Advanced septic arthritis of the shoulder treated by a two-stage arthroplasty.

The usual treatment of septic shoulder arthritis consists of arthroscopic or open lavage and debridement. However, in patients with advanced osteoarthritic changes and/or massive rotator cuff tendon tears, infection eradication can be challenging to achieve and the functional outcome is often not satisfying even after successful infection eradication. In such cases a two-stage approach with initial resection of the native infected articular surfaces, implantation of a cement spacer before final treatment with a total shoulder arthroplasty in a second stage is gaining popularity in recent years with the data in literature however being still limited. To evaluate the results of a short interval two-stage arthroplasty approach for septic arthritis with concomitant advanced degenerative changes of the shoulder joint. We retrospectively included five consecutive patients over a five-year period and evaluated the therapeutic management and the clinical outcome assessed by disability of the arm, shoulder and hand (DASH) score and subjective shoulder value (SSV). All procedures were performed through a deltopectoral approach and consisted in a debridement and synovectomy, articular surface resection and insertion of a custom made antibiotic enriched cement spacer. Shoulder arthroplasty was performed in a second stage. Mean age was 61 years (range, 47-70 years). Four patients had previous surgeries ahead of the septic arthritis. All patients had a surgical debridement ahead of the index procedure. Mean follow-up was 13 mo (range, 6-24 mo). Persistent microbiological infection was confirmed in all five cases at the time of the first stage of the procedure. The shoulder arthroplasties were performed 6 to 12 wk after insertion of the antibiotic-loaded spacer. There were two hemi and three reverse shoulder arthroplasties. Infection was successfully eradicated in all patients. The clinical outcome was satisfactory with a mean DASH score and SSV of 18.4 points and 70% respectively. Short interval two-stage approach for septic shoulder arthritis is an effective treatment option. It should nonetheless be reserved for selected patients with advanced disease in which lavage and debridement have failed

Failure of lactate clearance predicts the outcome of critically ill septic patients

Purpose: Early lactate clearance is an important parameter for prognosis assessment and therapy control in sepsis. Patients with a lactate clearance >0% might differ from patients with an inferior clearance in terms of intensive care management and outcomes. This study analyzes a large collective with regards to baseline risk distribution and outcomes. Methods: In total, 3299 patients were included in this analysis, consisting of 1528 (46%) ≤0% and 1771 (54%) >0% patients. The primary endpoint was intensive care unit (ICU) mortality. Multilevel logistic regression analyses were used to compare both groups: A baseline model (model 1) with lactate clearance as a fixed effect and ICU as a random effect was installed. For model 2, patient characteristics (model 2) were included. For model 3, intensive care treatment (mechanical ventilation and vasopressors) was added to the model. Models 1 and 2 were used to evaluate the primary and secondary outcomes, respectively. Model 3 was only used to evaluate the primary outcomes. Adjusted odds ratios (aORs) with respective 95% confidence intervals (CI) were calculated. Results: The cohorts had no relevant differences regarding the gender, BMI, age, heart rate, body temperature, and baseline lactate. Neither the primary infection focuses nor the ethnic background differed between both groups. In both groups, the most common infection sites were of pulmonary origin, the urinary tract, and the gastrointestinal tract. Patients with lactate clearance >0% evidenced lower sepsis-related organ failure assessment (SOFA) scores (7 ± 6 versus 9 ± 6; p < 0.001) and creatinine (1.53 ± 1.49 versus 1.80 ± 1.67; p < 0.001). The ICU mortality differed significantly (14% versus 32%), and remained this way after multivariable adjustment for patient characteristics and intensive care treatment (aOR 0.43 95% CI 0.36–0.53; p < 0.001). In the additional sensitivity analysis, the lack of lactate clearance was associated with a worse prognosis in each subgroup. Conclusion: In this large collective of septic patients, the 6 h lactate clearance is an independent method for outcome prediction

Impella versus extracorporal life support in cardiogenic shock: a propensity score adjusted analysis

