Risk factors for peri-intubation cardiac arrest: a systematic review and meta-analysis.

BACKGROUND: Peri-intubation cardiac arrest (PICA) is an uncommon yet serious complication of intubation. Although some associated risk factors have been identified, the results have been inconsistent. The aim of this study was to systematically review the relevant research and examine the associated risk factors of PICA through meta-analysis. METHODS: Studies examining the risk factors for PICA before 1 Nov. 2022 were identified through searches in MEDLINE (OvidSP) and EMBASE. The reported adjusted or unadjusted odds ratios (ORs) and risk ratios (RRs) were recorded. We calculated pooled ORs and created forest plots using a random-effects model to identify the statistically significant risk factors. We assessed the certainty of evidence for each risk factor. RESULTS: Eight studies were included in the meta-analysis. Pre-intubation hypotension, with a pooled OR of 4.96 (95% confidence interval [C.I.]: 3.75-6.57), pre-intubation hypoxemia, with a pooled OR of 4.43 (95% C.I.: 1.24-15.81), and two or more intubation attempts, with a pooled OR of 1.88 (95% C.I.: 1.09-3.23) were associated with a significantly higher risk of PICA. The pooled incidence of PICA was 2.1% (95% C.I.: 1.5%-3.0%). CONCLUSIONS: Pre-intubation hypotension, hypoxemia, and more intubation attempts are significant risk factors for PICA. The findings could help physicians identify patients at risk under the acute setting.

Clinical characteristics and risk factors for 30-day mortality in esophageal cancer patients with upper gastrointestinal bleeding: a multicenter study.

Background: Esophageal cancer is a highly malignant neoplasm with poor prognosis. Of its patients, upper gastrointestinal bleeding (UGIB) is one of the most challenging and threatening conditions in the emergency department (ED). However, no previous studies have analyzed the etiologies and clinical outcomes in this specific population. This study aimed to identify the clinical characteristics and risk factors for 30-day mortality in esophageal cancer patients with UGIB. Methods: This retrospective cohort study enrolled 249 adult patients with esophageal cancer presenting with UGIB in the ED. Patients was divided into the survivor and non-survivor groups, and their demographic information, medical history, comorbidities, laboratory parameters, and clinical findings were recorded. The factors associated with 30-day mortality were identified using Cox's proportional hazard model. Results: Among the 249 patients in this study, 30-day mortality occurred in 47 patients (18.9%). The most common causes of UGIB were tumor ulcer (53.8%), followed by gastric/duodenal ulcer (14.5%), and arterial-esophageal fistula (AEF) (12.0%). Multivariate analyses indicated that underweight (HR = 2.02, p = 0.044), history of chronic kidney disease (HR = 6.39, p < 0.001), active bleeding (HR = 2.24, p = 0.039), AEF (HR = 2.23, p = 0.046), and metastatic lymph nodes (HR = 2.99, p = 0.021) were independent risk factors for 30-day mortality. Conclusions: The most common cause of UGIB in esophageal cancer patients was tumor ulcer. AEF, accounting for 12% of UGIB in our study, is not an uncommon cause. Underweight, underlying chronic kidney disease, active bleeding, AEF, and tumor N stage > 0 were independent risk factors for 30-day mortality.

Performance of novice intubators in using direct laryngoscope with 3 stylets on a manikin model.

