Assessment of severity in hospitalized community- acquired pneumonia by the use of validated scoring systems

Assessment of severity in hospitalized community- acquired pneumonia by the use of validated scoring systems | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Assessment of severity in hospitalized community- acquired pneumonia by the use of validated scoring systems Sandleen Iftikhar, Bjørn Waagsbø This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4828646/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 03 Mar, 2025 Read the published version in BMC Pulmonary Medicine → Version 1 posted 4 You are reading this latest preprint version Abstract Background Severity assessment of community-acquired pneumonia (CAP) is essential for many purposes. Among these are the microbiological confirmation strategy and choice of empirical antimicrobial therapy. However, many severity assessment systems have been developed to aid clinicians to reach reliable predictions of severe outcomes. Methods We aimed to apply nine disease severity assessment scoring systems to a large 2016 to 2021 CAP cohort in order to achieve test sensitivity, specificity and predictive values. We used intra-hospital case fatality rate and the need for intensive care therapy as outcomes. The area under the receiver operating characteristic (ROC) curve was used to display test performance. Results A total of 1.112 CAP episodes were included in the analysis, of which 91.4% were radiologically, and 43.7% were microbiologically confirmed. When intra-hospital case fatality was set as outcome, frequently used tests with few data entries typically underperformed as compared to infrequently used tests that require more comprehensive data entries. Comparable results were gained when intensive care admittance was set as outcome. The area under the receiving operating curve was 0.0955, 0.845 and 0.892 for the sequential organ failure assessment (SOFA), pneumonia severity index (PSI), and the Infectious Diseases Society of America/American Thoracic Society definitions, respectively. Conclusion CAP severity assessment remains important. Simplified scoring systems underperformed as compared to more comprehensive and sophisticated ones. Community-acquired pneumonia severity assessment antimicrobial stewardship antimicrobial therapy Figures Figure 1 Introduction Community acquired pneumonia (CAP), albeit a common infection, can be a potential life-threatening illness and is the most common causes of sepsis ( 1 , 2 ). It is associated with high morbidity and mortality rates especially in the elderly and in patients with underlying comorbidities ( 3 ). Hospital admission rates can vary widely and are often not directly related to disease severity. A number of factors contribute to decisions on site of care and level of therapy, among these medication compliance, ability to maintain oral intake, cognitive or functional impairment, social circumstances, and disease severity. Clinicians can misinterpret or misjudge disease severity, leading to unwarranted therapy for relatively mild cases, or missed therapy for more severe cases. However, the risk of short-term mortality in CAP is more likely to be over-, rather than underestimated ( 4 ). The initiation of empirical antimicrobial therapy and the site of care are by most professional guideline recommendations determined by CAP severity at presentation. However, the evidence to support a standardized approach with the use of disease severity assessments for CAP, is still sparse in terms of improved outcomes ( 5 ). In countries with low rates of antimicrobial resistance, unwarranted broad-spectrum antimicrobial therapy is of particular concern. A wide array of supporting systems have been developed and validated to aid clinicians when assessing disease severity in especially CAP. Of these systems, some are relatively effortless, while some are complex. In this study, we have applied these systems to a CAP-cohort, and established test properties and performance. Patients and methods Study setting A single-center, 1.000 bed, university teaching hospital in mid-Norway, accepting all patient categories, except transplantation surgery. Study population We identified all cases of CAP admitted to a university teaching hospital in Norway between 2016 and 2021. Due to labor-intensive registrations, only the months between March and May and the departments of medicine and pulmonology were eligible for inclusion. Months were chosen to represent an influenza-diminished period, regular hospital staffing situations, and standardized laboratory services. Final discharge diagnoses (ICD-10 between J13 to J18.9) were used to identify eligible cases for inclusion. We have earlier reported patient characteristics, aetiology, resistance patterns and antimicrobial therapy to these case series ( 6 ). Study outcomes The primary outcome of this particular study was to report the validity and eligibility of established, and commonly used, clinical scoring systems for disease severity assessment in the emergency room setting for CAP patients. Sensitivity, specificity, and predictive values were calculated using intra-hospital case fatality and ICU-admittance as outcomes. Area under the receiver operating curve were used to depict performance of the assessments strategies for intra-hospital case fatality rate. Data collection All data registered were collected retrospectively after each ensuing year between 2016 and 2021. Included variables were patient characteristics, clinical characteristics present at admittance, radiological and laboratory findings, antimicrobial therapy, and clinical outcomes. Severity assessments In Table 1 we have presented the clinical scoring systems that were selected by the study group. Table 1 Selected scoring systems for disease severity. System a Year launhced Subcriteria b Reference c Validation d qSOFA 2016 3 ( 7 ) ( 8 – 11 ) CRB65 - 4 - ( 12 – 14 ) CURB65 2003 5 ( 5 ) ( 15 , 16 ) SIRS (Sepsis 1) 1992 4 ( 17 ) ( 18 , 19 ) NEWS2 2017 7 ( 20 ) ( 21 – 23 ) SOFA (Sepsis-3) 2016 6 ( 24 ) ( 25 – 27 ) PSI 1997 20 ( 14 ) ( 15 , 28 ) IDSA/ATS 2007 11 ( 29 ) ( 30 – 33 ) Sepsis-2 2003 A myriade ( 34 ) - a See appendix for full outlining of system name b Number of subcriteria included in system c Reference to the original publication of the system d Relevant validation studies When assessing disease severity by the use of qSOFA, CRB65, CURB-65, SIRS, and NEWS2 we calculated sensitivity, specificity, and predictive values by extracting the necessary subcriteria directly from the collected data. When assessing consciousness, we considered new-onset confusion, disorientation, agitation, responds to voice, responds