Aims: The mortality in cardiogenic shock (CS) is high. The role of specific mechanical circulatory support (MCS) systems is unclear. We aimed to compare patients receiving Impella versus ECLS (extracorporal life support) with regard to baseline characteristics, feasibility, and outcomes in CS. Methods and results: This is a retrospective cohort study including CS patients over 18 years with a complete follow-up of the primary endpoint and available baseline lactate level, receiving haemodynamic support either by Impella 2.5 or ECLS from two European registries. The decision for device implementation was made at the discretion of the treating physician. The primary endpoint of this study was all-cause mortality at 30 days. A propensity score for the use of Impella was calculated, and multivariable logistic regression was used to obtain adjusted odds ratios (aOR). In total, 149 patients were included, receiving either Impella (n = 73) or ECLS (n = 76) for CS. The feasibility of device implantation was high (87%) and similar (aOR: 3.14; 95% CI: 0.18–56.50; P = 0.41) with both systems. The rates of vascular injuries (aOR: 0.95; 95% CI: 0.10–3.50; P = 0.56) and bleedings requiring transfusions (aOR: 0.44; 95% CI: 0.09–2.10; P = 0.29) were similar in ECLS patients and Impella patients. The use of Impella or ECLS was not associated with increased odds of mortality (aOR: 4.19; 95% CI: 0.53–33.25; P = 0.17), after correction for propensity score and baseline lactate level. Baseline lactate level was independently associated with increased odds of 30 day mortality (per mmol/L increase; OR: 1.29; 95% CI: 1.14–1.45; P < 0.001). Conclusions: In CS patients, the adjusted mortality rates of both ECLS and Impella were high and similar. The baseline lactate level was a potent predictor of mortality and could play a role in patient selection for therapy in future studies. In patients with profound CS, the type of device is likely to be less important compared with other parameters including non-cardiac and neurological factors

Machine learning predicts mortality based on analysis of ventilation parameters of critically ill patients: multi-centre validation

Background Mechanical Ventilation (MV) is a complex and central treatment process in the care of critically ill patients. It influences acid–base balance and can also cause prognostically relevant biotrauma by generating forces and liberating reactive oxygen species, negatively affecting outcomes. In this work we evaluate the use of a Recurrent Neural Network (RNN) modelling to predict outcomes of mechanically ventilated patients, using standard mechanical ventilation parameters. Methods We performed our analysis on VENTILA dataset, an observational, prospective, international, multi-centre study, performed to investigate the effect of baseline characteristics and management changes over time on the all-cause mortality rate in mechanically ventilated patients in ICU. Our cohort includes 12,596 adult patients older than 18, associated with 12,755 distinct admissions in ICUs across 37 countries and receiving invasive and non-invasive mechanical ventilation. We carry out four different analysis. Initially we select typical mechanical ventilation parameters and evaluate the machine learning model on both, the overall cohort and a subgroup of patients admitted with respiratory disorders. Furthermore, we carry out sensitivity analysis to evaluate whether inclusion of variables related to the function of other organs, improve the predictive performance of the model for both the overall cohort as well as the subgroup of patients with respiratory disorders. Results Predictive performance of RNN-based model was higher with Area Under the Receiver Operating Characteristic (ROC) Curve (AUC) of 0.72 (± 0.01) and Average Precision (AP) of 0.57 (± 0.01) in comparison to RF and LR for the overall patient dataset. Higher predictive performance was recorded in the subgroup of patients admitted with respiratory disorders with AUC of 0.75 (± 0.02) and AP of 0.65 (± 0.03). Inclusion of function of other organs further improved the performance to AUC of 0.79 (± 0.01) and AP 0.68 (± 0.02) for the overall patient dataset and AUC of 0.79 (± 0.01) and AP 0.72 (± 0.02) for the subgroup with respiratory disorders. Conclusion The RNN-based model demonstrated better performance than RF and LR in patients in mechanical ventilation and its subgroup admitted with respiratory disorders. Clinical studies are needed to evaluate whether it impacts decision-making and patient outcomes

Machine learning predicts mortality in septic patients using only routinely available ABG variables: a multi-centre evaluation

open5siPurpose: To evaluate the application of machine learning methods, specifically Deep Neural Networks (DNN) models for intensive care (ICU) mortality prediction. The aim was to predict mortality within 96 hours after admission to mirror the clinical situation of patient evaluation after an ICU trial, which consists of 24-48 hours of ICU treatment and then “re-triage”. The input variables were deliberately restricted to ABG values to maximise real-world practicability. Methods: We retrospectively evaluated septic patients in the multi-centre eICU dataset as well as single centre MIMIC-III dataset. Included were all patients alive after 48 hours with available data on ABG (n = 3979 and n = 9655 ICU stays for the multi-centre and single centre respectively). The primary endpoint was 96 -h-mortality. Results: The model was developed using long short-term memory (LSTM), a type of DNN designed to learn temporal dependencies between variables. Input variables were all ABG values within the first 48 hours. The SOFA score (AUC of 0.72) was moderately predictive. Logistic regression showed good performance (AUC of 0.82). The best performance was achieved by the LSTM-based model with AUC of 0.88 in the multi-centre study and AUC of 0.85 in the single centre study. Conclusions: An LSTM-based model could help physicians with the “re-triage” and the decision to restrict treatment in patients with a poor prognosis.openWernly, Bernhard; Mamandipoor, Behrooz; Baldia, Philipp; Jung, Christian; Osmani, VenetWernly, Bernhard; Mamandipoor, Behrooz; Baldia, Philipp; Jung, Christian; Osmani, Vene

