Immunogenicity and safety of Mebella™ vaccine developed by Human Biologicals Institute in a Phase II/III, randomized, multicentric, non-inferiority study.

BACKGROUND: The goal of 'Measles and Rubella Strategic Framework 2021-2030' is to make "A world free from measles and rubella". To be a part of this journey, Human Biologicals Institute has developed Mebella™ vaccine, which is a lyophilized Measles and Rubella (Live) vaccine. A randomized, single blind, comparative, multicenter Phase II/III trial was conducted to compare the immunogenicity and safety of Mebella™ vaccine with MR-VAC® vaccine in healthy subjects. METHODS: A total of 888 subjects were enrolled in four age groups (222 subjects in each group) of 18 years to 49 years; 2 years to below 18 years; 12 months to below 24 months; and 9 months to below 12 months of age. The subjects were randomized in 2:1 ratio to receive single dose of either Mebella™ vaccine of Human Biologicals Institute or MR-VAC® vaccine. Immunogenicity was assessed at 42 days after the vaccination and was compared between the vaccine arms in each group. Safety was also assessed and compared between the vaccine arms during the study period. RESULTS: A total of 875 subjects completed the study out of 888 enrolled subjects. The seroprotection rates, seroconversion rates, and geometric mean titres for both Measles and Rubella components of Mebella™ vaccine were found to be comparable and non-inferior to the MR-VAC® vaccine after 42 days of vaccination. Injection site pain was the most common local adverse event reported whereas fever was the only systemic adverse event reported in both the vaccine arms. No serious adverse event was reported. CONCLUSION: It was concluded from the study results that the test vaccine, Mebella™, was immunogenic and well tolerated and was non-inferior to the comparator vaccine, MR-VAC®, when administered to healthy subjects of 9 months to 49 years of age. Clinical Trial Registry of India Identifier: CTRI/2020/07/026930.

Immunogenicity and safety of HavisureTM vaccine developed by Human Biologicals Institute in healthy subjects of 12 months to 49 years of age: A phase II/III, randomized, single blind, non-inferiority study.

BACKGROUND: Hepatitis A is an inflammation of the liver caused by the hepatitis A virus (HAV). It is transmitted mainly because of poor personal hygiene via the faecal/oral route through ingestion of contaminated food or water or through the direct contact with an infectious person. Though most of the infected individuals recover from the infection, a few may develop fatal fulminant hepatitis. In this randomized, multicenter study, immunogenicity and safety of Havisure™ vaccine of Human Biologicals Institute was compared with Havrix® vaccine. METHODS: The study was carried out in 528 eligible healthy subjects, in two age groups across eight centres in India. Group A included subjects of 19-49 years and Group B subjects of 12 months to below 19 years of age. All subjects received two doses of either Havisure™ vaccine or Havrix® vaccine as per randomization at six months interval. Blood samples for antibody titre estimation were collected before vaccination and 4-6 weeks after 2nd dose of vaccination. Immunogenicity was assessed by estimating seroconversion rate, seroprotection rate, and geometric mean titres of antibodies. Safety was evaluated by collection and analysis of data on solicited and unsolicited adverse events. RESULTS: Of 528 enrolled subjects, 493 subjects completed the study. There was 100% seroconversion and seroprotection in both the vaccine arms. There was no statistical difference in the geometric mean titres between the two vaccine arms. Pain and swelling at the site of injection were the most common local adverse events whereas fever and headache were the most common systemic adverse events observed in both vaccine arms. No serious adverse event was reported in the study. CONCLUSION: The study results indicate that the Havisure™ vaccine is immunogenic and safe when administered to healthy subjects of 12 months to 49 years of age, and is non-inferior to Havrix® Vaccine.

Augmented Reality Demonstration Survey Results From a Veteran Affairs Medical Center.

Background: Augmented reality (AR) has a wide range of potential applications to enhance health care. Understanding how the introduction of a new technology may impact employees is essential for overall health care system success. Methods: Survey responses were obtained before and after a health care-focused interactive AR demonstration at a US Department of Veterans Affairs (VA) medical center. Data were assessed with descriptive statistics, Wilcoxon signed rank matched pairs test, pooled t test, and analysis of variance. Results: A total of 166 individuals participated in the demonstration and survey. Statistically significant improvements were seen after the use of the new AR technology in each of the categories assessed using a 5-point Likert scale. Scores for perceptions of institutional innovativeness increased from 3.4 to 4.5 (a 22% increase; P < .001); employee excitement about the VA increased from 3.7 to 4.3 (a 12% increase; P < .001); and employee likelihood to continue working at VA increased from 4.2 to 4.5 (a 6% increase; P < .001). Subgroup analysis demonstrated statistically significant differences by employee veteran status, VA tenure, and sex. Respondents felt strongly that this type of work will positively impact health care and that the VA should continue these efforts. Conclusions: An AR demonstration significantly increased employee excitement and intention to continue employment at the VA and provided valuable insights about the most impactful uses of AR in health care.

