Citations

ABSTRACT Introduction Postoperative mortality commonly follows complications that are not prevented, recognised or managed effectively. Ward‐based nursing care is central to surveillance, escalation and rescue, but population‐level evidence using shift‐level staffing data is limited. This national population‐based cohort study examined the association between surgical ward nurse staffing and postoperative outcomes. Methods Adults aged 18 years or older undergoing inpatient surgery under general or neuraxial anaesthesia in public hospitals in Aotearoa New Zealand between 2022 and 2024 were included. Prospectively recorded TrendCare staffing data were linked to administrative health datasets. The exposure was shift‐level staffing variance, defined as the difference between required and available nursing care hours on surgical wards in the treating hospital during admission. The primary outcome was 90‐day postoperative mortality. Secondary outcomes were postoperative complications and failure to rescue. Results The cohort included 202 428 patients undergoing 223 415 surgical admissions. Within 90 days, 6296 admissions resulted in death (2.8%). Complications occurred in 41 722 admissions (18.7%), with failure to rescue in 15.1%. Of 281 147 surgical ward shifts, 122 186 (43.5%) were understaffed. After adjustment, each one‐nurse reduction in staffing per shift was associated with higher odds of mortality (aOR: 1.13, 95% CI: 1.07–1.18), complications (aOR: 1.07, 95% CI: 1.05–1.10) and failure to rescue (aOR: 1.07, 95% CI: 1.00–1.14). Modelling estimated that correcting observed staffing deficits was associated with 182 fewer deaths annually. Conclusion Lower surgical ward nurse staffing was associated with increased postoperative mortality, complications and failure to rescue. Nurse staffing is a modifiable system factor associated with postoperative safety and should be prioritised to improve surgical outcomes.

Abstract Background Failure to rescue (FTR) is a key driver of postoperative mortality and reflects a hospital’s ability to recognize, escalate, and treat complications. Although FTR varies substantially between hospitals, the hospital characteristics that underpin this variation are inconsistently described. The aim of this study was to synthesize evidence on hospital-level factors associated with FTR after postoperative complications across surgical populations and health systems. Methods A systematic review of observational studies evaluating associations between hospital-level characteristics and FTR in surgical patients was undertaken. MEDLINE, EMBASE, and Scopus were systematically searched on 17 July 2024 and updated to 31 December 2025. Hospital factors were classified into structural, staffing, and system domains. Where three or more non-overlapping studies reported adjusted estimates in comparable formats, random-effects meta-analyses were performed; otherwise, findings were summarized narratively. Methodological quality of included studies was assessed using the ROBINS-I tool (version 2). Results A total of 111 studies encompassing over 137 million patients and 301 hospital factors were included. Meta-analyses demonstrated lower FTR rates in larger hospitals (odds ratio 0.85, 95% confidence interval 0.74 to 0.97), hospitals with greater intensive care unit capacity (odds ratio 0.80, 0.71 to 0.90), and teaching hospitals (odds ratio 0.88, 0.83 to 0.93). Better nursing resources were consistently associated with lower FTR, including patient-to-nurse ratios (odds ratio 1.07, 1.03 to 1.10), higher nurse education (odds ratio 0.95, 0.91 to 0.99), and more favourable work environments (odds ratio 0.93, 0.90 to 0.95). Safety-net hospital status was associated with higher FTR (odds ratio 1.22, 1.03 to 1.45). Substantial heterogeneity was observed across most analyses. Conclusion Hospital-level structural, staffing, and system characteristics are associated with variation in FTR. Postoperative mortality is closely linked to institutional capacity to detect and manage complications, underscoring the importance of adequate resourcing and system organization to improve surgical outcomes.

