Identifying novel acute pancreatitis sub-phenotypes using total serum calcium trajectories.

BACKGROUND: Acute pancreatitis (AP) has heterogeneous clinical features, and identifying clinically relevant sub-phenotypes is useful. We aimed to identify novel sub-phenotypes in hospitalized AP patients using longitudinal total serum calcium (TSC) trajectories. METHODS: AP patients had at least two TSC measurements during the first 24 h of hospitalization in the US-based critical care database (Medical Information Mart for Intensive Care-III (MIMIC-III) and MIMIC-IV were included. Group-based trajectory modeling was used to identify calcium trajectory phenotypes, and patient characteristics and treatment outcomes were compared between the phenotypes. RESULTS: A total of 4518 admissions were included in the analysis. Four TSC trajectory groups were identified: "Very low TSC, slow resolvers" (n = 65; 1.4% of the cohort); "Moderately low TSC" (n = 559; 12.4%); "Stable normal-calcium" (n = 3875; 85.8%); and "Fluctuating high TSC" (n = 19; 0.4%). The "Very low TSC, slow resolvers" had the lowest initial, maximum, minimum, and mean TSC, and highest SOFA score, creatinine and glucose level. In contrast, the "Stable normal-calcium" had the fewest ICU admission, antibiotic use, intubation and renal replace treatment. In adjusted analysis, significantly higher in-hospital mortality was noted among "Very low TSC, slow resolvers" (odds ratio [OR], 7.2; 95% CI, 3.7 to 14.0), "moderately low TSC" (OR, 5.0; 95% CI, 3.8 to 6.7), and "Fluctuating high TSC" (OR, 5.6; 95% CI, 1.5 to 20.6) compared with the "Stable normal-calcium" group. CONCLUSIONS: We identified four novel sub-phenotypes of patients with AP, with significant variability in clinical outcomes. Not only the absolute TSC levels but also their trajectories were significantly associated with in-hospital mortality.

The Global and Regional Prevalence of Hospital-Acquired Carbapenem-Resistant Klebsiella pneumoniae Infection: A Systematic Review and Meta-analysis.

Background: Due to scarce therapeutic options, hospital-acquired infections caused by Klebsiella pneumoniae (KP), particularly carbapenem-resistant KP (CRKP), pose enormous threat to patients' health worldwide. This study aimed to characterize the epidemiology and risk factors of CRKP among nosocomial KP infections. Method: MEDLINE, Embase, PubMed, and Google Scholar were searched for studies reporting CRKP prevalence from inception to 30 March 2023. Data from eligible publications were extracted and subjected to meta-analysis to obtain global, regional, and country-specific estimates. To determine the cause of heterogeneity among the selected studies, prespecified subgroup analyses and meta-regression were also performed. Odds ratios of CRKP-associated risk factors were pooled by a DerSimonian and Laird random-effects method. Results: We retained 61 articles across 14 countries and territories. The global prevalence of CRKP among patients with KP infections was 28.69% (95% CI, 26.53%-30.86%). South Asia had the highest CRKP prevalence at 66.04% (95% CI, 54.22%-77.85%), while high-income North America had the lowest prevalence at 14.29% (95% CI, 6.50%-22.0%). In the country/territory level, Greece had the highest prevalence at 70.61% (95% CI, 56.77%-84.45%), followed by India at 67.62% (95% CI, 53.74%-81.79%) and Taiwan at 67.54% (95% CI, 58.65%-76.14%). Hospital-acquired CRKP infections were associated with the following factors: hematologic malignancies, corticosteroid therapies, intensive care unit stays, mechanical ventilations, central venous catheter implantations, previous hospitalization, and antibiotic-related exposures (antifungals, carbapenems, quinolones, and cephalosporins). Conclusions: Study findings highlight the importance of routine surveillance to control carbapenem resistance and suggest that patients with nosocomial KP infection have a very high prevalence of CRKP.

Early warning system enables accurate mortality risk prediction for acute gastrointestinal bleeding admitted to intensive care unit.