to pain, or unresponsive as relevant. To some extent, we used clinical judgement to deem the level of affected consciousness When calculating the initial SOFA-score, we frequently used the arterial partial pressure of oxygen (P a O 2 ) instead of P a O 2 /F i O 2 . In cases initially lacking measurements of P a O 2 , we imputed peripheral saturation of oxygen (SO 2 ) to the calculation. This has earlier been demonstrated to accurately correlate and provide acceptable outcomes ( 35 ). We were able to calculate the SOFA-score to 96.4% of included cases. The PSI is much more detailed as 20 subcriteria are needed to calculate the score. A great proportion of these subcriteria are related to comorbidity status, to which we used some extent of clinical judgement. This represents, in deed, everyday clinical practice. None of the cases included were nursing home residents. We also used the serum creatinine level at > 120 µmol/L to represent new-onset kidney dysfunction instead of blood urea nitrogen concentration. To assess the haematocrit value we imputed three-folded haemoglobin levels according to earlier practice ( 36 ). PSI-score was ultimately calculated to 90.7% of included cases. The 2007 IDSA/ATS clinical practice guideline for CAP stated a set of major or minor criteria for the disease severity assessment. The fulfilment of one major or at least three minor criteria would tentatively imply severe CAP. The minor criteria resemble CURB65-criteria, and the major criteria are invasive mechanical ventilation or septic shock with the need for vasopressors. An initial score could be established to 94.5% of included cases. We also set out to include the 2001 international sepsis definition and case criteria (Sepsis-2) in this study. The case criteria are aggregated from multiple variables, including general, inflammatory, hemodynamic, organ dysfunction, and tissue perfusion variables. In contrast to others systems, there is no established or suggestive level of number of subcriteria to fulfil the case criteria. Instead, judicious and extensive clinical judgement from the bedside attending doctor, to evaluate the myriad of presenting signs and symptoms, determines whether the infection is severe or not. Because this extensive individual evaluation universally was poorly documented in our study, we were unable to calculate scoring for all inclusions. Statistical analyses To calculate sensitivity, specificity, and predictive values we used cross tabulation functions in IBM SPSS (Statistical Package for the Social Sciences), version 29. We defined thresholds for positive or negative test, which are summarized in Table 2 . Table 2 Thresholds for positive test. System Test threshold for positive test qSOFA 2 or more subcriteria CRB65 2 or more subcriteria CURB65 2 or more subcriteria SIRS (Sepsis 1) 2 or more subcriteria NEWS2 5 or more points SOFA (Sepsis-3) Increase of 2 or more points PSI Risk class II with 90 or more points IDSA/ATS One major or 3 or more minor criteria Sepsis-2 No threshold established Ethical considerations The study group has previously been granted approval by the hospital administration and data protections officials to conduct studies on lower respiratory tract infections. We also received approval by the Regional Committee for Medical and Health Research Ethics (REK 2017/1439), stating that inclusion consent was deemed unnecessary due to retrospective study design. Results Patient characteristics and outcomes Over six years we included 1.112 patients in this study. All patients were ultimately diagnosed and discharged from hospital with CAP as a primary diagnose, of which 91.4% were radiologically, and 43.7% microbiologically confirmed, on average for all years. We have previously reported patient characteristics, aetiology, resistance patterns and antimicrobial therapy in this case series ( 6 ). Among included cases, mean age was 70.3 years and nearly 40% were aged above 65 years. Table 3 summarizes relevant characteristics and outcomes. Table 3 A selection of patient characteristics and outcomes of studied inclusions Characteristics and outcomes Age Mean 70.3 years Proportion > 65 years 39.0% Gender Male 45.5% Comorbidities Median number of conditions 3 Median Charlson comorbidity index 4 ICU Proportion admitted 6.1% Invasive ventilation 4.7% Sepsis Without shock 9.9% With shock 1.9% Length of stay Mean 7.2 (95% CI 6.9–7.5) Case fatality In-hospital 10.9% 30-day 14.3% 90-day 23.8% Intra-hospital case fatality Firstly, we calculated sensitivity, specificity and predictive values to a positive test when the outcome was intra-hospital case fatality. Table 4 summarizes the calculations. Table 4 Results when outcome is intra-hospital case fatality Test system n Data Sensitivity Specificity PPV NPV qSOFA 1112 100% 14/117 (12.0%) 911/995 (91.6%) 14.3% 89.8% CRB65 1112 100% 36/117 (30.8%) 737/995 (74.1%) 12.2% 90.1% CURB65 1112 100% 38/117 (32.5%) 716/995 (72.0%) 12.0% 90.1% SIRS (Sepsis 1) 1112 100% 84/117 (71.8%) 321/995 (67.7%) 11.1% 90.7% NEWS2 1112 100% 89/117 (76.1%) 377/995 (37.9%) 12.6% 93.7% SOFA (Sepsis-3) 1072 96,4% 90/96 (93.8%) 916/976 (93.9%) 60.0% 99.3% PSI 1009 90,7% 76/88 (88.6%) 847/921 (92.0%) 47.8% 98.8% IDSA/ATS 1112 100% 88/101 (87.1%) 961/1011 (95.1%) 63.8% 98.7% Sepsis-2 0 0% NA* NA* NA* NA* *Not applicable Sensitivity was low and specificity was somewhat reciprocally high among frequently used tests to assess disease severity when in-hospital case fatality was the outcome. Among the more infrequently used tests in Norway that require more extensive data entries, sensitivity and specificity were considerable higher, all reaching > 87%. The predicted positive values were low for most tests, whilst the negative predicted values were all > 89%. Calculations in accordance with the Sepsis-2-criteria were universally unattainable. Intensive care admittance Secondly, we calculated sensitivity, specificity and predictive values to a positive test when the outcome was ICU-admittance from CAP. Table 5 summarizes the calculations. Table 5 Results when the outcome is need for intensive care admittance. Test system n Data Sensitivity Specificity PPV NPV qSOFA 1112 100% 20/68 (29.4%) 966/1014 (92.5%) 20.4% 95.3% CRB65 1112 100% 44/68 (64.7%) 794/1044 (76.1%) 15.0% 97.1% CURB65 1112 100% 46/68 (67.7%) 773/1044 (74.0%) 14.5% 97.2% SIRS (Sepsis 1) 1112 100% 58/68 (85.3%) 344/1044 (33.0%) 7.7% 97.2% NEWS2 1112 100% 55/68 (80.9%) 392/1044 (37.5%) 7.8% 96.8% SOFA (Sepsis 3) 1072 96,4% 45/68 (66.2%) 484/1044 (46.4%) 7.4% 95.5% PSI 1009 90,7% 70/78 (89.7%) 882/931 (94.7%) 58.8% 99.1% IDSA/ATS 1112 100% 81/88 (92.0%) 881/963 (91.5%) 49.7% 99.2% Sepsis-2 0 0 NA* NA* NA* NA* *Not applicable