"Failure to Rescue" following Colorectal Cancer Resection: Variation and Improvements in a National Study of Postoperative Mortality.

OBJECTIVE: To examine variation in "failure to rescue" (FTR) as a driver of differences in mortality between centres and over time for patients undergoing colorectal cancer surgery. BACKGROUND: Wide variation exists in postoperative mortality following colorectal cancer surgery. FTR has been identified as an important determinant of variation in postoperative outcomes. We hypothesized that differences in mortality both between hospitals and over time are driven by variation in FTR. METHODS: A national population-based study of patients undergoing colorectal cancer resection from 2010 to 2019 in Aotearoa New Zealand was conducted. Rates of 90-day FTR, mortality, and complications were calculated overall, and for surgical and nonoperative complications. Twenty District Health Boards (DHBs) were ranked into quartiles using risk- and reliability-adjusted 90-day mortality rates. Variation between DHBs and trends over the 10-year period were examined. RESULTS: Overall, 15,686 patients undergoing resection for colorectal adenocarcinoma were included. Increased postoperative mortality at high-mortality centers (OR 2.4, 95% CI 1.8-3.3) was driven by higher rates of FTR (OR 2.0, 95% CI 1.5-2.8), and postoperative complications (OR 1.4, 95% CI 1.3-1.6). These trends were consistent across operative and nonoperative complications. Over the 2010 to 2019 period, postoperative mortality halved (OR 0.5, 95% CI 0.4-0.6), associated with a greater improvement in FTR (OR 0.5, 95% CI 0.4-0.7) than complications (OR 0.8, 95% CI 0.8-0.9). Differences between centers and over time remained when only analyzing patients undergoing elective surgery. CONCLUSION: Mortality following colorectal cancer resection has halved over the past decade, predominantly driven by improvements in "rescue" from complications. Differences in FTR also drive hospital-level variation in mortality, highlighting the central importance of "rescue" as a target for surgical quality improvement.

Editor's Choice - Development and Validation of a Multivariable Prediction Model of Peri-operative Mortality in Vascular Surgery: The New Zealand Vascular Surgical Risk Tool (NZRISK-VASC).

OBJECTIVE: Risk calculators and prediction models are available to assist clinicians and patients with peri-operative decision making to optimise outcomes. In a vascular surgical setting, the majority of these models is based on open AAA repair outcomes, and in general their clinical use is limited. The objective of this study was to develop and validate a simple and accurate vascular surgical risk prediction model. METHODS: A national administrative database was accessed to collect information on all adult patients undergoing vascular surgery between 1 July 2011 and 30 June 2016 in New Zealand. The primary outcomes were mortality at 30 days, one year, and two years. Previously established covariables including American Society of Anaesthesiologists (ASA) physical status score, sex, surgical urgency, cancer status and ethnicity were tested, and other covariables such as smoking status, presence of renal failure, diabetes, anatomical site of operation, structure operated, and type of procedures (open or endovascular) were explored. LASSO regression was used to select variables for inclusion in the model. RESULTS: A total of 21 597 cases formed the final risk prediction models, with covariables including ASA score, gender, surgical urgency, cancer status, presence of renal failure, diabetes, anatomical site, structure operated, and endovascular procedure. The area under the receiver operating curve (AUROC) for 30 day, one year, and two year mortality using L-min model was 0.869, 0.833, and 0.824, respectively, demonstrating very good discrimination. Calibration with the validation dataset was also excellent, with slopes of 0.971, 1.129, and 1.011, respectively, and McFadden's pseudo-R2 statistics of 0.250, 0.227, and 0.227, respectively. CONCLUSION: A simple and accurate multivariable risk calculator for vascular surgical patients was developed and validated using the New Zealand national dataset, with excellent discrimination and calibration for 30 day, one year, and two year mortality.

Validated criteria for the interpretation of a single measurement of serum cortisol in the investigation of suspected adrenal insufficiency.