Acute gastrointestinal (GI) bleeding are potentially life-threatening conditions. Early risk stratification is important for triaging patients to the appropriate level of medical care and intervention. Patients admitted to intensive care unit (ICU) has a high mortality, but risk tool is scarce for these patients. This study aimed to develop and validate a risk score to improve the prognostication of death at the time of patient admission to ICU. We developed and internally validated a nomogram for mortality in patients with acute GI bleeding from the eICU Collaborative Research Database (eICU-CRD), and externally validated it in patients from the Medical Information Mart for Intensive Care III database (MIMIC-III) and Wuhan Tongji Hospital. The performance of the model was assessed by examining discrimination (C-index), calibration (calibration curves) and usefulness (decision curves). 4750 patients were included in the development cohort, with 1184 patients in the internal validation cohort, 1406 patients in the MIMIC-III validation cohort, and 342 patients in the Tongji validation cohort. The nomogram, which incorporated ten variables, showed good calibration and discrimination in the training and validation cohorts, yielded C-index ranged from 0.832 (95%CI 0.811-0.853) to 0.926 (95CI% 0.905-0.947). The nomogram-defined high-risk group had a higher mortality than the low-risk group (44.8% vs. 3.5%, P < 0.001; 41.4% vs 3.1%, P < 0.001;53.6% vs 7.5%, P < 0.001; 38.2% vs 4.2%, P < 0.001). The model performed better than the conventional Glasgow-Blatchford score, AIMS65 and the newer Oakland and Sengupta scores for mortality prediction in both the derivation and validation cohorts concerning discrimination and usefulness. Our nomogram is a reliable prognostic tool that might be useful to identify high-risk acute GI bleeding patients admitted to ICU.

The incidence of brain trauma caused by road injuries: Results from the Global Burden of Disease Study 2019.

BACKGROUND: Road collisions are a significant source of traumatic brain injury (TBI). We aimed to determine the pattern of road injury related TBI (RI-TBI) incidence, as well as its temporal trends. METHODS: We collected detailed information on RI-TBI between 1990 and 2019, derived from the Global Burden of Disease Study 2019. Estimated annual percentage changes (EAPCs) of RI-TBI age standardized incidence rate (ASIR), by sex, region, and cause of road injuries, were assessed to quantify the temporal trends of RI-TBI burden. RESULTS: Globally, incident cases of RI-TBI increased 68.1% from 6,900,000 in 1990 to 11,600,000 in 2019. The overall ASIR increased by an average of 0.43% (95% CI 0.30%-0.56%) per year during this period. The ASIR of RI-TBI due to cyclist, motorcyclist and other road injuries increased between 1990 and 2019; the corresponding EAPCs were 0.56 (95% CI 0.37-0.75), 1.60 (95% CI 1.35-1.86), and 0.75 (95% CI 0.59-0.91), respectively. In contrast, the ASIR of RI-TBI due to motor vehicle and pedestrian decreased with an EAPC of -0.12 and -0.14 respectively. The changing pattern for RI-TBI was heterogeneous across countries and regions. The most pronounced increases were observed in Mexico (EAPC = 3.74), followed by China (EAPC = 2.45) and Lesotho (EAPC = 1.91). CONCLUSIONS: RI-TBI remains a major public health concern worldwide, although road safety legislations have contributed to the decreasing incidence in some countries. We found an unfavorable trend in several countries with a relatively low socio-demographic index, suggesting that much more targeted and specific approaches should be adopted in these areas to forestall the increase in RI-TBI.

Explainable machine learning model for predicting furosemide responsiveness in patients with oliguric acute kidney injury.

BACKGROUND: Although current guidelines didn't support the routine use of furosemide in oliguric acute kidney injury (AKI) management, some patients may benefit from furosemide administration at an early stage. We aimed to develop an explainable machine learning (ML) model to differentiate between furosemide-responsive (FR) and furosemide-unresponsive (FU) oliguric AKI. METHODS: From Medical Information Mart for Intensive Care-IV (MIMIC-IV) and eICU Collaborative Research Database (eICU-CRD), oliguric AKI patients with urine output (UO) < 0.5 ml/kg/h for the first 6 h after ICU admission and furosemide infusion ≥ 40 mg in the following 6 h were retrospectively selected. The MIMIC-IV cohort was used in training a XGBoost model to predict UO > 0.65 ml/kg/h during 6-24 h succeeding the initial 6 h for assessing oliguria, and it was validated in the eICU-CRD cohort. We compared the predictive performance of the XGBoost model with the traditional logistic regression and other ML models. RESULTS: 6897 patients were included in the MIMIC-IV training cohort, with 2235 patients in the eICU-CRD validation cohort. The XGBoost model showed an AUC of 0.97 (95% CI: 0.96-0.98) for differentiating FR and FU oliguric AKI. It outperformed the logistic regression and other ML models in correctly predicting furosemide diuretic response, achieved 92.43% sensitivity (95% CI: 90.88-93.73%) and 95.12% specificity (95% CI: 93.51-96.3%). CONCLUSION: A boosted ensemble algorithm can be used to accurately differentiate between patients who would and would not respond to furosemide in oliguric AKI. By making the model explainable, clinicians would be able to better understand the reasoning behind the prediction outcome and make individualized treatment.

