Most Common Statistical Methodologies in Recent Clinical Studies of Community-Acquired Pneumonia

Background: Training new individuals in pneumonia research is imperative to produce a new generation of clinical investigators with the expertise necessary to fill gaps in knowledge. Clinical investigators are often intimidated by their unfamiliarity with statistics. The objective of this study is to define the most common statistical methodologies in recent clinical studies of CAP to inform teaching approaches in the field. Methods: Articles met inclusion criteria if they were clinical research with an emphasis on incidence, epidemiology, or patient outcomes, searchable via PubMed or Google Scholar, published within the timeframe of January 1st 2012 to August 1st 2017, and contained Medical Subject Headings (MeSH) keywords of “pneumonia” and one of the following: “epidemiologic studies”, “health services research”, or “comparative effectiveness research” or search keywords of community-acquired pneumonia” and one of the following: “cohort study”, “observational study”, “prospective study”, “retrospective study”, “clinical trial”, “controlled trial”, or “clinical study”. Descriptive statistics for the most common statistical methods were reported. Results: Thirty articles were included in the analysis. Descriptive statistics most commonly contained within articles were frequency (n=30 [100%]) and percent (n=30 [100%]), along with medians (n=22 [73%]) and interquartile ranges (n=19 [63%]). Most commonly performed analytical statistics were the Chi-squared test (n=20 [67%]), logistic regression (n=18 [60%]), Fisher’s exact test (n=17 [57%]), Wilcoxon rank sum test (n=16 [53%]), T-test (n=13 [43%]), and Cox proportional hazards regression (n=10 [33%]). Conclusions: We identified the most common clinical research tests performed in studies of hospitalized patients with CAP. Junior investigators should become very familiar with these tests early in their research careers

Assessment of Pneumonia Severity Indices as Mortality Predictors

BACKGROUND The leading cause of infectious disease death in the United States is community-acquired pneumonia (CAP). Several pneumonia severity indices exist and are widely used as tools to assist physicians regarding site of care based on risk of death. However, limited data exists that discerns which of the most commonly used severity scores is the best predictor of mortality across multiple time points. The objective of this study is to determine the best mortality predictor at different time points between four of the most commonly used pneumonia severity scores. METHODS This was a secondary analysis of a prospective, multicenter, population-based, observational study of patients hospitalized with CAP in the city of Louisville, KY. The severity indices used were the American Thoracic Society (ATS) criteria, the Pneumonia Severity Index (PSI), the British Thoracic Society criteria (CURB-65), Quick Sepsis-Related Organ Failure Assessment (QSOFA), and direct ICU admission to represent physician discretion. The accuracy, kappa statistic, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated for the ability to predict in-hospital, 30-day, 6-month, and 1-year mortality. 95% confidence intervals for each variable were generated by bootstrapping with random sampling and resampling of the subjects 1000 times. In addition, the area under the curve (AUC) was calculated for each severity score and mortality time point. RESULTS There were 6013 eligible patients included in this analysis with data collected between the years 2014 and 2016. At each time point, the QSOFA had the highest sensitivity and NPV, while the PSI had the highest specificity and PPV. QSOFA had the highest accuracy for in-hospital mortality, 30-day mortality, and 6-month mortality, and the CURB-65 had highest mortality for 1-year mortality. The QSOFA had the highest kappa statistic for in-hospital mortality, the CURB-65 had the highest kappa statistic for 30-day mortality, and the PSI had the highest kappa statistic for 6-month and 1-year mortality. The AUC was highest for the ATS criteria for in-hospital mortality, and was highest for the PSI at the remaining time points. CONCLUSIONS The results of this study show that QSOFA and the PSI are the most reliable severity indices for mortality predictions based on these measures. QSOFA was found, on average, to have the highest accuracy, sensitivity, and NPV. Additionally, PSI was found, on average, to have the highest kappa statistic, specificity, and PPV. The AUC, on average, was best with PSI as the predictor. QSOFA is most capable of making true negative predictions and the PSI is the most capable of making true positive predictions across the four time points

