Automated surveillance of non-ventilator-associated hospital-acquired pneumonia (nvHAP): a systematic literature review.

BACKGROUND: Hospital-acquired pneumonia (HAP) and its specific subset, non-ventilator hospital-acquired pneumonia (nvHAP) are significant contributors to patient morbidity and mortality. Automated surveillance systems for these healthcare-associated infections have emerged as a potentially beneficial replacement for manual surveillance. This systematic review aims to synthesise the existing literature on the characteristics and performance of automated nvHAP and HAP surveillance systems. METHODS: We conducted a systematic search of publications describing automated surveillance of nvHAP and HAP. Our inclusion criteria covered articles that described fully and semi-automated systems without limitations on patient demographics or healthcare settings. We detailed the algorithms in each study and reported the performance characteristics of automated systems that were validated against specific reference methods. Two published metrics were employed to assess the quality of the included studies. RESULTS: Our review identified 12 eligible studies that collectively describe 24 distinct candidate definitions, 23 for fully automated systems and one for a semi-automated system. These systems were employed exclusively in high-income countries and the majority were published after 2018. The algorithms commonly included radiology, leukocyte counts, temperature, antibiotic administration, and microbiology results. Validated surveillance systems' performance varied, with sensitivities for fully automated systems ranging from 40 to 99%, specificities from 58 and 98%, and positive predictive values from 8 to 71%. Validation was often carried out on small, pre-selected patient populations. CONCLUSIONS: Recent years have seen a steep increase in publications on automated surveillance systems for nvHAP and HAP, which increase efficiency and reduce manual workload. However, the performance of fully automated surveillance remains moderate when compared to manual surveillance. The considerable heterogeneity in candidate surveillance definitions and reference standards, as well as validation on small or pre-selected samples, limits the generalisability of the findings. Further research, involving larger and broader patient populations is required to better understand the performance and applicability of automated nvHAP surveillance.

[Diagnosis and antibiotic therapy of nosocomial pneumonia in adults: from recommendations to real practice. A review].

Nosocomial pneumonia is a healthcare-associated infection with significant consequences for the patient and the healthcare system. The efficacy of treatment significantly depends on the timeliness and adequacy of the antibiotic therapy regimen. The growth of resistance of gram-negative pathogens of nosocomial pneumonia to antimicrobial agents increases the risk of prescribing inadequate empirical therapy, which worsens the results of patient treatment. Identification of risk factors for infection with multidrug-resistant microorganisms, careful local microbiological monitoring with detection of resistance mechanisms, implementation of antimicrobial therapy control strategy and use of rational combinations of antibacterial drugs are of great importance. In addition, the importance of using new drugs with activity against carbapenem-resistant strains, including ceftazidime/aviabactam, must be understood. This review outlines the current data on the etiology, features of diagnosis and antibacterial therapy of nosocomial pneumonia.

Identifying patients at increased risk of non-ventilator-associated pneumonia on admission to hospital: a pragmatic prognostic screening tool to trigger preventative action.

BACKGROUND: Non-ventilator healthcare-associated pneumonia (NV-HAP) is an important healthcare-associated infection. This study tested the feasibility of using routine admission data to identify those patients at high risk of NV-HAP who could benefit from targeted, preventive interventions. METHODS: Patients aged ≥64 years who developed NV-HAP five days or more after admission to elderly-care wards, were identified by retrospective case note review together with matched controls. Data on potential predictors of NV-HAP were captured from admission records. Multi-variate analysis was used to build a prognostic screening tool (PRHAPs); acceptability and feasibility of the tool was evaluated. RESULTS: A total of 382 cases/381 control patients were included in the analysis. Ten predictors were included in the final model; nine increased the risk of NV-HAP (OR between 1.68 and 2.42) and one (independent mobility) was protective (OR 0.48; 95% CI 0.30-0.75). The model correctly predicted 68% of the patients with and without NV-HAP; sensitivity 77%; specificity 61%. The PRHAPs tool risk score was 60% or more if two predictors were present and over 70% if three were present. An expert consensus group supported incorporating the PRHAPs tool into electronic logic systems as an efficient mechanism to identify patients at risk of NV-HAP and target preventative strategies. CONCLUSIONS: This prognostic screening (PRHAPs) tool, applied to data routinely collected when a patient is admitted to hospital, could enable staff to identify patients at greatest risk of NV-HAP, target scarce resources in implementing a prevention care bundle, and reduce the use of antimicrobial agents.

