Pain in Colorectal Surgery: How Does It Occur and What Tools Do We Have for Treatment?

Pain is a complex entity with deleterious effects on the entire organism. Poorly controlled postoperative pain impacts the patient outcome, being associated with increased morbidity, inadequate quality of life and functional recovery. In the current surgical environment with less invasive surgical procedures increasingly being used and a trend towards rapid discharge home after surgery, we need to continuously re-evaluate analgesic strategies. We have performed a narrative review consisting of a description of the acute surgical pain anatomic pathways and the connection between pain and the surgical stress response followed by reviewing methods of multimodal analgesia in colorectal surgery found in recent literature data. We have described various regional analgesia techniques and drugs effective in pain treatment, emphasizing their advantages and concerns. We have also tried to identify present knowledge gaps requiring future research. Our review concludes that surgical pain has peculiarities that make its management complex, implying a consistent, multimodal approach aiming to block both peripheral and central pain pathways.

Development and Internal Validation of a New Prognostic Model Powered to Predict 28-Day All-Cause Mortality in ICU COVID-19 Patients-The COVID-SOFA Score.

Background: The sequential organ failure assessment (SOFA) score has poor discriminative ability for death in severely or critically ill patients with Coronavirus disease 2019 (COVID-19) requiring intensive care unit (ICU) admission. Our aim was to create a new score powered to predict 28-day mortality. Methods: Retrospective, observational, bicentric cohort study including 425 patients with COVID-19 pneumonia, acute respiratory failure and SOFA score ≥ 2 requiring ICU admission for ≥72 h. Factors with independent predictive value for 28-day mortality were identified after stepwise Cox proportional hazards (PH) regression. Based on the regression coefficients, an equation was computed representing the COVID-SOFA score. Discriminative ability was tested using receiver operating characteristic (ROC) analysis, concordance statistics and precision-recall curves. This score was internally validated. Results: Median (Q1−Q3) age for the whole sample was 64 [55−72], with 290 (68.2%) of patients being male. The 28-day mortality was 54.58%. After stepwise Cox PH regression, age, neutrophil-to-lymphocyte ratio (NLR) and SOFA score remained in the final model. The following equation was computed: COVID-SOFA score = 10 × [0.037 × Age + 0.347 × ln(NLR) + 0.16 × SOFA]. Harrell's C-index for the COVID-SOFA score was higher than the SOFA score alone for 28-day mortality (0.697 [95% CI; 0.662−0.731] versus 0.639 [95% CI: 0.605−0.672]). Subsequently, the prediction error rate was improved up to 16.06%. Area under the ROC (AUROC) was significantly higher for the COVID-SOFA score compared with the SOFA score for 28-day mortality: 0.796 [95% CI: 0.755−0.833] versus 0.699 [95% CI: 0.653−0.742, p < 0.001]. Better predictive value was observed with repeated measurement at 48 h after ICU admission. Conclusions: The COVID-SOFA score is better than the SOFA score alone for 28-day mortality prediction. Improvement in predictive value seen with measurements at 48 h after ICU admission suggests that the COVID-SOFA score can be used in a repetitive manner. External validation is required to support these results.

Dynamic Changes of the Neutrophil-to-Lymphocyte Ratio, Systemic Inflammation Index, and Derived Neutrophil-to-Lymphocyte Ratio Independently Predict Invasive Mechanical Ventilation Need and Death in Critically Ill COVID-19 Patients.

BACKGROUND: Hematological indices can predict disease severity, progression, and death in patients with coronavirus disease-19 (COVID-19). OBJECTIVES: To study the predictive value of the dynamic changes (first 48 h after ICU admission) of the following ratios: neutrophil-to-lymphocyte (NLR), platelet-to-lymphocyte (PLR), monocyte-to-lymphocyte (MLR), systemic inflammation index (SII), and derived neutrophil-to-lymphocyte (dNLR) for invasive mechanical ventilation (IMV) need and death in critically ill COVID-19 patients. METHODS: Observational, retrospective, and multicentric analysis on 272 patients with severe or critical COVID-19 from two tertiary centers. Hematological indices were adjusted for confounders through multivariate analysis using Cox regression. RESULTS: Patients comprised 186 males and 86 females with no difference across groups (p > 0.05). ΔNLR > 2 had the best independent predictive value for IMV need (HR = 5.05 (95% CI, 3.06-8.33, p < 0.0001)), followed by ΔSII > 340 (HR = 3.56, 95% CI 2.21-5.74, p < 0.0001) and ΔdNLR > 1 (HR = 2.61, 95% CI 1.7-4.01, p < 0.0001). Death was also best predicted by an NLR > 11 (HR = 2.25, 95% CI: 1.31-3.86, p = 0.003) followed by dNLR > 6.93 (HR = 1.89, 95% CI: 1.2-2.98, p = 0.005) and SII > 3700 (HR = 1.68, 95% CI: 1.13-2.49, p = 0.01). CONCLUSIONS: Dynamic changes of NLR, SII, and dNLR independently predict IMV need and death in critically ill COVID-19 patients.