OBJECTIVE: The diagnostic value of a single measurement of serum cortisol as a first step in the investigation of suspected adrenal insufficiency remains unclear. Previously proposed criteria have not been validated, and little is known regarding the performance of the test outwith morning samples in outpatients. We aimed to identify and validate criteria for morning and afternoon serum cortisol which could be used to determine which individuals require dynamic testing, in both outpatient and medical inpatient settings. METHODS: We performed a retrospective analysis of 2768 patients attending endocrinology clinics and patients admitted to general medical units in two hospitals in Edinburgh, UK. In baseline samples from the short synacthen test, thresholds which identified a subnormal-stimulated serum cortisol (<430 nmol/L using the Abbott Architect assay) with 95% sensitivity were identified. Criteria drawn from data in patients attending outpatient clinics in one hospital were tested in additional outpatient and inpatient validation cohorts. RESULTS: A morning (8 am-12 pm) serum cortisol of <275 nmol/L identified subnormal-stimulated cortisol with 96.2% sensitivity. For afternoon (12 pm-6 pm) samples, a cut-off of <250 nmol/L achieved 96.1% sensitivity. Sensitivity was maintained when the criteria were applied to outpatients in the validation cohort for both morning and afternoon samples. For inpatients, the test was sufficiently sensitive in morning samples only. CONCLUSIONS: A single measurement of serum cortisol carries the potential to significantly reduce the need for dynamic testing in the investigation of adrenal insufficiency, whether this is taken in morning or afternoon outpatient clinics, or in morning samples from medical inpatients.

Pharmacotherapy for older people with obesity.

Rates of obesity continue to rise, including in older adults. Use of medication for obesity in the elderly has been considered controversial, due to concerns around potential progression of age-related sarcopenia and a general lack of evidence for its use in this age group. Within this review, we describe the general considerations when prescribing obesity pharmacotherapy for older adults living with obesity. We evaluate in detail the anti-obesity medications currently licenced in Europe, with emphasis on the available efficacy, safety and cardiovascular outcome data gathered from study of older people. Finally, we discuss future directions and avenues of research.

Days Alive and Out of Hospital as an Outcome Measure in Patients Receiving Hyperacute Stroke Intervention.

BACKGROUND: Patient outcome after stroke is frequently assessed with clinical scales such as the modified Rankin Scale score (mRS). Days alive and out of hospital at 90 days (DAOH-90), which measures survival, time spent in hospital or rehabilitation settings, readmission and institutionalization, is an objective outcome measure that can be obtained from large administrative data sets without the need for patient contact. We aimed to assess the comparability of DAOH with mRS and its relationship with other prognostic variables after acute stroke reperfusion therapy. METHODS AND RESULTS: Consecutive patients with ischemic stroke treated with intravenous thrombolysis or endovascular thrombectomy were analyzed. DAOH-90 was calculated from a national minimum data set, a mandatory nationwide administrative database. mRS score at day 90 (mRS-90) was assessed with in-person or telephone interviews. The study included 1278 patients with ischemic stroke (714 male, median age 70 [59-79], median National Institutes of Health Stroke Scale score 14 [9-20]). Median DAOH-90 was 71 [29-84] and median mRS-90 score was 3 [2-5]. DAOH-90 was correlated with admission National Institutes of Health Stroke Scale score (Spearman rho -0.44, P<0.001) and Alberta Stroke Program Early CT [Computed Tomography] Score (Spearman rho 0.24, P<0.001). There was a strong association between mRS-90 and DAOH-90 (Spearman rho correlation -0.79, P<0.001). Area under receiver operating curve for predicting mRS score >0 was 0.86 (95% CI, 0.84-0.88), mRS score >1 was 0.88 (95% CI, 0.86-0.90) and mRS score >2 was 0.90 (95% CI, 0.89-0.92). CONCLUSIONS: In patients with stroke treated with reperfusion therapies, DAOH-90 shows reasonable comparability to the more established outcome measure of mRS-90. DAOH-90 can be readily obtained from administrative databases and therefore has the potential to be used in large-scale clinical trials and comparative effectiveness studies.

Time to unshackle the medical treatment of obesity in the NHS.