Sensitivity and specificity varied considerably among frequently used tests to assess disease severity when the need for ICU admittance was the outcome. Among the more infrequently used tests that require more extensive data entries, sensitivity and specificity also varied, albeit all reaching > 66%. The predicted positive values were universally low, whilst the negative predicted values were all > 95%. Area under the receiver operating curve We estimated the area under the receiver operating characteristic (ROC) curve for the calculations when the outcome was intra-hospital case fatality. The frequently used severity assessment scoring systems, like qSOFA, CURB65, CRB65, SIRS and NEWS2, performed poorly as the curve closely resembled the reference line. The ROC-curves for scoring systems that need more extensive data entries are shown in Table 1 . The estimated area for these curves all achieved values above 0.845, which were statistical significant. The area results are provided in Table 6 . Table 6 Area under the receiver operating (ROC) curve. Test system Area Std error p 95% CI SOFA 0.955 0.015 0.0001 0.93–0.98 PSI 0.845 0.026 0.0001 0.79–0.87 IDSA/ATS 0.892 0.025 0.0001 0.84–0.94 Discussion In this study, we have demonstrated the low specificity and positive predicted value of frequently used strategies to assess disease severity in CAP. On the other hand, more sophisticated and complex systems like the SOFA-, PSI- or IDSA-criteria, provide superior results in terms of both sensitivity, specificity and predicted values. The results pinpoint limitations of simplified disease severity scoring systems, and underscore the importance of judicious clinical assessment by the skilled clinician. Validation studies of clinical scorings systems in the infection severity assessment have shown various results. They have also been applied to various patient populations, at various location settings, and to predict various outcomes. We used intra-hospital case fatality and ICU-referral as outcomes, and concluded that qSOFA, CRB65, CURB65, SIRS and NEWS all provided inferior AUROC (~ 0.50), and SOFA, PSI and IDSA/ATS superior AUROC (> 0.84). Disease severity assessment is crucial for many reasons. Firstly, the initiation of empirical antimicrobial therapy is often based on the assessment of disease severity, as is also the choice of antimicrobial regimen ( 37 ). Secondly, recommendations on the timing of antimicrobial therapy administration vary according to disease severity ( 38 ). Thirdly, strategy to establish reliable microbiological aetiology is linked to disease severity assessment in infections ( 39 ). Fourthly, disease severity assessment determines site of care, both for community- or hospital settings. And fifthly, diseases severity assessments are prerequisites for determining overall therapy duration, oral transition, advanced diagnostic and therapeutic approaches, hospital discharge, and more. Clinical scoring systems to assess disease severity are attempts to provide the attending clinician with information to judge infections especially in the emergency room setting. Of importance, most systems was originally derived in patients already suspected of having infection ( 40 ). The CURB65-, CRB65-, PSI- and the IDSA-criteria targeted lower respiratory tract infections specifically, while all other systems aimed to be applicable regardless of infection site. However, all systems tend to simplify complex processes of infection, inflammation and pathophysiology of heterogeneous patient groups, pathogens, and infection sites ( 41 ). Of importance, other circumstances also affect outcomes, among these are time to diagnosis, time to antimicrobial therapy ( 40 ) and prevalence of antimicrobial resistance ( 42 ). Importantly, the various clinical scoring systems have been developed and validated with much of the same discrete subcriteria, but at very different levels for positivity. A typical example is the respiratory rate criterion that has a level for positivity that vary by almost 40% between scoring systems ( 7 ). Also, the more complex scoring systems, that require more data entries, are developed in conjunction with clinical judgement ( 29 ). A frequently cited meta-analysis of the IDSA-criteria reporting one major or three minor criteria had a pooled sensitivity of 84% and a specificity of 78% for predicting ICU admission ( 43 ). On the other hand, without a major criterion, a threshold of three or more minor criteria had a pooled sensitivity of 56% and specificity of 91% for predicting ICU admission ( 44 ). The Sepsis-2-criteria were generally appraised by physicians when launched in 2003 ( 34 ). According to this, the skilled physician should judiciously and comprehensively evaluate the myriad of signs and symptoms of possible sepsis to establish a reliable sepsis-diagnosis. Arbitrary criteria were thereby abandoned, and physician autonomy was re-established and accentuated. Since there is no threshold for the number of criteria fulfilled in Sepsis-2, we were unable to calculate test specifics and performance for our cohort. Oversimplification has been the mainstay of criticism to disease severity assessment systems for CAP in particular, and infections in general ( 45 ). Simplified systems for complex pathophysiological events may fail to correctly address the involvement of organ dysfunction, especially respiratory failure. For instance IDSA/ATS seem to predict mortality and requirements for mechanical ventilation and vasopressor much more accurately, thereby predicting the need for intensive care admission ( 4 ). In conclusion, we have here demonstrated that more sophisticated, less used, disease severity assessment systems, outperformed simplified and commonly used ones. This calls for a refined debate in Norwegian hospitals. 