Effect of Dietary Amino Acids L-Arginine and Lysine on Implant Osseointegration.

Background: Low protein diets have been linked to decreased bone strength in humans. Arginine and lysine can help improve the healing process and stimulate growth factors. Aim: To evaluate if dietary arginine and lysine combination aids in reducing the time frame for osseo-integration process and bone formation in animal models. Materials and Methods: Controls (Group I) and Experimental (Group II) consisted of twelve New Zealand rabbits. Animals in the experimental group were fed a conventional pellet food, water, and the amino acids L-Lysine and L-Arginine (Biovea, USA), whereas those in the control group were offered a standard diet. In both groups of animals, titanium implants measuring 2.5mm* 6mm were implanted in each tibial osteotomy. At the end of two weeks, four weeks, and eight weeks, the animals were euthanized. The tibial bone was removed and preserved in 1% formalin. The samples were analysed histologically for presence or absence of Necrosis, presence or absence of clot formation, Vascularization, Fibroblast, Osteoblasts and Osteoid Bone growth. Results: Histological outcomes on vascularization, fibroblasts, osteoblasts, osteoid bone growth inferred no significant variation between the control and experimental groups after 8 weeks (P>.05). Conclusion: Vascularity, clot organisation, osteoblasts, fibroblasts, and osteoid bone production in the protein fed experimental group animals were better in initial stages of healing when compared to control groups.

Data acquisition process for VA and non-VA emergency department and hospital utilization by veterans with spinal cord injury and disorders in California using VA and state data.

Context: To identify VA and non-VA Emergency Department (ED) and hospital utilization by veterans with spinal cord injury and disorders (SCI/D) in California.Design: Retrospective cohort study.Setting: VA and Office of Statewide Health Planning and Development (OSHPD) in California.Participants: Total 300 veterans admitted to the study VA SCI/D Center for initial rehabilitations from 01/01/1999 through 08/17/2014.Interventions: N/A.Outcome Measures: Individual-level ED visits and hospitalizations during the first-year post-rehabilitation.Results: Among 145 veterans for whom ED visit data available, 168 ED visits were identified: 94 (55.2%) at non-VA EDs and 74 (44.8%) at the VA ED, with a mean of 1.16 (±2.21) ED visit/person. Seventy-seven (53.1%) veterans did not visit any ED. Of 68 (46.9%) veterans with ≥ one ED visit, 20 (29.4%) visited the VA ED only, 34 (50.0%) visited non-VA EDs only, and 14 (20.6%) visited both VA and non-VA EDs. Among 212 Veterans for whom hospitalization data were available, 247 hospitalizations were identified: 82 (33.2%) non-VA hospitalizations and 165 (66.8%) VA hospitalization with a mean of 1.17 (±1.62) hospitalizations/person. One hundred-seven (50.5%) veterans had no hospitalizations. Of 105 veterans with ≥ one hospitalization, 58 (55.2%) were hospitalized at the study VA hospital, 15 (14.3%) at a non-VA hospital, and 32 (30.5%) at both VA and non-VA hospitals.Conclusion: Non-VA ED and hospital usage among veterans with SCI/D occurred frequently. The acquisition of non-VA healthcare data managed by state agencies is vital to accurately and comprehensively evaluate needs and utilization rates among veteran populations.

Risk Factors for Readmissions After Total Joint Replacement: A Meta-Analysis.