An MRI-based Radiomics Approach to Improve Breast Cancer Histological Grading.

RATIONALE AND OBJECTIVES: Nottingham histological grade (NHG) 2 breast cancer has an intermediate risk of recurrence, which is not informative for therapeutic decision-making. We sought to develop and independently validate an MRI-based radiomics signature (Rad-Grade) to improve prognostic re-stratification of NHG 2 tumors. MATERIALS AND METHODS: Nine hundred-eight subjects with invasive breast cancer and preoperative MRI scans were retrospectively obtained. The NHG 1 and 3 tumors were randomly split into training and independent test cohort, with the NHG 2 as the prognostic validation set. From MRI image features, a radiomics-based signature predictive of the histological grade was built by use of the LASSO logistic regression algorithm. The model was developed for identifying NHG 1 and 3 radiological patterns, followed with re-stratification of NHG 2 tumors into Rad-Grade (RG)2-low (NHG 1-like) and RG2-high (NHG 3-like) subtypes using the learned patterns, and the prognostic value was assessed in terms of recurrence-free survival (RFS). RESULTS: The Rad-Grade showed independent prognostic value for re-stratification of NHG 2 tumors, where RG2-high had an increased risk for recurrence (HR 2.20, 1.10-4.40, p = 0.026) compared with RG2-low after adjusting for established risk factors. RG2-low shared similar phenotypic characteristics and RFS outcomes with NHG 1, and RG2-high with NHG 3, revealing that the model captures radiomic features in NHG 2 that are associated with different aggressiveness. The prognostic value of Rad-Grade was further validated in the NHG2 ER+ (HR 2.53, 1.13-5.56, p = 0.023) and NHG 2 ER+LN- (HR 5.72, 1.24-26.44, p = 0.025) subgroups, and in specific treatment contexts. CONCLUSION: The radiomics-based re-stratification of NHG 2 tumors offers a cost-effective promising alternative to gene expression profiling for tumor grading and thus may improve clinical decisions.

The trends of maternal mortality ratios and cause pattern in 34 Chinese provinces, 1990-2017.

BACKGROUND: Understanding the trends and causes to the burden of maternal deaths is a key requirement to further reduce the maternal mortality ratio (MMR), and devise targeted intervention policy. We aimed to evaluate the spatiotemporal trends of MMRs and cause patterns across the 34 provinces of China during 1990-2017. METHODS: Using data from the Global Burden of Disease Study 2017, we calculated the levels and trends of total maternal deaths and MMR due to ten different causes through Bayesian multivariable regression model for pregnancies aged 10-54 years, and assessed the age and regional distribution over time. RESULTS: China has experienced fast decline in MMR, dropped from 95.2 (87.8-102.3) in 1990 to 13.6 (12.5-15.0) in 2017, with an annualised rate of decline of 7.0%. In 1990, the range of MMRs in mainland China was 31.1 in Shanghai, to 323.4 in Tibet. Almost all provinces showed remarkable decline in the last two decades. However, spatial heterogeneity in levels and trends still existed. The annualised rate of decline across provinces from 1990 to 2017 ranged from 0.54% to 10.14%. Decline accelerated between 2005 and 2017 compared with between 1990 and 2005. In 2017, the lowest MMR was 4.2 in Zhejiang; the highest was still in Tibet, but had fallen to 82.7, dropped by 74.4%. MMR was highest in the 40-49 years age group in both 1990 and 2017. In 2017, haemorrhage and hypertensive disorders were the leading two specific causes for maternal deaths. CONCLUSIONS: MMRs have declined rapidly and universally across the provinces of China. Setting of associated interventions in the future will need careful consideration of provinces that still have MMR significantly higher than the national mean level.

