scholarly journals Risk factors and outcomes of conversion in minimally invasive distal pancreatectomy: a systematic review

2020 ◽  
Author(s):  
A. Balduzzi ◽  
◽  
N. van der Heijde ◽  
A. Alseidi ◽  
S. Dokmak ◽  
...  
Keyword(s):  
Risk Factors ◽  
Systematic Review ◽  
Minimally Invasive ◽  
Distal Pancreatectomy ◽  
Preoperative Imaging ◽  
Vascular Involvement ◽  
Patient Counseling ◽  
Conversion Rates ◽  
Surgeon Experience ◽  
The Impact

Abstract Purpose The reported conversion rates for minimally invasive distal pancreatectomy (MIDP) range widely from 2 to 38%. The identification of risk factors for conversion may help surgeons during preoperative planning and patient counseling. Moreover, the impact of conversion on outcomes of MIDP is unknown. Methods A systematic review was conducted as part of the 2019 Miami International Evidence-Based Guidelines on Minimally Invasive Pancreas Resection (IG-MIPR). The PubMed, Cochrane, and Embase databases were searched for studies concerning conversion to open surgery in MIDP. Results Of the 828 studies screened, eight met the eligibility criteria, resulting in a combined dataset including 2592 patients after MIDP. The overall conversion rate was 17.1% (range 13.0–32.7%) with heterogeneity between studies associated with the definition of conversion adopted. Only one study divided conversion into elective and emergency conversion. The main indications for conversion were vascular involvement (23.7%), concern for oncological radicality (21.9%), and bleeding (18.9%). The reported risk factors for conversion included a malignancy as an indication for surgery, the proximity of the tumor to vascular structures in preoperative imaging, higher BMI or visceral fat, and multi-organ resection or extended resection. Contrasting results were seen in terms of blood loss and length of stay in comparing converted MIDP and completed MIDP patients. Conclusion The identified risk factors for conversion from this study can be used for patient selection and counseling. Surgeon experience should be considered when contemplating MIDP for a complex patient. Future studies should divide conversion into elective and emergency conversion.

Minimally Invasive Lobectomy Modality and Other Predictors of Conversion to Thoracotomy

2019 ◽  
Vol 14 (4) ◽  
pp. 342-352 ◽  
Author(s):  
Brandon S. Hendriksen ◽  
Christopher S. Hollenbeak ◽  
Matthew D. Taylor ◽  
Michael F. Reed
Keyword(s):  
Risk Factors ◽  
Propensity Score ◽  
Minimally Invasive ◽  
Propensity Score Matching ◽  
Thoracoscopic Surgery ◽  
Patient Characteristics ◽  
Logistic Regression Models ◽  
Conversion Rates ◽  
Chi Squared ◽  
The Impact

Objective Minimally invasive approaches to lobectomy are increasing. Rates of conversion to thoracotomy are well reported but risk factors are poorly understood. This study aimed to determine the impact of surgical modality (video-assisted thoracoscopic surgery [VATS] and robotic) on conversion as well as to identify other risk factors for conversion. Methods The National Cancer Database (NCDB) was used to identify patients who underwent minimally invasive lobectomy between 2010 and 2015. Patient characteristics were compared between VATS and robotic approaches using chi-squared tests and t-tests. Logistic regression models were used to control for covariates and identify factors associated with all minimally invasive conversion, VATS conversion, and robotic conversion. Propensity score matching was used to compare conversion rates of VATS and robotic lobectomy. Results The study included 51,723 patients with lung cancer who underwent minimally invasive lobectomy (VATS or robotic). Conversion was identified in 7,109 (7.3%) operations. The odds of VATS conversions were nearly twice that of robotic conversions (OR 1.94 P < 0.0001). After controlling for VATS and robotic patient imbalances with propensity score matching, there was a 5% difference in conversion rates (14% vs. 9%, P < 0.0001). Other predictors of minimally invasive conversion included community hospitals, tumor size 4.5 cm or greater, and an increasing Charlson comorbidity index ( P < 0.03 for all). Conclusions VATS is associated with nearly twice the odds of conversion as robotic lobectomy. Identifying specific risk factors for both VATS and robotic conversions may aid in appropriate modality selection and reduction of conversions.

Stress, anxiety, depression and burnout in frontline health care workers during COVID-19 pandemic: a brief systematic review and new data from Russia

2021 ◽  
Author(s):  
Ekaterina Mosolova ◽  
Dmitry Sosin ◽  
Sergey Mosolov
Keyword(s):  
Risk Factors ◽  
Systematic Review ◽  
Female Gender ◽  
Assessment Tools ◽  
Care Workers ◽  
Younger Age ◽  
Wide Range ◽  
Associated Risk Factors ◽  
Anxiety Depression ◽  
The Impact

During the COVID-19 pandemic, healthcare workers (HCWs) have been subject to increased workload while also exposed to many psychosocial stressors. In a systematic review we analyze the impact that the pandemic has had on HCWs mental state and associated risk factors. Most studies reported high levels of depression and anxiety among HCWs worldwide, however, due to a wide range of assessment tools, cut-off scores, and number of frontline participants in the studies, results were difficult to compare. Our study is based on two online surveys of 2195 HCWs from different regions of Russia during spring and autumn epidemic outbreaks revealed the rates of anxiety, stress, depression, emotional exhaustion and depersonalization and perceived stress as 32.3%, 31.1%, 45.5%, 74.2%, 37.7% ,67.8%, respectively. Moreover, 2.4% of HCWs reported suicidal thoughts. The most common risk factors include: female gender, nurse as an occupation, younger age, working for over 6 months, chronic diseases, smoking, high working demands, lack of personal protective equipment, low salary, lack of social support, isolation from families, the fear of relatives getting infected. These results demonstrate the need for urgent supportive programs for HCWs fighting COVID-19 that fall into higher risk factors groups.