¼: We performed a systematic review and meta-analysis of predictive modeling studies examining the risk of readmission after total hip arthroplasty (THA) and total knee arthroplasty (TKA) in order to synthesize key risk factors and evaluate their pooled effects. Our analysis entailed 15 compliant studies for qualitative review and 17 compliant studies for quantitative meta-analysis. ¼: A qualitative review of 15 predictive modeling studies highlighted 5 key risk factors for risk of readmission after THA and/or TKA: age, length of stay, readmission reduction policy, use of peripheral nerve block, and type of joint replacement procedure. ¼: A meta-analysis of 17 studies unveiled 3 significant risk factors: discharge to a skilled nursing facility rather than to home (approximately 61% higher risk), surgery at a low- or medium-procedure-volume hospital (approximately 26% higher risk), and the presence of patient obesity (approximately 34% higher risk). We demonstrated clinically meaningful relationships between these factors and moderator variables of procedure type, source of data used for model-building, and the proportion of male patients in the cohort. ¼: We found that many studies did not adhere to gold-standard criteria for reporting and study construction based on the PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) and NOS (Newcastle-Ottawa Scale) methodologies. ¼: We recommend that these risk factors be considered in clinical practice and future work alike as they relate to surgical, discharge, and care decision-making. Future work should also prioritize greater observance of gold-standard reporting criteria for predictive models.

Safety and immunogenicity of inactivated hepatitis-A vaccine developed by Human Biologicals Institute in two age groups of healthy subjects: A phase I open label study.

BACKGROUND: Hepatitis-A is an acute viral infection of the liver. Hepatitis-A virus has worldwide spread and is endemic in India. Though the disease is self-limiting in most cases, outbreaks are reported frequently from both developing and developed countries of the world. Severity and fatality occur more among infected symptomatic adults. The infection can be prevented with proper and timely immunization. This phase I, single arm, open label, multicenter trial was designed to assess the safety and immunogenicity of the inactivated hepatitis-A vaccine developed by Human Biologicals Institute when administered in a single dose in two age groups of healthy subjects. METHODS: This study was carried out in 55 subjects in two healthy age groups at two centers in India. Group A included subjects of 19-49 years and group B subjects of 12-18 years of age. Enrolled subjects received a single dose of inactivated hepatitis A vaccine. Blood samples were collected at baseline and 4-6 weeks after vaccination. Safety was assessed by collection and analysis of data on solicited and unsolicited adverse events and immunogenicity was assessed by estimating the seroconversion rate, seroprotection rate and the geometric mean titres of antibodies. RESULTS: Among the 55 subjects enrolled, 15 reported adverse events. No serious adverse event was reported. Pain at the injection site was the lone local adverse event. Systemic adverse events reported in Group A were: fatigue, headache, diarrhoea, fever, anorexia, nausea and upper respiratory tract infection, whereas there was no systemic event reported in Group B. There was 100% seroconversion and seroprotection and significant rise in antibody titre levels were observed in both the groups post vaccination. CONCLUSIONS: This study found HBI inactivated hepatitis-A vaccine to be safe and highly immunogenic when administered as a single dose in adolescent and adult subjects.

Association of mortality and aspirin prescription for COVID-19 patients at the Veterans Health Administration.

There is growing evidence that thrombotic and inflammatory pathways contribute to the severity of COVID-19. Common medications such as aspirin, that mitigate these pathways, may decrease COVID-19 mortality. This retrospective assessment was designed to quantify the correlation between pre-diagnosis aspirin and mortality for COVID-19 positive patients in our care. Data from the Veterans Health Administration national electronic health record database was utilized for the evaluation. Veterans from across the country with a first positive COVID-19 polymerase chain reaction lab result were included in the evaluation which comprised 35,370 patients from March 2, 2020 to September 13, 2020 for the 14-day mortality cohort and 32,836 patients from March 2, 2020 to August 28, 2020 for the 30-day mortality cohort. Patients were matched via propensity scores and the odds of mortality were then compared. Among COVID-19 positive Veterans, preexisting aspirin prescription was associated with a statistically and clinically significant decrease in overall mortality at 14-days (OR 0.38, 95% CI 0.32-0.46) and at 30-days (OR 0.38, 95% CI 0.33-0.45), cutting the odds of mortality by more than half. Findings demonstrated that pre-diagnosis aspirin prescription was strongly associated with decreased mortality rates for Veterans diagnosed with COVID-19. Prospective evaluation is required to more completely assess this correlation and its implications for patient care.

