Combined effect of early diagnosis and treatment on the case fatality risk of COVID-19 in Japan, 2020.

Japanese government initially enforced restrictions on outpatient attendances among febrile individuals suspected of having COVID-19, asking everyone to remain at home for at least 4 days from the onset of fever. This restriction was cancelled on 8 May 2020, and a new antiviral, remdesivir, was approved from 7 May 2020. To investigate how this policy change influenced the prognosis of people with COVID-19, we estimated the case fatality risk as a function of the date of illness onset from April to June 2020. We used an interrupted time-series analysis model with an intervention date of 8 May 2020, and estimated time-dependent case fatality risk by age group. The case fatality risk showed a decreasing trend in all groups, and models were favored accounting for an abrupt causal effect, i.e., immediate decline in fatality risk. The trend was estimated at - 1.1% (95% CI [confidence interval]: - 3.9, 3.0) among people aged 60-69 years, - 7.2% (95% CI - 11.2, - 2.4) among those aged 70-79 years, - 7.4% (95% CI - 14.2, 0.2) among those aged 80-89 years, and - 10.3% (95% CI - 21.1, 2.7) among those aged 90 and over. Early diagnosis and treatment greatly contributed to reducing the case fatality risk.

Saliva - a new opportunity for fluid biopsy.

Saliva is a complex biological fluid with a variety of biomolecules, such as DNA, RNA, proteins, metabolites and microbiota, which can be used for the screening and diagnosis of many diseases. In addition, saliva has the characteristics of simple collection, non-invasive and convenient storage, which gives it the potential to replace blood as a new main body of fluid biopsy, and it is an excellent biological diagnostic fluid. This review integrates recent studies and summarizes the research contents of salivaomics and the research progress of saliva in early diagnosis of oral and systemic diseases. This review aims to explore the value and prospect of saliva diagnosis in clinical application.

Assessment of Urinary Biomarkers for Infectious Diseases Using Lateral Flow Assays: A Comprehensive Overview.

Screening of biomarkers is a powerful approach for providing a holistic view of the disease spectrum and facilitating the diagnosis and prognosis of the state of infectious diseases. Unaffected by the homeostasis mechanism in the human body, urine accommodates systemic changes and reflects the pathophysiological condition of an individual. Easy availability in large volumes and non-invasive sample collection have rendered urine an ideal source of biomarkers for various diseases. Infectious diseases may be communicable, and therefore early diagnosis and treatment are of immense importance. Current diagnostic approaches preclude the timely identification of clinical conditions and also lack portability. Point-of-care (POC) testing solutions have gained attention as alternative diagnostic measures due to their ability to provide rapid and on-site results. Lateral flow assays (LFAs) are the mainstay in POC device development and have attracted interest owing to their potential to provide instantaneous results in resource-limited settings. The discovery and optimization of a definitive biomarker can render POC testing an excellent platform, thus impacting unwarranted antibiotic administration and preventing the spread of infectious diseases. This Review summarizes the importance of urine as an emerging biological fluid in infectious disease research and diagnosis in clinical settings. We review the academic research related to LFAs. Further, we also describe commercial POC devices based on the identification of urinary biomarkers as diagnostic targets for infectious diseases. We also discuss the future use of LFAs in developing more effective POC tests for urinary biomarkers of various infections.

EEI-IoT: Edge-Enabled Intelligent IoT Framework for Early Detection of COVID-19 Threats.

Coronavirus disease 2019 (COVID-19) has caused severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) across the globe, impacting effective diagnosis and treatment for any chronic illnesses and long-term health implications. In this worldwide crisis, the pandemic shows its daily extension (i.e., active cases) and genome variants (i.e., Alpha) within the virus class and diversifies the association with treatment outcomes and drug resistance. As a consequence, healthcare-related data including instances of sore throat, fever, fatigue, cough, and shortness of breath are given due consideration to assess the conditional state of patients. To gain unique insights, wearable sensors can be implanted in a patient's body that periodically generates an analysis report of the vital organs to a medical center. However, it is still challenging to analyze risks and predict their related countermeasures. Therefore, this paper presents an intelligent Edge-IoT framework (IE-IoT) to detect potential threats (i.e., behavioral and environmental) in the early stage of the disease. The prime objective of this framework is to apply a new pre-trained deep learning model enabled by self-supervised transfer learning to build an ensemble-based hybrid learning model and to offer an effective analysis of prediction accuracy. To construct proper clinical symptoms, treatment, and diagnosis, an effective analysis such as STL observes the impact of the learning models such as ANN, CNN, and RNN. The experimental analysis proves that the ANN model considers the most effective features and attains a better accuracy (~98.3%) than other learning models. Also, the proposed IE-IoT can utilize the communication technologies of IoT such as BLE, Zigbee, and 6LoWPAN to examine the factor of power consumption. Above all, the real-time analysis reveals that the proposed IE-IoT with 6LoWPAN consumes less power and response time than the other state-of-the-art approaches to infer the suspected victims at an early stage of development of the disease.