A recalibrated prediction model can identify level-1 trauma patients at risk of nosocomial pneumonia.

INTRODUCTION: Nosocomial pneumonia has poor prognosis in hospitalized trauma patients. Croce et al. published a model to predict post-traumatic ventilator-associated pneumonia, which achieved high discrimination and reasonable sensitivity. We aimed to externally validate Croce's model to predict nosocomial pneumonia in patients admitted to a Dutch level-1 trauma center. MATERIALS AND METHODS: This retrospective study included all trauma patients (≥ 16y) admitted for > 24 h to our level-1 trauma center in 2017. Exclusion criteria were pneumonia or antibiotic treatment upon hospital admission, treatment elsewhere > 24 h, or death < 48 h. Croce's model used eight clinical variables-on trauma severity and treatment, available in the emergency department-to predict nosocomial pneumonia risk. The model's predictive performance was assessed through discrimination and calibration before and after re-estimating the model's coefficients. In sensitivity analysis, the model was updated using Ridge regression. RESULTS: 809 Patients were included (median age 51y, 67% male, 97% blunt trauma), of whom 86 (11%) developed nosocomial pneumonia. Pneumonia patients were older, more severely injured, and underwent more emergent interventions. Croce's model showed good discrimination (AUC 0.83, 95% CI 0.79-0.87), yet predicted probabilities were too low (mean predicted risk 6.4%), and calibration was suboptimal (calibration slope 0.63). After full model recalibration, discrimination (AUC 0.84, 95% CI 0.80-0.88) and calibration improved. Adding age to the model increased the AUC to 0.87 (95% CI 0.84-0.91). Prediction parameters were similar after the models were updated using Ridge regression. CONCLUSION: The externally validated and intercept-recalibrated models show good discrimination and have the potential to predict nosocomial pneumonia. At this time, clinicians could apply these models to identify high-risk patients, increase patient monitoring, and initiate preventative measures. Recalibration of Croce's model improved the predictive performance (discrimination and calibration). The recalibrated model provides a further basis for nosocomial pneumonia prediction in level-1 trauma patients. Several models are accessible via an online tool. LEVEL OF EVIDENCE: Level III, Prognostic/Epidemiological Study.

A multiplex pneumonia panel for diagnosis of hospital-acquired and ventilator-associated pneumonia in the era of emerging antimicrobial resistance.

Background: Antimicrobial resistance (AMR), including multidrug (MDR) and extensively drug-resistant (XDR) bacteria, is an essential consideration in the prevention and management of hospital-acquired pneumonia (HAP) and ventilator-associated pneumonia (VAP). In the AMR era, the clinical utility of the BioFire FilmArray Pneumonia Panel Plus (BFPP) to diagnose HAP/VAP has not been thoroughly evaluated. Methods: We enrolled adult hospitalized patients with HAP or VAP at Siriraj Hospital and Saraburi Hospital from July 2019-October 2021. Respiratory samples were collected for standard microbiological assays, antimicrobial susceptibility testing (AST), and the BFPP analysis. Results: Of 40 subjects, 21 were men. The median duration of HAP/VAP diagnoses was 10.5 (5, 21.5) days, and 36 endotracheal aspirate and 4 sputum samples were collected. Standard cultures isolated 54 organisms-A. baumannii (37.0%), P. aeruginosa (29.6%), and S. maltophilia (16.7%). 68.6% of Gram Negatives showed an MDR or XDR profile. BFPP detected 77 bacterial targets-A. baumannii 32.5%, P. aeruginosa 26.3%, and K. pneumoniae 17.5%. Of 28 detected AMR gene targets, CTX-M (42.5%), OXA-48-like (25%), and NDM (14.3%) were the most common. Compared with standard testing, the BFPP had an overall sensitivity of 98% (88-100%), specificity of 81% (74-87%), positive predictive value of 60% (47-71%), negative predictive value of 99% (96-100%), and kappa (κ) coefficient of 0.64 (0.53-0.75). The concordance between phenotypic AST and detected AMR genes in Enterobacterales was 0.57. There was no concordance among A. baumannii, P. aeruginosa, and S. aureus. Conclusions: The BFPP has excellent diagnostic sensitivity to detect HAP/VAP etiology. The absence of S. maltophilia and discordance of AMR gene results limit the test performance.