Association of Mortality and Aspirin Prescription for COVID-19 Patients at the Veterans Health Administration

There is growing evidence that thrombotic and inflammatory pathways contribute to the severity of COVID-19. Common medications such as aspirin, that mitigate these pathways, may decrease COVID-19 mortality. This assessment was designed to quantify the correlation between aspirin and mortality for COVID-19 positive patients in our care. Data from the Veterans Health Administration national electronic health record database was utilized for the evaluation. Veterans from across the country with a first positive COVID-19 polymerase chain reaction lab result were included in the evaluation which comprised 28,350 patients from March 2, 2020 to September 13, 2020 for the 14-day mortality cohort and 26,346 patients from March 2, 2020 to August 28, 2020 for the 30-day mortality cohort. Patients were matched via propensity scores and the odds of mortality were then compared. Among COVID-19 positive Veterans, preexisting aspirin prescription was associated with a statistically and clinically significant decrease in overall mortality at 14-days (OR 0.38, 95% CI 0.32-0.46) and at 30-days (OR 0.38, 95% CI 0.33-0.45), cutting the odds of mortality by more than half. Findings demonstrated that pre-diagnosis aspirin prescription was strongly associated with decreased mortality rates for Veterans diagnosed with COVID-19. Prospective evaluation is required to more completely assess this correlation and its implications for patient care.

Risk Factors for Readmission After Knee Arthroplasty Based on Predictive Models: A Systematic Review.

BACKGROUND: An increase in the aging yet active US population will continue to make total knee arthroplasty (TKA) procedures routine in the coming decades. For such joint procedures, the Centers for Medicare and Medicaid Services introduced programs such as the Comprehensive Care for Joint Replacement to emphasize accountable and efficient transitions of care. Accordingly, many studies have proposed models using risk factors for predicting readmissions after the procedure. We performed a systematic review of TKA literature to identify such models and risk factors therein using a reliable appraisal tool for their quality assessment. METHODS: Five databases were searched to identify studies that examined correlations between post-TKA readmission and risk factors using multivariate models. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis methodology and Transparent Reporting of a multivariate prediction model for Individual Prognosis Or Diagnosis criteria established for quality assessment of prognostic studies. RESULTS: Of 29 models in the final selection, 6 models reported performance using a C-statistic, ranging from 0.51 to 0.76, and 2 studies used a validation cohort for assessment. The average 30-day and 90-day readmission rates across the studies were 5.33% and 7.12%, respectively. Three new significant risk factors were discovered. CONCLUSIONS: Current models for TKA readmissions lack in performance measurement and reporting when assessed with established criteria. In addition to using new techniques for better performance, work is needed to build models that follow the systematic process of calibration, external validation, and reporting for pursuing their deployment in clinical settings.

Predictive models for identifying risk of readmission after index hospitalization for hip arthroplasty: A systematic review.

BACKGROUND: An aging United States population profoundly impacts healthcare from both a medical and financial standpoint, especially with an increase in related procedures such as Total Hip Arthroplasty (THA). The Hospital Readmission Reduction Program and Comprehensive Care for Joint Replacement Program incentivize hospitals to decrease post-operative readmissions by correlating reimbursements with smoother care transitions, thereby decreasing hospital burden and improving quantifiable patient outcomes. Many studies have proposed predictive models built upon risk factors for predicting 30-day THA readmissions. QUESTIONS: (1) Are there validated statistical models that predict 30-day readmissions for THA patients when appraised with a standards-based, reliable assessment tool?. (2) Which evidence-based factors are significant and have support across models for predicting risk of 30-day readmissions post-THA? METHODS: Five major electronic databases were searched to identify studies that examined correlations between post-THA readmission and risk factors using multivariate models. We rigorously applied the PRISMA methodology and TRIPOD criteria for assessment of the prognostic studies. RESULTS: We found 26 studies that offered predictive models, of which two presented models tested with validation cohorts. In addition to the many factors grouped into demographic, administrative, and clinical categories, bleeding disorder, higher ASA status, discharge disposition, and functional status appeared to have broad and significant support across the studies. CONCLUSIONS: Reporting of recent predictive models establishing risk factors for 30-day THA readmissions against the current standard could be improved. Aside from building better performing models, more work is needed to follow the thorough process of undergoing calibration, external validation, and integration with existing EHR systems for pursuing their use in clinical settings. There are several risk factors that are significant in multiple models; these factors should be closely examined clinically and leveraged in future risk modeling efforts.

Interfacially Interactive Ternary Silver-Supported Polyaniline/Multiwalled Carbon Nanotube Nanocomposites for Catalytic and Antibacterial Activity.