BACKGROUND: Tracheal intubation is an important clinical skill for medical students and junior residents (novice intubators). They are usually trained to use a direct laryngoscope (DL) with straight-to-cuff styletted tracheal tubes first. Only later are they exposed to the bougie as an airway adjunct and videolaryngoscope (VL) with either a standard blade or a hyperangulated blade. The purpose of this study was to investigate the performance of novice intubators in using DL with 3 common stylets. METHODS: We conducted a prospective study to compare the performance of DL with 3 common stylets, namely the straight-to-cuff stylet (S), hyperangulated VL stylet (G), and bougie (B), on a manikin model. RESULTS: Among 72 participants, no significant difference was observed between the success rates of S, G, and B at the first attempt (84.72%, 81.94%, and 86.11%, respectively [P = .78]) or within 2 minutes (91.67%, 93.06%, and 91.67%, respectively [P = .94]). For participants with successful intubation within 2 minutes, the average total intubation times for S, G, and B were 25.05, 24.39, and 37.45 seconds, respectively. Among the 3 stylets, B had the longest intubation time, which differed significantly from S and G (P < .01). CONCLUSIONS: The performances of novice intubators with 3 different stylets were similar. The success rates for DL with either hyperangulated VL stylet or bougie were not inferior compared with the straight-to-cuff stylet on manikin airway training model. If we properly trained novice intubators to use corresponding maneuvers, they can learn to use the 3 stylets early in their airway learning course.

Risk factors associated with peri-intubation cardiac arrest in the emergency department.

BACKGROUND: Peri-intubation cardiac arrest is an uncommon, serious complication following endotracheal intubation in the emergency department. Although several risk factors have been previously identified, this study aimed to comprehensively identify risk factors associated with peri-intubation cardiac arrest. METHODS: This retrospective, nested case-control study conducted from January 1, 2016 to December 31, 2020 analyzed variables including demographic characteristics, triage, and pre-intubation vital signs, medications, and laboratory data. Univariate analysis and multivariable logistic regression models were used to compare clinical factors between the patients with peri-intubation cardiac arrest and patients without cardiac arrest. RESULTS: Of the 6983 patients intubated during the study period, 5130 patients met the inclusion criteria; 92 (1.8%) patients met the criteria for peri-intubation cardiac arrest and 276 were age- and sex-matched to the control group. Before intubation, systolic blood pressure and diastolic blood pressure were lower (104 vs. 136.5 mmHg, p < 0.01; 59.5 vs. 78 mmHg, p < 0.01 respectively) and the shock index was higher in the patients with peri-intubation cardiac arrest than the control group (0.97 vs. 0.83, p < 0.0001). Cardiogenic pulmonary edema as an indication for intubation (adjusted odds ratio [aOR]: 5.921, 95% confidence interval [CI]: 1.044-33.57, p = 0.04), systolic blood pressure < 90 mmHg before intubation (aOR: 5.217, 95% CI: 1.484-18.34, p = 0.01), and elevated lactate levels (aOR: 1.012, 95% CI: 1.002-1.022, p = 0.01) were independent risk factors of peri-intubation cardiac arrest. CONCLUSIONS: Patients with hypotension before intubation have a higher risk of peri-intubation cardiac arrest in the emergency department. Future studies are needed to evaluate the influence of resuscitation before intubation and establish airway management strategies to avoid serious complications.

Statistical principle-based approach for gene and protein related object recognition.

The large number of chemical and pharmaceutical patents has attracted researchers doing biomedical text mining to extract valuable information such as chemicals, genes and gene products. To facilitate gene and gene product annotations in patents, BioCreative V.5 organized a gene- and protein-related object (GPRO) recognition task, in which participants were assigned to identify GPRO mentions and determine whether they could be linked to their unique biological database records. In this paper, we describe the system constructed for this task. Our system is based on two different NER approaches: the statistical-principle-based approach (SPBA) and conditional random fields (CRF). Therefore, we call our system SPBA-CRF. SPBA is an interpretable machine-learning framework for gene mention recognition. The predictions of SPBA are used as features for our CRF-based GPRO recognizer. The recognizer was developed for identifying chemical mentions in patents, and we adapted it for GPRO recognition. In the BioCreative V.5 GPRO recognition task, SPBA-CRF obtained an F-score of 73.73% on the evaluation metric of GPRO type 1 and an F-score of 78.66% on the evaluation metric of combining GPRO types 1 and 2. Our results show that SPBA trained on an external NER dataset can perform reasonably well on the partial match evaluation metric. Furthermore, SPBA can significantly improve performance of the CRF-based recognizer trained on the GPRO dataset.