Obesity affects one in four people in the United Kingdom and costs the National Health Service (NHS) ∼£6.5 billion annually. The glucagon-like peptide-1 (GLP-1) receptor analogues, such as once-daily subcutaneous Liraglutide 3.0 mg (Saxenda®) and once-weekly subcutaneous Semaglutide 2.4 mg (Wegovy®), were approved by the National Institute of Health and Care Excellence (NICE) as a treatment for obesity and funded by the NHS for 2 years. Our local data shows that Saxenda is effective at reducing body weight and glycaemia in people with obesity and diabetes; however, the supply issues of GLP-1 receptor analogues have contributed to the unavailability of Saxenda and Wegovy in our service. Our patients are devastated that they cannot access NICE-approved GLP-1 receptor analogues for obesity. The 2-year GLP-1 receptor analogue treatment limit for obesity alongside a lack of funded NHS services and supply issues represent barriers to treatment for people living with obesity who have clear medical indications.

UCP1 expression in human brown adipose tissue is inversely associated with cardiometabolic risk factors.

OBJECTIVE: Brown adipose tissue (BAT) is a therapeutic target for obesity. 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) is commonly used to quantify human BAT mass and activity. Detectable 18F-FDG uptake by BAT is associated with reduced prevalence of cardiometabolic disease. However, 18F-FDG uptake may not always be a reliable marker of BAT thermogenesis, for example, insulin resistance may reduce glucose uptake. Uncoupling protein 1 (UCP1) is the key thermogenic protein in BAT. Therefore, we hypothesised that UCP1 expression may be altered in individuals with cardiometabolic risk factors. METHODS: We quantified UCP1 expression as an alternative marker of thermogenic capacity in BAT and white adipose tissue (WAT) samples (n = 53) and in differentiated brown and white pre-adipocytes (n = 85). RESULTS: UCP1 expression in BAT, but not in WAT or brown/white differentiated pre-adipocytes, was reduced with increasing age, obesity, and adverse cardiometabolic risk factors such as fasting glucose, insulin, and blood pressure. However, UCP1 expression in BAT was preserved in obese subjects of <40 years of age. To determine if BAT activity was also preserved in vivo, we undertook a case-control study, performing 18F-FDG scanning during mild cold exposure in young (mean age ∼22 years) normal weight and obese volunteers. 18F-FDG uptake by BAT and BAT volume were similar between groups, despite increased insulin resistance. CONCLUSION: 18F-FDG uptake by BAT and UCP1 expression are preserved in young obese adults. Older subjects retain precursor cells with the capacity to form new thermogenic adipocytes. These data highlight the therapeutic potential of BAT mass expansion and activation in obesity.

Ambient fine particulate matter alters cerebral hemodynamics in the elderly.

BACKGROUND AND PURPOSE: Short-term elevations in fine particulate matter air pollution (PM2.5) are associated with increased risk of acute cerebrovascular events. Evidence from the peripheral circulation suggests that vascular dysfunction may be a central mechanism. However, the effects of PM2.5 on cerebrovascular function and hemodynamics are unknown. METHODS: We used transcranial Doppler ultrasound to measure beat-to-beat blood flow velocity in the middle cerebral artery at rest and in response to changes in end-tidal CO2 (cerebral vasoreactivity) and arterial blood pressure (cerebral autoregulation) in 482 participants from the Maintenance of Balance, Independent Living, Intellect, and Zest in the Elderly (MOBILIZE) of Boston study. We used linear mixed effects models with random subject intercepts to evaluate the association between cerebrovascular hemodynamic parameters and mean PM2.5 levels 1 to 28 days earlier adjusting for age, race, medical history, meteorologic covariates, day of week, temporal trends, and season. RESULTS: An interquartile range increase (3.0 µg/m(3)) in mean PM2.5 levels during the previous 28 days was associated with an 8.6% (95% confidence interval, 3.7%-13.8%; P<0.001) higher cerebral vascular resistance and a 7.5% (95% confidence interval, 4.2%-10.6%; P<0.001) lower blood flow velocity at rest. Measures of cerebral vasoreactivity and autoregulation were not associated with PM2.5 levels. CONCLUSIONS: In this cohort of community-dwelling seniors, exposure to PM2.5 was associated with higher resting cerebrovascular resistance and lower cerebral blood flow velocity. If replicated, these findings suggest that alterations in cerebrovascular hemodynamics may underlie the increased risk of particle-related acute cerebrovascular events.