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Supplementary Files Systemsusedintheassessmentfordiseaseseverityincommunityacquiredpneumonia.docx Cite Share Download PDF Status: Published Journal Publication published 03 Mar, 2025 Read the published version in BMC Pulmonary Medicine → Version 1 posted Editorial decision: Revision requested 01 Aug, 2024 Editor assigned by journal 31 Jul, 2024 Submission checks completed at journal 31 Jul, 2024 First submitted to journal 30 Jul, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4828646","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":334764577,"identity":"1476e7d7-ba62-4b32-a71d-39526c35bcd1","order_by":0,"name":"Sandleen Iftikhar","email":"","orcid":"","institution":"St. Olavs university hospital","correspondingAuthor":false,"prefix":"","firstName":"Sandleen","middleName":"","lastName":"Iftikhar","suffix":""},{"id":334764579,"identity":"33e7a7f6-cbb4-424f-a380-8cc457acf539","order_by":1,"name":"Bjørn Waagsbø","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/ElEQVRIiWNgGAWjYBACA4YDcDYbA0MFkGInTcsZBgkGZoJaEICNgbGNCC3mjIePfS5gOCzP37/82YOP8+rq+JmZn0kw7rDBqcWy4Vjy7BkMhw1n3Hhjbjhz22EJyWY2MwnGM2m4HXbgjDEzD8NtxoYbZ9ikebcdkDA4zGBswNh2mKAW+/k3jj+T5p1TB9TC/pkoLYkbzjeYSfM2MAO18Bg+wKcF5BdmHoP/yRtv8Jgbzjh2WHJmM0/hg8Q23H4xlzh8mJmnIs123vnjzx58qKnj52dv33DgYxvuEGOQOMAAiR2JBCTRBGxKYYC/AcY4gE/ZKBgFo2AUjGQAAE9nVDy61C4DAAAAAElFTkSuQmCC","orcid":"","institution":"Regional Health Trust Mid","correspondingAuthor":true,"prefix":"","firstName":"Bjørn","middleName":"","lastName":"Waagsbø","suffix":""}],"badges":[],"createdAt":"2024-07-30 12:06:37","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4828646/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4828646/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12890-025-03550-y","type":"published","date":"2025-03-03T15:58:38+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":64005651,"identity":"c6df3f14-19f3-441c-8a1a-f7c3b69e7aee","added_by":"auto","created_at":"2024-09-04 21:39:09","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":31866,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eReceiver operating curve for SOFA, PSI and IDSA (for intra-hospital case fatality as outcome)\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4828646/v1/25eac5b27214dc174a3afc3d.png"},{"id":78190531,"identity":"a35551bf-cffa-4011-9db4-73cc9945551d","added_by":"auto","created_at":"2025-03-10 19:49:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":659209,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4828646/v1/ce863da2-8c3c-43a7-90a2-cf53440f0072.pdf"},{"id":64005650,"identity":"4fa2df8e-df17-417d-8db4-0e85aa1fa180","added_by":"auto","created_at":"2024-09-04 21:39:09","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":14464,"visible":true,"origin":"","legend":"","description":"","filename":"Systemsusedintheassessmentfordiseaseseverityincommunityacquiredpneumonia.docx","url":"https://assets-eu.researchsquare.com/files/rs-4828646/v1/e4c7c8550a6214de99260e33.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Assessment of severity in hospitalized community- acquired pneumonia by the use of validated scoring systems","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCommunity acquired pneumonia (CAP), albeit a common infection, can be a potential life-threatening illness and is the most common causes of sepsis (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). It is associated with high morbidity and mortality rates especially in the elderly and in patients with underlying comorbidities (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHospital admission rates can vary widely and are often not directly related to disease severity. A number of factors contribute to decisions on site of care and level of therapy, among these medication compliance, ability to maintain oral intake, cognitive or functional impairment, social circumstances, and disease severity. Clinicians can misinterpret or misjudge disease severity, leading to unwarranted therapy for relatively mild cases, or missed therapy for more severe cases. However, the risk of short-term mortality in CAP is more likely to be over-, rather than underestimated (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e The initiation of empirical antimicrobial therapy and the site of care are by most professional guideline recommendations determined by CAP severity at presentation. However, the evidence to support a standardized approach with the use of disease severity assessments for CAP, is still sparse in terms of improved outcomes (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). In countries with low rates of antimicrobial resistance, unwarranted broad-spectrum antimicrobial therapy is of particular concern.\u003c/p\u003e \u003cp\u003eA wide array of supporting systems have been developed and validated to aid clinicians when assessing disease severity in especially CAP. Of these systems, some are relatively effortless, while some are complex. In this study, we have applied these systems to a CAP-cohort, and established test properties and performance.\u003c/p\u003e "},{"header":"Patients and methods","content":"\u003cp\u003eStudy setting\u003c/p\u003e\u003cp\u003eA single-center, 1.000 bed, university teaching hospital in mid-Norway, accepting all patient categories, except transplantation surgery.\u003c/p\u003e\u003cp\u003eStudy population\u003c/p\u003e\u003cp\u003eWe identified all cases of CAP admitted to a university teaching hospital in Norway between 2016 and 2021. Due to labor-intensive registrations, only the months between March and May and the departments of medicine and pulmonology were eligible for inclusion. Months were chosen to represent an influenza-diminished period, regular hospital staffing situations, and standardized laboratory services.\u003c/p\u003e\u003cp\u003eFinal discharge diagnoses (ICD-10 between J13 to J18.9) were used to identify eligible cases for inclusion. We have earlier reported patient characteristics, aetiology, resistance patterns and antimicrobial therapy to these case series (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eStudy outcomes\u003c/p\u003e\u003cp\u003eThe primary outcome of this particular study was to report the validity and eligibility of established, and commonly used, clinical scoring systems for disease severity assessment in the emergency room setting for CAP patients. Sensitivity, specificity, and predictive values were calculated using intra-hospital case fatality and ICU-admittance as outcomes. Area under the receiver operating curve were used to depict performance of the assessments strategies for intra-hospital case fatality rate.\u003c/p\u003e\u003cp\u003eData collection\u003c/p\u003e\u003cp\u003eAll data registered were collected retrospectively after each ensuing year between 2016 and 2021. Included variables were patient characteristics, clinical characteristics present at admittance, radiological and laboratory findings, antimicrobial therapy, and clinical outcomes.\u003c/p\u003e\u003cp\u003eSeverity assessments\u003c/p\u003e\u003cp\u003eIn Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e we have presented the clinical scoring systems that were selected by the study group.\u003c/p\u003e\u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSelected scoring systems for disease severity.