Background Mental illness (MI) is common among those who work in health care settings. Whether MI is related to employees’ mental status at work is yet to be determined. An MI app is developed and proposed to help employees assess their mental status in the hope of detecting MI at an earlier stage. Objective This study aims to build a model using convolutional neural networks (CNNs) and fit statistics based on 2 aspects of measures and outfit mean square errors for the automatic detection and classification of personal MI at the workplace using the emotional labor and mental health (ELMH) questionnaire, so as to equip the staff in assessing and understanding their own mental status with an app on their mobile device. Methods We recruited 352 respiratory therapists (RTs) working in Taiwan medical centers and regional hospitals to fill out the 44-item ELMH questionnaire in March 2019. The exploratory factor analysis (EFA), Rasch analysis, and CNN were used as unsupervised and supervised learnings for (1) dividing RTs into 4 classes (ie, MI, false MI, health, and false health) and (2) building an ELMH predictive model to estimate 108 parameters of the CNN model. We calculated the prediction accuracy rate and created an app for classifying MI for RTs at the workplace as a web-based assessment. Results We observed that (1) 8 domains in ELMH were retained by EFA, (2) 4 types of mental health (n=6, 63, 265, and 18 located in 4 quadrants) were classified using the Rasch analysis, (3) the 44-item model yields a higher accuracy rate (0.92), and (4) an MI app available for RTs predicting MI was successfully developed and demonstrated in this study. Conclusions The 44-item model with 108 parameters was estimated by using CNN to improve the accuracy of mental health for RTs. An MI app developed to help RTs self-detect work-related MI at an early stage should be made more available and viable in the future.

The aim of this study was to establish predictors for successfully planned extubation, which can be followed by medical personnel. The patients who were admitted to the adult intensive care unit of a tertiary hospital and met the following criteria between January 2005 and December 2014 were collected retrospectively: intubation > 48 hours; and candidate for extubation. The patient characteristics, including disease severity, rapid shallow breath index (RSBI), maximal inspiratory pressure (MIP), maximal expiratory pressure (MEP), cuff leak test (CLT) before extubation, and outcome, were recorded. The CLT was classified as 2+ with audible flow without a stethoscope, 1+ with audible flow using a stethoscope, and negative (N) with no audible flow, even with a stethoscope. Failure to extubate was defined as reintubation within 48 hours. In total, 6583 patients were enrolled and 403 patients (6.1%) had extubation failures. Male patients dominated the patient cohort (4261 [64.7%]). The mean age was 64.5±16.3 years. The overall in-hospital mortality rate was 11.3%. The extubation failure rate for females was greater than males (7.7% vs 5.3%, P < 0.001). The group of patients who failed extubation were older (66.7 ± 14.4 vs 64.3 ± 16.4, P = 0.002), had higher APACHE II scores (16.8 ± 7.6 vs 15.9 ± 7.8, P = 0.023), lower coma scales (10.3 ± 3.7 vs 10.8 ± 3.7, P = 0.07), a higher RSBI (69.9 ± 37.3 vs 58.6 ± 30.3, P < 0.001), a lower MIP, and MEP (−35.6 ± 15.3 vs −37.8 ± 14.6, P = 0.0001 and 49.6 ± 28.4 vs 58.6 ± 30.2, P < 0.001, respectively), and a higher mortality rate (25.6% vs 10.5%, P < 0.001) compared to the successful extubation group. Based on multivariate logistic regression, a CLT of 2+ (odds ratio [OR] = 2.07, P < 0.001), a MEP ≥ 55 cmH2O (OR = 1.73, P < 0.001), and a RSBI < 68 breath/min/ml (OR = 1.57, P < 0.001) were independent predictors for successful extubation.This study identified 3 independent risk factors for successful extubation after a successful breathing trial, including a CLT of 2+, a MEP ≥ 55 cmH2O, and a RSBI < 68 breath/min/ml. Furthermore, a nomogram integrating these 3 parameters, which represented the combined consideration of the upper airway patentency, cough strength, and respiratory capacity, was developed to better predict extubation success.

This study investigated the prognostic factors and outcomes of unplanned extubation (UE) in patients in a medical center’s 6 intensive care units (ICUs) and calculated their mortality risk. We retrospectively reviewed the medical records of all adult patients in Chi Mei Medical Center who underwent UE between 2009 and 2015. During the study period, there were 305 episodes of UE in 295 ICU patients (men: 199 [67.5%]; mean age: 65.7 years; age range: 18–94 years). The mean Acute Physiology and Chronic Health Evaluation (APACHE) II score was 16.4, mean therapeutic intervention scoring system (TISS) score was 26.5, and mean Glasgow coma scale score was 10.4. One hundred thirty-six patients (46.1%) were re-intubated within 48 h. Forty-five died (mortality rate: 15.3%). Multivariate analyses showed 5 risk factors—respiratory rate, APACHE II score, uremia, liver cirrhosis, and weaning status—were independently associated with mortality. In conclusion, five risk factors including a high respiratory rate before UE, high APACHE II score, uremia, liver cirrhosis, and not in the process of being weaned—were associated with high mortality in patients who underwent UE.

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We investigated failure predictors for the planned extubation of overweight (body mass index [BMI] = 25.0–29.9) and obese (BMI ≥ 30) patients. All patients admitted to the adult intensive care unit (ICU) of a tertiary hospital in Taiwan were identified. They had all undergone endotracheal intubation for > 48 h and were candidates for extubation. During the study, 595 patients (overweight = 458 [77%]); obese = 137 [23%]) with planned extubation after weaning were included in the analysis; extubation failed in 34 patients (5.7%). Their mean BMI was 28.5 ± 3.8. Only BMI and age were significantly different between overweight and obese patients. The mortality rate for ICU patients was 0.8%, and 2.9% for inpatients during days 1–28; the overall in-hospital mortality rate was 8.4%. Failed Extubation group patients were significantly older, had more end-stage renal disease (ESRD), more cardiovascular system-related respiratory failure, higher maximal inspiratory pressure (MIP), lower maximal expiratory pressure (MEP), higher blood urea nitrogen, and higher ICU- and 28-day mortality rates than did the Successful Extubation group. Multivariate logistic regression showed that cardiovascular-related respiratory failure (odds ratio [OR]: 2.60; 95% [confidence interval] CI: 1.16–5.80), ESRD (OR: 14.00; 95% CI: 6.25–31.35), and MIP levels (OR: 0.94; 95% CI: 0.90–0.97) were associated with extubation failure. We conclude that the extubation failure risk in overweight and obese patients was associated with cardiovascular system-related respiratory failure, ESRD, and low MIP levels.