Emerging sodium/glucose co-transporter 2 inhibitors for type 2 diabetes.

INTRODUCTION: Type 2 diabetes mellitus (T2DM) is a public health challenge globally. Numerous treatments are available which can improve insulin sensitivity or stimulate its secretion including biguanides, sulphonylureas and glitazones, as well as insulin, GLP-1 agonists and DPP-IV inhibitors. These are usually unable to halt progression with high resulting morbidity and mortality. New therapies are, therefore, being developed; inhibition of glucose reabsorption from the renal filtrate has been proposed as a novel therapeutic target, and sodium/glucose co-transporter 2 (SGLT2) inhibitors have been developed accordingly. AREAS COVERED: This review summarises the challenge that T2DM poses and describes established therapies. The market for these therapies and likely changes are examined, as well as the scientific rationale behind the development of SGLT2 inhibitors. SGLT2 inhibitors in clinical trials worldwide are reviewed and issues affecting their development are discussed. EXPERT OPINION: SGLT2 inhibitors offer a novel therapeutic approach to the management of T2DM; advantages over other agents include weight loss and blood pressure lowering with a low intrinsic risk of hypoglycaemia. The main adverse effects likely to be seen in clinical practice are a very small increase in risk of urinary tract infections, and a modest risk of developing genital fungal infections - which appear more common in the first few months of treatment. Meta-analyses suggest no increased risk of cardiovascular disease, but longer duration outcome studies are essential to prove long-term safety and efficacy.

Development and validation of a national perioperative mortality risk model for pediatric surgery: The New Zealand pediatric surgical risk tool (NZRISK-pediatric): NZRISK-Pediatric.

BACKGROUND: Risk prediction models are well established as an adjunct to perioperative decision making, but few exist for pediatric surgical outcomes. The majority of risk tools do not feature Australasian data and do not estimate mortality risk beyond 30-days. Our aim was to develop and validate a model for mortality risk prediction in children (age <18yrs) at 30-days, 90-days and 1 year following all types of surgery using a national database. METHODS AND RESULTS: The New Zealand Ministry of Health National Minimum Dataset was accessed to obtain clinical and demographic data for all children having surgery between June 1st 2011 and July 1st 2016. Three quarters of the data were used to derive 3 models to predict 30-day, 90-day and 1-year mortality risk, and the remaining data used for validation. We constructed 3 models using data from 135 217 patients, validating a total of 11 covariates for risk prediction. Included were neonate, prematurity, ASA-PS status, heart and lung disease, active malignancy, sepsis, surgical type, surgical severity score, surgical urgency, ethnicity and socioeconomic deprivation. All models showed excellent discrimination (area under the receiver operating characteristic curve (AUROC) values of 0.947, 0.933 and 0.908 respectively) and calibration statistics (calibration slopes of 0.778, 1.125, 1.153, Brier scores of 0.001, 0.002, 0.003 respectively). CONCLUSION: Combining objective data with severity indices, NZRISK-Paed presents a risk stratification model which is intuitive and practical. Application of 30-day, 90-day and 1-year percentage mortality risk aids in longer-term planning, shared decision-making and allocation of resource to the individual and to high needs populations. Risk prediction tools add an objective measure to pre-operative assessment but few exist for pediatric surgery and none predict mortality beyond 30-days.

Temporal validation of a multivariable surgical mortality prediction model (NZRisk): a New Zealand national cohort study.