Herein, a protocol strategy has been designed for the preparation of ternary silver nanoparticles-supported polyaniline multiwalled carbon nanotube (Ag NPs-PANI/MWCNT) nanocomposites with a chemical interaction for catalytic and antibacterial activity. The morphological study confirmed that Ag NPs were immobilized on the surface of PANI, and afterward, Ag NPs-PANI were mixed with the MWCNTs. The X-ray diffraction technique revealed the face-centered cubic structure of Ag NPs, and the X-ray photoelectron spectroscopy study revealed the chemical constituent and signature of π-π* and C-N interactions in the nanocomposites. The ternary Ag NPs-PANI/MWCNTs nanocomposites have the apparent rate of reaction (K app) as 5.4 × 10-3 s-1, higher than binary nanocomposites for catalytic reduction of 4-nitrophenol to 4-aminophenol at room temperature. Antibacterial activity of Ag NPs-PANI/MWCNT nanocomposites is higher against pathogenic bacteria. Thereafter, because of multifold applications of ternary nanocomposites, they have a broad scope in the field of environmental and healthcare sectors.

Combining Structured and Unstructured Data for Predicting Risk of Readmission for Heart Failure Patients.

Researchers have studied many models for predicting the risk of readmission for heart failure over the last decade. Most models have used a parametric statistical approach while a few have ventured into using machine learning methods such as statistical natural language processing. We created three predictive models by combining these two techniques for the cohort of 1,629 patients from six hosptials using structured data along with their 136,963 clinical notes till their index admission, stored in the EMR system over five years. The AUCs for structured and combined models were very close (0.6494 and 0.6447) and that for the unstructured model was 0.5219. The clinical impact of the models using decision curve analysis showed that, at a threshold predicted probability of 0.20, the combined model offered 15%, 30%, and 70% net benefit over its individual counterparts, treat-all, and treat-none strategy respectively.

Using Ensemble Machine Learning Methods for Predicting Risk of Readmission for Heart Failure.

Recently, researchers have been applying many new machine learning techniques for predicting the risk of readmission for heart failure. Combining such techniques through ensemble schemes holds a promise to further harness predictive performance of the resulting models. To that end, we examined two ensemble schemes and applied them to a real world dataset obtained from the EMR systems for 36,245 patients from 117 hospitals across the United States over five years. Both the ensemble schemes provided similar discriminative ability (AUC: 0.70, F1-score: 0.58) that was at least equal to or better than the base models that used a single machine learning method. The clinical impact of the models using decision curve analysis showed that at a threshold predicted probability of 0.40, the ensemble models offered 20% net benefit over the treat-all and treat-none strategies.

Immunogenicity and safety of a liquid Pentavalent (DTwP-Hb-Hib) combination vaccine manufactured by Human Biologicals Institute in 6-8 weeks old healthy infants: A phase III, randomized, single blind, non-inferiority study.

BACKGROUND: A liquid Pentavalent (DTwP-Hb-Hib) combination vaccine, developed by Human Biologicals Institute, underwent a Phase III clinical study in India. In this randomized, single blind, non-inferiority study, the immunogenicity and safety of this Investigational vaccine was compared with Pentavac SD® vaccine in 6-8 weeks old healthy infants. METHODS: A total of 405 healthy infants aged 6-8 weeks old were randomized in 2:1 ratio to receive three doses of either the Investigational liquid Pentavalent (DTwP-Hb-Hib) combination vaccine or Pentavac SD® vaccine at four to six weeks interval. Immunogenicity was compared by estimation of antibody titers before the first dose and 4-6 weeks after the third dose of vaccination. Safety of each vaccine was assessed and compared by collection of data on solicited and unsolicited adverse events throughout the study period. RESULTS: Out of a total of 405 enrolled subjects, 387 subjects completed the study. The seroconversion rates, seroprotection rates and geometric mean titres of the Investigational liquid Pentavalent (DTwP-Hb-Hib) combination vaccine group were found to be comparable and non-inferior to the Pentavac SD® vaccine group at 4-6 weeks after the third dose of vaccination. Pain, erythema and swelling at the site of injection were found to be the most common local adverse events whereas fever, irritability and unusual crying were found to be the most common systemic adverse events in both the vaccine groups. No vaccine related serious adverse event was reported. In this study, both the Investigational vaccine as well as the Comparator vaccine were found to be immunogenic and well tolerated. CONCLUSION: After assessment of the results of the study it was concluded that the Investigational liquid Pentavalent (DTwP-Hb-Hib) combination vaccine developed by Human Biologicals Institute was immunogenic and safe when administered to infants aged 6-8 weeks and was non-inferior in immunogenicity and safety to Pentavac SD® vaccine. Clinical Trial Registry of India Identifier: CTRI/2016/01/006541.