Chimpanzee Fab Fragments and a Derived Humanized Immunoglobulin G1 Antibody That Efficiently Cross-Neutralize Dengue Type 1 and Type 2 Viruses

Passive immunization with monoclonal antibodies from humans or nonhuman primates represents an attractive alternative to vaccines for prevention of illness caused by dengue viruses (DENV) and other flaviviruses, including the West Nile virus. In a previous study, repertoire cloning to recover Fab fragments from bone marrow mRNA of chimpanzees infected with all four DENV serotypes (dengue virus serotype 1 [DENV-1] to DENV-4) was described. In that study, a humanized immunoglobulin G1 (IgG1) antibody that efficiently neutralized DENV-4 was recovered and characterized. In this study, the phage library constructed from the chimpanzees was used to recover Fab antibodies against the other three DENV serotypes. Serotype-specific neutralizing Fabs were not identified. Instead, we recovered DENV-neutralizing Fabs that specifically precipitated the envelope protein and were cross-reactive with all four DENV serotypes. Three of the Fabs competed with each other for binding to DENV-1 and DENV-2, although each of these Fabs contained a distinct complementarity determining region 3 (CDR3)-H sequence. Fabs that shared an identical or nearly identical CDR3-H sequences cross-neutralized DENV-1 and DENV-2 at a similar high 50% plaque reduction neutralization test (PRNT(50)) titer, ranging from 0.26 to 1.33 μg/ml, and neutralized DENV-3 and DENV-4 but at a titer 10- to 20-fold lower. One of these Fabs, 1A5, also neutralized the West Nile virus most efficiently among other flaviviruses tested. Fab 1A5 was converted to a full-length antibody in combination with human sequences for production in mammalian CHO cells. Humanized IgG1 1A5 proved to be as efficient as Fab 1A5 for cross-neutralization of DENV-1 and DENV-2 at a titer of 0.48 and 0.95 μg/ml, respectively. IgG1 1A5 also neutralized DENV-3, DENV-4, and the West Nile virus at a PRNT(50) titer of approximately 3.2 to 4.2 μg/ml. This humanized antibody represents an attractive candidate for further development of immunoprophylaxis against DENV and perhaps other flavivirus-associated diseases

Identification of Chimpanzee Fab Fragments by Repertoire Cloning and Production of a Full-Length Humanized Immunoglobulin G1 Antibody That Is Highly Efficient for Neutralization of Dengue Type 4 Virus

A safe and effective dengue vaccine is still not available. Passive immunization with monoclonal antibodies from humans or nonhuman primates represents an attractive alternative for the prevention of dengue virus infection. Fab monoclonal antibodies to dengue type 4 virus (DENV-4) were recovered by repertoire cloning of bone marrow mRNAs from an immune chimpanzee and analyzed for antigen binding specificity, V(H) and V(L) sequences, and neutralizing activity against DENV-4 in vitro. Fabs 5A7, 3C1, 3E4, and 7G4 were isolated from a library constructed from a chimpanzee following intrahepatic transfection with infectious DENV-4 RNA. Fabs 5H2 and 5D9, which had nearly identical V(H) sequences but varied in their V(L) sequences, were recovered from a library constructed from the same chimpanzee after superinfection with a mixture of DENV-1, DENV-2, and DENV-3. In radioimmunoprecipitation, Fab 5A7 precipitated only DENV-4 prM, and Fabs 3E4, 7G4, 5D9, and 5H2 precipitated DENV-4 E but little or no prM. Fab 3E4 and Fab 7G4 competed with each other for binding to DENV-4 in an enzyme-linked immunosorbent assay, as did Fab 3C1 and Fab 5A7. Fab 5H2 recognized an epitope on DENV-4 that was separate from the epitope(s) recognized by other Fabs. Both Fab 5H2 and Fab 5D9 neutralized DENV-4 efficiently with a titer of 0.24 to 0.58 μg/ml by plaque reduction neutralization test (PRNT), whereas DENV-4-neutralizing activity of other Fabs was low or not detected. Fab 5H2 was converted to full-length immunoglobulin G1 (IgG1) by combining it with human sequences. The humanized chimpanzee antibody IgG1 5H2 produced in CHO cells neutralized DENV-4 strains from different geographical origins at a similar 50% plaque reduction (PRNT(50)) titer of 0.03 to 0.05 μg/ml. The DENV-4 binding affinities were 0.42 nM for Fab 5H2 and 0.24 nM for full-length IgG1 5H2. Monoclonal antibody IgG1 5H2 may prove valuable for passive immunoprophylaxis against dengue virus in humans