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSystem\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYear launhced\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSubcriteria\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eReference\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eValidation\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eqSOFA\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2016\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(\u003cspan additionalcitationids=\"CR9 CR10\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e–\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRB65\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e–\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCURB65\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2003\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSIRS (Sepsis 1)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1992\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNEWS2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2017\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(\u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e–\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSOFA (Sepsis-3)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2016\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(\u003cspan additionalcitationids=\"CR26\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e–\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePSI\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1997\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIDSA/ATS\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2007\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(\u003cspan additionalcitationids=\"CR31 CR32\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e–\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSepsis-2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2003\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eA myriade\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003ea\u003c/sup\u003eSee appendix for full outlining of system name\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003eb\u003c/sup\u003eNumber of subcriteria included in system\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003ec\u003c/sup\u003eReference to the original publication of the system\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003ed\u003c/sup\u003eRelevant validation studies\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWhen assessing disease severity by the use of qSOFA, CRB65, CURB-65, SIRS, and NEWS2 we calculated sensitivity, specificity, and predictive values by extracting the necessary subcriteria directly from the collected data.\u003c/p\u003e\u003cp\u003eWhen assessing consciousness, we considered new-onset confusion, disorientation, agitation, responds to voice, responds to pain, or unresponsive as relevant. To some extent, we used clinical judgement to deem the level of affected consciousness\u003c/p\u003e\u003cp\u003eWhen calculating the initial SOFA-score, we frequently used the arterial partial pressure of oxygen (P\u003csub\u003ea\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e) instead of P\u003csub\u003ea\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e/F\u003csub\u003ei\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e. In cases initially lacking measurements of P\u003csub\u003ea\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e, we imputed peripheral saturation of oxygen (SO\u003csub\u003e2\u003c/sub\u003e) to the calculation. This has earlier been demonstrated to accurately correlate and provide acceptable outcomes (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). We were able to calculate the SOFA-score to 96.4% of included cases.\u003c/p\u003e\u003cp\u003eThe PSI is much more detailed as 20 subcriteria are needed to calculate the score. A great proportion of these subcriteria are related to comorbidity status, to which we used some extent of clinical judgement. This represents, in deed, everyday clinical practice. None of the cases included were nursing home residents. We also used the serum creatinine level at \u0026gt; 120 µmol/L to represent new-onset kidney dysfunction instead of blood urea nitrogen concentration. To assess the haematocrit value we imputed three-folded haemoglobin levels according to earlier practice (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). PSI-score was ultimately calculated to 90.7% of included cases.\u003c/p\u003e\u003cp\u003e The 2007 IDSA/ATS clinical practice guideline for CAP stated a set of major or minor criteria for the disease severity assessment. The fulfilment of one major or at least three minor criteria would tentatively imply severe CAP. The minor criteria resemble CURB65-criteria, and the major criteria are invasive mechanical ventilation or septic shock with the need for vasopressors. An initial score could be established to 94.5% of included cases.\u003c/p\u003e\u003cp\u003eWe also set out to include the 2001 international sepsis definition and case criteria (Sepsis-2) in this study. The case criteria are aggregated from multiple variables, including general, inflammatory, hemodynamic, organ dysfunction, and tissue perfusion variables. In contrast to others systems, there is no established or suggestive level of number of subcriteria to fulfil the case criteria. Instead, judicious and extensive clinical judgement from the bedside attending doctor, to evaluate the myriad of presenting signs and symptoms, determines whether the infection is severe or not. Because this extensive individual evaluation universally was poorly documented in our study, we were unable to calculate scoring for all inclusions.\u003c/p\u003e\u003cp\u003eStatistical analyses\u003c/p\u003e\u003cp\u003eTo calculate sensitivity, specificity, and predictive values we used cross tabulation functions in IBM SPSS (Statistical Package for the Social Sciences), version 29. We defined thresholds for positive or negative test, which are summarized in Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThresholds for positive test.