Radiomics model based on shear-wave elastography in the assessment of axillary lymph node status in early-stage breast cancer.

OBJECTIVES: To develop and validate an ultrasound elastography radiomics nomogram for preoperative evaluation of the axillary lymph node (ALN) burden in early-stage breast cancer. METHODS: Data of 303 patients from hospital #1 (training cohort) and 130 cases from hospital #2 (external validation cohort) between Jun 2016 and May 2019 were enrolled. Radiomics features were extracted from shear-wave elastography (SWE) and corresponding B-mode ultrasound (BMUS) images. The minimum redundancy maximum relevance and least absolute shrinkage and selection operator algorithms were used to select ALN status-related features. Proportional odds ordinal logistic regression was performed using the radiomics signature together with clinical data, and an ordinal nomogram was subsequently developed. We evaluated its performance using C-index and calibration. RESULTS: SWE signature, US-reported LN status, and molecular subtype were independent risk factors associated with ALN status. The nomogram based on these variables showed good discrimination in the training (overall C-index: 0.842; 95%CI, 0.773-0.879) and the validation set (overall C-index: 0.822; 95%CI, 0.765-0.838). For discriminating between disease-free axilla (N0) and any axillary metastasis (N + (≥ 1)), it achieved a C-index of 0.845 (95%CI, 0.777-0.914) for the training cohort and 0.817 (95%CI, 0.769-0.865) for the validation cohort. The tool could also discriminate between low (N + (1-2)) and heavy metastatic ALN burden (N + (≥ 3)), with a C-index of 0.827 (95%CI, 0.742-0.913) in the training cohort and 0.810 (95%CI, 0.755-0.864) in the validation cohort. CONCLUSION: The radiomics model shows favourable predictive ability for ALN staging in patients with early-stage breast cancer, which could provide incremental information for decision-making. KEY POINTS: • Radiomics analysis helps radiologists to evaluate the axillary lymph node status of breast cancer with accuracy. • This multicentre retrospective study showed that radiomics nomogram based on shear-wave elastography provides incremental information for risk stratification. • Treatment can be given with more precision based on the model.

The global, regional, and national burden of acute pancreatitis in 204 countries and territories, 1990-2019.

BACKGROUND: Acute pancreatitis is a common and potentially lethal gastrointestinal disease, but literatures for the disease burden are scarce for many countries. Understanding the current burden of acute pancreatitis and the different trends across various countries is essential for formulating effective preventive intervenes. We aimed to report the incidence, mortality, and disability-adjusted life-years (DALYs) caused by acute pancreatitis in 204 countries and territories between 1990 and 2019. METHODS: Estimates from the Global Burden of Disease Study 2019 (GBD 2019) were used to analyze the epidemiology of acute pancreatitis at the global, regional, and national levels. We also reported the correlation between development status and acute pancreatitis' age-standardized DALY rates, and calculated DALYs attributable to alcohol etiology that had evidence of causation with acute pancreatitis. All of the estimates were shown as counts and age-standardized rates per 100,000 person-years. RESULTS: There were 2,814,972.3 (95% UI 2,414,361.3-3,293,591.8) incident cases of acute pancreatitis occurred in 2019 globally; 1,273,955.2 (1,098,304.6-1,478,594.1) in women and 1,541,017.1 (1,307,264.4-1,814,454.3) in men. The global age-standardized incidence rate declined from 37.9/100,000 to 34.8/100,000 during 1990-2019, an annual decrease of 8.4% (5.9-10.4%). In 2019, there were 115,053.2 (104,304.4-128,173.4) deaths and 3,641,105.7 (3,282,952.5-4,026,948.1) DALYs due to acute pancreatitis. The global age-standardized mortality rate decreased by 17.2% (6.6-27.1%) annually from 1.7/100,000 in 1990 to 1.4/100,000 in 2019; over the same period, the age-standardized DALY rate declined by 17.6% (7.8-27.0%) annually. There were substantial differences in the incidence, mortality and DALYs across regions. Alcohol etiology attributed to a sizable fraction of acute pancreatitis-related deaths, especially in the high and high-middle SDI regions. CONCLUSION: Substantial variation existed in the burden of acute pancreatitis worldwide, and the overall burden remains high with aging population. Geographically targeted considerations are needed to tailor future intervenes to relieve the burden of acute pancreatitis in specific countries, especially for Eastern Europe.

