Arthroscopic versus open distal clavicle excision: comparative results at six months and one year from a randomized, prospective clinical trial

The purpose of this report is to compare outcomes after arthroscopic versus open distal clavicle excision in the treatment of refractory acromioclavicular joint pain. A randomized, prospective clinical trial comparing the 6-month and 1-year outcomes of patients undergoing open distal clavicle excision (group 1) with those undergoing arthroscopic distal clavicle excision (group 2) was carried out. The Modified American Shoulder and Elbow Surgeons form, visual analog scale pain score, Short Form 36, and satisfaction questions were assessed preoperatively and at 6 months and 1 year postoperatively. Seventeen patients were enrolled. There was a trend across all measures for earlier or better outcomes (or both) after arthroscopic over open treatment. The improvement in visual analog scale pain score from preoperatively to 1 year postoperatively was significant for group 2 but not group 1 (P = .006 vs P = .13). Occult intra-articular pathology was detected and treated in 50% of group 2 patients. Arthroscopic and open distal clavicle excisions both provide significant pain reduction at 1 year. Both are effective surgeries for the treatment of refractory acromioclavicular joint pain. The ability to diagnosis and treat subtle concomitant shoulder pathology is a unique advantage of the arthroscopic approach.     

Detection of circulating tumour DNA after neoadjuvant chemoradiotherapy in patients with locally advanced oesophageal cancer

Active surveillance instead of standard surgery after neoadjuvant chemoradiotherapy (nCRT) has been proposed for patients with oesophageal cancer. Circulating tumour DNA (ctDNA) may be used to facilitate selection of patients for surgery. We show that detection of ctDNA after nCRT seems highly suggestive of major residual disease. Tumour biopsies and blood samples were taken before, and 6 and 12 weeks after, nCRT. Biopsies were analysed with regular targeted next-generation sequencing (NGS). Circulating cell-free DNA (cfDNA) was analysed using targeted NGS with unique molecular identifiers and digital polymerase chain reaction. cfDNA mutations matching pre-treatment biopsy mutations confirmed the presence of ctDNA. In total, 31 patients were included, of whom 24 had a biopsy mutation that was potentially detectable in cfDNA (77%). Pre-treatment ctDNA was detected in nine of 24 patients (38%), four of whom had incurable disease progression before surgery. Pre-treatment ctDNA detection had a sensitivity of 47% (95% CI 24–71) (8/17), specificity of 85% (95% CI 42–99) (6/7), positive predictive value (PPV) of 89% (95% CI 51–99) (8/9), and negative predictive value (NPV) of 40% (95% CI 17–67) (6/15) for detecting major residual disease (>10% residue in the resection specimen or progression before surgery). After nCRT, ctDNA was detected in three patients, two of whom had disease progression. Post-nCRT ctDNA detection had a sensitivity of 21% (95% CI 6–51) (3/14), specificity of 100% (95% CI 56–100) (7/7), PPV of 100% (95% CI 31–100) (3/3), and NPV of 39% (95% CI 18–64) (7/18) for detecting major residual disease. The addition of ctDNA to the current set of diagnostics did not lead to more patients being clinically identified with residual disease. These results indicate that pre-treatment and post-nCRT ctDNA detection may be useful in identifying patients at high risk of disease progression. The addition of ctDNA analysis to the current set of diagnostic modalities may not improve detection of residual disease after nCRT. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.     

A goal-oriented hemodynamic approach to acute myocardial infarction complicated by cardiogenic shock—A single center experience

Background

Acute myocardial infarction complicated by cardiogenic shock (AMI-CS) is the most common cause of mortality following AMI, and treatment algorithms vary widely. We report the results of an analysis using time-sensitive, hemodynamic goals in the treatment of AMI-CS in a single center study.

Methods

Consecutive patients with AMI-CS from November 2016 through December 2021 were included in our retrospective analysis. Clinical characteristics and outcomes were analyzed using the electronic medical records. We identified 63 total patients who were admitted to our center with AMI-CS, and we excluded patients who did not have clear timing of AMI onset or CS onset. We evaluated the rate of survival to hospital discharge based on the quantity of certain time-sensitive hemodynamic goals were met.

Results

We identified 63 patients who met criteria for AMI-CS, 39 (62%) of whom survived to hospital discharge. Odds of survival were closely related to the achievement of four time-dependent goals: cardiac power output (CPO) >0.6 Watts (W), pulmonary artery pulsatility index (PAPi) >1, lactate <4 mmol/L, and <2 vasopressors required. Of the 63 total patients, 36 (57%) received intra-aortic balloon pump (IABP) and 18 (29%) received an Impella CP (Abiomed) as an initial mechanical circulatory support strategy. Six patients were escalated from IABP to Impella CP for additional hemodynamic support. Nine patients were treated with vasopressors/inotropes alone. Regarding the 39 patients who survived to hospital discharge, 75% of patients met 3 or 4 goals at 24 h, whereas only 16% of deceased patients met 3 or 4 goals at 24 h. Of the 24 patients who did not survive to hospital discharge, 18 (75%) met either 0–1 goal at 24 h. There was no effect of the initial treatment strategy on achieving 3–4 goals at 24 h.

Conclusion

Our study evaluated the association of meeting 4 time-sensitive goals (CPO >0.6 W, PAPi >1, <2 vasopressors, and lactate <4 mmol/L) at 24 h after treatment for AMI-CS with in-hospital mortality. Our data show, in line with previous data, that the higher number of goals met at 24 h was associated with improved in-hospital mortality regardless of treatment strategy.     

Predicting inpatient mortality in patients with inflammatory bowel disease: A machine learning approach

Background and Aim

Data are lacking on predicting inpatient mortality (IM) in patients admitted for inflammatory bowel disease (IBD). IM is a critical outcome; however, difficulty in its prediction exists due to infrequent occurrence. We assessed IM predictors and developed a predictive model for IM using machine-learning (ML).

Methods

Using the National Inpatient Sample (NIS) database (2005–2017), we extracted adults admitted for IBD. After ML-guided predictor selection, we trained and internally validated multiple algorithms, targeting minimum sensitivity and positive likelihood ratio (+LR) ≥ 80% and ≥ 3, respectively. Diagnostic odds ratio (DOR) compared algorithm performance. The best performing algorithm was additionally trained and validated for an IBD-related surgery sub-cohort. External validation was done using NIS 2018.

Results

In 398 426 adult IBD admissions, IM was 0.32% overall, and 0.87% among the surgical cohort (n = 40 784). Increasing age, ulcerative colitis, IBD-related surgery, pneumonia, chronic lung disease, acute kidney injury, malnutrition, frailty, heart failure, blood transfusion, sepsis/septic shock and thromboembolism were associated with increased IM. The QLattice algorithm, provided the highest performance model (+LR: 3.2, 95% CI 3.0–3.3; area-under-curve [AUC]:0.87, 85% sensitivity, 73% specificity), distinguishing IM patients by 15.6-fold when comparing high to low-risk patients. The surgical cohort model (+LR: 8.5, AUC: 0.94, 85% sensitivity, 90% specificity), distinguished IM patients by 49-fold. Both models performed excellently in external validation. An online calculator ( https://clinicalc.ai/im-ibd/ ) was developed allowing bedside model predictions.

Conclusions

An online prediction-model calculator captured > 80% IM cases during IBD-related admissions, with high discriminatory effectiveness. This allows for risk stratification and provides a basis for assessing interventions to reduce mortality in high-risk patients.