes of mechanical ventilation [<span>3</span>]. While respiration rate is reflected as directly proportional to mechanical power in both expressions under volume- and pressure-controlled ventilation, tidal volume is not only reflected as directly proportional to mechanical power but also may be reflected through its indirect effect on driving pressure and peak airway pressure that are included in mechanical power expressions. For the same simulated lung mechanics, our data showed that volume-controlled ventilation results in lower generated mechanical power compared with pressure control given the same tidal volume and breathing frequency. Al
{"title":"Evaluating ventilator settings as related to mechanical power: tidal volume vs. respiratory rate dynamics","authors":"Mohamad F. El-Khatib, Robert L. Chatburn","doi":"10.1111/anae.16616","DOIUrl":"https://doi.org/10.1111/anae.16616","url":null,"abstract":"<p>We read with great interest the article by Buiteman-Kruizinga et al. [<span>1</span>] which investigated the effect of individual components of mechanical ventilation on mechanical power and provided evidence that the respiratory rate may be the most attractive ventilator setting to adjust when targeting a lower mechanical power. The authors utilised data from three randomised clinical trials that involved patients receiving invasive mechanical ventilation in the form of either volume- or pressure-controlled ventilation for reasons other than acute respiratory distress syndrome (ARDS). In addition, the authors grouped the patients by an upper quartile cut-point of 17 J.min<sup>-1</sup> for mechanical power but did not segregate patients based on the mode of mechanical ventilation utilised.</p>\u0000<p>This exploration aligns well with our study in which we modelled the effects of individual ventilator settings such as tidal volume, respiration rate and positive end-expiratory pressure on mechanical power across various ventilation modes and ARDS severity using a mathematical simulator [<span>2</span>]. Some of our findings align well with those of Buiteman-Kruizinga et al. However, our data showed that tidal volume reduction may be the most effective and consistent strategy for reducing mechanical power to ≤ 17 J.min<sup>-1</sup>, especially under volume-controlled ventilation with constant flow, which yielded the lowest mechanical power compared with pressure-controlled ventilation and descending ramp volume-controlled ventilation.</p>\u0000<p>Notably, Buiteman-Kruizinga et al. emphasised respiratory rate as a prime target to lower mechanical power in patients without ARDS, whereas our modelling data suggest tidal volume reduction is more efficient in simulated ARDS scenarios. An obvious reason for this divergence is the fact that the patients in the study by Buiteman-Kruizinga et al. did not have ARDS while our study included simulated patients with mild, moderate and severe ARDS. However, we believe another important reason may be the fact that Buiteman-Kruizinga et al. did not segregate patients based on the mode of mechanical ventilation but mixed mechanical power values obtained under volume- and pressure-controlled ventilation despite mechanical power being expressed differently under these two widely used modes of mechanical ventilation [<span>3</span>]. While respiration rate is reflected as directly proportional to mechanical power in both expressions under volume- and pressure-controlled ventilation, tidal volume is not only reflected as directly proportional to mechanical power but also may be reflected through its indirect effect on driving pressure and peak airway pressure that are included in mechanical power expressions. For the same simulated lung mechanics, our data showed that volume-controlled ventilation results in lower generated mechanical power compared with pressure control given the same tidal volume and breathing frequency. Al","PeriodicalId":7742,"journal":{"name":"Anaesthesia","volume":"91 1","pages":""},"PeriodicalIF":10.7,"publicationDate":"2025-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143853636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
<p>We thank Fajardo-Campoverdi et al. for their letter [<span>1</span>] and appreciate the insightful comments regarding our study about the effect of rate reduction on the amount of mechanical power [<span>2</span>]. The authors raise an interesting point about the potential influence of the way of flow delivery, whether constant or decelerated, on mechanical power.</p><p>We acknowledge that the method of inspiratory flow delivery can be a relevant factor in energy transfer within the respiratory system. The viscoelastic properties of lung tissue suggest that cyclic deformation, influenced by flow patterns, might contribute to mechanical power and tissue strain. Importantly, energy transfer is not solely determined by peak pressures but also by other parameters and the duration of the respiratory cycle [<span>3</span>]. Although our analysis did not examine the effects of inspiratory flow delivery explicitly, these are, to some extent, captured in the mechanical power equation through peak pressure, which is influenced by flow patterns and resistive pressure components.