Chest CT diagnostic potential as a tool for early detection of suspected COVID-19 cases in pandemic peaks.

INTRODUCTION: The emergence of severe acute respiratory syndrome coronavirus disease (COVID-19) in China at the end of 2019 caused a massive global outbreak that has become a major public health issue. AIM: Our aim was to investigate the diagnostic potential of chest CT in screening patients suspected of having COVID-19 in high-prevalence settings. MATERIALS AND METHODS: This is a real-life, prospective, observational study involving 260 patients. All patients received chest CT scan at the emergency department (ED) of Kaspela University Hospital, Plovdiv, Bulgaria and RT-PCR testing for suspected COVID-19 from March 27 to December 31, 2020. COVID-19 likelihood was assessed by assigning each CT scan to a particular category of the COVID-19 Reporting and Data System (CO-RADS). IBM SPSS v. 26 was used to process the data. RESULTS: The male-to-female distribution ratio was 1.4:1 - 150 (57.7%) males vs. 110 (42.3%) females (p=0.014). The median age was 55 yrs (range 46-65 yrs). Discharged patients were 247 (95.0%), the rest died in the COVID-19 intensive care unit. Males were 4.13 times more likely to be diagnosed with CO-RADS≥3 score than females. Increasing age was associated with an increased likelihood of being classified with higher CO-RADS scores. The ROC curves analysis demonstrated that CO-RADS ≥3 was the optimal cutoff for discrimi-nating between a positive and negative PCR (Youden's index J=0.67), with an AUC of 0.825 (95% CI 0.72-0.93), sensitivity of 91.9% (95% CI 87.7%-95.1%), specificity of 75.0% (95% CI 53.3%-90.2%) and accuracy of 76.4% (95% CI 70.7%-81.4%). CONCLUSIONS: The results of this study reveal that a CT examination can provide a quick and accurate diagnosis of patients with sus-pected COVID-19 infection, whereas the PCR test is time-consuming, and the delay in receiving results can be substantial when the incidence curve begins to grow rapidly.

The clinical effect of point-of-care HIV diagnosis in infants: a systematic review and meta-analysis.

BACKGROUND: Timely diagnosis and treatment of HIV is crucial in HIV-exposed infants to prevent the high rates of mortality seen during the first 2 years of life if HIV is untreated. However, challenges with sample transportation, testing, and result delivery to caregivers have led to long delays in treatment initiation. We aimed to compare the clinical effect of point-of-care HIV testing versus laboratory-based testing (standard of care) in HIV-exposed infants. METHODS: We did a systematic review and meta-analysis and searched PubMed, MEDLINE, Cochrane Central Register of Controlled Trials, Embase, Conference Proceedings Citation Index-Science, and WHO Global Index Medicus, from Jan 1, 2014, to Aug 31, 2020. Studies were included if they pertained to the use of point-of-care nucleic acid testing for infant HIV diagnosis, had a laboratory-based nucleic acid test as the comparator or standard of care against the index test (same-day point-of-care testing), evaluated clinical outcomes when point-of-care testing was used, and included HIV-exposed infants aged younger than 2 years. Studies were excluded if they did not use a laboratory-based comparator, a nucleic acid test that had been approved by a stringent regulatory authority, or diagnostic-accuracy or performance evaluations (eg, no clinical outcomes included). Reviews, non-research letters, commentaries, and editorials were also excluded. The risk of bias was evaluated using the ROBINS-I framework. Data were extracted from published reports. Data from all studies were analysed using frequency statistics to describe the overall populations evaluated and their results. Key outcomes were time to result delivery and antiretroviral therapy initiation, and proportion of HIV-positive infants initiated on antiretroviral therapy within 60 days after sample collection. FINDINGS: 164 studies were identified by the search and seven were included in the analysis, comprising 37 377 infants in total across 15 countries, including 25 170 (67%) who had point-of-care HIV testing and 12 207 (33%) who had standard-of-care testing. The certainty of evidence was high. Same-day point-of-care testing led to a significantly shorter time between sample collection and result delivery to caregivers compared with standard-of-care testing (median 0 days [95% CI 0-0] vs 35 days [35-37]). Time from sample collection to antiretroviral therapy initiation in infants found to be HIV-positive was significantly lower with point-of-care testing compared with standard of care (median 0 days [95% CI 0-1] vs 40 days [36-44]). When each study's result was weighted equally, 90·3% (95% CI 76·7-96·5) of HIV-positive infants diagnosed using point-of-care testing had started antiretroviral therapy within 60 days of sample collection, compared with only 51·6% (27·1-75·7) who had standard-of-care testing (odds ratio 8·74 [95% CI 6·6-11·6]; p<0·0001). INTERPRETATION: Overall, the certainty of the evidence in this analysis was rated as high for the primary outcomes related to result delivery and treatment initiation, with no serious risk of bias, inconsistency, indirectness, or imprecision. In HIV-exposed infants, same-day point-of-care HIV testing was associated with significantly improved time to result delivery, time to antiretroviral therapy initiation, and proportion of HIV-positive infants starting antiretroviral therapy within 60 days compared with standard of care. FUNDING: The Bill & Melinda Gates Foundation.