OBJECTIVES: Clinical risk calculators (CRCs), such as NZRisk, are used daily by clinicians to guide clinical decisions and explain individual risk to patients. The utility and robustness of these tools depends on the methods used to create the underlying mathematical model, as well as the stability of that model in relation to changing clinical practice and patient populations over time. The later should be checked by temporal validation using external data. Few if any of the clinical prediction models in current clinical use have published temporal validation. Here, we use a large external dataset to temporally validate NZRisk; a perioperative risk prediction model used in the New Zealand population. METHODS: A sample of 1 976 362 adult non-cardiac surgical procedures collected over 15 years from the New Zealand Ministry of Health National Minimum Dataset, was used to temporally validate NZRisk. We divided the dataset into 15 single year cohorts and compared 13 of these to our NZRisk model (2 years used for the model building were excluded). We compared the area under the curve (AUC) value, calibration slope and intercept for each single year cohort, to the same values produced by the data used to create NZRisk, by fitting a random effects meta-regression with each year cohort acting as a separate study point. In addition, we used two-sided t-tests to compare each measure across the cohorts. RESULTS: The AUC values for the 30-day NZRisk model applied to our single year cohorts ranged from 0.918 to 0.940 (NZRisk AUC was 0.921). There were eight statistically different AUC values for the following years 2007-2009, 2016 and 2018-2021. The intercept values ranged from -0.004 to 0.007 and 7 years had statistically significant different intercepts during leave-one-out t-tests; 2007-2010, 2012, 2018 and 2021. The slope values ranged from 0.72 to 1.12 and 7 years had statistically significant different slopes during leave-one-out t-tests; 2010, 2011, 2017, 2018 and 2019-2021. The random effects meta-regression upheld our results related to AUC (0.54 (95% CI 0.40 to 0.99), I2 67.57 (95% CI 40.67 to 88.50), Cochran's Q<0.001) and slope (τ 0.14 (95% CI 0.01 to 0.23), I2 98.61 (95% CI 97.31 to 99.50), Cochran's Q<0.001) between year difference. CONCLUSION: The NZRisk model shows differences in AUC and slope but not intercept values over time. The biggest differences were in the calibration slope. The models maintained excellent discrimination over time as shown by the AUC values. These findings suggest we update our model in the next 5 years. To our knowledge, this is the first temporal validation of a CRC in current use.

Using days alive and out of hospital to measure surgical outcomes in New Zealand: a cross-sectional study.

OBJECTIVES: To measure differences at various deciles in days alive and out of hospital to 90 days (DAOH90) and explore its utility for identifying outliers of performance among district health boards (DHBs). METHODS: Days in hospital and mortality within 90 days of surgery were extracted by linking data from the New Zealand National Minimum Data Set and the births and deaths registry between 1 January 2011 and 31 December 2021 for all adults in New Zealand undergoing acute laparotomy (AL-a relatively high-risk group), elective total hip replacement (THR-a medium risk group) or lower segment caesarean section (LSCS-a low-risk group). DAOH90 was calculated without censoring to zero in cases of mortality. For each DHB, direct risk standardisation was used to adjust for potential confounders and presented in deciles according to baseline patient risk. The Mann-Whitney U test assessed overall DAOH90 differences between DHBs, and comparisons are presented between selected deciles of DAOH90 for each operation. RESULTS: We obtained national data for 35 175, 52 032 and 117 695 patients undergoing AL, THR and LSCS procedures, respectively. We have demonstrated that calculating DAOH without censoring zero allows for differences between procedures and DHBs to be identified. Risk-adjusted national mean DAOH90 Scores were 64.0 days, 79.0 days and 82.0 days at the 0.1 decile and 75.0 days, 82.0 days and 84.0 days at the 0.2 decile for AL, THR and LSCS, respectively, matching to their expected risk profiles. Differences between procedures and DHBs were most marked at lower deciles of the DAOH90 distribution, and outlier DHBs were detectable. Corresponding 90-day mortality rates were 5.45%, 0.78% and 0.01%. CONCLUSION: In New Zealand after direct risk adjustment, differences in DAOH90 between three types of surgical procedure reflected their respective risk levels and associated mortality rates. Outlier DHBs were identified for each procedure. Thus, our approach to analysing DAOH90 appears to have considerable face validity and potential utility for contributing to the measurement of perioperative outcomes in an audit or quality improvement setting.

Incidence of postoperative delirium in surgical patients: An observational retrospective cohort study.