Including Organ Dysfunctions in a Predictive Score for Nosocomial Pneumonia After Cardiothoracic Surgery.

BACKGROUND: Clinical diagnosis of ICU-acquired pneumonia after cardiothoracic surgery is challenging. Johanson criteria (chest radiograph infiltrate, purulent tracheal secretions, fever, and leukocytosis) fail in half the cases. A high Clinical Pulmonary Infection Score (CPIS) and ≥ 2-point increase in Sequential Organ Failure Assessment (SOFA) score (SOFA↑ ≥ 2) may improve diagnosis. The aim of the study was to evaluate whether CPIS or SOFA↑ ≥ 2 contributes to predict ICU-acquired pneumonia in subjects after cardiothoracic surgery. METHODS: We used a prospective observational design. Spiegelhalter-Knill-Jones scoring systems including CPIS or SOFA↑ ≥ 2, together with other clinical and laboratory variables, were developed in a derivation cohort. A positive quantitative pulmonary sample culture was required to confirm ICU-acquired pneumonia. Area under the receiver operating characteristic curve (AUROC) was computed for each of the 2 scoring systems. The best system was evaluated in a validation cohort. RESULTS: Derivation and validation cohorts included 172 and 108 subjects, with 410 and 216 suspected ICU-acquired pneumonia episodes, respectively. AUROC was 0.53 ± 0.03 for CPIS (P = .29) and 0.54 ± 0.03 for SOFA↑ ≥ 2 (P = .29). Adding purulent tracheal secretions and leukocytosis to SOFA↑ ≥ 2 (SOFA model) increased AUROC to 0.65 ± 0.03 (P < .001). Adding catecholamine use to CPIS (CPIS model) increased AUROC only slightly, to 0.57 ± 0.03. The probabilities predicted by the SOFA model were reliable, especially when high or low. CONCLUSIONS: A clinical scoring system including at least SOFA↑ ≥ 2 increase barely improved ICU-acquired pneumonia prediction in subjects after cardiothoracic surgery.

Factors predicting non-ventilated hospital-acquired pneumonia: systematic review and meta-analysis.

BACKGROUND: Hospital-acquired pneumonia (HAP) results in approximately 15-20% of all infections in hospitals, with more than two-thirds being in patients not using mechanical ventilation. The incidence of non-ventilated hospital-acquired pneumonia (NVHAP) is increasing, and it is associated with a longer length of stay, the need for intensive care unit hospitalization and mechanical ventilation use, and higher mortality. AIM: To identify, quantify, and summarize predictive factors for NVHAP in adult patients admitted to non-intensive care units as determined by previous observational studies. METHODS: PubMed, Embase, Scopus, and LILACS were systematically searched. Case-control and cohort studies were included, and a meta-analysis was performed for all factors studied more than once. National Institute of Health assessment tools were applied to assess the quality of the studies. FINDINGS: Thirty-eight articles showing 204 predictive factors were included. A meta-analysis was performed for 58 factors, 32 of which were significantly associated with NVHAP. When the sensitivity analysis was performed without poor-quality studies, 24 factors remained associated with NVHAP. CONCLUSION: Although there is a lack of good-quality studies to establish predictive factors for NVHAP, the results of this study showed 24 factors associated with the development of this infectious complication. Knowledge of the significant predictive factors for NVHAP will enable the identification of patients most likely to develop it.

