Association of pre-operative chronic kidney disease and acute kidney injury with in-hospital outcomes of emergency colorectal surgery: a cohort study

Dose-related effects of norepinephrine on early-stage endotoxemic shock in a swine model

Background

The benefits of early use of norepinephrine in endotoxemic shock remain unknown. We aimed to elucidate the effects of different doses of norepinephrine in early-stage endotoxemic shock using a clinically relevant large animal model.

Methods

Vasodilatory shock was induced by endotoxin bolus in 30 Bama suckling pigs. Treatment included fluid resuscitation and administration of different doses of norepinephrine, to induce return to baseline mean arterial pressure (MAP). Fluid management, hemodynamic, microcirculation, inflammation, and organ function variables were monitored. All animals were supported for 6 h after endotoxemic shock.

Results

Infused fluid volume decreased with increasing norepinephrine dose. Return to baseline MAP was achieved more frequently with doses of 0.8 µg/kg/min and 1.6 µg/kg/min (P <0.01). At the end of the shock resuscitation period, cardiac index was higher in pigs treated with 0.8 µg/kg/min norepinephrine (P <0.01), while systemic vascular resistance was higher in those receiving 0.4 µg/kg/min (P <0.01). Extravascular lung water level and degree of organ edema were higher in animals administered no or 0.2 µg/kg/min norepinephrine (P <0.01), while the percentage of perfused small vessel density (PSVD) was higher in those receiving 0.8 µg/kg/min (P <0.05) and serum lactate was higher in the groups administered no and 1.6 µg/kg/min norepinephrine (P <0.01).

Conclusions

The impact of norepinephrine on the macro- and micro-circulation in early-stage endotoxemic shock is dose-dependent, with very low and very high doses resulting in detrimental effects. Only an appropriate norepinephrine dose was associated with improved tissue perfusion and organ function.

Preoperative urine neutrophil gelatinase-associated lipocalin predicts mortality in colorectal cancer patients after laparoscopic surgery: A single-center study

Purpose

To determine the rate of acute kidney injury (AKI) after laparoscopic colorectal cancer (CRC) surgery and the predictive value of urine neutrophil gelatinase-associated lipocalin (uNGAL) for postoperative AKI and mortality during 3 years of follow-up.

Methods

A total of 216 CRC patients who had undergone laparoscopic surgery were included in our study. We divided all patients into two groups, including group 1 (n = 31) with postoperative AKI and group 2 (n = 185) without postoperative AKI. Urine NGAL was measured using the ELISA technique. Clinical and laboratory data were collected the day before surgery. Postoperative AKI included events occurring within 7 days of the index operation, and mortality was obtained during 3 years of follow-up.

Results

The ratio of postoperative AKI was 14.35% (31/216 patients). The urine NGAL level in group 1 was significantly higher than in group 2, p < 0.001. At cut-off value = 14.94 ng/mL, uNGAL has a predictive value for AKI (area under the curve [AUC] = 0.858, p < 0.001). After 3 years of follow-up, the total mortality rate was 7.9%. The mortality rate in group 1 (45.2%) was significantly higher than in group 2 (1.6%) with p < 0.001). At cut-off value = 19.85 ng/mL, uNGAL has a predictive value for mortality (AUC = 0.941, p < 0.001).

Conclusions

The rate of acute kidney injury after laparoscopic CRC surgery was 14.35%. Preoperative urine NGAL has a good predictive value for postoperative acute kidney injury and mortality during 3 years of follow-up.

Machine learning-based prediction of postoperative mortality in emergency colorectal surgery: A retrospective, multicenter cohort study using Tokushukai medical database

Background

Although prognostic factors associated with mortality in patients with emergency colorectal surgery have been identified, an accurate mortality risk assessment is still necessary to determine the range of therapeutic resources in accordance with the severity of patients. We established machine-learning models to predict in-hospital mortality for patients who had emergency colorectal surgery using clinical data at admission and attempted to identify prognostic factors associated with in-hospital mortality.

Methods

This retrospective cohort study included adult patients undergoing emergency colorectal surgery in 42 hospitals between 2012 and 2020. We employed logistic regression and three supervised machine-learning models: random forests, gradient-boosting decision trees (GBDT), and multilayer perceptron (MLP). The area under the receiver operating characteristics curve (AUROC) was calculated for each model. The Shapley additive explanations (SHAP) values are also calculated to identify the significant variables in GBDT.

