Clinical application of bronchoalveolar lavage fluid metagenomics next-generation sequencing in cancer patients with severe pneumonia.

OBJECTIVE: Metagenomic next-generation sequencing (mNGS), as an emerging technique for pathogen detection, has been widely used in clinic. However, reports on the application of mNGS in cancer patients with severe pneumonia remain limited. This study aims to evaluate the diagnostic performance of bronchoalveolar lavage fluid (BALF) mNGS in cancer patients complicated with severe pneumonia. METHODS: A total of 62 cancer patients with severe pneumonia simultaneously received culture and mNGS of BALF were enrolled in this study. We systematically analyzed the diagnostic significance of BALF mNGS. Subsequently, optimization of anti-infective therapy based on the distribution of pathogens obtained from BALF mNGS was also assessed. RESULTS: For bacteria and fungi, the positive detection rate of mNGS was significantly higher than culture method (91.94% versus 51.61%, P < 0.001), especially for poly-microbial infections (70.97% versus 12.90%, P < 0.001). Compared with the culture method, mNGS exhibited a diagnostic sensitivity of 100% and a specificity of 16.67%, with the positive predictive value (PPV) and negative predictive value (NPV) being 56.14% and 100%, respectively. The agreement rate between these two methods was 59.68%, whereas kappa consensus analysis indicated a poor concordance (kappa = 0.171). After receipt of BALF mNGS results, anti-infective treatment strategies in 39 out of 62 cases (62.90%) were optimized. Moreover, anti-tumor therapy was a high-risk factor for mixed infections (87.18% versus 65.22%, P = 0.04). CONCLUSIONS: The present study showed that cancer patients with severe pneumonia, especially those received anti-tumor therapy, were more likely to have poly-microbial infections. BALF mNGS can provide a rapid and comprehensive pathogen distribution of pulmonary infection, making it a promising technique in clinical practice, especially for optimizing therapeutic strategies for cancer patients.

Prognostic and risk factor analysis of cancer patients after unplanned ICU admission: a real-world multicenter study.

To investigate the occurrence and 90-day mortality of cancer patients following unplanned admission to the intensive care unit (ICU), as well as to develop a risk prediction model for their 90-day prognosis. We prospectively analyzed data from cancer patients who were admitted to the ICU without prior planning within the past 7 days, specifically between May 12, 2021, and July 12, 2021. The patients were grouped based on their 90-day survival status, and the aim was to identify the risk factors influencing their survival status. A total of 1488 cases were included in the study, with an average age of 63.2 ± 12.4 years. The most common reason for ICU admission was sepsis (n = 940, 63.2%). During their ICU stay, 29.7% of patients required vasoactive drug support (n = 442), 39.8% needed invasive mechanical ventilation support (n = 592), and 82 patients (5.5%) received renal replacement therapy. We conducted a multivariate COX proportional hazards model analysis, which revealed that BMI and a history of hypertension were protective factors. On the other hand, antitumor treatment within the 3 months prior to admission, transfer from the emergency department, general ward, or external hospital, high APACHE score, diagnosis of shock and respiratory failure, receiving invasive ventilation, and experiencing acute kidney injury (AKI) were identified as risk factors for poor prognosis within 90 days after ICU admission. The average length of stay in the ICU was 4 days, while the hospital stay duration was 18 days. A total of 415 patients died within 90 days after ICU admission, resulting in a mortality rate of 27.9%. We selected 8 indicators to construct the predictive model, which demonstrated good discrimination and calibration. The prognosis of cancer patients who are unplanned transferred to the ICU is generally poor. Assessing the risk factors and developing a risk prediction model for these patients can play a significant role in evaluating their prognosis.

Intraoperative airway management for patients with tracheal tumors: A case series of 37 patients.

BACKGROUND: Tracheal tumors are rare. The aim of this case series was to investigate airway selection during radical surgery for patients with tracheal tumors. METHODS: Here, we performed a retrospective case review of patients with tracheal tumors who underwent tracheal surgery in our center. A total of 37 cases, including 26 patients with primary tracheal tumors and 11 cases with advanced thyroid cancer, were enrolled into the study. Baseline characteristics and differential prognosis of included patients were estimated. We summarize the strategies for intraoperative airway selection and analyze the risk factors associated with delayed extubation. RESULTS: There is a trend for primary tracheal tumors to appear toward the upper (9 of 26) and middle third (9 of 26) of the trachea, followed by the lower third airway (8 of 26). Advanced thyroid cancers occur most frequently in the upper trachea (7 of 11) and then the middle trachea (4 of 11). All primary and secondary patients underwent R0 resection. Minor histological subtypes were found to correlate with a poor prognosis. Extracorporeal support and tracheotomy intubation were applied in high-risk cases, and a total of 32 patients achieved intrathoracic intubation during the surgical process. Intensive care unit (ICU) delay (>1 day) was observed among 25 patients, which were not enriched in cases who underwent cross-field endotracheal intubation. Additionally, temporal suboptimal oxygenation (SpO2 < 95%) was an independent risk factor of ICU delay. CONCLUSIONS: Airway selection plays an important role in successful tracheal surgery, and an appropriate ventilation routine depends on the patient and a surgical process which is safe and effective.