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OBJECTIVE: Perioperative in-hospital cardiac arrests (Perioperative IHCAs) may have better outcomes than IHCAs in the ward (Ward IHCAs), due to enhanced monitoring and faster response. However, quantitative comparisons of their long-term outcomes are lacking, posing challenges for prognostication.
METHODS: This retrospective multicentre study included adult intensive care unit (ICU) admissions from theatre/recovery or wards with a diagnosis of cardiac arrest between January 2018 and March 2022. We used data from 175 ICUs in the ANZICS adult patient database. The primary outcome was a survival time of up to 4 years. We used the Cox proportional hazards model adjusted for Sequential Organ Failure Assessment (SOFA) score, age, sex, comorbidities, hospital type, treatment limitation on admission to the ICU, and ICU treatments. Subgroup analyses examined age (≥ 65 years), intubation within the first 24 h, elective vs. emergency admission, and survival on discharge.
RESULTS: Of 702,675 ICU admissions, 5,659 IHCAs were included (Perioperative IHCA 38%; Ward IHCA 62%). Perioperative IHCA group were younger, less frail, and less comorbid. Perioperative IHCA were most frequent in patients admitted to ICU after cardiovascular, gastrointestinal, or trauma surgeries. Perioperative IHCA group had longer 4-year survival (59.9% vs. 33.0%, p < 0.001) than the Ward IHCA group, even after adjustments (adjusted hazard ratio [HR]: 0.63, 95% confidence interval [CI] 0.57-0.69). This was concordant across all subgroups. Of note, older patients with Perioperative IHCA survived longer than both younger and older patients with Ward IHCA.
CONCLUSIONS: Patients admitted to the ICU following Perioperative IHCA had longer survival than Ward IHCA. Future studies on IHCA should distinguish these patients.

BACKGROUND: Patients undergoing surgery deserve the best possible peri-operative outcomes. Each stage of the peri-operative patient journey offers opportunities to improve care delivery, with shorter lengths of stay, less complications, reduced costs and better value.
METHODS: These opportunities were identified through narrative review of the literature, with consultation and consensus at the hidden pandemic (of postoperative complications) summit 2, July 2023 in Adelaide, Australia RESULTS: Before surgery: Some patients who receive timely alternative treatments may not need surgery at all. The period of waiting after listing should be a time of preparation. Risk assessment at the time of surgical listing facilitates recognition of need for comorbidity optimisation and identifies those who will most benefit from prehabilitation, particularly frail and deconditioned patients.
UNASSIGNED: During the surgical admission, ERAS programs result in less postoperative complications, shorter length of stay and better patient experience but require agreement between clinicians, and coordinated monitoring of delivery of the elements in the ERAS bundle of care.
UNASSIGNED: At-risk patients need to have the appropriate levels of monitoring for cardiovascular instability, renal impairment or respiratory dysfunction, to facilitate timely, proactive management if they develop. Access to allied health in the early postoperative period is also critical for promoting mobility, and earlier discharge, particularly after joint surgery. Where appropriate, provision of rehabilitation services at home improves patient experience and adds value. The peri-operative patient journey begins and ends with primary care so there is a need for clear communication, documentation, around sharing of responsibility between practitioners at each stage.
CONCLUSIONS: Identifying and mitigating risk to reduce complications and length of stay in hospital will improve outcomes for patients and deliver the best value for the health system.

UNASSIGNED: This article describes the statistical analysis plan for the Biomarker-guided intervention to prevent AKI after major surgery (BigpAK-2) trial.
UNASSIGNED: Adaptive trial design with an interim analysis after enrolment of 618 evaluable patients.
UNASSIGNED: The BigpAK.-2 trial is an international, prospective, randomised controlled multicentre study.
UNASSIGNED: The BigpAK-2 study enrols patients after major surgery who are admitted to the intensive care or high dependency unit and are at high-risk for postoperative AKI as identified by urinary biomarkers (tissue inhibitor of metalloproteinases-2 and insulin-like growth factor binding protein 7 ([TIMP-2]∗[IGFBP7]) will be enrolled.
UNASSIGNED: Patients are randomly and evenly allocated to standard of care (control) group or the implementation of a nephroprotective care bundle (intervention group), as recommended by the Kidney Disease: Improving Global Outcomes (KDIGO) guidelines. The KDIGO care bundle recommends discontinuation of nephrotoxic agents if possible, ensuring adequate volume status and perfusion pressure, considering functional haemodynamic monitoring, regular monitoring of serum creatinine and urine output, avoiding hyperglycemia, and considering alternatives to radiocontrast procedures when possible.
UNASSIGNED: The BigpAK-2 study investigates whether the biomarker-gudied implementation of the KDIGO care bundle reduces the incidence of moderate or severe AKI (stage 2 or 3), according to the KDIGO 2012 criteria, within 72 h after surgery.
UNASSIGNED: AKI is a common and often severe complication after major surgery. As no specific treatments exist, prevention of AKI is of high importance. The BigpAK-2 study investigates a promising approach to prevent AKI after major surgery.
UNASSIGNED: The trial was registered prior to start at clinicaltrials.gov; NCT04647396.