Management of breast lesions seen on US images: dual-model radiomics including shear-wave elastography may match performance of expert radiologists.

PURPOSE: To develop a nomogram incorporating B-mode ultrasound (BMUS) and shear-wave elastography (SWE) radiomics to predict malignant status of breast lesions seen on US non-invasively. METHODS: Data on 278 consecutive patients from Hospital #1 (training cohort) and 123 cases from Hospital #2 (external validation cohort) referred for breast US with subsequent histopathologic analysis between May 2017 and October 2019 were retrospectively collected. Using their BMUS and SWE images, we built a radiomics nomogram to improve radiology workflow for management of breast lesions. The performance of the algorithm was compared with a consensus of three ACR BI-RADS committee experts and four individual radiologists, all of whom interpreted breast US images in clinical practice. RESULTS: Twelve features from BMUS and three from SWE were selected finally to construct the respective radiomic signature. The nomogram based on the dual-modal US radiomics achieved good diagnostic performance in the training (AUC 0.96; 95% confidence intervals [CI], 0.94-0.98) and the validation set (AUC 0.92; 95% CI, 0.87-0.97). For the 123 test lesions, the algorithm achieved 105 of 123 (85%) accuracy, comparable to the expert consensus (104 of 123 [85%], P =  0.86) and four individual radiologists (93, 99, 95 and 97 of 123, with P value of 0.05, 0.31, 0.10 and 0.18 respectively). Furthermore, the model also performed well in the BI-RADS 4 and 5 categories. CONCLUSIONS: Performance of a dual-model US radiomics nomogram based on SWE for breast lesion classification may comparable to that of expert radiologists who used ACR BI-RADS guideline.

Ultrasound-based deep learning radiomics in the assessment of pathological complete response to neoadjuvant chemotherapy in locally advanced breast cancer.

PURPOSE: The aim of the study was to develop and validate a deep learning radiomic nomogram (DLRN) for preoperatively assessing breast cancer pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) based on the pre- and post-treatment ultrasound. METHODS: Patients with locally advanced breast cancer (LABC) proved by biopsy who proceeded to undergo preoperative NAC were enrolled from hospital #1 (training cohort, 356 cases) and hospital #2 (independent external validation cohort, 236 cases). Deep learning and handcrafted radiomic features reflecting the phenotypes of the pre-treatment (radiomic signature [RS] 1) and post-treatment tumour (RS2) were extracted. The minimum redundancy maximum relevance algorithm and the least absolute shrinkage and selection operator regression were used for feature selection and RS construction. A DLRN was then developed based on the RSs and independent clinicopathological risk factors. The performance of the model was assessed with regard to calibration, discrimination and clinical usefulness. RESULTS: The DLRN predicted the pCR status with accuracy, yielded an area under the receiver operator characteristic curve of 0.94 (95% confidence interval, 0.91-0.97) in the validation cohort, with good calibration. The DLRN outperformed the clinical model and single RS within both cohorts (P < 0.05, as per the DeLong test) and performed better than two experts' prediction of pCR (both P < 0.01 for comparison of total accuracy). Besides, prediction within the hormone receptor-positive/human epidermal growth factor receptor 2 (HER2)-negative, HER2+ and triple-negative subgroups also achieved good discrimination performance, with an AUC of 0.90, 0.95 and 0.93, respectively, in the external validation cohort. Decision curve analysis confirmed that the model was clinically useful. CONCLUSION: A deep learning-based radiomic nomogram had good predictive value for pCR in LABC, which could provide valuable information for individual treatment.

Production of 1,3-propanediol and lactic acid from crude glycerol by a microbial consortium from intertidal sludge.