Results

There were 8792 patients who underwent emergency colorectal surgery. As a result, the AUROC values of 0.742, 0.782, 0.814, and 0.768 were obtained for logistic regression, random forests, GBDT, and MLP. According to SHAP values, age, colorectal cancer, use of laparoscopy, and some laboratory variables, including serum lactate dehydrogenase serum albumin, and blood urea nitrogen, were significantly associated with in-hospital mortality.

Conclusion

We successfully generated a machine-learning prediction model, including GBDT, with the best prediction performance and exploited the potential for use in evaluating in-hospital mortality risk for patients who undergo emergency colorectal surgery.

Association of Hyperkalemia and Hypokalemia with Patient Characteristics and Clinical Outcomes in Japanese Hemodialysis (HD) Patients

This study aimed to examine the characteristics and clinical outcomes of Japanese hemodialysis patients with dyskalemia. A retrospective study was conducted using a large Japanese hospital group database. Outpatients undergoing thrice-a-week maintenance hemodialysis were stratified into hyperkalemia, hypokalemia, and normokalemia groups based on their pre-dialysis serum potassium (sK) levels during the three-month baseline period. Baseline characteristics of the three groups were described and compared for the following outcomes during follow-up: all-cause mortality, all-cause hospitalization, major adverse cardiovascular events (MACE), cardiac arrest, fatal arrythmia, and death related to arrhythmia. The study included 2846 eligible patients, of which 67% were men with a mean age of 65.65 (SD: 12.63) years. When compared with the normokalemia group (n = 1624, 57.06%), patients in the hypokalemia group (n = 313, 11.00%) were older and suffered from malnutrition, whereas patients in the hyperkalemia group (n = 909, 31.94%) had longer dialysis vintage. The hazard ratios for all-cause mortality and MACE in the hypokalemia group were 1.47 (95% confidence interval [CI], 1.13–1.92) and 1.48 (95% CI, 1.17–1.86), respectively, whereas that of death related to arrhythmia in the hyperkalemia group was 3.11 (95% CI, 1.03–9.33). Thus, dyskalemia in maintenance hemodialysis patients was associated with adverse outcomes, suggesting the importance of optimized sK levels.

Which factors influence the decision to perform Hartmann's reversal in various causative disease situations? A retrospective cohort study between 2006 and 2021

AIM

Our aim was to investigate the predictive factors for Hartmann's reversal and to describe the differences in the rates and timings of Hartmann's reversal for various causative diseases.

METHOD

In this multicentre retrospective cohort study patients who underwent Hartmann's procedure (HP) between 2006 and 2018 were enrolled. To describe the demographic patterns of Hartmann's reversal through to 2021, we analysed the cumulative incidence rate of Hartmann's reversal over time based on the Kaplan-Meier failure estimate. Multivariable Cox proportional hazard analysis was performed with cluster-adjusted robust standard errors to calculate hazard ratios (HRs) for the assessment of variables associated with colostomy reversal.

RESULTS

Of 250 patients who underwent the index HP and survived to discharge, 112 (45%) underwent subsequent Hartmann's reversal (36% for malignant and 51% for benign disease). The causative diseases with the highest probability of colostomy reversal were trauma (85%) and diverticular disease (73%). Conversely, colostomy reversal was performed in only 16% for colonic volvulus and 17% for bowel ischaemia. Home discharge after index HP (HR 5.22, 95% CI 3.31-8.23) and a higher body mass index (HR 1.03, 95% CI 1.01-1.04) were associated with a higher probability of Hartmann's reversal, whereas older age, malignant disease and a history of cardiovascular and psychoneurological diseases were independently associated with a lower probability of colostomy reversal.

CONCLUSION

The probability and timing of Hartmann's reversal varied considerably with the surgical indications for colostomy creation. Our results could help surgeons counsel patients and their families regarding stoma closure surgery to set realistic expectations.

Risk factors of serious postoperative outcomes in patients aged ≥90 years undergoing surgical intervention

Objective

We aimed to identify preoperative and intraoperative factors associated with serious postoperative outcomes, which may help patients and clinicians make better-informed decisions.

Methods

We conducted a retrospective study including all patients aged ≥90 years who underwent surgery between January 1, 2011, and January 1, 2021, at Chongqing University Central Hospital. We assessed 30 pre- and intraoperative demographic and clinical variables. Logistic regression was used to identify the independent risk factors for serious postoperative outcomes in patients aged ≥90 years.