Effectiveness of the Influenza Vaccine in Preventing Hospitalizations of Patients with Influenza Community-Acquired Pneumonia

Introduction: Influenza vaccination is the primary strategy for prevention of influenza infection. Influenza infection can vary from mild or even asymptomatic illness to severe community-acquired pneumonia (CAP). Although many national and international investigators and organizations report annual estimates of influenza vaccine effectiveness for prevention of influenza infection in the community, few studies report estimates for the prevention of hospitalizations due to influenza CAP, the most severe form of the infection. The objective of this study is to determine the effectiveness of the influenza vaccine for prevention of hospitalization in patients with influenza-associated CAP. Methods: This was a test-negative study using data from the first two years of the University of Louisville Pneumonia Study, a prospective, observational study of all hospitalized patients with pneumonia in Louisville, Kentucky from 6/1/2014 – 5/31/2016. Univariate and multivariate logistic models were used to evaluate the association between vaccine status and influenza-associated/non-influenza-associated CAP hospitalization. Unadjusted and adjusted vaccine effectiveness estimates were calculated. Results: A total of 1951 hospitalized patients with CAP were included in the analysis, and 831 (43%) reported having received the influenza vaccination for the influenza season by the time they were hospitalized. A total of 152 (8%) cases of influenza-CAP were confirmed in the study population, with 63 (8%) cases confirmed in vaccinated individuals. The unadjusted vaccine effectiveness was not significant, with a point estimate of 5% (95% CI: -33%, 32%). After adjusting for potential cofounders, vaccine effectiveness was also found to not be significant with a point estimate of 8% (95% CI: -30%, 35%). Conclusions: In conclusion, we found that, over the 2014/2015 and 2015/2016 influenza seasons, influenza vaccine was not effective for prevention of hospitalization with CAP due to influenza. More effective vaccines are necessary to prevent the most serious forms of influenza

Impact of Temperature Relative Humidity and Absolute Humidity on the Incidence of Hospitalizations for Lower Respiratory Tract Infections Due to Influenza, Rhinovirus, and Respiratory Syncytial Virus: Results from Community-Acquired Pneumonia Organization (CAPO) International Cohort Study

Abstract Background: Transmissibility of several etiologies of lower respiratory tract infections (LRTI) may vary based on outdoor climate factors. The objective of this study was to evaluate the impact of outdoor temperature, relative humidity, and absolute humidity on the incidence of hospitalizations for lower respiratory tract infections due to influenza, rhinovirus, and respiratory syncytial virus (RSV). Methods: This was a secondary analysis of an ancillary study of the Community Acquired Pneumonia Organization (CAPO) database. Respiratory viruses were detected using the Luminex xTAG respiratory viral panel. Climate factors were obtained from the National Weather Service. Adjusted Poisson regression models with robust error variance were used to model the incidence of hospitalization with a LRTI due to: 1) influenza, 2) rhinovirus, and 3) RSV (A and/or B), separately. Results: A total of 467 hospitalized patients with LRTI were included in the study; 135 (29%) with influenza, 41 (9%) with rhinovirus, and 27 (6%) with RSV (20 RSV A, 7 RSV B). The average, minimum, and maximum absolute humidity and temperatur e variables were associated with hospitalization due to influenza LRTI, while the relative humidity variables were not. None of the climate variables were associated with hospitalization due to rhinovirus or RSV. Conclusions: This study suggests that outdoor absolute humidity and temperature are associated with hospitalizations due to influenza LRTIs, but not with LRTIs due to rhinovirus or RSV. Understanding factors contributing to the transmission of respiratory viruses may assist in the prediction of future outbreaks and facilitate the development of transmission prevention interventions