OBJECTIVES: To select a microbial consortium from intertidal sludge and evaluate its ability to convert crude glycerol from biodisel to high value-added products such as 1,3-propanediol (1,3-PDO) and lactic acid (LA). RESULTS: A microbial consortium named CJD-S was selected from intertidal sludge and exhibited excellent performance for the conversion of crude glycerol to 1,3-PDO and LA. The composition of CJD-S was determined to be 85.99% Enterobacteriaceae and 13.75% Enterococcaceae by 16S rRNA gene amplicon high-throughput sequencing. In fed-batch fermentation with crude glycerol under nonsterile conditions, the highest concentrations of 1,3-PDO and LA were 41.47 g/L and 45.86 g/L, respectively. CONCLUSIONS: The selected microbial consortium, CJD-S, effectively converted crude glycerol to 1,3-PDO and LA under nonsterile conditions and can contribute to the sustainable development of the biodiesel industry.

Nomogram for predicting transmural bowel infarction in patients with acute superior mesenteric venous thrombosis.

BACKGROUND: The prognosis of acute mesenteric ischemia (AMI) caused by superior mesenteric venous thrombosis (SMVT) remains undetermined and early detection of transmural bowel infarction (TBI) is crucial. The predisposition to develop TBI is of clinical concern, which can lead to fatal sepsis with hemodynamic instability and multi-organ failure. Early resection of necrotic bowel could improve the prognosis of AMI, however, accurate prediction of TBI remains a challenge for clinicians. When determining the eligibility for explorative laparotomy, the underlying risk factors for bowel infarction should be fully evaluated. AIM: To develop and externally validate a nomogram for prediction of TBI in patients with acute SMVT. METHODS: Consecutive data from 207 acute SMVT patients at the Wuhan Tongji Hospital and 89 patients at the Guangzhou Nanfang Hospital between July 2005 and December 2018 were included in this study. They were grouped as training and external validation cohort. The 207 cases (training cohort) from Tongji Hospital were divided into TBI and reversible intestinal ischemia groups based on the final therapeutic outcomes. Univariate and multivariate logistic regression analyses were conducted to identify independent risk factors for TBI using the training data, and a nomogram was subsequently developed. The performance of the nomogram was evaluated with respect to discrimination, calibration, and clinical usefulness in the training and external validation cohort. RESULTS: Univariate and multivariate logistic regression analyses identified the following independent prognostic factors associated with TBI in the training cohort: The decreased bowel wall enhancement (OR = 6.37, P < 0.001), rebound tenderness (OR = 7.14, P < 0.001), serum lactate levels > 2 mmol/L (OR = 3.14, P = 0.009) and previous history of deep venous thrombosis (OR = 6.37, P < 0.001). Incorporating these four factors, the nomogram achieved good calibration in the training set [area under the receiver operator characteristic curve (AUC) 0.860; 95%CI: 0.771-0.925] and the external validation set (AUC 0.851; 95%CI: 0.796-0.897). The positive and negative predictive values (95%CIs) of the nomogram were calculated, resulting in positive predictive values of 54.55% (40.07%-68.29%) and 53.85% (43.66%-63.72%) and negative predictive values of 93.33% (82.14%-97.71%) and 92.24% (85.91%-95.86%) for the training and validation cohorts, respectively. Based on the nomogram, patients who had a Nomo-score of more than 90 were considered to have high risk for TBI. Decision curve analysis indicated that the nomogram was clinically useful. CONCLUSION: The nomogram achieved an optimal prediction of TBI in patients with AMI. Using the model, the risk for an individual patient inclined to TBI can be assessed, thus providing a rational therapeutic choice.

Risk of venous thromboembolism associated with totally implantable venous access ports in cancer patients: A systematic review and meta-analysis.