Results

A total of 428 patients were included in our analysis. The mean age was 92.6 years (SD ± 2.6). There were 240 (56.1%) females and 188 (43.9%) males. The most common comorbidities were hypertension (44.9%) and arrhythmias (34.8%). The 30-day hospital mortality was 5.6%, and severe morbidity was 33.2%. Based on the multivariate logistic regression classification analysis of the American Society of Anesthesiologists (ASA)≥ Ⅳ [odds ratio (OR), 5.39, 95% confidence interval (CI), 2.06-14.16, P = .001], emergency surgery (OR, 5.02, 95% CI, 2.85-15.98, P = .001) and chronic heart failure (OR, 6.11, 95% CI, 1.93-13.06, P = .001) were identified as independent risk factors for 30-day hospital mortality, and ASA≥ Ⅳ (OR, 4.56, 95%CI, 2.56-8.15, P < .001), Barthel index (BI) < 35 (OR, 2.28, 95%CI, 1.30-3.98, P = .001), chronic heart failure (OR, 3.67, 95%CI, 1.62-8.31, P = .002), chronic kidney disease (OR, 4.24, 95%CI, 1.99-9.05, P < .001), general anesthesia (OR, 3.31, 95%CI, 1.91-5.76, P < .001), emergency surgery (OR, 3.72, 95%CI, 1.98-6.99, P < .001), and major surgery (OR, 3.44, 95%CI, 1.90-6.22, P < .001) were identified as independent risk factors for serious postoperative complications.

Conclusions

Patients aged ≥90 years with ASA≥ Ⅳ, BI < 35, combined with chronic heart failure or chronic kidney disease, undergoing emergency surgery, major surgery or general anesthesia have a higher risk of serious postoperative outcomes. Identifying these risk factors in an early stage may contribute to our clinical decision-making and improve the quality of treatments.

Machine learning-based prognostic modeling of patients with acute heart failure receiving furosemide in intensive care units

Purpose

This study developed machine learning models to predict in-hospital mortality, initiation of acute renal replacement therapy, and mechanical ventilation in patients with acute heart failure receiving furosemide in intensive care units.

Method

An extensive database comprising static and dynamic features obtained from a Japanese hospital chain was used to construct and train the machine learning models.

Results

The results revealed that the proposed machine learning models predict in-hospital mortality, initiation of acute renal replacement therapy, and mechanical ventilation with good accuracy. However, the optimal models vary depending on the predicted outcomes. The linear support vector machine classification models exhibited the highest in-hospital mortality and mechanical ventilation prediction accuracy, with the area under the receiver operating characteristic curve of 0.73 and 0.73, respectively, whereas the multi-layer neural network exhibited the highest accuracy for acute renal replacement therapy initiation prediction with an area under the receiver operating characteristic curve of 0.70.

Conclusions

In conclusion, this study demonstrated that machine learning models could help predict the clinical outcomes of patients with acute heart failure receiving furosemide. However, the optimal models may differ depending on the outcome of interest.

Outcomes of Patients with Necrotizing Soft Tissue Infections: A Propensity-Matched Analysis Using the National Inpatient Sample

Background: Necrotizing soft tissue infections (NSTIs) are severe, rapidly spreading infections with high morbidity and mortality. Attempts to identify risk factors for mortality and morbidity have produced variable results. We hope to determine which factors across the NSTI population impact mortality, morbidities, and discharge disposition. Patients and Methods: Retrospective data from the National Inpatient Sample from 2012-2018 of patients with primary diagnosis of NSTI (gas gangrene, necrotizing faciitis, cutaneous gangrene, or Fournier gangrene) were identified for analysis. A 1:4 greedy match was performed and risk factors for in-hospital mortality and discharge disposition were examined. Continuous variables were assessed using t-tests and Wilcoxon rank sum tests. Categorical variables were assessed using χ² and Fisher exact tests. Statistical significance was defined as p < 0.05. Results: A total of 6,608 patients were identified. Weighted, this represents 33,040 patients; 32,390 are in the no-mortality cohort and 650 in the mortality cohort. Advanced age group was a risk factor for both in-hospital mortality and morbidity, but not for discharge to a skilled nursing or rehabilitation facility. Having two or more comorbidities was a risk factor for mortality, morbidity, and discharge to skilled nursing or rehabilitation facility. Cancer, liver disease, and kidney disease were predictors of in-hospital mortality. Diabetes mellitus and kidney disease were predictors of experiencing an in-hospital complication. Diabetes mellitus, heart disease, and kidney disease were predictors for discharge to skilled nursing or rehabilitation facility. Conclusions: Necrotizing soft tissue infections are associated with substantial morbidity and mortality. Identifying patients at higher risk for mortality, morbidity, and higher level of care at discharge can help providers properly allocate resources to improve patient outcomes and reduce the financial burden on patients and healthcare facilities. Special attention should be paid to those with existing or acute kidney dysfunction because this was the only comorbidity associated with increased risk mortality, morbidity, and discharge to higher level of care.