Return to Travel in the Coronavirus Disease 2019 Pandemic Recovery Period and Implications for Imported Malaria: Reinforcing Prevention, Early Diagnosis, and Appropriate Treatment of Malaria.

Return to international travel in the COVID-19 pandemic recovery period is expected to increase the number of patients with imported malaria in the United States (US). Malaria prevention in travelers and preparedness for timely diagnosis and appropriate treatment are key to minimize imported malaria morbidity and mortality. Intravenous artesunate (IVAS) is now available from commercial distributors in the US for the treatment of severe malaria. Hospitals and pharmacists should have a plan for malaria treatment, including stocking artemether-lumefantrine for uncomplicated malaria, and stocking or planning for rapid procurement of IVAS for the treatment of severe malaria.

Decision support-tools for early detection of infection in older people (aged> 65 years): a scoping review.

BACKGROUND: Infection is more frequent, and serious in people aged > 65 as they experience non-specific signs and symptoms delaying diagnosis and prompt treatment. Monitoring signs and symptoms using decision support tools (DST) is one approach that could help improve early detection ensuring timely treatment and effective care. OBJECTIVE: To identify and analyse decision support tools available to support detection of infection in older people (> 65 years). METHODS: A scoping review of the literature 2010-2021 following Arksey and O'Malley (2005) framework and PRISMA-ScR guidelines. A search of MEDLINE, Cochrane, EMBASE, PubMed, CINAHL, Scopus and PsycINFO using terms to identify decision support tools for detection of infection in people > 65 years was conducted, supplemented with manual searches. RESULTS: Seventeen papers, reporting varying stages of development of different DSTs were analysed. DSTs largely focussed on specific types of infection i.e. urine, respiratory, sepsis and were frequently hospital based (n = 9) for use by physicians. Four DSTs had been developed in nursing homes and one a care home, two of which explored detection of non- specific infection. CONCLUSIONS: DSTs provide an opportunity to ensure a consistent approach to early detection of infection supporting prompt action and treatment, thus avoiding emergency hospital admissions. A lack of consideration regarding their implementation in practice means that any attempt to create an optimal validated and tested DST for infection detection will be impeded. This absence may ultimately affect the ability of the workforce to provide more effective and timely care, particularly during the current covid-19 pandemic.

A novel multimodal fusion framework for early diagnosis and accurate classification of COVID-19 patients using X-ray images and speech signal processing techniques.