Quantitative Analyses of the Effectiveness of a Newly Designed Preceptor Workshop.

Educational preparation for nurse preceptors helps reduce anxiety and stress in precepting. A quality improvement project was initiated in a large U.S. West Coast federal healthcare system to evaluate an existing training program for preceptors. A new 2-day preceptor workshop was subsequently created to address identified gaps. Results demonstrated statistically significant gains in preceptors' essential knowledge and skills required in precepting, and room for improvement in faculty teaching techniques and course materials.

Autologous platelet-rich fibrin: can it secure a better healing?

OBJECTIVE: The aim of this study was to evaluate the efficacy of platelet-rich fibrin (PRF) in the healing of impacted mandibular third molar (M3) extraction sockets. STUDY DESIGN: This study included 30 patients with bilaterally symmetric impacted M3 (N = 60) requiring transalveolar extraction. All patients were assigned numbers randomly; left-sided M3 patients with odd numbers and right-sided patients with even numbers were categorized into group A (test group), and the other side of the mouth was classified as "group B" (control group). Group A M3 extraction sockets received PRF, whereas group B sockets were closed without PRF. Patients were evaluated for pain and swelling on postoperative days 1, 3, 7, and 14. Bone healing was compared on postoperative weeks 8 and 16. Analysis of variance (ANOVA) and Tukey's multiple comparison tests were applied for statistical analysis. RESULTS: A total of 30 patients, ages 18 to 40 years, participated in this study. The overall postoperative pain score (visual analogue scale [VAS]) and facial swelling percentages were lower for group A compared with group B (P < .05). Early bone healing was also evident on postoperative radiographs obtained at weeks 8 and 16 in group A (P < .001). CONCLUSIONS: The use of autologous PRF aids in earlier and better wound healing in a controlled manner.

Can We Do More With Less While Building Predictive Models? A Study in Parsimony of Risk Models for Predicting Heart Failure Readmissions.

Hospital readmission due to heart failure is a topic of concern for patients and hospitals alike: it is both the most frequent and expensive diagnosis for hospitalization. Therefore, accurate prediction of readmission risk while patients are still in the hospital helps to guide appropriate postdischarge interventions. As our understanding of the disease and the volume of electronic health record data both increase, the number of predictors and model-building time for predicting risk grow rapidly. This suggests a need to use methods for reducing the number of predictors without losing predictive performance. We explored and described three such methods and demonstrated their use by applying them to a real-world dataset consisting of 57 variables from health data of 1210 patients from one hospital system. We compared all models generated from predictor reduction methods against the full, 57-predictor model for predicting risk of 30-day readmissions for patients with heart failure. Our predictive performance, measured by the C-statistic, ranged from 0.630 to 0.840, while model-building time ranged from 10 minutes to 10 hours. Our final model achieved a C-statistic (0.832) comparable to the full model (0.840) in the validation cohort while using only 16 predictors and providing a 66-fold improvement in model-building time.

Predictive models for identifying risk of readmission after index hospitalization for heart failure: A systematic review.

AIMS: Readmission rates for patients with heart failure have consistently remained high over the past two decades. As more electronic data, computing power, and newer statistical techniques become available, data-driven care could be achieved by creating predictive models for adverse outcomes such as readmissions. We therefore aimed to review models for predicting risk of readmission for patients admitted for heart failure. We also aimed to analyze and possibly group the predictors used across the models. METHODS: Major electronic databases were searched to identify studies that examined correlation between readmission for heart failure and risk factors using multivariate models. We rigorously followed the review process using PRISMA methodology and other established criteria for quality assessment of the studies. RESULTS: We did a detailed review of 334 papers and found 25 multivariate predictive models built using data from either health system or trials. A majority of models was built using multiple logistic regression followed by Cox proportional hazards regression. Some newer studies ventured into non-parametric and machine learning methods. Overall predictive accuracy with C-statistics ranged from 0.59 to 0.84. We examined significant predictors across the studies using clinical, administrative, and psychosocial groups. CONCLUSIONS: Complex disease management and correspondingly increasing costs for heart failure are driving innovations in building risk prediction models for readmission. Large volumes of diverse electronic data and new statistical methods have improved the predictive power of the models over the past two decades. More work is needed for calibration, external validation, and deployment of such models for clinical use.