BackgroundDelta check is widely used for detecting specimen mix-ups. Owing to the inadequate specificity and sparseness of the absolute incidence of mix-ups, the positive predictive value (PPV) of delta check is considerably low as it is labor consuming to identify true mix-up errors among a large number of false alerts. To overcome this problem, we developed a new accurate detection model through machine learning.MethodsInspired by delta check, we decided to conduct comparisons with the past examinations and broaden the time range. Fifteen common items were selected from complete blood cell counts and biochemical tests. We considered examinations in which ≥11 among the 15 items were measured simultaneously in our hospital; we created individual partial time-series data of the consecutive examinations with a sliding window size of 4. The last examinations of the partial time-series data were shuffled to generate artificial mix-up cases. After splitting the dataset into development and validation sets, we allowed a gradient-boosting-decision-tree (GBDT) model to learn using the development set to detect whether the last examination results of the partial time-series data were artificial mixed-up results. The model’s performance was evaluated on the validation set.ResultsThe area under the receiver operating characteristic curve (ROC AUC) of our model was 0.9983 (bootstrap confidence interval [bsCI]: 0.9983–0.9985).ConclusionsThe GBDT model was more effective in detecting specimen mix-up. The improved accuracy will enable more facilities to perform more efficient and centralized mix-up detection, leading to improved patient safety.

Objectives Cytoreductive surgery combined with hyperthermic intraperitoneal chemotherapy (CRS-HIPEC) has been established in the management of peritoneal carcinomatosis. Although it is still necessary to take adequate measures against major postoperative complications including acute kidney injury (AKI), consensus is lacking on how to assess and stratify risk for patients with postoperative AKI after CRS-HIPEC. The aim of this retrospective cohort study was to investigate the association of intraoperative gross hematuria as a surrogate marker of ureter injury with postoperative AKI incidence. Methods This retrospective cohort study investigated patients without impaired preoperative kidney function who underwent CRS-HIPEC at a single referral center, and evaluated the relationship between intraoperative gross hematuria and incidence of postoperative AKI as defined by the Kidney Disease Improving Global Outcomes practice guidelines. Logistic regression analysis was performed to calculate the odds ratio of intraoperative gross hematuria for AKI, adjusting for confounding factors and other risk factors for AKI. Results We enrolled 185 patients (males, 37%). Twenty-five patients developed intraoperative gross hematuria. Postoperative AKI occurred in 10 (40%) of 25 patients with hematuria and 28 (17.5%) of 160 patients without hematuria. The crude odds ratio for exposure to hematuria was 3.14 (95% confidence interval, 1.30–7.60; p=0.020) for postoperative AKI. Adjusted odds ratio as estimated by multivariate logistic regression was 4.57 (95% confidence interval, 1.55–13.45; p=0.006). Conclusions Intraoperative gross hematuria is significantly associated with postoperative AKI incidence after CRS-HIPEC.

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Background: Intracranial embolism related to cerebral angiography is rare but one of the complications of the procedure. However, the standard management of acute intracranial embolism for this etiology has not been established, and there have been very few reports in the past. Case Description: A 68-year-old male was incidentally found to have an unruptured aneurysm of anterior communicating artery (ACoA). Immediately after the cerebral angiography for the purpose of detailed examination of the aneurysm, the right partial hemiparalysis and mild aphasia developed. Magnetic resonance imaging/angiography (MRI/A) revealed an occlusion in the peripheral part of the left middle cerebral artery (MCA). Due to the existence of magnetic resonance angiography-diffusion mismatch, emergent craniotomy was immediately performed to remove intra-arterial thrombus. We also performed clipping for an unruptured ACoA aneurysm with this approach. Postoperative MRI/A showed that the occluded artery was recanalized and a slight infarction was observed in the left cerebral hemisphere. The patient was discharged on foot and followed at outpatient clinic over 4 years without no neurological deficit. Conclusion: Emergent surgical embolectomy for distal MCA occlusion related to cerebral angiography followed by neck clipping for an unruptured aneurysm of the ACoA was successful in treating acute occlusion of the peripheral part of the MCA in a patient with an unruptured aneurysm. As there are few similar cases, there is controversy about the best management, but this surgical method can be a safe and effective treatment.

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