Diagnosis Value of Procalcitonin Variation on Early Pneumonia after Adult Cardiac Surgery.

BACKGROUND: Postoperative pneumonia (PP) is a complication after cardiac surgery. This study aimed to investigate the ability of procalcitonin (PCT) variation to diagnose postoperative pneumonia. METHOD: In this prospective observational study, patients with PP and age- and sex-matched cases in our center from October 10, 2020, to January 31, 2021, were included. Patients diagnosed with PP in this study met both clinical and microbiological diagnostic criteria. Blood samples were collected in all patients from the first postoperative day (POD1) to POD5 to measure PCT, white blood cells (WBCs), and C-reactive protein (CRP). PCT variation was calculated by the equation: (PCTdelayed - PCTPOD1)/PCTPOD1. The receiver operating characteristic and area under the curve (AUC) analyses were used to evaluate the diagnostic performance of different biomarkers. RESULTS: Our study enrolled 272 patients, including 24 patients with PP and 248 age- and sex-matched cases. From POD1 to POD5, the absolute value of PCT showed diagnostic significance for pneumonia (P < .05), WBC showed no differences, and CRP had no diagnostic value until POD4. Furthermore, PCT variation showed the best diagnostic value among those biomarkers (AUC 0.84, 95% confidence interval [CI] 0.71, 0.91). Multivariable logistic regression showed that PCT variation on POD2 had significant value to predict PP (odds ratio 5.602, 95% CI 2.178, 14.409, P < .01). CONCLUSION: Compared with PCT level, WBC count, and CRP level, PCT variation had the best diagnostic value in predicting PP.

Using NSQIP Data to Reduce Institutional Postoperative Pneumonia Rates in Non-ICU Patients: A Plan-Do-Study-Act Approach.

BACKGROUND: The American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) is a program designed to measure and improve surgical care quality. In 2015, the study institution formed a multidisciplinary team to address the poor adult postoperative pneumonia performance (worst decile). STUDY DESIGN: The study institution is a 450+ bed tertiary care center that performs 12,000+ surgical procedures annually. From January 2016 to December 2019, the institution abstracted surgical cases and assigned postoperative pneumonia as a complication per the NSQIP operations manual. Using a plan-do-study-act approach, a multidisciplinary postoperative pneumonia prevention team implemented initiatives regarding incentive spirometry education, anesthetic optimization, early mobility, and oral care. The team measured the initiatives' success by analyzing semiannual reports (SAR) provided by the ACS NSQIP and regional adjusted percentile rankings provided by the Georgia Surgical Quality Collaborative (GSQC). RESULTS: The 2015 SAR postoperative pneumonia rate was 4.20% (odds ratio [OR] 3.86, confidence interval [CI] 2.92-5.11). After project initiation, the postoperative pneumonia rates decreased for all NSQIP cases, from 2.51% (OR 2.67, CI 1.89-3.77) in 2016 to 2.08% (OR 2.61, CI 1.82-3.74) in 2017, to 0.85% (OR 1.10, CI 0.69-1.75) in 2018, and then increased slightly to 1.14% (OR 1.27, CI 0.84-1.92) in 2019. The institution's adjusted percentile regional rank of participating regional ACS NSQIP hospitals' postoperative pneumonia rate improved from 14/14 (July 2015-June 2016) to 6/14 (July 2018-June 2019). CONCLUSIONS: The multidisciplinary postoperative pneumonia prevention team successfully decreased the postoperative pneumonia rate, therefore improving surgical patients' outcomes. Furthermore, this quality improvement project also saved valuable revenue for the hospital.

Nutritional risk screening score as an independent predictor of nonventilator hospital-acquired pneumonia: a cohort study of 67,280 patients.