SummaryPerioperative neurocognitive disorders including postoperative delirium (POD) are common complications of anaesthesia and surgery, associated with morbidity, mortality and a large economic cost. Currently, limited data are available on the incidence of POD in the New Zealand population. The objective of this study was to utilise New Zealand national level datasets to identify the incidence of POD. Our primary outcome was defined as a diagnosis of delirium via ICD 9/10 coding within seven days of surgery. We also analysed demographic, anaesthetic and surgical characteristics. All adult patients undergoing any surgical intervention under sedation, regional, general or neuraxial anaesthesia were included, and patients who received surgical intervention under local anaesthetic infiltration alone were excluded. We reviewed ten years of patient admissions from 2007 to 2016. Our sample size was 2,249,910 patients. The incidence of POD was 1.9%, much lower than previously observed, potentially indicating significant under-reporting of POD in this national level database. With acknowledgement of the limitations of potential undercoding and under-reporting, we found that the incidence of POD was higher with increasing age, male sex, general anaesthesia, Maori ethnicity, increasing comorbidity, surgical severity and emergency surgery. A diagnosis of POD was associated with increased mortality and hospital length of stay. Our results highlight potential risk factors of POD and disparities in health outcomes in New Zealand. Additionally, these findings suggest systemic under-reporting of POD in national level datasets.

Using Days Alive and Out of Hospital to measure inequities and possible pathways for them after cardiovascular surgery in Aotearoa New Zealand: study protocol for a secondary data analysis.

INTRODUCTION: In Aotearoa New Zealand (NZ), socioeconomic status and being of Maori ethnicity are often associated with poorer health outcomes, including after surgery. Inequities can be partially explained by differences in health status and health system biases are hypothesised as important factors for remaining inequities. Previous work identified inequities between Maori and non-Maori following cardiovascular surgery, some of which have been identified in studies between 1990 and 2012. Days Alive and Out of Hospital (DAOH) is an emerging surgical outcome metric. DAOH is a composite measure of outcomes, which may reflect patient experience and longer periods of DAOH may also reflect extended interactions with the health system. Recently, a 1.1-day difference in DAOH was observed between Maori and non-Maori at a hospital in NZ across a range of operations. METHODS AND ANALYSIS: We will conduct a secondary data analysis using data from the National Minimum Data Set, maintained by the Ministry of Health. We will report unadjusted and risk-adjusted DAOH values between Maori and non-Maori using direct risk standardisation. We will risk adjust first for age and sex, then for each of deprivation (NZDep18), levels of morbidity (M3 score) and rurality. We will report DAOH values across three time periods, 30, 90 and 365 days and across nine deciles of the DAOH distribution (0.1-0.9 inclusive). We will interpret all results from a Kaupapa Maori research positioning, acknowledging that Maori health outcomes are directly tied to the unequal distribution of the social determinants of health. ETHICS AND DISSEMINATION: Ethics approval for this study was given by the Auckland Health Research Ethics Committee. Outputs from this study are likely to interest a range of audiences. We plan to disseminate our findings through academic channels, presentations to interested groups including Maori-specific hui (meetings), social media and lay press.

Effects of Obesity and Insulin on Tissue-Specific Recycling Between Cortisol and Cortisone in Men.

CONTEXT: 11ß-Hydroxysteroid dehydrogenase 1 (11ßHSD1) reduces inert cortisone into active cortisol but also catalyzes reverse dehydrogenase activity. Drivers of cortisol/cortisone equilibrium are unclear. With obesity, 11ßHSD1 transcripts are more abundant in adipose, but the consequences for oxidation vs reduction remain unknown. OBJECTIVE: This work aimed to determine whether 11ßHSD1 equilibrium in metabolic tissues is regulated by insulin and obesity. METHODS: A 2-phase, randomized, crossover, single-blinded study in a clinical research facility was conducted of 10 lean and obese healthy men. 11ß-Reductase and 11ß-dehydrogenase activities were measured during infusion of 9,11,12,12-[2H]4-cortisol and 1,2-[2H]2-cortisone, respectively, on 2 occasions: once during saline infusion and once during a hyperinsulinemic-euglycemic clamp. Arterialized and venous samples were obtained across forearm skeletal muscle and abdominal subcutaneous adipose. Steroids were quantified by liquid chromatography-tandem mass spectrometry and adipose tissue transcripts by quantitative polymerase chain reaction. RESULTS: Neither whole-body nor tissue-specific rates of production of cortisol or cortisone differed between lean and obese men, however insulin attenuated the diurnal decrease. Whole-body 11ß-HSD1 reductase activity tended to be higher in obesity (~ 10%) and was further increased by insulin. Across adipose tissue, 11ß-reductase activity was detected in obese individuals only and increased in the presence of insulin (18.99 ±â€…9.62 vs placebo 11.68 ±â€…3.63 pmol/100 g/minute; P < .05). Across skeletal muscle, 11ß-dehydrogenase activity was reduced by insulin in lean men only (2.55 ±â€…0.90 vs 4.50 ±â€…1.42 pmol/100 g/minute, P < .05). CONCLUSIONS: Regeneration of cortisol is upregulated by insulin in adipose tissue but not skeletal muscle. In obesity, the equilibrium between 11ß-reductase and 11ß-dehydrogenase activities likely promotes cortisol accumulation in adipose, which may lead to adverse metabolic consequences.