Predicting 30-Day Mortality in Hospitalized Patients with Community-Acquired Pneumonia Using Statistical and Machine Learning Approaches

Background: Predicting if a hospitalized patient with community-acquired pneumonia (CAP) will or will not survive after admission to the hospital is important for research purposes as well as for institution of early patient management interventions. Although population-level mortality prediction scores for these patients have been around for many years, novel patient-level algorithms are needed. The objective of this study was to assess several statistical and machine learning models for their ability to predict 30-day mortality in hospitalized patients with CAP. Methods: This was a secondary analysis of the University of Louisville (UofL) Pneumonia Study database. Six different statistical and/or machine learning methods were used to develop patientlevel prediction models for hospitalized patients with CAP. For each model, nine different statistics were calculated to provide measures of the overall performance of the models. Results: A total of 3249 unique hospitalized patients with CAP were enrolled in the study, 2743 were included in the model building (training) dataset, while the remaining 686 were included in the testing dataset. From the full population, death at 30-days post discharge was documented in 458 (13.4%) patients. All models resulted in high variation in the ability to predict survivors and non-survivors at 30 days. Conclusions: In conclusion, this study suggests that accurate patient-level prediction of 30-day mortality in hospitalized patients with CAP is difficult with statistical and machine learning approaches. It will be important to evaluate novel variables and other modeling approaches to better predict poor clinical outcomes in these patients to ensure early and appropriate interventions are instituted

Level of Recall Bias Regarding Pneumococcal Vaccination History among Adults Hospitalized with Community-Acquired Pneumonia: Results from the University of Louisville Pneumonia Study

Background: Recall bias is likely to occur in vaccine effectiveness studies using self-reported vaccination history. The validity of patient-reported vaccination status for adults is not well defined. The objective of this study was to evaluate the validity of self-reported pneumococcal vaccination history among patients hospitalized with community-acquired pneumonia (CAP). Methods: Prospective ancillary study of a population-based observational study of hospitalized patients with CAP in the city of Louisville. To be included in the analysis, patients had to (i) be reached by phone 30-days after discharge from the hospital and (ii) report that they remembered whether or not they received a pneumococcal vaccine in the past five years. The vaccination history was classified as 1) Subjective: patient recollection, or 2) Objective: vaccination records from insurance companies or primary care physicians. Results: A total of 2,787 patients who recalled their vaccination history were included in the analysis. Subjective vaccination history was documented to be inaccurate in 1,023 (37%) patients. Conclusions: Our study indicates that in adult patients, self-reported data regarding pneumococcal vaccination is likely to be inaccurate in one out of three patients. This level of recall bias may incorporate a fatal flaw in vaccine effectiveness studies

Modulation of the virus-receptor interaction by mutations in the V5 loop of feline immunodeficiency virus (FIV) following in vivo escape from neutralising antibody

<b>BACKGROUND:</b> In the acute phase of infection with feline immunodeficiency virus (FIV), the virus targets activated CD4+ T cells by utilising CD134 (OX40) as a primary attachment receptor and CXCR4 as a co-receptor. The nature of the virus-receptor interaction varies between isolates; strains such as GL8 and CPGammer recognise a "complex" determinant on CD134 formed by cysteine-rich domains (CRDs) 1 and 2 of the molecule while strains such as PPR and B2542 require a more "simple" determinant comprising CRD1 only for infection. These differences in receptor recognition manifest as variations in sensitivity to receptor antagonists. In this study, we ask whether the nature of the virus-receptor interaction evolves in vivo.<p></p> <b>RESULTS:</b> Following infection with a homogeneous viral population derived from a pathogenic molecular clone, a quasispecies emerged comprising variants with distinct sensitivities to neutralising antibody and displaying evidence of conversion from a "complex" to a "simple" interaction with CD134. Escape from neutralising antibody was mediated primarily by length and sequence polymorphisms in the V5 region of Env, and these alterations in V5 modulated the virus-receptor interaction as indicated by altered sensitivities to antagonism by both anti-CD134 antibody and soluble CD134.<p></p> <b>CONCLUSIONS:</b> The FIV-receptor interaction evolves under the selective pressure of the host humoral immune response, and the V5 loop contributes to the virus-receptor interaction. Our data are consistent with a model whereby viruses with distinct biological properties are present in early versus late infection and with a shift from a "complex" to a "simple" interaction with CD134 with time post-infection.<p></p&gt