BACKGROUND: Currently, the association of nutritional risk screening score with the development of nonventilator hospital-acquired pneumonia (NV-HAP) is unknown. This study investigated whether nutritional risk screening score is an independent predictor of NV-HAP. METHODS: This retrospective cohort study was conducted between September 2017 and June 2020 in a tertiary hospital in China. The tool of Nutritional Risk Screening 2002 (NRS-2002) was used for nutritional risk screening. A total score of ≥3 indicated a patient was "at nutritional risk." Logistic regression was applied to explore the association between the NRS score and NV-HAP. RESULTS: A total of 67,280 unique patients were included in the study. The incidence of NV-HAP in the cohort for the NRS < 3 and ≥ 3 NRS group was 0.4% (232/62702) and 2.6% (121/4578), respectively. In a multivariable logistic regression model adjusted for all of the covariates, per 1-point increase in the NRS score was associated with a 30% higher risk of NV-HAP (OR = 1.30; 95%CI:1.19-1.43). Similarly, patients with NRS score ≥ 3 had a higher risk of NV-HAP with an odds ratio (OR) of 2.06 (confidence interval (CI): 1.58-2.70) than those with NRS score < 3. Subgroup analyses indicated that the association between the NRS score and the risk of NV-HAP was similar for most strata. Furthermore, the interaction analyses revealed no interactive role in the association between NRS score and NV-HAP. CONCLUSION: NRS score is an independent predictor of NV-HAP, irrespective of the patient's characteristics. NRS-2002 has the potential as a convenient tool for risk stratification of adult hospitalized patients with different NV-HAP risks.

Headspace analyses using multi-capillary column-ion mobility spectrometry allow rapid pathogen differentiation in hospital-acquired pneumonia relevant bacteria.

BACKGROUND: Hospital-acquired pneumonia (HAP) is a common problem in intensive care medicine and the patient outcome depends on the fast beginning of adequate antibiotic therapy. Until today pathogen identification is performed using conventional microbiological methods with turnaround times of at least 24 h for the first results. It was the aim of this study to investigate the potential of headspace analyses detecting bacterial species-specific patterns of volatile organic compounds (VOCs) for the rapid differentiation of HAP-relevant bacteria. METHODS: Eleven HAP-relevant bacteria (Acinetobacter baumanii, Acinetobacter pittii, Citrobacter freundii, Enterobacter cloacae, Escherichia coli, Klebsiella oxytoca, Klebsiella pneumoniae, Pseudomonas aeruginosa, Proteus mirabilis, Staphylococcus aureus, Serratia marcescens) were each grown for 6 hours in Lysogeny Broth and the headspace over the grown cultures was investigated using multi-capillary column-ion mobility spectrometry (MCC-IMS) to detect differences in the VOC composition between the bacteria in the panel. Peak areas with changing signal intensities were statistically analysed, including significance testing using one-way ANOVA or Kruskal-Wallis test (p < 0.05). RESULTS: 30 VOC signals (23 in the positive ion mode and 7 in the negative ion mode of the MCC-IMS) showed statistically significant differences in at least one of the investigated bacteria. The VOC patterns of the bacteria within the HAP panel differed substantially and allowed species differentiation. CONCLUSIONS: MCC-IMS headspace analyses allow differentiation of bacteria within HAP-relevant panel after 6 h of incubation in a complex fluid growth medium. The method has the potential to be developed towards a feasible point-of-care diagnostic tool for pathogen differentiation on HAP.

Extra-pulmonary complications of 45 critically ill patients with COVID-19 in Yichang, Hubei province, China: A single-centered, retrospective, observation study.