BACKGROUND: Totally implantable venous access ports (TIVAPs) for chemotherapy are associated with venous thromboembolism (VTE). We aimed to quantify the incidence of TIVAP-associated VTE and compare it with external central venous catheters (CVCs) in cancer patients through a meta-analysis. METHODS: Studies reporting on VTE risk associated with TIVAP were retrieved from medical literature databases. In publications without a comparison group, the pooled incidence of TIVAP-related VTE was calculated. For studies comparing TIVAPs with external CVCs, odds ratios (ORs) were calculated to assess the risk of VTE. RESULTS: In total, 80 studies (11 with a comparison group and 69 without) including 39 148 patients were retrieved. In the noncomparison studies, the overall symptomatic VTE incidence was 2.76% (95% confidence interval [CI]: 2.24-3.28), and 0.08 (95 CI: 0.06-0.10) per 1000 catheter-days. This risk was highest when TIVAPs were inserted via the upper-extremity vein (3.54%, 95% CI: 2.94-4.76). Our meta-analysis of the case-control studies showed that TIVAPs were associated with a decreased risk of VTE compared with peripherally inserted central catheters (OR = 0.20, 95% CI: 0.09-0.43), and a trend for lower VTE risk compared with Hickman catheters (OR = 0.75, 95% CI: 0.37-1.50). Meta-regression models suggested that regional difference may significantly impact on the incidence of VTE associated with TIVAPs. CONCLUSIONS: Current evidence suggests that the cancer patients with TIVAP are less likely to develop VTE compared with external CVCs. This should be considered when choosing the indwelling intravenous device for chemotherapy. However, more attention should be paid when choosing upper-extremity veins as the insertion site.

The risk of bloodstream infection associated with totally implantable venous access ports in cancer patient: a systematic review and meta-analysis.

OBJECTIVE: This systematic review and meta-analysis aimed to provide evidence-based guidance to better understand the risk of central line-associated bloodstream infection (CLABSI) in cancer patients who received totally implantable venous access ports (TIVAPs) compared with those who received external central venous catheters (CVCs). METHODS: A systematic search of PubMed, Web of science, Embase, and the Cochrane Library was carried out from inception through Oct 2018, with no language restrictions. Trials examining the risk of CLABSI in cancer patients who received TIVAPs compared with those who received external CVCs were included. Two reviewers independently reviewed, extracted data, and assessed the risk of bias of each study. A random-effect model was used to estimate relative risks (RRs) with 95% CIs. RESULTS: In all, 26 studies involving 27 cohorts and 5575 patients reporting the incidence of CLABSI in patients with TIVAPs compared with external CVCs were included. Pooled meta-analysis of these trials revealed that TIVAPs were associated with a significant lower risk of CLABSI than were external CVCs (relative risk [RR], 0.44; 95% confidence interval [CI], 0.31-0.62; P < 0.00001), which was confirmed by trial sequential analysis for the cumulative z curve entered the futility area. Subgroup analyses demonstrated that CLABSI reduction was greatest in adult patients (RR [95% CI], 0.35 [0.22-0.56]) compared with pediatric patients who received TIVAPs (RR [95% CI], 0.55 [0.38-0.79]). CONCLUSIONS: TIVAP can significantly reduce the risk of CLABSI compared with external CVCs.

Laparoscopic Redo Pull-Through for Hirschsprung Disease Due to Innervation Disorders.

BACKGROUND: Reoperations in Hirschsprung disease (HD) may be required due to pathological problems. We conducted this retrospective study to determine the incidence and outcomes of innervation disorders among HD patients following pull-through operation. MATERIALS AND METHODS: We retrospectively reviewed the data of patients who underwent pull-through procedure from 2005 to 2017. Only patients who underwent reoperation due to histological disorders were analyzed. Patients with mechanical obstruction that caused recurrent constipation were excluded. RESULTS: There were 836 patients who got treated for HD in our department during the study period, and of these, 72 (8.6%) had redo operation. Thirty-one out of the 72 patients (43.1%) showed abnormal histological findings on full-thickness biopsies. Primary operations included totally transanal endorectal pull-through (18), laparoscopic-assisted Duhamel (5) and Soave (8) techniques. The full-thickness biopsies before the reoperation showed aganglionosis (n = 8, 1 was residual resulted from false-positive intraoperative frozen sections and 7 were acquired aganglionosis), transition-zone (3), intestinal neuronal dysplasia B (IND B, n = 15), and hypoganglionosis (5). The final diagnoses according to the resection specimens of the initial and second operations were HD (11), Hirschsprung-associated IND B (15), and Hirschsprung-associated hypoganglionosis (5). Reoperation consisted of laparoscopic-assisted Duhamel (14) and Soave procedures (17). In these patients, 77.4% had excellent/good bowel function, 16.1% were fair, and 6.5% were poor. CONCLUSIONS: Innervation disorders are still the underlying causes of recurrent constipation in almost half of all HD patients requiring redo pull-through operation. Most patients have a satisfactory outcome after redoing laparoscopic-assisted Duhamel or Soave operation.