</p><p>We divided our analysed cohort into patients who received volume-controlled ventilation (n = 920) and those who received pressure-controlled ventilation (n = 812). We then repeated the analysis by creating four subgroups, each for tidal volume and respiratory rate and for peak pressure and respiratory rate. Mechanical power levels were visualised using cumulative distribution graphs for each subgroup. We observed no differences between the two ventilation modes, both in terms of the absolute mechanical power levels and differences in the four subgroups (Fig. 1).</p><figure><picture><source media="(min-width: 1650px)" srcset="/cms/asset/5b647d2c-613f-47e6-af22-3502d9e1743b/anae16617-fig-0001-m.jpg"/><img alt="Details are in the caption following the image" data-lg-src="/cms/asset/5b647d2c-613f-47e6-af22-3502d9e1743b/anae16617-fig-0001-m.jpg" loading="lazy" src="/cms/asset/f653d79e-aa47-433f-be14-7fdaae225cac/anae16617-fig-0001-m.png" title="Details are in the caption following the image"/></picture><figcaption><div><strong>Figure 1<span style="font-weight:normal"></span></strong><div>Open in figure viewer<i aria-hidden="true"></i><span>PowerPoint</span></div></div><div>Cumulative distribution plots of mechanical power in four groups, divided into two ventilation modes. (a) Dark blue, low tidal volume (V<sub>T</sub>) and low respiratory rate; green, high V<sub>T</sub> and low respiratory rate; red, low V<sub>T</sub> and high respiratory rate; light blue, high V<sub>T</sub> and high respiratory rate, in patients who received volume-controlled ventilation. (b) Dark blue, low peak pressure (Ppeak) and low respiratory rate; red, low Ppeak and high respiratory rate; green, high Ppeak and low respiratory rate; light blue, high Ppeak and high respiratory rate, in patients who received volume-controlled ventilation. (c) Dark blue, low tidal volume (V<sub>T</sub>) and low respi
{"title":"Stress, strain and mechanical power: a reply","authors":"Laura A. Buiteman-Kruizinga","doi":"10.1111/anae.16617","DOIUrl":"https://doi.org/10.1111/anae.16617","url":null,"abstract":"<p>We thank Fajardo-Campoverdi et al. for their letter [<span>1</span>] and appreciate the insightful comments regarding our study about the effect of rate reduction on the amount of mechanical power [<span>2</span>]. The authors raise an interesting point about the potential influence of the way of flow delivery, whether constant or decelerated, on mechanical power.</p>\u0000<p>We acknowledge that the method of inspiratory flow delivery can be a relevant factor in energy transfer within the respiratory system. The viscoelastic properties of lung tissue suggest that cyclic deformation, influenced by flow patterns, might contribute to mechanical power and tissue strain. Importantly, energy transfer is not solely determined by peak pressures but also by other parameters and the duration of the respiratory cycle [<span>3</span>]. Although our analysis did not examine the effects of inspiratory flow delivery explicitly, these are, to some extent, captured in the mechanical power equation through peak pressure, which is influenced by flow patterns and resistive pressure components.</p>\u0000<p>We divided our analysed cohort into patients who received volume-controlled ventilation (n = 920) and those who received pressure-controlled ventilation (n = 812). We then repeated the analysis by creating four subgroups, each for tidal volume and respiratory rate and for peak pressure and respiratory rate. Mechanical power levels were visualised using cumulative distribution graphs for each subgroup. We observed no differences between the two ventilation modes, both in terms of the absolute mechanical power levels and differences in the four subgroups (Fig. 1).</p>\u0000<figure><picture>\u0000<source media=\"(min-width: 1650px)\" srcset=\"/cms/asset/5b647d2c-613f-47e6-af22-3502d9e1743b/anae16617-fig-0001-m.jpg\"/><img alt=\"Details are in the caption following the image\" data-lg-src=\"/cms/asset/5b647d2c-613f-47e6-af22-3502d9e1743b/anae16617-fig-0001-m.jpg\" loading=\"lazy\" src=\"/cms/asset/f653d79e-aa47-433f-be14-7fdaae225cac/anae16617-fig-0001-m.png\" title=\"Details are in the caption following the image\"/></picture><figcaption>\u0000<div><strong>Figure 1<span style=\"font-weight:normal\"></span></strong><div>Open in figure viewer<i aria-hidden=\"true\"></i><span>PowerPoint</span></div>\u0000</div>\u0000<div>Cumulative distribution plots of mechanical power in four groups, divided into two ventilation modes. (a) Dark blue, low tidal volume (V<sub>T</sub>) and low respiratory rate; green, high V<sub>T</sub> and low respiratory rate; red, low V<sub>T</sub> and high respiratory rate; light blue, high V<sub>T</sub> and high respiratory rate, in patients who received volume-controlled ventilation. (b) Dark blue, low peak pressure (Ppeak) and low respiratory rate; red, low Ppeak and high respiratory rate; green, high Ppeak and low respiratory rate; light blue, high Ppeak and high respiratory rate, in patients who received volume-controlled ventilation. (c) Dark blue, low tidal volume (V<sub>T</sub>) and low respi","PeriodicalId":7742,"journal":{"name":"Anaesthesia","volume":"72 1","pages":""},"PeriodicalIF":10.7,"publicationDate":"2025-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143853637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