BACKGROUND AND OBJECTIVE: COVID-19 outbreak has become one of the most challenging problems for human being. It is a communicable disease caused by a new coronavirus strain, which infected over 375 million people already and caused almost 6 million deaths. This paper aims to develop and design a framework for early diagnosis and fast classification of COVID-19 symptoms using multimodal Deep Learning techniques. METHODS: we collected chest X-ray and cough sample data from open source datasets, Cohen and datasets and local hospitals. The features are extracted from the chest X-ray images are extracted from chest X-ray datasets. We also used cough audio datasets from Coswara project and local hospitals. The publicly available Coughvid DetectNow and Virufy datasets are used to evaluate COVID-19 detection based on speech sounds, respiratory, and cough. The collected audio data comprises slow and fast breathing, shallow and deep coughing, spoken digits, and phonation of sustained vowels. Gender, geographical location, age, preexisting medical conditions, and current health status (COVID-19 and Non-COVID-19) are recorded. RESULTS: The proposed framework uses the selection algorithm of the pre-trained network to determine the best fusion model characterized by the pre-trained chest X-ray and cough models. Third, deep chest X-ray fusion by discriminant correlation analysis is used to fuse discriminatory features from the two models. The proposed framework achieved recognition accuracy, specificity, and sensitivity of 98.91%, 96.25%, and 97.69%, respectively. With the fusion method we obtained 94.99% accuracy. CONCLUSION: This paper examines the effectiveness of well-known ML architectures on a joint collection of chest-X-rays and cough samples for early classification of COVID-19. It shows that existing methods can effectively used for diagnosis and suggesting that the fusion learning paradigm could be a crucial asset in diagnosing future unknown illnesses. The proposed framework supports health informatics basis on early diagnosis, clinical decision support, and accurate prediction.

Respiratory surveillance wards as a strategy to reduce nosocomial transmission of COVID-19 through early detection: The experience of a tertiary-care hospital in Singapore.

OBJECTIVES: Patients with COVID-19 may present with respiratory syndromes indistinguishable from those caused by common viruses. Early isolation and containment is challenging. Although screening all patients with respiratory symptoms for COVID-19 has been recommended, the practicality of such an effort has yet to be assessed. METHODS: Over a 6-week period during a SARS-CoV-2 outbreak, our institution introduced a "respiratory surveillance ward" (RSW) to segregate all patients with respiratory symptoms in designated areas, where appropriate personal protective equipment (PPE) could be utilized until SARS-CoV-2 testing was done. Patients could be transferred when SARS-CoV-2 tests were negative on 2 consecutive occasions, 24 hours apart. RESULTS: Over the study period, 1,178 patients were admitted to the RSWs. The mean length-of-stay (LOS) was 1.89 days (SD, 1.23). Among confirmed cases of pneumonia admitted to the RSW, 5 of 310 patients (1.61%) tested positive for SARS-CoV-2. This finding was comparable to the pickup rate from our isolation ward. In total, 126 HCWs were potentially exposed to these cases; however, only 3 (2.38%) required quarantine because most used appropriate PPE. In addition, 13 inpatients overlapped with the index cases during their stay in the RSW; of these 13 exposed inpatients, 1 patient subsequently developed COVID-19 after exposure. No patient-HCW transmission was detected despite intensive surveillance. CONCLUSIONS: Our institution successfully utilized the strategy of an RSW over a 6-week period to contain a cluster of COVID-19 cases and to prevent patient-HCW transmission. However, this method was resource-intensive in terms of testing and bed capacity.

Blood Cell Parameters Combined with Inflammatory Markers in the Early Diagnosis of Pulmonary Embolism.

Venous thrombosis is a semi-solid formation of blood components that coalesce in the venous system, and the pathological process of its formation is called venous thrombosis. The deep veins of the lower extremities are a common site of prevalence, and the clinical diagnosis of lower extremity deep vein thrombosis can occur independently or as a complication of other diseases. There is a clear link between inflammation and coagulation/anticoagulation, with inflammatory mechanisms upregulating pro-inflammatory factors, downregulating natural anticoagulant substances, and inhibiting fibrinolytic activity; systemic inflammation is a strong pro-thrombotic stimulus; and in vivo, natural anticoagulant substances not only prevent thrombosis, but also deter inflammatory processes. The interconnection between inflammation and coagulation plays an important role in venous thrombosis. In this study, we analyzed the relationship between inflammatory markers CRP and Fg, FVIII:C and FIX:C by measuring plasma CRP concentration, Fg level, FVIII:C and FIX:C levels in patients with DVT diagnosed by ultrasound, and explored the role and mechanism of inflammatory response and coagulation factor abnormalities and the interaction between them in the development of DVT. In this paper, human blood DNA was extracted by phenol-chloroform-isoamyl alcohol extraction, and CRP 1059G/C gene polymorphism was detected by polymerase chain reaction-restriction enzyme segment length polymorphism (PCR-RFLP) nucleotide typing technique, and the genotypes of each subject were distinguished according to the bands seen by gel electrophoresis, and the frequency of each genotype was counted. Plasma CRP concentrations were measured by immunoturbidimetric assay, FVIII:C and FIX:C levels were measured by phase I assay, and plasma Fg levels were measured by coagulation assay in 59 cases (38 males and 21 females, aged 21-82 years, mean 49.67±11.12 years) and 26 controls (17 males and 9 females, aged 32-67 years, mean 50.13±8.96 years). The above indexes were compared between the two groups, and the correlation between CRP and FVIII:C, FIX:C and Fg was analyzed. Polymerase chain reaction-restriction enzyme segment length polymorphism nucleotide typing technique was used to detect the relationship between CRP 1059G/C gene polymorphism and DVT, to further search for risk factors of venous thrombosis, thus providing new ideas for the future prevention and treatment of this disease in clinical practice.