Pre-surgical chronic kidney disease continues to drive outcomes in the modern era of minimally invasive renal surgery, despite advances in technology

PURPOSE

To assess the impact of preoperative chronic kidney disease (CKD) on perioperative morbidity and mortality in a contemporary cohort undergoing renal surgery in an era of increased prevalence of minimally invasive surgery and partial nephrectomy.

METHODS

The National Surgery Quality Improvement Program dataset was queried to identify patients undergoing radical nephrectomy (RN) or partial nephrectomy (PN) between 2010 and 2018. CKD staging was assigned based on creatinine clearance calculated using the Cockcroft-Gault formula. Multivariable logistic regression was performed to assess the effect of preoperative CKD stage on postoperative outcomes, including a composite variable encompassing multiple major complications.

RESULTS

We analyzed 19,545 patients with CKD undergoing renal surgery. CKD stage ≥ 2 predicted an increase in major perioperative complications, OR 1.54 (95% CI 1.46-1.63); p < 0.01. The risk of perioperative morbidity increased linearly with increasing CKD stage. Patients with CKD stage > 2 also demonstrated increased 30-day mortality, OR 1.87 (95% CI 1.26-2.48); p < 0.01. Adjusting for surgery type, CKD staging predicted perioperative mortality in patients undergoing RN only, and perioperative morbidity in RN and PN.

CONCLUSIONS

Here, we demonstrate a statistically significant increase in the risk of major postoperative complications following RN and PN with increasing CKD stage. Amongst patients undergoing RN, we also demonstrate increasing 30-day mortality with increasing CKD stage. Importantly, we highlight the ability of CKD staging to predict major perioperative outcomes with greater magnitude of effect than surgery type alone. Thus, we provide a model for translating CKD staging into operative risk amongst patients undergoing surgery for a renal mass.

Is Chronic Kidney Disease Affecting the Postoperative Complications of Vitrectomy for Proliferative Diabetic Retinopathy?

Chronic kidney disease (CKD) is a well-known risk factor for postoperative complications in several surgical fields. However, although prevalent among diabetic candidates for vitrectomy, the effect of CKD on vitrectomy outcomes remains unclear. This study aimed at clarifying the relationship between CKD and the occurrence of vitrectomy-related complications in patients with proliferative diabetic retinopathy (PDR). The 6-month incidences of vitreous hemorrhage (VH) and neovascular glaucoma (NVG) following vitrectomy for PDR were compared among the following groups: stages 1–2 CKD (60 patients), stages 3–5 CKD (70 patients not on hemodialysis), and hemodialysis (HD; 30 patients). We also determined whether the deterioration of the estimated glomerular filtration rate (eGFR) was associated with post-vitrectomy events. The incidence of VH was significantly higher in the stages 3–5 CKD group (43%) than in the stages 1–2 CKD (10%) and HD (10%) groups. NVG was more common in the stages 3–5 CKD group (17%) than in the stages 1–2 CKD (2%) and HD (0%) groups. The reduced estimated glomerular filtration rate (eGFR) was the only significant variable associated with post-vitrectomy VH and NVG. Patients with PDR and CKD, particularly those with lower eGFR, might be at risk for post-vitrectomy VH and NVG.

Effect of preoperative asymptomatic renal dysfunction on the clinical course after colectomy for colon cancer

PURPOSE

To evaluate the effect of mild renal dysfunction on the clinical course after colectomy in patients with colon cancer.

METHODS

The subjects of this retrospective study were 263 patients who underwent surgical resection for colon cancer at our hospital between 2011 and 2015. Renal function was assessed based on preoperative estimated glomerular filtration rate (eGFR) values. Patients were divided into groups based on their eGFR value of 55 ml/min/1.73 m². The Mann-Whitney U test, chi-square or Fisher exact test, and log-rank test were used in the data analysis.

RESULTS

There were 59 patients (22.4%) in the low eGFR group and 204 patients in the normal eGFR group. There were differences between the groups in age, comorbidities, and the levels of hemoglobin, albumin, and serum creatinine. The overall postoperative complication rate, frequency of severe complications, and length of stay were significantly higher in the low eGFR group than in the normal eGFR group. Multivariate analysis revealed that low eGFR was the only independent risk factor for severe complications (Clavien-Dindo classification III/IV). There were no differences in survival between the groups.

CONCLUSION

Preoperative asymptomatic renal dysfunction may be correlated with the development of postoperative complications and a possible significant risk factor for severe complications after colon cancer surgery.