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.

ABSTRACT Introduction Chronic gastroduodenal disorders remain challenging to manage, and new diagnostic approaches are needed to better delineate underlying causes and guide therapeutic decisions. Body Surface Gastric Mapping (BSGM) technologies combine high‐resolution gastric myoelectrical activity measurements with symptom and psychological profiling to provide mechanistic insights into gastric motor and sensory dysfunction. An International Working Group convened to derive the first consensus classification of BSGM phenotypes (the “Auckland Classification”). Methods A Technical Group conducted a systematic literature and clinical database review to identify objective test biomarkers and candidate disease mechanisms. Evidence was synthesized across 50 studies (primarily in gastroparesis, chronic nausea and vomiting, and functional dyspepsia), and BSGM phenotypes were mapped to existing treatment guidelines. Subsequently, iterative review and development of consensus was performed by a Consensus Group composed of international clinical experts familiar with BSGM. Eleven statements underlying the classification were then derived and circulated as a final survey to establish agreement. Results Six BSGM phenotypes were endorsed: three defined by myoelectrical abnormalities (Dysrhythmic, High Frequency, and Low Meal Response) and three by characteristic symptom associations (Sensorimotor, Continuous, and Delayed Onset Symptoms). Published studies plausibly linked these phenotypes to mechanisms including interstitial cell of Cajal depletion, vagal impairment, hypomotility, visceral hypersensitivity, gut‐brain dysregulation, and small bowel dysfunction. Phenotypes were also mapped to existing mechanism‐based treatment guidelines. Ten out of the eleven statements had > 80% agreement. Conclusions The Auckland Classification, derived by international consensus, presents a structured framework for BSGM‐defined patient phenotypes. Evidence and mechanism‐based treatment options are suggested for each phenotype to provide a foundation for research, further validation, and a pathway for integrating BSGM into clinical care.

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.

ABSTRACT Background The assessment of gastrointestinal (GI) motility disorders is limited by the invasive, resource‐intensive, and subjective nature of current testing. Artificial Intelligence (AI) is being applied to address these challenges. This review aimed to comprehensively identify, appraise, and synthesize the spectrum of AI applications in GI motility diagnostics. Methods A systematic search of PubMed, Embase, Scopus, Web of Science, and Medline for original studies was conducted in March 2025. Results were narratively synthesized and grouped by anatomic region. Key Results Of 1383 articles, 90 primary studies met the inclusion criteria. In the esophagus ( n = 31), the primary focus was automation of High‐Resolution Esophageal Manometry (HREM), pH impedance, and Functional Luminal Imaging Probe (FLIP) panometry analysis. In the gastroduodenum ( n = 21), studies looked to improve diagnostic accuracy and interpretability of legacy electrogastrography (EGG). In the small and large intestine ( n = 19), AI was used to determine transit time and predict post‐operative ileus. In the anorectum ( n = 9), tools focused on standardizing manometry interpretation. Review of pan‐GI applications ( n = 10) highlighted AI's application to wireless capsule endoscopy and bowel sounds analysis. While promising, all areas need more rigorous research and external validation before widespread deployment. Conclusions and Inferences AI will play an essential role in improving and automating the interpretation of GI motility diagnostics. However, even the most promising models require large‐scale prospective validation before clinical implementation. Trial Registration PROSPERO (ID: 1128662)

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.

Chronic nausea and vomiting syndromes (NVSs) are prevalent and debilitating disorders. Putative mechanisms include gastric neuromuscular disease and dysregulation of brain-gut interaction, but clinical tests for objectively defining gastric motor function are lacking. A medical device enabling noninvasive body surface gastric mapping (BSGM) was developed and applied to evaluate NVS pathophysiology. BSGM was performed in 43 patients with NVS and 43 matched controls using Gastric Alimetry (Alimetry), a conformable high-resolution array (8 × 8 electrodes; 20-mm interelectrode spacing), wearable reader, and validated symptom-logging app. Continuous measurement encompassed a fasting baseline (30 minutes), 482-kilocalorie meal, and 4-hour postprandial recording, followed by spectral and spatial biomarker analyses. Meal responses were impaired in NVS, with reduced amplitudes compared to controls (median, 23.3 microvolts versus 38.0 microvolts, P < 0.001), impaired fed-fasting power ratios (1.1 versus 1.6, P = 0.02), and disorganized slow waves (spatial frequency stability, 13.6 versus 49.5; P < 0.001). Two distinct NVS subgroups were evident with indistinguishable symptoms (all P > 0.05). Most patients (62%) had normal BSGM studies with increased psychological comorbidities (43.5% versus 7.7%; P = 0.03) and anxiety scores (median, 16.5 versus 13.0; P = 0.035). A smaller subgroup (31%) had markedly abnormal BSGM, with biomarkers correlating with symptoms (nausea, pain, excessive fullness, early satiety, and bloating; all r > 0.35, P < 0.05). Patients with NVS share overlapping symptoms but comprise distinct underlying phenotypes as revealed by a BSGM device. These phenotypes correlate with symptoms, which should inform clinical management and therapeutic trial design.

Depletion of interstitial cells of Cajal (ICC) networks is known to occur in several gastrointestinal motility disorders. Although confocal microscopy can effectively image and visualize the spatial distribution of ICC networks, current descriptors of ICC depletion are limited to cell numbers and volume computations. Spatial changes in ICC network structural properties have not been quantified. Given that ICC generate electrical signals, the organization of a network may also affect physiology. In this study, six numerical metrics were formulated to automatically determine complex ICC network structural properties from confocal images: density , thickness , hole size , contact ratio , connectivity and anisotropy . These metrics were validated and applied in proof-of-concept studies to quantitatively determine jejunal ICC network changes in mouse models with decreased ( 5-HT 2 B receptor knockout (KO)) and normal ( Ano1 KO) ICC numbers, and during post-natal network maturation. Results revealed a novel remodelling phenomenon occurring during ICC depletion, namely a spatial rearrangement of ICC and the preferential longitudinal alignment. In the post-natal networks, an apparent pruning of the ICC network was demonstrated. The metrics developed here enabled the first detailed quantitative analyses of structural changes that may occur in ICC networks during depletion and development.