Summary Background Postoperative nausea and vomiting (PONV) is a common consequence of anaesthesia, affecting up to 30% of postoperative patients. Female sex is one of the strongest risk factors for PONV, yet no dedicated analysis has examined how this association varies across surgical settings and timepoints. This systematic review and meta-analysis aimed to quantify sex differences in PONV incidence across different surgical contexts. Methods A systematic search was conducted using PRISMA guidelines across Medline and Embase from inception to September 1, 2025. Eligible studies were observational cohort studies (n≥500) of adult patients that conducted multivariate regression analyses including sex as a variable. Two reviewers independently screened, extracted data, and assessed risk of bias using ROBINS-E. A random-effects meta-analysis was performed. Subgroup analyses and multiple sensitivity analyses were completed. Results From 4620 identified studies, 23 met the inclusion criteria, including 462,828 patients across various surgical settings and specialties (52% female). The pooled incidence of PONV was 21% (95% CI[16-27%]), with high heterogeneity (I 2 =99.9%). Meta-analysis confirmed females had a higher risk of developing PONV compared to males (pooled OR=2.40, 95% CI[2.06-2.79], I 2 =93.1%, p<0.0001). Sensitivity analyses confirmed robustness of pooled estimates. Subgroup analyses demonstrated consistently elevated risk of PONV for females at all three timepoints (PACU, 24-hour, 48-hour post-operative) and across studies including and excluding female-only surgeries. Studies were generally at high risk of bias. Discussion Female sex is a strong risk factor for PONV across surgical settings. Further research into precise subgroups, underlying mechanisms of sex-differences, and the use of prophylaxis may help improve this inequity.

Background Predictive models employing machine learning algorithms are increasingly being used in clinical decision making, and improperly calibrated models can result in systematic harm. We sought to investigate the impact of class imbalance correction, a commonly applied preprocessing step in machine learning model development, on calibration and modelled clinical decision making in a large real-world context. Methods A histogram boosted gradient classifier was trained on a highly imbalanced national dataset of >1.8 million patients undergoing surgery, to predict the risk of 90-day mortality and complications after surgery. Class imbalance correction strategies including random oversampling, synthetic minority oversampling technique, random under-sampling, and cost-sensitive learning were compared to the natural distribution ('natural'). Models were tested and compared with classification metrics, calibration plots, decision curve analysis, and simulated clinical impact analysis. Results The natural model demonstrated high performance (AUROC 0.94, 95% CI 0.94--0.95 for mortality; 0.84, 95% CI 0.84--0.85 for complications) and calibration (log loss 0.05, 95% CI 0.04--0.05 for mortality; 0.23, 95% CI 0.23--0.24 for complications). Class imbalance mitigation (CSL, ROS, RUS, and SMOTE) did not improve AUROC or AUPRC but increased recall and F1 scores at the expense of precision and accuracy. However, these methods severely compromised model calibration, leading to significant over-prediction of risks (up to a 62.8 % increase) as further evidenced by increased log loss across all mitigation techniques. Decision curve analysis and clinical scenario testing confirmed that the natural model provided the highest net benefit. Conclusion Class imbalance correction methods result in significant miscalibration, leading to possible harm whenused for clinical decision making.

ABSTRACT Background Many older adults undergo gastrointestinal (GI) cancer surgery, yet the relative impacts of advanced age, comorbidity, and frailty on postoperative mortality and failure to rescue (FTR) remain unclear. We aimed to compare the impacts of these factors on postoperative outcomes in a large population‐based cohort. Method We conducted a national retrospective linked database study of patients aged ≥ 65 years who underwent resection for GI or hepatobiliary cancer in Aotearoa New Zealand between 2005 and 2020. Age, comorbidity (C3 Comorbidity Score), and frailty (Hospital Frailty Risk Score) were examined as independent predictors of 90‐day mortality, complications, and FTR (death following a complication). Logistic regression models were adjusted for demographic and clinical covariates. Results Among 21,729 patients (mean age 75.8 ± 6.8 years), 49.3% experienced one or more complications and 6.1% died within 90 days (FTR rate of 12.3%). In adjusted models, each additional 5 years of age increased 90‐day mortality odds by 40% (adjusted odds ratio [aOR] 1.40 and 95% CI 1.34–1.46). Although higher comorbidity (C3 > 3) and frailty (Hospital Frailty Risk Score > 15) also independently raised mortality risk (aOR 1.98 and 2.04, respectively), age exerted the largest effect on mortality and FTR. Conclusion Chronological age, comorbidity, and frailty each predict worse outcomes following GI cancer surgery, but advanced age remains the dominant driver of 90‐day mortality and FTR. These findings underscore the need for risk stratification, shared decision‐making, and preoperative optimization as wells as intense surveillance for complications and early definitive care of older adults undergoing major oncologic operations.