Development and Validation of a Multivariate Prediction Model of Perioperative Mortality in Neurosurgery: The New Zealand Neurosurgical Risk Tool (NZRISK-NEURO).

BACKGROUND: Multivariate risk prediction models individualize prediction of adverse outcomes, assisting perioperative decision-making. There are currently no models specifically designed for the neurosurgical population. OBJECTIVE: To develop and validate a neurosurgical risk prediction model, with 30-d, 1-yr, and 2-yr mortality endpoints. METHODS: We accessed information on all adults in New Zealand who underwent neurosurgery or spinal surgery between July 1, 2011, and June 30, 2016, from an administrative database. Our dataset comprised of 18 375 participants, split randomly into derivation (75%) and validation (25%) datasets. Previously established covariates tested included American Society of Anesthesiologists physical status grade (ASA-PS), surgical acuity, operative severity, cancer status, and age. Exploratory covariates included anatomical site, gender, diabetes, trauma, ethnicity, and socioeconomic status. Least absolute shrinkage and selection operator (LASSO) regression analysis was used to construct 30-d, 1-yr, and 2-yr mortality models. RESULTS: Our final models included 8 covariates: age, ASA-PS grade, surgical acuity, cancer status, anatomical site, diabetes, ethnicity, and trauma. The area under the receiver operating curve for the 30-d, 1-yr, and 2-yr mortality models was 0.90, 0.91, and 0.91 indicating excellent discrimination, respectively. Calibration also showed excellent performance with McFadden's pseudo R2 statistics of 0.28, 0.37, and 0.41 and calibration plot slopes of 0.93, 0.95, and 0.94, respectively. The strongest predictors of mortality were ASA-PS 4 and 5 (30 d) and cancer (1 and 2 yr). CONCLUSION: NZRISK-NEURO is a robust multivariate calculator created specifically for neurosurgery, enabling physicians to generate data-driven individualized risk estimates, assisting shared decision-making and perioperative planning.

Postoperative mortality in New Zealand following general anaesthetic: demographic patterns and temporal trends.

OBJECTIVES: In this manuscript, we describe broad trends in postoperative mortality in New Zealand (a country with universal healthcare) for acute and elective/waiting list procedures conducted between 2005 and 2017. DESIGN, PARTICIPANTS AND SETTING: We use high-quality national-level hospitalisation data to compare the risk of postoperative mortality between demographic subgroups after adjusting for key patient-level confounders and mediators. We also present temporal trends and consider how rates in postoperative death following acute and elective/waiting list procedures have changed over this time period. RESULTS AND CONCLUSION: A total of 1 836 683 unique patients accounted for 3 117 374 admissions in which a procedure was performed under general anaesthetic over the study period. We observed an overall 30-day mortality rate of 0.5 per 100 procedures and a 90-day mortality rate of 0.9 per 100. For acute procedures, we observed a 30-day mortality rate of 1.6 per 100, compared with 0.2 per 100 for elective/waiting list procedures. In terms of procedure specialty, respiratory and cardiovascular procedures had the highest rate of 30-day mortality (age-standardised rate, acute procedures: 3-6 per 100; elective/waiting list: 0.7-1 per 100). As in other contexts, we observed that the likelihood of postoperative death was not proportionally distributed within our population: older patients, Maori patients, those living in areas with higher deprivation and those with comorbidity were at increased risk of postoperative death, even after adjusting for all available factors that might explain differences between these groups. Increasing procedure risk (measured using the Johns Hopkins Surgical Risk Classification System) was also associated with an increased risk of postoperative death. Encouragingly, it appears that risk of postoperative mortality has declined over the past decade, possibly reflecting improvements in perioperative quality of care; however, this decline did not occur equally across procedure specialties.