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSystem\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTest threshold for positive test\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eqSOFA\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 or more subcriteria\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRB65\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 or more subcriteria\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCURB65\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 or more subcriteria\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSIRS (Sepsis 1)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 or more subcriteria\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNEWS2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 or more points\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSOFA (Sepsis-3)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIncrease of 2 or more points\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePSI\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRisk class II with 90 or more points\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIDSA/ATS\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOne major or 3 or more minor criteria\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSepsis-2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo threshold established\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"2\"\u003eEthical considerations\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe study group has previously been granted approval by the hospital administration and data protections officials to conduct studies on lower respiratory tract infections. We also received approval by the Regional Committee for Medical and Health Research Ethics (REK 2017/1439), stating that inclusion consent was deemed unnecessary due to retrospective study design.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003ePatient characteristics and outcomes\u003c/p\u003e \u003cp\u003eOver six years we included 1.112 patients in this study. All patients were ultimately diagnosed and discharged from hospital with CAP as a primary diagnose, of which 91.4% were radiologically, and 43.7% microbiologically confirmed, on average for all years. We have previously reported patient characteristics, aetiology, resistance patterns and antimicrobial therapy in this case series (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Among included cases, mean age was 70.3 years and nearly 40% were aged above 65 years. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e summarizes relevant characteristics and outcomes.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eA selection of patient characteristics and outcomes of studied inclusions\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCharacteristics and outcomes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70.3 years\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProportion\u0026thinsp;\u0026gt;\u0026thinsp;65 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45.5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComorbidities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedian number of conditions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedian Charlson comorbidity index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProportion admitted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInvasive ventilation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSepsis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWithout shock\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.9%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWith shock\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.9%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLength of stay\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.2 (95% CI 6.9\u0026ndash;7.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCase fatality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIn-hospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.9%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30-day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e90-day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIntra-hospital case fatality\u003c/p\u003e \u003cp\u003eFirstly, we calculated sensitivity, specificity and predictive values to a positive test when the outcome was intra-hospital case fatality. Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e summarizes the calculations.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults when outcome is intra-hospital case fatality\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTest system\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eData\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSensitivity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSpecificity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePPV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNPV\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eqSOFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14/117 (12.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e911/995 (91.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e89.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRB65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36/117 (30.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e737/995 (74.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e90.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCURB65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38/117 (32.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e716/995 (72.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e90.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSIRS (Sepsis 1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e84/117 (71.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e321/995 (67.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e90.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNEWS2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e89/117 (76.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e377/995 (37.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e93.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSOFA (Sepsis-3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96,4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e90/96 (93.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e916/976 (93.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e60.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e99.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePSI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90,7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e76/88 (88.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e847/921 (92.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e47.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e98.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIDSA/ATS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e88/101 (87.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e961/1011 (95.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e63.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e98.