ABSTRACT: Mortality of critically ill patients with coronavirus disease 2019 (COVID-19) was high. Aims to examine whether time from symptoms onset to intensive care unit (ICU) admission affects incidence of extra-pulmonary complications and prognosis in order to provide a new insight for reducing the mortality. A single-centered, retrospective, observational study investigated 45 critically ill patients with COVID-19 hospitalized in ICU of The Third People's Hospital of Yichang from January 17 to March 29, 2020. Patients were divided into 2 groups according to time from symptoms onset to ICU admission (>7 and ≤7 days) and into 2 groups according to prognosis (survivors and non-survivors). Epidemiological, clinical, laboratory, radiological characteristics and treatment data were studied. Compared with patients who admitted to the ICU since symptoms onset ≤7 days (55.6%), patients who admitted to the ICU since symptoms onset >7 days (44.4%) were more likely to have extra-pulmonary complications (19 [95.0%] vs 16 [64.0%], P = .034), including acute kidney injury, cardiac injury, acute heart failure, liver dysfunction, gastrointestinal hemorrhage, hyperamylasemia, and hypernatremia. The incidence rates of acute respiratory distress syndrome, pneumothorax, and hospital-acquired pneumonia had no difference between the 2 groups. Except activated partial thromboplastin and Na+ concentration, the laboratory findings were worse in group of time from symptoms onset to ICU admission >7 days. There was no difference in mortality between the 2 groups. Of the 45 cases in the ICU, 19 (42.2%) were non-survivors, and 16 (35.6%) were with hospital-acquired pneumonia. Among these non-survivors, hospital-acquired pneumonia was up to 12 (63.2%) besides higher incidence of extra-pulmonary complications. However, hospital-acquired pneumonia occurred in only 4 (15.4%) survivors. Critically ill patients with COVID-19 who admitted to ICU at once might get benefit from intensive care via lower rate of extra-pulmonary complications.

Polymerase-chain reaction testing to prevent hospital-acquired severe acute respiratory syndrome coronavirus 2 infection in Shinjuku, an epicenter in Tokyo: The Tokyo Women's Medical University model.

Hospital-acquired severe acute respiratory virus coronavirus 2 (SARS-CoV-2) infection is a healthcare challenge. We hypothesized that polymerase chain reaction testing of symptomatic triaged outpatients and all inpatients before hospitalization in Shinjuku, a coronavirus disease 2019 (COVID-19) epicenter in Tokyo, using the Tokyo Women's Medical University (TMWU) model would be feasible and efficient at preventing COVID-19. This retrospective study enrolled 2981 patients from March to May 2020. The prevalence of SARS-CoV-2 infection was 1.81% (95% credible interval [CI]: 0.95-3.47%) in triaged symptomatic outpatients, 0.04% (95% CI: 0.0002-0.2%) in scheduled asymptomatic inpatients, 3.78% (95% CI: 1.82-7.26%) in emergency inpatients, and 2.4% (95% CI: 1.49-3.82%) in symptomatic patients. There were no cases of hospital-acquired SARS-CoV-2 infection. This shows that the TWMU model could prevent hospital-acquired SARS-CoV-2 infection and is feasible and effective in reducing the impact of SARS-CoV-2 infection in the hospitals.

How accurately is hospital acquired pneumonia documented for the correct assignment of a hospital acquired complication (HAC)?

BACKGROUND: In 2016, the Australian Commission on Safety and Quality in Healthcare (ACSQHC) released a list of 16 categories of potentially preventable, high impact hospital-acquired complications (HAC) identified by using administrative coded data (ACD). An important category are hospital-acquired infections (HAI). Within this category, hospital-acquired pneumonia (HAP) is among the most frequent complications documented. There are no published studies concerning the current ACSQHC approach to HAI surveillance using ACD and no pneumonia-specific ACD studies reported from Australia. Published work indicates that ACD detection of HAP has low a sensitivity and positive predictive value (PPV). The current study was designed to examine whether coders correctly reflected the documentation of HAP that was present in the medical record and also evaluated the medical documentation that was present. METHODS: One hundred patients with ACD encoded HAP were selected for review, drawn from admissions to 2 Hunter New England Health hospitals during 2017. Patient records and the eMR were reviewed by two medical officers to assess medical and radiological documentation of pneumonia. The district coding manager reviewed the accuracy of coding of a subset of 23 cases where medical review had not located documented evidence of HAP. RESULTS: Of the 100 reviewed cases, the median patient age was 75 years (range 0-95 years) with 3% under 16 years of age. Twenty one were intensive care-associated of which 13 were associated with ventilation. In 23 cases the documentation was disputed and a secondary review took place - the coding manager confirmed coding changes in 14 of these 23 cases. CONCLUSIONS: This study found that administrative coded data of HAP, utilizing the ACSQHC method reliably reflected the available documentation with a PPV of 86% (95% binomial exact confidence interval 77-92%), much higher than documented by previous ACD studies. The actual documentation of pneumonia by medical staff frequently used the non-specific term 'lower respiratory infection (LRTI)' which we recommend to be avoided. Radiological confirmation was absent in one third of cases. We recommend the adoption of a medical note template checklist for HAP to prompt clinicians with the accepted diagnostic criteria. We also recommend documenting a reason as to why any antibiotic has been commenced in a hospitalized patient in accord with the ACSQHC Antimicrobial Stewardship Clinical Care Standard.

