Machine-Learned Algorithms to Predict the Risk of Pneumothorax Requiring Chest Tube Placement after Lung Biopsy

PURPOSE

To develop a machine-learned algorithm to predict the risk of postlung biopsy pneumothorax requiring chest tube placement (CTP) to facilitate preprocedural decision making, optimize patient care, and improve resource allocation.

MATERIALS AND METHODS

This retrospective study collected clinical and imaging features of biopsy samples obtained from patients with lung nodule biopsy and included information from 59 procedures resulting in pneumothorax requiring CTP and randomly selected 67 procedures without CTP (convenience sample). The data were divided into 70 and 30 as training and testing sets, respectively. Conventional machine-learned binary classifiers were explored with preprocedural imaging and clinical data as input features and CTP as the output.

RESULTS

There was no single pathognomonic imaging or predictive clinical feature. For the independent test set under the high-specificity mode, a decision tree, logistic regression, and Naïve Bayes classifier achieved accuracies of identifying CTP at 0.79, 0.93, and 0.89 and area under receiver operating curves (AUROCs) of 0.68, 0.76, and 0.82, respectively. Under high-sensitivity mode, a decision tree, logistic regression, and Naïve Bayes achieved accuracies of identifying CTP of 0.60, 0.45, and 0.60 with AUROCs of 0.71, 0.81, and 0.82, respectively. High importance features included lesion character, chronic obstructive pulmonary disease, lesion depth, and age. A coarse decision tree requiring 4 inputs achieved comparable performance as other methods and previous machine learning prediction studies.

CONCLUSIONS

The results support the possibility of predicting pneumothorax requiring CTP after biopsy based on an automated decision support, reliant on readily available preprocedural information.

Taking Control of Your Surgery: Impact of a Prehabilitation Program on Major Abdominal Surgery

BACKGROUND

Surgery is a major physiologic stress comparable to intense exercise. Diminished cardiopulmonary reserve is a major predictor of poor outcomes. Current preoperative workup focuses mainly on identifying risk factors; however, little attention is devoted to improving cardiopulmonary reserve beyond counseling. We propose that patients could be optimized for a "surgical marathon" similar to the preparation of an athlete.

STUDY DESIGN

The Michigan Surgical and Health Optimization Program (MSHOP) is a formal prehabilitation program that engages patients in 4 activities before surgery: physical activity, pulmonary rehabilitation, nutritional optimization, and stress reduction. We prospectively collected demographic, intraoperative (first hour), and postoperative data for patients enrolled in MSHOP undergoing major abdominal surgery. Statistical analysis was performed using 2:1 propensity score matching to compare the MSHOP group (n = 40) to emergency (n = 40) and elective, non-MSHOP (n = 76) patients.

RESULTS

Overall, 70% of MSHOP patients complied with the program. Age, sex, American Society of Anesthesiologists (ASA) classification, and BMI did not differ significantly between groups. One hour intraoperatively, MSHOP patients showed improved systolic and diastolic blood pressures and lower heart rate (Figure). There was a significant reduction in Clavien-Dindo class 3 to 4 complications in the MSHOP group (30%) compared with the nonprehabilitation (38%) and emergency (48%) groups (p = 0.05). This translated to total hospital charges averaging $75,494 for the MSHOP group, $97,440 for the nonprehabilitation group, and $166,085 for the emergency group (p < 0.001).

CONCLUSIONS

Patients undergoing prehabilitation before colectomy showed positive physiologic effects and experienced fewer complications. The average savings of $21,946 per patient represents a significant cost offset for a prehabilitation program, and should be considered for all patients undergoing surgery.

Bt Eggplant Project in Bangladesh: History, Present Status, and Future Direction

The purpose of this article is to provide information on the history, accomplishments, and future direction of the Bt brinjal (eggplant) program in Bangladesh, formerly under the Agricultural Biotechnology Support Project II, now the South Asia Eggplant Improvement Partnership (SAEIP). The India-based Maharashtra Hybrid Seed Company (Mahyco) developed an eggplant expressing Cry1Ac (EE-1) for control of the eggplant fruit and shoot borer (EFSB). In a partnership among Mahyco, USAID, Sathguru Management Consultants and Cornell University EE-1 was provided to the Bangladesh Agricultural Research Institute (BARI) who bred it into local varieties. After regulatory approval, four varieties were distributed to 20 farmers who harvested Bt brinjal in 2014. Adoption in subsequent years has increased rapidly so that, in 2018, 27,012 farmers used this technology. This article provides background information on the process leading up to current adoption levels, the level of control of EFSB achieved and the economic benefits of Bt brinjal. Efforts on stewardship, farmer training and communication are discussed. In order to ensure the long-term future of the partnership, we discuss the need to enhance involvement of the private sector in the production and stewardship of Bt eggplant. Bt brinjal is the first genetically engineered crop to be commercially released in Bangladesh, and other GE crops are in the pipeline. Hence, success of the Bt brinjal partnership is likely to affect the future of other GE crops in Bangladesh, as well as other parts of the world where biotechnology is needed for food security and environmental safety.

Provision of mouth-care in long-term care facilities: an educational trial

OBJECTIVES

This randomized clinical trial aimed to assess the effectiveness of a pyramid-based education for improving the oral health of elders in long-term care (LTC) facilities.

METHODS

Fourteen facilities matched for size were assigned randomly to an active or control group. At baseline in each facility, care-aides in the active group participated with a full-time nurse educator in a seminar about oral health care, and had unlimited access to the educator for oral health-related advice throughout the 3-month trial. Care-aides in the control group participated in a similar seminar with a dental hygienist but they received no additional advice. The residents in the facilities at baseline and after 3 months were examined clinically to measure their oral hygiene, gingival health, masticatory potential, Body Mass Index and Malnutrition Indicator Score, and asked to report on chewing difficulties.

RESULTS

Clinical measures after 3 months were not significantly different from baseline in either group, indicating that education neither influenced the oral health nor the dental hygiene of the residents.

CONCLUSIONS

A pyramid-based educational scheme with nurses and care-aides did not improve the oral health of frail elders in this urban sample of LTC facilities.