Background Patient complaints provide a complementary lens on surgical safety, yet prior analyses have been small and specialty specific. We aimed to characterise themes, perioperative processes, system factors and outcomes in surgical complaints using a scalable, large language model (LLM)-assisted approach. Methods We performed a national, retrospective, cross-sectional, sequential methods study of publicly available investigation reports from the Aotearoa New Zealand Health and Disability Commissioner. All reports published since 1998 were retrieved and screened for relevance across all surgical specialties. A fixed-parameter LLM workflow extracted demographics, clinical context, complications, breached patient rights, system factors and outcomes. An inductive LLM-supported thematic synthesis generated complaint themes, followed by rescoring of theme relevance across reports. Human validation supported the LLM-assisted process (Cohen’s κ >0.85). Results Of 1827 reports screened, 650 involved surgical care. Postoperative complications were frequent (84.2%), commonly accompanied by permanent disability (33.2%) or death (24.2%). Delays in recognition of deterioration (76.1%), escalation (58.3%) and definitive management (49.5%) of complications were common and associated with higher mortality. Prominent themes concerned postoperative clinical management/monitoring, communication/informed consent and professional conduct/competence. Technical/procedural errors and medication errors were comparatively less common. Breaches are most often related to reasonable care and skill, and to informed consent, with marked variation across specialties. Conclusions Complaints about surgical care predominantly reflect postoperative monitoring, escalation and communication rather than intraoperative technical errors. System priorities should include robust deterioration recognition and response, reliable handover and escalation pathways, and strengthened consent and communication processes. An LLM-assisted pipeline can scale complaint analysis to support organisational learning and quality improvement.

Abstract Background Indigenous populations worldwide experience unjust inequities in surgical outcomes. In Aotearoa New Zealand, Indigenous Māori experience poorer health outcomes, including higher rates of postoperative mortality. The aim of this study was to quantify ethnic disparities in ‘failure to rescue’ (FTR), complications, and mortality following gastrointestinal cancer surgery and to analyse trends over time. Methods A retrospective national population-based cohort study of patients undergoing resection for gastrointestinal and hepatopancreatobiliary cancers from 2005 to 2020 was conducted. Self-reported ethnicity data were collected at the time of surgery. The primary outcome was FTR, defined as mortality following a complication within 90 days of surgery. Results In total, 31 185 patients were included; 2479 (7.9%) were Māori, 46.5% were female, and the median age was 71 (interquartile range 62–78) years. Māori patients were younger and had higher levels of socio-economic deprivation and co-morbidity. Māori had higher age-standardized rates of mortality (5.9% versus 3.2%), complications (52.9% versus 42.4%), and FTR (10.8% versus 7.2%), compared with European/Other. Multivariable regression demonstrated higher odds of mortality (adjusted OR (aOR) 1.45 (95% c.i. 1.15–1.82)), complications (aOR 1.30 (95% c.i. 1.17–1.45)), and FTR (aOR 1.29 (95% c.i. 1.01–1.62)) for Māori. Analysis over time showed a significant improvement in risk-adjusted rates of mortality (6.2% in 2005–2008 versus 3.4% in 2017–2020) and FTR (7.3% in 2005–2008 versus 4.0% in 2017–2020) for European/Other, but no change for Māori (rates of mortality were 6.6% in 2005–2008 versus 5.4% in 2017–2020 and rates of FTR were 7.8% in 2005–2008 versus 6.3% in 2017–2020). Conclusion Widening inequities in FTR have worsened disparities in postoperative mortality for Māori patients. ‘Complication rescue’ is a target to reduce inequities and improve perioperative care for Māori patients.