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSepsis-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNA*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNA*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNA*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNA*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e*Not applicable\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSensitivity was low and specificity was somewhat reciprocally high among frequently used tests to assess disease severity when in-hospital case fatality was the outcome. Among the more infrequently used tests in Norway that require more extensive data entries, sensitivity and specificity were considerable higher, all reaching\u0026thinsp;\u0026gt;\u0026thinsp;87%. The predicted positive values were low for most tests, whilst the negative predicted values were all \u0026gt;\u0026thinsp;89%. Calculations in accordance with the Sepsis-2-criteria were universally unattainable.\u003c/p\u003e \u003cp\u003eIntensive care admittance\u003c/p\u003e \u003cp\u003eSecondly, we calculated sensitivity, specificity and predictive values to a positive test when the outcome was ICU-admittance from CAP. Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e summarizes the calculations.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults when the outcome is need for intensive care admittance.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTest system\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eData\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSensitivity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSpecificity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePPV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNPV\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eqSOFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20/68 (29.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e966/1014 (92.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e95.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRB65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44/68 (64.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e794/1044 (76.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e97.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCURB65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46/68 (67.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e773/1044 (74.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e97.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSIRS (Sepsis 1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58/68 (85.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e344/1044 (33.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e97.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNEWS2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55/68 (80.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e392/1044 (37.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e96.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSOFA (Sepsis 3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96,4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45/68 (66.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e484/1044 (46.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e95.5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePSI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90,7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70/78 (89.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e882/931 (94.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e58.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e99.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIDSA/ATS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e81/88 (92.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e881/963 (91.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e49.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e99.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSepsis-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNA*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNA*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNA*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNA*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e*Not applicable\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSensitivity and specificity varied considerably among frequently used tests to assess disease severity when the need for ICU admittance was the outcome. Among the more infrequently used tests that require more extensive data entries, sensitivity and specificity also varied, albeit all reaching\u0026thinsp;\u0026gt;\u0026thinsp;66%. The predicted positive values were universally low, whilst the negative predicted values were all \u0026gt;\u0026thinsp;95%.\u003c/p\u003e \u003cp\u003eArea under the receiver operating curve\u003c/p\u003e \u003cp\u003eWe estimated the area under the receiver operating characteristic (ROC) curve for the calculations when the outcome was intra-hospital case fatality. The frequently used severity assessment scoring systems, like qSOFA, CURB65, CRB65, SIRS and NEWS2, performed poorly as the curve closely resembled the reference line. The ROC-curves for scoring systems that need more extensive data entries are shown in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The estimated area for these curves all achieved values above 0.845, which were statistical significant. The area results are provided in Table \u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eArea under the receiver operating (ROC) curve.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTest system\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eArea\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStd error\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSOFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.955\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.93\u0026ndash;0.98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePSI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.845\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.79\u0026ndash;0.87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIDSA/ATS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.892\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.84\u0026ndash;0.94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we have demonstrated the low specificity and positive predicted value of frequently used strategies to assess disease severity in CAP. On the other hand, more sophisticated and complex systems like the SOFA-, PSI- or IDSA-criteria, provide superior results in terms of both sensitivity, specificity and predicted values. The results pinpoint limitations of simplified disease severity scoring systems, and underscore the importance of judicious clinical assessment by the skilled clinician.