Three Risk Stratification Tools and Postoperative Pneumonia After Noncardiothoracic Surgery.

BACKGROUND: Postoperative in-hospital pneumonia is a serious complication. This study aims to investigate the association between 3 preoperative stratification tools (American Society of Anesthesiologists Physical Status [ASA-PS] score, Charlson Comorbidity Index [CCI], and Rockwood Frailty Deficit Index [FI]) and risk for postoperative pneumonia. METHODS: We identified adult patients who developed postoperative pneumonia following noncardiothoracic surgery under general anesthesia, between January 1, 2016 and December 31, 2017. Patients with postoperative pneumonia were 1:1 matched to control subjects based on age, sex, and the exact type of operations. Medical records were reviewed to identify variables that may be associated with risk for developing postoperative pneumonia. Analyses adjusted for clinical characteristics were performed using the conditional logistic regression, taking into account 1:1 matched set case-control study design. RESULTS: We identified 211 cases of postoperative pneumonia, and all 3 tested stratification tools were associated with increased risk: ASA-PS (after all adjustments of American Society of Anesthesiologists (ASA) III, odds ratio 4.17 [95% confidence interval 1.74-10.01]; ASA > III 24.03 [6.54-88.32]), CCI (CCI values > 3, 1.29 [1.02-1.63] per unit CCI score), and frail FI score 3.25 (1.45-7.27). Because of incomplete intake documentation, the FI could not be calculated in 57 (13.5%) patients, but these "unknown frailty" patients were also at increased risk for postoperative pneumonia, 3.15 (1.29-7.72). DISCUSSION: Three commonly used stratification indices (ASA-PS score, CCI, and FI) were associated with increased risk for postoperative pneumonia. Patients unable to complete intake form to calculate the FI were also at increased risk.

Hospital-acquired and ventilator-associated pneumonia: Diagnosis, management, and prevention.

Hospital-acquired pneumonia (HAP) and ventilator-associated pneumonia (VAP) cause significant inpatient morbidity and mortality. They are especially challenging to diagnose promptly in the intensive care unit because a plethora of other causes can contribute to clinical decline in complex, critically ill patients. The authors describe the diagnosis, management, and prevention of these diseases based on current guidelines and recent evidence.

Disease burden and prognostic factors for clinical failure in elderly community acquired pneumonia patients.

BACKGROUND: The study was to evaluate initial antimicrobial regimen and clinical outcomes and to explore risk factors for clinical failure (CF) in elderly patients with community-acquired pneumonia (CAP). METHODS: 3011 hospitalized elderly patients were enrolled from 13 national teaching hospitals between January 1, 2014 and December 31, 2014 initiated by the CAP-China network. Risk factors for CF were screened by multivariable logistic regression analysis. RESULTS: The incidence of CF in elderly CAP patients was 13.1%. CF patients were older, longer hospital stays and higher treatment costs than clinical success (CS) patients. The CF patients were more prone to present hyperglycemia, hyponatremia, hypoproteinemia, pleural effusion, respiratory failure and cardiovascular events. Inappropriate initial antimicrobial regimens in CF group were significantly higher than CS group. Undertreatment, CURB-65, PH < 7.3, PaO2/FiO2 < 200 mmHg, sodium < 130 mmol/L, healthcare-associated pneumonia, white blood cells > 10,000/mm3, pleural effusion and congestive heart failure were independent risk factors for CF in multivariable logistic regression analysis. Male and bronchiectasis were protective factors. CONCLUSIONS: Discordant therapy was a cause of CF. Early accurate detection and management of prevention to potential causes is likely to improve clinical outcomes in elderly patients CAP. TRIAL REGISTRATION: A Retrospective Study on Hospitalized Patients With Community-acquired Pneumonia in China (CAP-China) (RSCAP-China), NCT02489578. Registered 16 March 2015, https://register.clinicaltrials.gov/prs/app/action/SelectProtocol?sid=S0005E5S&selectaction=Edit&uid=U0000GWC&ts=2&cx=1bnotb.