Spectroscopic methods for COVID-19 detection and early diagnosis.

The coronavirus pandemic is a worldwide hazard that poses a threat to millions of individuals throughout the world. This pandemic is caused by the severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2), which was initially identified in Wuhan, China's Hubei provincial capital, and has since spread throughout the world. According to the World Health Organization's Weekly Epidemiological Update, there were more than 250 million documented cases of coronavirus infections globally, with five million fatalities. Early detection of coronavirus does not only reduce the spread of the virus, but it also increases the chance of curing the infection. Spectroscopic techniques have been widely used in the early detection and diagnosis of COVID-19 using Raman, Infrared, mass spectrometry and fluorescence spectroscopy. In this review, the reported spectroscopic methods for COVID-19 detection were discussed with emphasis on the practical aspects, limitations and applications.

An Innovative Sensorized Face Mask for Early Detection of Physiological Changes Associated with Viral Infection.

A sensorized face mask could be a useful tool in the case of a viral pandemic event, as well as the Covid-19 emergency. In the context of the proposed project "RESPIRE", we have developed a "Smart-Mask" able to collect the signal patterns of body temperature, respiration, and symptoms such as cough, through a set of textile sensors. The signals have been analyzed by Artificial Intelligence algorithms in order to compare them with gold standard measurements, and to recognize the physiological changes associated with a viral infection. This low-cost prototype of a smart face mask is a reliable tool for the estimation of the individual physiological parameters. Moreover, it enables both personal protection and the early and rapid identification and tracking of potentially infected individuals.

Early diagnosis by antigen test kit and early treatment by antiviral therapy: An ambulatory management strategy during COVID-19 crisis in Thailand.

This study aimed to assess the clinical characteristics of patients who registered at the Siriraj Favipiravir Clinic and to share our experiences in this comparatively unique clinical setting. This retrospective study included patients who registered at the Siriraj Favipiravir Clinic during August 11, 2021 to September 14, 2021. Included adult patients were those with severe acute respiratory syndrome coronavirus 2 (coronavirus disease 2019 [COVID-19]) infection confirmed by antigen test kit (ATK) or real-time reverse transcription-polymerase chain reaction, no favipiravir contraindication, no prior COVID-19 treatment, and not receiving care from another medical facility. Demographic data and outcomes were collected and analyzed. Of the 1168 patients (mean age: 44.8 ± 16.4 years, 55.7% female) who registered at the clinic, 117 (10%) did not meet the treatment criteria, and 141 (12%) patients did not pick up their medication. One-third of patients had at least 1 symptom that indicated severe disease. Higher proportion of unvaccinated status (56.7% vs 47.5%, P = .005), higher proportion of persons with risk factors for disease progression (37.7% vs 31.3%, P = .028), and longer duration between the date of clinic registration and the date of positive diagnostic test (3 vs 2 days, P = .004) were significantly more commonly observed in the severe disease group compared to the nonsevere disease group. The duration between symptom onset and the date of clinic registration was significantly longer in the real-time reverse transcription-polymerase chain reaction group than in the ATK group (6 vs 4 days, P < .001). Most patients (90.0%) had completed favipiravir treatment regimen. The improvement and mortality rates were 86.7% and 1.2%, respectively. COVID-19 severity is associated with vaccination status, baseline risk factors, and timing between disease detection and treatment. The use of ATK influences patients to seek treatment significantly earlier in ambulatory setting. Our early diagnosis and antiviral treatment strategy yielded favorable results in an outpatient setting during a COVID-19 outbreak in Thailand.