Selective expansion of viral variants following experimental transmission of a reconstituted feline immunodeficiency virus quasispecies

Following long-term infection with virus derived from the pathogenic GL8 molecular clone of feline immunodeficiency virus (FIV), a range of viral variants emerged with distinct modes of interaction with the viral receptors CD134 and CXCR4, and sensitivities to neutralizing antibodies. In order to assess whether this viral diversity would be maintained following subsequent transmission, a synthetic quasispecies was reconstituted comprising molecular clones bearing envs from six viral variants and its replicative capacity compared in vivo with a clonal preparation of the parent virus. Infection with either clonal (Group 1) or diverse (Group 2) challenge viruses, resulted in a reduction in CD4+ lymphocytes and an increase in CD8+ lymphocytes. Proviral loads were similar in both study groups, peaking by 10 weeks post-infection, a higher plateau (set-point) being achieved and maintained in study Group 1. Marked differences in the ability of individual viral variants to replicate were noted in Group 2; those most similar to GL8 achieved higher viral loads while variants such as the chimaeras bearing the B14 and B28 Envs grew less well. The defective replication of these variants was not due to suppression by the humoral immune response as virus neutralising antibodies were not elicited within the study period. Similarly, although potent cellular immune responses were detected against determinants in Env, no qualitative differences were revealed between animals infected with either the clonal or the diverse inocula. However, in vitro studies indicated that the reduced replicative capacity of variants B14 and B28 in vivo was associated with altered interactions between the viruses and the viral receptor and co-receptor. The data suggest that viral variants with GL8-like characteristics have an early, replicative advantage and should provide the focus for future vaccine development

Which women stop smoking during pregnancy and the effect on breastfeeding duration

BACKGROUND: Cigarette smoking during pregnancy increases the risk of adverse pregnancy outcomes and women who quit smoking at this time are able to reduce the risk of low birth weight, preterm labour, spontaneous abortion and perinatal death. This study investigates the socio-demographic characteristics of pregnant women who stop smoking during pregnancy and the association between stopping smoking and breastfeeding duration. METHODS: A 12 month longitudinal study was conducted in two public maternity hospitals in Perth, Australia between mid-September 2002 and mid-July 2003. While in hospital, participating mothers completed a self-administered baseline questionnaire. Follow up telephone interviews were conducted at 4, 10, 16, 22, 32, 40 and 52 weeks. RESULTS: A total of 587 (55%) mothers participated in the study. Two hundred and twenty six (39%) mothers reported smoking prior to pregnancy and 77 (34%) of these stopped smoking during pregnancy. Women who were pregnant for the first time were twice as likely (OR = 2.05; 95% CI 1.047 – 4.03; p < 0.05) to quit smoking as multiparous women. Women who smoked more than 10 cigarettes per day were significantly less likely to quit smoking during pregnancy (OR = 0.36; 95% CI 0.18 – 0.69; p < 0.05). Women who consumed alcohol before pregnancy were three times more likely to quit smoking (OR = 2.58; 95% CI 1.00 – 6.66; p < 0.05). Quitting smoking during pregnancy was significantly associated with breastfeeding for longer than six months (OR = 3.70; 95% CI 1.55 – 8.83; p < 0.05). CONCLUSION: Pregnancy is a time when many women are motivated to quit smoking and providing targeted smoking cessation interventions at this time, which take into account factors predictive of quitting smoking, are more likely to be successful