BACKGROUND: The preadmission clinic (PAC) is crucial in perioperative care, offering evaluations, education, and patient optimization before surgical procedures. During the COVID-19 pandemic, the PAC adapted by implementing telephone visits due to a lack of infrastructure for video consultations. While the pandemic significantly increased the use of virtual care, including video appointments as an alternative to in-person consultations, our PAC had not used video consultations for preoperative assessments.
OBJECTIVE: This study aimed to develop, implement, and integrate preoperative video consultations into the PAC workflow.
METHODS: A prospective quality improvement project was undertaken using the Plan-Do-Study-Act (PDSA) methodology. The project focused on developing, implementing, and integrating virtual video consultations at London Health Sciences Centre and St. Joseph Health Care (London, Ontario, Canada) in the PAC. Data were systematically collected to monitor the number of patients undergoing video consultations, address patient flow concerns, and increase the percentage of video consultations. Communication between the PAC, surgeon offices, and patients was analyzed for continuous improvement. Technological challenges were addressed, and procedures were streamlined to facilitate video calls on appointment days.
RESULTS: The PAC team, which includes professionals from medicine, anesthesia, nursing, pharmacy, occupational therapy, and physiotherapy, offers preoperative evaluation and education to surgical patients, conducting approximately 8000 consultations annually across 3 hospital locations. Following the initial PDSA cycles, the interventions consistently improved the video consultation utilization rate to 17%, indicating positive progress. With the onset of PDSA cycle 3, there was a notable surge to a 29% utilization rate in the early phase. This upward trend continued, culminating in a 38% utilization rate of virtual video consultations in the later stages of the cycle. This heightened level was consistently maintained throughout 2023, highlighting the sustained success of our interventions.
CONCLUSIONS: The quality improvement process significantly enhanced the institution\'s preoperative video consultation workflow. By understanding the complexities within the PAC, strategic interventions were made to integrate video consultations without compromising efficiency, morale, or safety. This project highlights the potential for transformative improvements in health care delivery through the thoughtful integration of virtual care technologies.

Ultrasound shear wave elastography (SWE) is a non-invasive, low risk technology allowing the assessment of tissue stiffness. Used clinically for nearly two decades to diagnose and stage liver fibrosis and cirrhosis, it has recently been appreciated for its ability to differentiate between more subtle forms of liver dysfunction. In this review, we will discuss the principle of ultrasound shear wave elastography, its traditional utilization in grading liver cirrhosis, as well as its evolving role in identifying more subtle degrees of liver injury. Finally, we will show how this capacity to distinguish nuanced changes may provide an opportunity for its use in perioperative risk stratification.

BACKGROUND: The Revised Cardiac Risk Index (RCRI) is a six-parameter model that is commonly used in assessing individual 30-day perioperative cardiovascular risk before general surgery, but its use in patients on chronic kidney replacement therapy (KRT) is unvalidated. This study aimed to externally validate RCRI in this patient group over a 15-year period.
METHODS: Data linkage was used between the the Australia and New Zealand Dialysis and Transplant (ANZDATA) Registry and jurisdictional hospital admisisons data across Australia and New Zealand to identify all incident and prevalent patients on chronic KRT between 2000 and 2015 who underwent elective abdominal surgery. Chronic KRT was categorised as haemodialysis (HD), peritoneal dialysis (PD), home haemodialysis (HHD) and kidney transplant. The outcome of interest was major adverse cardiovascular event (MACE) which was defined as nonfatal myocardial infarction, nonfatal stroke, non-fatal cardiac arrest and cardiovascular mortality at 30 days. Logistic regression was used with the RCRI score included as a continuous variable to estimate discrimination by area under the receiver operating curve (AUROC). Calibration was evaluated using a calibration plot. Clinical utility was assessed using a decision curve analysis to determine the net benefit.
RESULTS: A total of 5094 elective surgeries were undertaken, and MACE occurred in 153 individuals (3.0%). Overall, RCRI had poor discrimination in patients on chronic KRT undergoing elective surgery (AUROC 0.67), particularly in patients aged greater than 65 years (AUROC 0.591). A calibration plot showed that RCRI overestimated risk of MACE. The expected-to-observed outcome ratio was 6.0, 5.1 and 2.5 for those with RCRI scores of 1, 2 and ≥ 3, respectively. Discrimination was moderate in patients under 65 years and in kidney transplant recipients, with AUROC values of 0.740 and 0.718, respectively. Overestimation was common but less so for kidney transplant recipients. Decision curve analysis showed that there was no net benefit of using the tool in neither the overall cohort nor patients under 65 years, but a slight benefit associated with threshold probability > 5.5% in kidney transplant recipients.
CONCLUSIONS: The RCRI tool performed poorly and overestimated risk in patients on chronic dialysis, potentially misinforming patients and clinicians about the risk of elective surgery. Further research is needed to define a more comprehensive means of estimating risk in this unique population.

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We present the INSPIRE dataset, a publicly available research dataset in perioperative medicine, which includes approximately 130,000 surgical operations at an academic institution in South Korea over a ten-year period between 2011 and 2020. This comprehensive dataset includes patient characteristics such as age, sex, American Society of Anesthesiologists physical status classification, diagnosis, surgical procedure code, department, and type of anaesthesia. The dataset also includes vital signs in the operating theatre, general wards, and intensive care units (ICUs), laboratory results from six months before admission to six months after discharge, and medication during hospitalisation. Complications include total hospital and ICU length of stay and in-hospital death. We hope this dataset will inspire collaborative research and development in perioperative medicine and serve as a reproducible external validation dataset to improve surgical outcomes.

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