Wearable technology for early detection of COVID-19: A systematic scoping review.

Wearable technology is an emerging method for the early detection of coronavirus disease 2019 (COVID-19) infection. This scoping review explored the types, mechanisms, and accuracy of wearable technology for the early detection of COVID-19. This review was conducted according to the five-step framework of Arksey and O'Malley. Studies published between December 31, 2019 and December 15, 2021 were obtained from 10 electronic databases, namely, PubMed, Embase, Cochrane, CINAHL, PsycINFO, ProQuest, Scopus, Web of Science, IEEE Xplore, and Taylor & Francis Online. Grey literature, reference lists, and key journals were also searched. All types of articles describing wearable technology for the detection of COVID-19 infection were included. Two reviewers independently screened the articles against the eligibility criteria and extracted the data using a data charting form. A total of 40 articles were included in this review. There are 22 different types of wearable technology used to detect COVID-19 infections early in the existing literature and are categorized as smartwatches or fitness trackers (67%), medical devices (27%), or others (6%). Based on deviations in physiological characteristics, anomaly detection models that can detect COVID-19 infection early were built using artificial intelligence or statistical analysis techniques. Reported area-under-the-curve values ranged from 75% to 94.4%, and sensitivity and specificity values ranged from 36.5% to 100% and 73% to 95.3%, respectively. Further research is necessary to validate the effectiveness and clinical dependability of wearable technology before healthcare policymakers can mandate its use for remote surveillance.

Usefulness of High-Resolution Computed Tomography in Early Diagnosis of Patients with Suspected COVID-19.

BACKGROUND: Diagnosis of coronavirus disease 2019 (COVID-19) is mainly based on molecular testing. General population studies have shown that chest Computed Tomography (CT) can also be useful. OBJECTIVE: The study aims to examine the usefulness of high-resolution chest CT for early diagnosis of patients with suspected COVID-19. DESIGN AND SETTING: This is a cross-sectional study from May 1, 2020, to August 31, 2021, at the COVID Hospital, Mexico City. METHODS: This study examined the clinical, high-resolution chest CT imaging, and laboratory data of 160 patients who were suspected to have COVID-19. Patients with positive Reverse Transcription- Polymerase Chain Reaction (RT-PCR) testing and those with negative RT-PCR testing but clinical data compatible with COVID-19 and positive antibody testing were considered to have COVID-19 (positive). Sensitivity and specificity of CT for diagnosis of COVID-19 were calculated. p < 0.05 was considered significant. RESULTS: Median age of 160 study patients was 58 years. The proportion of patients with groundglass pattern was significantly higher in patients with COVID-19 than in those without COVID (65.1% versus 0%; P = 0.005). COVID-19 was ruled out in sixteen (11.1%). Only four of the 132 patients diagnosed with COVID-19 (3.0%) did not show CT alterations (p < 0.001). Sensitivity and specificity of CT for COVID-19 diagnosis were 96.7% and 42.8%, respectively. CONCLUSIONS: Chest CT can identify patients with COVID-19, as characteristic disease patterns are observed on CT in the early disease stage.

Early Diagnosis and Prevention of Infections in Cirrhosis.

Strategies to prevent infection and improve outcomes in patients with cirrhosis. HAV, hepatitis A virus; HBV, hepatitis B virus; COVID-19, novel coronavirus disease 2019; NSBB, nonselective ß-blocker; PPI, proton pump inhibitors.Cirrhosis is a risk factor for infections. Majority of hospital admissions in patients with cirrhosis are due to infections. Sepsis is an immunological response to an infectious process that leads to end-organ dysfunction and death. Preventing infections may avoid the downstream complications, and early diagnosis of infections may improve the outcomes. In this review, we discuss the pathogenesis, diagnosis, and biomarkers of infection; the incremental preventive strategies for infections and sepsi; and the consequent organ failures in cirrhosis. Strategies for primary prevention include reducing gut translocation by selective intestinal decontamination, avoiding unnecessary proton pump inhibitors' use, appropriate use of ß-blockers, and vaccinations for viral diseases including novel coronavirus disease 2019. Secondary prevention includes early diagnosis and a timely and judicious use of antibiotics to prevent organ dysfunction. Organ failure support constitutes tertiary intervention in cirrhosis. In conclusion, infections in cirrhosis are potentially preventable with appropriate care strategies to then enable improved outcomes.