The Contributing Risk of Tobacco Use for ARDS Development in Burn-Injured Adults With Inhalation Injury

Smoking on the risk of acute respiratory distress syndrome: a systematic review and meta-analysis

BACKGROUND

The relationship between smoking and the risk of acute respiratory distress syndrome (ARDS) has been recognized, but the conclusions have been inconsistent. This systematic review and meta-analysis investigated the association between smoking and ARDS risk in adults.

METHODS

The PubMed, EMBASE, Cochrane Library, and Web of Science databases were searched for eligible studies published from January 1, 2000, to December 31, 2023. We enrolled adult patients exhibiting clinical risk factors for ARDS and smoking condition. Outcomes were quantified using odds ratios (ORs) for binary variables and mean differences (MDs) for continuous variables, with a standard 95% confidence interval (CI).

RESULTS

A total of 26 observational studies involving 36,995 patients were included. The meta-analysis revealed a significant association between smoking and an increased risk of ARDS (OR 1.67; 95% CI 1.33-2.08; P < 0.001). Further analysis revealed that the associations between patient-reported smoking history and ARDS occurrence were generally similar to the results of all the studies (OR 1.78; 95% CI 1.38-2.28; P < 0.001). In contrast, patients identified through the detection of tobacco metabolites (cotinine, a metabolite of nicotine, and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL), a metabolite of tobacco products) showed no significant difference in ARDS risk (OR 1.19; 95% CI 0.69-2.05; P = 0.53). The smoking group was younger than the control group (MD - 7.15; 95% CI - 11.58 to - 2.72; P = 0.002). Subgroup analysis revealed that smoking notably elevated the incidence of ARDS with extrapulmonary etiologies (OR 1.85; 95% CI 1.43-2.38; P < 0.001). Publication bias did not affect the integrity of our conclusions. Sensitivity analysis further reinforced the reliability of our aggregated outcomes.

CONCLUSIONS

There is a strong association between smoking and elevated ARDS risk. This emphasizes the need for thorough assessment of patients' smoking status, urging healthcare providers to vigilantly monitor individuals with a history of smoking, especially those with additional extrapulmonary risk factors for ARDS.

Life after Burn, Part II: Substance Abuse, Relationship and Living Situation of Burn Survivors

Background and Objectives: After burns, social reintegration is a primary long-term objective. At the same time, substance-abuse disorders are more common in burn patients. The aim of this study was to assess prevalence of substance abuse pre- and postburn as well as living situation and relationship status relative to patient-reported health-related quality of life (HRQoL). Patients and Methods: Burn survivors treated as inpatients between 1 January 2012 and 31 December 2019 were retrospectively identified. Collected clinical data included: age, gender, time since injury, burn extent (%TBSA), and substance abuse. Patient-reported living situation, relationship status, smoking habits, alcohol and drug consumption pre- and postburn as well as the SF-36 study were ascertained via telephone survey. Inductive statistical analysis comprised uni- and multivariate testing. A p < 0.05 was considered as statistically significant. Results: A total of 128 patients, 93 (72.7%) men, with a mean age of 40.0 ± 15.7 years were included. Mean TBSA was 9.2 ± 11.0% and significantly lower in women (p = 0.005). General health SF-36 scores were significantly lower in women (67.6 ± 29.8) than men (86.0 ± 20.8, p = 0.002). Smoking decreased from 38.8% pre- to 31.1% postburn. A significant reduction in alcohol consumption was noted over time (p = 0.019). The rate of never-drinkers was 18.0% pre- and 27.3% postburn. Drug abuse was rare both pre- (7.8%) and postburn (5.3%). Living situation remained stable. None of the participants depended on assisted living or lived in a care facility postburn. In total, 75.8% and 67.2% were in a relationship pre- and postburn. Patients with higher alcohol consumption postburn were significantly more often male (p = 0.013) and had higher SF-36 general health scores (p < 0.001). Conclusions: HRQoL is better in men than in women after burn injury. A slight decrease in substance abuse postburn was noted. The connection between HRQoL and substance abuse after burn injuries needs to be investigated further in the future.

Outcomes and complications of diabetic burn injuries: a single center experience

INTRODUCTION

Comorbid conditions may adversely affect burn outcomes. Burn injuries remain one of the most prevalent injuries presenting to emergency departments. The current study compares the outcomes of burn injuries in diabetic and non-diabetic patients.

METHODS

A retrospective review of 705 burn patients admitted to the burn unit was performed. All adult patients (18 years old and above) who were admitted to the burn unit were included. The study compared the complications and outcomes of the diabetic and non-diabetic burn patient.

RESULTS

Patient were divided into diabetic (14%) and non-diabetic groups (86%). Diabetic burn patients were more likely to be older with a mean age of 58.7 years compared to 33.6 years in non-diabetic group (P=0.000). Inhalation injury was found in 3% of diabetic group compared to 14% of non-diabetic group (P=0.009). Diabetic patients were more likely to have associated medical comorbidities especially hypertension. Overall mortality rate was 13% and overall length of stay (LOS) was 28.4 days with no significant differences between groups.

CONCLUSION

Older age, hypertension and contact burns are significantly associated with DM in burn patients. No increased risk of burn-related infections, mortality and LOS were observed in the DM group.

A Computable Phenotype for Acute Respiratory Distress Syndrome Using Natural Language Processing and Machine Learning

Acute Respiratory Distress Syndrome (ARDS) is a syndrome of respiratory failure that may be identified using text from radiology reports. The objective of this study was to determine whether natural language processing (NLP) with machine learning performs better than a traditional keyword model for ARDS identification. Linguistic pre-processing of reports was performed and text features were inputs to machine learning classifiers tuned using 10-fold cross-validation on 80% of the sample size and tested in the remaining 20%. A cohort of 533 patients was evaluated, with a data corpus of 9,255 radiology reports. The traditional model had an accuracy of 67.3% (95% CI: 58.3-76.3) with a positive predictive value (PPV) of 41.7% (95% CI: 27.7-55.6). The best NLP model had an accuracy of 83.0% (95% CI: 75.9-90.2) with a PPV of 71.4% (95% CI: 52.1-90.8). A computable phenotype for ARDS with NLP may identify more cases than the traditional model.