Precision vascular anatomy for minimally invasive distal pancreatectomy: A systematic review

2021 ◽  
Author(s):  
Hitoe Nishino ◽  
Giuseppe Zimmitti ◽  
Takao Ohtsuka ◽  
Mohammed Abu Hilal ◽  
Brian K. P. Goh ◽  
...  
Keyword(s):  
Systematic Review ◽  
Minimally Invasive ◽  
Distal Pancreatectomy ◽  
Vascular Anatomy

Preoperative risk factors for conversion and learning curve of minimally invasive distal pancreatectomy

Surgery ◽  
2017 ◽  
Vol 162 (5) ◽  
pp. 1040-1047 ◽  
Author(s):  
Yongfei Hua ◽  
Ammar A. Javed ◽  
Richard A. Burkhart ◽  
Martin A. Makary ◽  
Matthew J. Weiss ◽  
...  
Keyword(s):  
Risk Factors ◽  
Minimally Invasive ◽  
Learning Curve ◽  
Distal Pancreatectomy ◽  
Preoperative Risk ◽  
Preoperative Risk Factors

Prostate cancer risk calculators for healthy population: A systematic review (Preprint)

2021 ◽  
Author(s):  
Antonio Bandala-Jacques ◽  
Kevin Daniel Castellanos Esquivel ◽  
Fernanda Pérez-Hurtado ◽  
Cristobal Hernández-Silva ◽  
Nancy Reynoso-Noverón
Keyword(s):  
Prostate Cancer ◽  
Risk Factors ◽  
Systematic Review ◽  
Cancer Risk ◽  
Digital Rectal Examination ◽  
Prostate Cancer Risk ◽  
Individual Risk ◽  
Healthy Population ◽  
Risk Of Cancer ◽  
The Impact

BACKGROUND Screening for prostate cancer has long been a debated, complex topic. The use of risk calculators for prostate cancer is recommended for determining patients’ individual risk of cancer and the subsequent need for a prostate biopsy. These tools could lead to a better discrimination of patients in need of invasive diagnostic procedures and for optimized allocation of healthcare resources OBJECTIVE To systematically review available literature on current prostate cancer risk calculators’ performance in healthy population, by comparing the impact factor of individual items on different cohorts, and the models’ overall performance. METHODS We performed a systematic review of available prostate cancer risk calculators targeted at healthy population. We included studies published from January 2000 to March 2021 in English, Spanish, French, Portuguese or German. Two reviewers independently decided for or against inclusion based on abstracts. A third reviewer intervened in case of disagreements. From the selected titles, we extracted information regarding the purpose of the manuscript, the analyzed calculators, the population for which it was calibrated, the included risk factors, and the model’s overall accuracy. RESULTS We included a total of 18 calculators across 53 different manuscripts. The most commonly analyzed ones were they PCPT and ERSPC risk calculators, developed from North American and European cohorts, respectively. Both calculators provided high precision for the diagnosis of aggressive prostate cancer (AUC as high as 0.798 for PCPT and 0.91 for ERSPC). We found 9 calculators developed from scratch for specific populations, which reached diagnostic precisions as high as 0.938. The most commonly included risk factors in the calculators were age, PSA levels and digital rectal examination findings. Additional calculators included race and detailed personal and family history CONCLUSIONS Both the PCPR and the ERSPC risk calculators have been successfully adapted for cohorts other than the ones they were originally created for with no loss of diagnostic accuracy. Furthermore, designing calculators from scratch considering each population’s sociocultural differences has resulted in risk tools that can be well adapted to be valid in more patients. The best risk calculator for prostate cancer will be that which was has been calibrated for its intended population and can be easily reproduced and implemented CLINICALTRIAL CRD42021242110

scholarly journals Systematic Review of the Impact of Behavioral Health Homes on Cardiometabolic Risk Factors for Adults With Serious Mental Illness

2020 ◽  
Vol 71 (1) ◽  
pp. 57-74 ◽  
Author(s):  
Karen L. Fortuna ◽  
Peter R. DiMilia ◽  
Matthew C. Lohman ◽  
Brandi P. Cotton ◽  
Janet R. Cummings ◽  
...  
Keyword(s):  
Risk Factors ◽  
Systematic Review ◽  
Mental Illness ◽  
Behavioral Health ◽  
Serious Mental Illness ◽  
Cardiometabolic Risk ◽  
Cardiometabolic Risk Factors ◽  
Health Homes ◽  
The Impact
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