Long-term exposure to ambient air pollution and renal function in African Americans: the Jackson Heart Study.

Renal dysfunction is prevalent in the US among African Americans. Air pollution is associated with renal dysfunction in mostly white American populations, but has not been studied among African Americans. We evaluated cross-sectional associations between 1-year and 3-year fine particulate matter (PM2.5) and ozone (O3) concentrations, and renal function among 5090 African American participants in the Jackson Heart Study. We used mixed-effect linear regression to estimate associations between 1-year and 3-year PM2.5 and O3 and estimated glomerular filtration rate (eGFR), urine albumin/creatinine ratio (UACR), serum creatinine, and serum cystatin C, adjusting for: sociodemographic factors, health behaviors, and medical history and accounting for clustering by census tract. At baseline, JHS participants had mean age 55.4 years, and 63.8% were female; mean 1-year and 3-year PM2.5 concentrations were 12.2 and 12.4 µg/m3, and mean 1-year and 3-year O3 concentrations were 40.2 and 40.7 ppb, respectively. Approximately 6.5% of participants had reduced eGFR (< 60 mL/min/1.73m2) and 12.7% had elevated UACR (> 30 mg/g), both indicating impaired renal function. Annual and 3-year O3 concentrations were inversely associated with eGFR and positively associated with serum creatinine; annual and 3-year PM2.5 concentrations were inversely associated with UACR. We observed impaired renal function associated with increased O3 but not PM2.5 exposure among African Americans.

Neutrophil elastase-cleaved corticosteroid-binding globulin is absent in human plasma.

Corticosteroid-binding globulin (CBG) transports glucocorticoids in blood and is a serine protease inhibitor family member. Human CBG has a reactive center loop (RCL) which, when cleaved by neutrophil elastase (NE), disrupts its steroid-binding activity. Measurements of CBG levels are typically based on steroid-binding capacity or immunoassays. Discrepancies in ELISAs using monoclonal antibodies that discriminate between intact vs RCL-cleaved CBG have been interpreted as evidence that CBG with a cleaved RCL and low affinity for cortisol exists in the circulation. We examined the biochemical properties of plasma CBG in samples with discordant ELISA measurements and sought to identify RCL-cleaved CBG in human blood samples. Plasma CBG-binding capacity and ELISA values were consistent in arterial and venous blood draining skeletal muscle, liver and brain, as well as from a tissue (adipose) expected to contain activated neutrophils in obese individuals. Moreover, RCL-cleaved CBG was undetectable in plasma from critically ill patients, irrespective of whether their ELISA measurements were concordant or discordant. We found no evidence of RCL-cleaved CBG in plasma using a heat-dependent polymerization assay, and CBG that resists immunoprecipitation with a monoclonal antibody designed to specifically recognize an intact RCL, bound steroids with a high affinity. In addition, mass spectrometry confirmed the absence of NE-cleaved CBG in plasma in which ELISA values were highly discordant. Human CBG with a NE-cleaved RCL and low affinity for steroids is absent in blood samples, and CBG ELISA discrepancies likely reflect structural differences that alter epitopes recognized by specific monoclonal antibodies.

Improving Clinical Named-Entity Recognition with Transfer Learning.

Transfer learning is a powerful machine learning technique that enables the internalizing and reuse of prior knowledge to new tasks. Transfer learning is currently the starting point for recognition tasks such as computer vision. However, in natural language processing (NLP), the application of this technique is less prevalent. Our research investigates how, through the application of transfer learning, existing knowledge can be used to build more accurate NLP models. We subsequently applied these models to a named-entity recognition (NER) task. Our experimental results show significantly better recognition performance can be obtained through leveraging knowledge from a base model, trained using poorly annotated data.