Hospital-acquired SARS-CoV-2 pneumonia in a person living with HIV.

We report the case of a 38 year-old man living with well-controlled HIV on antiretroviral therapy who developed cerebellar symptoms and was admitted to hospital for management of an intraventricular cryptococcoma. During his hospital stay he contracted SARS CoV-2 infection within the hospital setting with a fatal outcome.

Implementation and evaluation of a care bundle for prevention of non-ventilator-associated hospital-acquired pneumonia (nvHAP) - a mixed-methods study protocol for a hybrid type 2 effectiveness-implementation trial.

BACKGROUND: Hospital acquired pneumonia (HAP) is divided in two distinct groups, ventilator-associated pneumonia (VAP) and non-ventilator-associated HAP (nvHAP). Although nvHAP occurs more frequently than VAP and results in similar mortality and costs, prevention guidelines and prevention focus almost exclusively on VAP. Scientific evidence about nvHAP prevention and its implementation is scarce. Therefore, we designed a mixed-methods hybrid type 2 effectiveness-implementation study to investigate both the effectiveness and implementation of a newly developed nvHAP prevention bundle. METHODS: This single-centre project at the 950-bed University Hospital Zurich (UHZ) will engage the wards of nine departments with substantial nvHAP rates. The nvHAP bundle consists of five primary prevention measures: 1) oral care, 2) prevention of dysphagia-related aspiration, 3) mobilization, 4) stopping unnecessary proton pump inhibitors, and, 5) respiratory therapy. Implementation includes the engagement of department-level implementation teams, who sustain the 'core' intervention components of education, training, and environmental restructuring and tailor the implementation strategy to local needs. Both effectiveness and implementation outcomes will be assessed using mixed-methods. As a primary outcome, nvHAP incidence rates will be analysed by Poisson regression models to compare incidence rates before, during, and after the implementation phases (on the hospital and department level). Additionally, the association between process indicators and nvHAP incidence rates will be analysed using longitudinal Poisson regression models. A longitudinal, qualitative study and formative evaluation based on interviews, focus groups, and observations identifies supporting or hindering factors for implementation success in participating departments dynamically over time. This accumulating implementation experience will be constantly fed back to the implementation teams and thus, represents an active implementation element. DISCUSSION: This comprehensive hybrid mixed-methods study is designed to both, measure the effectiveness of a new nvHAP prevention bundle and multifaceted implementation strategy, while also providing insights into how and why it worked or failed. The results of this study may contribute substantially to advancing knowledge and patient safety in the area of a rediscovered healthcare-associated infection - nvHAP. TRIAL REGISTRATION: ClinicalTrials.gov : NCT03361085 . Registered December 2017.

Coronavirus disease 2019 (COVID-19): The right clinical information, right where it's needed

A potentially severe acute respiratory infection caused by the novel coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).[1] The clinical presentation is generally that of a respiratory infection with a symptom severity ranging from a mild common cold-like illness, to a severe viral pneumonia leading to acute respiratory distress syndrome that is potentially fatal. Characteristic symptoms include fever, cough, and dyspnea, although some patients may be asymptomatic. Complications of severe disease include, but are not limited to, multi-organ failure, septic shock, and blood clots.