<p>It is important to measure how survival following hip fracture changes over time because it is an important patient-centred outcome and a reflection of the care we offer our patients. Thirty-day mortality outcomes after hip fracture are published on a rolling basis by the National Hip Fracture Database (NHFD) [<span>1</span>]. Whereas case-mix adjusted mortality rates are useful for identifying hospital outliers from the national average, they are not well suited to identifying temporal changes in mortality rates attributable to improving standards of care. Case-mix adjusted mortality rates do not adjust for variations in the mortality risk of the general population, such as those associated with the COVID-19 pandemic and, importantly, the progressive long-term trend of declining mortality risk over time. Furthermore, 30 days is too brief a period to capture the impact of many important interventions designed to improve survival [<span>2, 3</span>].</p><p>The purpose of this study was to apply an alternative analysis to existing hip fracture mortality data to distinguish improvements in mortality due to better care from changes due to fluctuating population mortality rates. All patients meeting the inclusion criteria for the NHFD between 2012 and 2023 were identified within a single London hospital. The survival status, including date of death if applicable, was established for each patient by searching the electronic patient record and the National Spine database. Patients were not included if they did not have surgery or their survival status could not be confirmed. Patients aged < 65 y and > 95 y were not studied due to limited numbers. Identified patients were segregated into four trienniums (2012–2014, 2015–2017, 2018–2020 and 2021–2023) according to the date of fracture. Each triennium was stratified by sex and 5-year age categories enabling the observed deaths at 1 month and 12 months to be calculated for each stratum. The expected deaths for each stratum were calculated using the mortality rates published in the Office for National Statistics lifetables [<span>4</span>]. These are published in trienniums matching those used in this study. Excess mortality rates for each triennium are presented as standardised mortality ratios (SMR), calculated using the indirect method with 95%CI. The SMR represents the ratio of observed to expected deaths, adjusted for age, sex and year of fracture.</p><p>The basic demographic data were consistent over the four trienniums (Table 1). The overall crude mortality rate was 5.08% at 1 month and 21.12% at 12 months.</p><div><header><span>Table 1. </span>Patient characteristics for each triennium post hip fracture surgery. Values are median (IQR [range]) or 95%CI.</header><div tabindex="0"><table><thead><tr><td rowspan="2"></td><th>2012–2014</th><th>2015–2017</th><th>2018–2020</th><th>2021–2023</th></tr><tr><th style="top: 41px;">n = 348</th><th style="top: 41px;">n = 484</th><th styl
{"title":"Separating the signal from the noise: how mortality rate associated with hip fracture changes over time after accounting for population level mortality rates","authors":"James R. G. Womersley","doi":"10.1111/anae.16622","DOIUrl":"https://doi.org/10.1111/anae.16622","url":null,"abstract":"<p>It is important to measure how survival following hip fracture changes over time because it is an important patient-centred outcome and a reflection of the care we offer our patients. Thirty-day mortality outcomes after hip fracture are published on a rolling basis by the National Hip Fracture Database (NHFD) [<span>1</span>]. Whereas case-mix adjusted mortality rates are useful for identifying hospital outliers from the national average, they are not well suited to identifying temporal changes in mortality rates attributable to improving standards of care. Case-mix adjusted mortality rates do not adjust for variations in the mortality risk of the general population, such as those associated with the COVID-19 pandemic and, importantly, the progressive long-term trend of declining mortality risk over time. Furthermore, 30 days is too brief a period to capture the impact of many important interventions designed to improve survival [<span>2, 3</span>].</p>\u0000<p>The purpose of this study was to apply an alternative analysis to existing hip fracture mortality data to distinguish improvements in mortality due to better care from changes due to fluctuating population mortality rates. All patients meeting the inclusion criteria for the NHFD between 2012 and 2023 were identified within a single London hospital. The survival status, including date of death if applicable, was established for each patient by searching the electronic patient record and the National Spine database. Patients were not included if they did not have surgery or their survival status could not be confirmed. Patients aged < 65 y and > 95 y were not studied due to limited numbers. Identified patients were segregated into four trienniums (2012–2014, 2015–2017, 2018–2020 and 2021–2023) according to the date of fracture. Each triennium was stratified by sex and 5-year age categories enabling the observed deaths at 1 month and 12 months to be calculated for each stratum. The expected deaths for each stratum were calculated using the mortality rates published in the Office for National Statistics lifetables [<span>4</span>]. These are published in trienniums matching those used in this study. Excess mortality rates for each triennium are presented as standardised mortality ratios (SMR), calculated using the indirect method with 95%CI. The SMR represents the ratio of observed to expected deaths, adjusted for age, sex and year of fracture.</p>\u0000<p>The basic demographic data were consistent over the four trienniums (Table 1). The overall crude mortality rate was 5.08% at 1 month and 21.12% at 12 months.</p>\u0000<div>\u0000<header><span>Table 1. </span>Patient characteristics for each triennium post hip fracture surgery. Values are median (IQR [range]) or 95%CI.</header>\u0000<div tabindex=\"0\">\u0000<table>\u0000<thead>\u0000<tr>\u0000<td rowspan=\"2\"></td>\u0000<th>2012–2014</th>\u0000<th>2015–2017</th>\u0000<th>2018–2020</th>\u0000<th>2021–2023</th>\u0000</tr>\u0000<tr>\u0000<th style=\"top: 41px;\">n = 348</th>\u0000<th style=\"top: 41px;\">n = 484</th>\u0000<th styl","PeriodicalId":7742,"journal":{"name":"Anaesthesia","volume":"66 1","pages":""},"PeriodicalIF":10.7,"publicationDate":"2025-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143853649","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Disparities in obstetric anaesthesia: an urgent call for action","authors":"Ella Quintela, Daniel Hind","doi":"10.1111/anae.16618","DOIUrl":"https://doi.org/10.1111/anae.16618","url":null,"abstract":"Click on the article title to read more.","PeriodicalId":7742,"journal":{"name":"Anaesthesia","volume":"26 1","pages":""},"PeriodicalIF":10.7,"publicationDate":"2025-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143853650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kariem El-Boghdadly, Yves Renard, Jean-Benoit Rossel, Eleni Moka, Thomas Volk, Narinder Rawal, Cécile Jaques, Marta Szyszko, Eric Albrecht
Intrathecal morphine provides effective postoperative analgesia, but there are concerns about potential pulmonary complications influencing peri-operative management. We aimed to determine whether there is an association between intrathecal morphine administration and pulmonary complications after non-obstetric surgery. We also aimed to determine whether there was a dose-dependent effect on pulmonary complications.
{"title":"Pulmonary complications after intrathecal morphine administration: a systematic review and meta-analysis with meta-regression and trial sequential analysis","authors":"Kariem El-Boghdadly, Yves Renard, Jean-Benoit Rossel, Eleni Moka, Thomas Volk, Narinder Rawal, Cécile Jaques, Marta Szyszko, Eric Albrecht","doi":"10.1111/anae.16606","DOIUrl":"https://doi.org/10.1111/anae.16606","url":null,"abstract":"Intrathecal morphine provides effective postoperative analgesia, but there are concerns about potential pulmonary complications influencing peri-operative management. We aimed to determine whether there is an association between intrathecal morphine administration and pulmonary complications after non-obstetric surgery. We also aimed to determine whether there was a dose-dependent effect on pulmonary complications.","PeriodicalId":7742,"journal":{"name":"Anaesthesia","volume":"199 1","pages":""},"PeriodicalIF":10.7,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143837066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jasmin Elkin, Siddharth Rele, Priya Sumithran, Michael Hii, Sharmala Thuraisingam, Tim Spelman, Tuong Phan, Peter Choong, Michelle Dowsey, Cade Shadbolt
Glucagon-like peptide-1 receptor agonists are known to delay gastric emptying; however, the association between glucagon-like peptide-1 receptor agonist use and peri-operative pulmonary aspiration risk is not known. This systematic review and meta-analysis aimed to summarise the evidence on whether glucagon-like peptide-1 receptor agonist exposure is associated with pulmonary aspiration or increased residual gastric content in fasted patients undergoing procedures requiring anaesthesia or sedation.
{"title":"Association between glucagon-like peptide-1 receptor agonist use and peri-operative pulmonary aspiration: a systematic review and meta-analysis","authors":"Jasmin Elkin, Siddharth Rele, Priya Sumithran, Michael Hii, Sharmala Thuraisingam, Tim Spelman, Tuong Phan, Peter Choong, Michelle Dowsey, Cade Shadbolt","doi":"10.1111/anae.16601","DOIUrl":"https://doi.org/10.1111/anae.16601","url":null,"abstract":"Glucagon-like peptide-1 receptor agonists are known to delay gastric emptying; however, the association between glucagon-like peptide-1 receptor agonist use and peri-operative pulmonary aspiration risk is not known. This systematic review and meta-analysis aimed to summarise the evidence on whether glucagon-like peptide-1 receptor agonist exposure is associated with pulmonary aspiration or increased residual gastric content in fasted patients undergoing procedures requiring anaesthesia or sedation.","PeriodicalId":7742,"journal":{"name":"Anaesthesia","volume":"72 1","pages":""},"PeriodicalIF":10.7,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143832020","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Anna Kirkopoulos, René M'Pembele, Sebastian Roth, Alexandra Stroda, Jan Larmann, Hans-Joerg Gillmann, Katarzyna Kotfis, Michael T. Ganter, Daniel Bolliger, Miodrag Filipovic, Luca Guzzetti, Eckhard Mauermann, Daniela Ionescu, Savino Spadaro, Wojciech Szczeklik, Stefan De Hert, Beatrice Beck-Schimmer, Simon J. Howell, Giovanna A. Lurati Buse
Heart failure is a frequent comorbidity in patients undergoing non-cardiac surgery and an acknowledged risk factor for postoperative mortality. The associations between stable chronic heart failure and postoperative outcomes have not been explored extensively. The aim of this study was to determine associations between stable chronic heart failure and its peri-operative management and postoperative outcomes after major non-cardiac surgery.
{"title":"Outcomes in patients with chronic heart failure undergoing non-cardiac surgery: a secondary analysis of the METREPAIR international cohort study*","authors":"Anna Kirkopoulos, René M'Pembele, Sebastian Roth, Alexandra Stroda, Jan Larmann, Hans-Joerg Gillmann, Katarzyna Kotfis, Michael T. Ganter, Daniel Bolliger, Miodrag Filipovic, Luca Guzzetti, Eckhard Mauermann, Daniela Ionescu, Savino Spadaro, Wojciech Szczeklik, Stefan De Hert, Beatrice Beck-Schimmer, Simon J. Howell, Giovanna A. Lurati Buse","doi":"10.1111/anae.16607","DOIUrl":"https://doi.org/10.1111/anae.16607","url":null,"abstract":"Heart failure is a frequent comorbidity in patients undergoing non-cardiac surgery and an acknowledged risk factor for postoperative mortality. The associations between stable chronic heart failure and postoperative outcomes have not been explored extensively. The aim of this study was to determine associations between stable chronic heart failure and its peri-operative management and postoperative outcomes after major non-cardiac surgery.","PeriodicalId":7742,"journal":{"name":"Anaesthesia","volume":"40 1","pages":""},"PeriodicalIF":10.7,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143832019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Best anaesthetic technique for prevention of postoperative cognitive dysfunction in older patients after hip fracture surgery – is the debate over?","authors":"Ana Kowark, Mark Coburn","doi":"10.1111/anae.16609","DOIUrl":"https://doi.org/10.1111/anae.16609","url":null,"abstract":"Click on the article title to read more.","PeriodicalId":7742,"journal":{"name":"Anaesthesia","volume":"74 5 Pt 1 1","pages":""},"PeriodicalIF":10.7,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143832025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Maite M. T. van Haeren, Meike Brouwers, Jimmy Schenk, Jennifer S. Breel, Sijm H. Noteboom, Eline Kho, Susanne Eberl, Denise P. Veelo, Alexander P. J. Vlaar, Marcella C. A. Müller, Henning Hermanns
Rotational thromboelastometry (ROTEM®) is used widely in cardiac surgery. Reference ranges are derived from healthy volunteers but may not be interchangeable with those from patients undergoing cardiac surgery. Furthermore, sex and age seem to influence rotational thromboelastometry profiles. We performed a secondary analysis of two prospective observational study cohorts from a single centre in the Netherlands, which establishes pre-operative ROTEM® sigma reference ranges for adult patients undergoing cardiac surgery and examines sex- and age-specific variations.
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