\u003c/p\u003e \u003cp\u003eValidation studies of clinical scorings systems in the infection severity assessment have shown various results. They have also been applied to various patient populations, at various location settings, and to predict various outcomes. We used intra-hospital case fatality and ICU-referral as outcomes, and concluded that qSOFA, CRB65, CURB65, SIRS and NEWS all provided inferior AUROC (~\u0026thinsp;0.50), and SOFA, PSI and IDSA/ATS superior AUROC (\u0026gt;\u0026thinsp;0.84).\u003c/p\u003e \u003cp\u003eDisease severity assessment is crucial for many reasons. Firstly, the initiation of empirical antimicrobial therapy is often based on the assessment of disease severity, as is also the choice of antimicrobial regimen (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). Secondly, recommendations on the timing of antimicrobial therapy administration vary according to disease severity (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). Thirdly, strategy to establish reliable microbiological aetiology is linked to disease severity assessment in infections (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). Fourthly, disease severity assessment determines site of care, both for community- or hospital settings. And fifthly, diseases severity assessments are prerequisites for determining overall therapy duration, oral transition, advanced diagnostic and therapeutic approaches, hospital discharge, and more.\u003c/p\u003e \u003cp\u003eClinical scoring systems to assess disease severity are attempts to provide the attending clinician with information to judge infections especially in the emergency room setting. Of importance, most systems was originally derived in patients already suspected of having infection (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). The CURB65-, CRB65-, PSI- and the IDSA-criteria targeted lower respiratory tract infections specifically, while all other systems aimed to be applicable regardless of infection site. However, all systems tend to simplify complex processes of infection, inflammation and pathophysiology of heterogeneous patient groups, pathogens, and infection sites (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). Of importance, other circumstances also affect outcomes, among these are time to diagnosis, time to antimicrobial therapy (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e) and prevalence of antimicrobial resistance (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eImportantly, the various clinical scoring systems have been developed and validated with much of the same discrete subcriteria, but at very different levels for positivity. A typical example is the respiratory rate criterion that has a level for positivity that vary by almost 40% between scoring systems (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Also, the more complex scoring systems, that require more data entries, are developed in conjunction with clinical judgement (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). A frequently cited meta-analysis of the IDSA-criteria reporting one major or three minor criteria had a pooled sensitivity of 84% and a specificity of 78% for predicting ICU admission (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e). On the other hand, without a major criterion, a threshold of three or more minor criteria had a pooled sensitivity of 56% and specificity of 91% for predicting ICU admission (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe Sepsis-2-criteria were generally appraised by physicians when launched in 2003 (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). According to this, the skilled physician should judiciously and comprehensively evaluate the myriad of signs and symptoms of possible sepsis to establish a reliable sepsis-diagnosis. Arbitrary criteria were thereby abandoned, and physician autonomy was re-established and accentuated. Since there is no threshold for the number of criteria fulfilled in Sepsis-2, we were unable to calculate test specifics and performance for our cohort.\u003c/p\u003e \u003cp\u003eOversimplification has been the mainstay of criticism to disease severity assessment systems for CAP in particular, and infections in general (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e). Simplified systems for complex pathophysiological events may fail to correctly address the involvement of organ dysfunction, especially respiratory failure. For instance IDSA/ATS seem to predict mortality and requirements for mechanical ventilation and vasopressor much more accurately, thereby predicting the need for intensive care admission (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn conclusion, we have here demonstrated that more sophisticated, less used, disease severity assessment systems, outperformed simplified and commonly used ones. This calls for a refined debate in Norwegian hospitals. It is our belief that clinicians should assess CAP severity judiciously and comprehensively by the use of severity assessment scoring systems in conjunction with clinical judgement.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eSI and BW contributed to the data prosessing, the writing process, and to establish figures and tables. BW contributed, in addition, to the collection of data, and with the idea of publishing.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eCilloniz C, Dominedo C, Garcia-Vidal C, Torres A. Community-acquired pneumonia as an emergency condition. Curr Opin Crit Care. 2018;24(6):531-9.\u003c/li\u003e\n\u003cli\u003eMontull B, Menendez R, Torres A, Reyes S, Mendez R, Zalacain R, et al. Predictors of Severe Sepsis among Patients Hospitalized for Community-Acquired Pneumonia. PLoS One. 2016;11(1):e0145929.\u003c/li\u003e\n\u003cli\u003eLaporte L, Hermetet C, Jouan Y, Gaborit C, Rouve E, Shea KM, et al. Ten-year trends in intensive care admissions for respiratory infections in the elderly. Ann Intensive Care. 2018;8(1):84.\u003c/li\u003e\n\u003cli\u003eTorres A, Chalmers JD, Dela Cruz CS, Dominedo C, Kollef M, Martin-Loeches I, et al. Challenges in severe community-acquired pneumonia: a point-of-view review. 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Crit Care Med. 2009;37(4):1317-21.\u003c/li\u003e\n\u003cli\u003eKarakochuk CD, Hess SY, Moorthy D, Namaste S, Parker ME, Rappaport AI, et al. Measurement and interpretation of hemoglobin concentration in clinical and field settings: a narrative review. Ann N Y Acad Sci. 2019;1450(1):126-46.\u003c/li\u003e\n\u003cli\u003eEvans L, Rhodes A, Alhazzani W, Antonelli M, Coopersmith CM, French C, et al. Surviving Sepsis Campaign: International Guidelines for Management of Sepsis and Septic Shock 2021. Crit Care Med. 2021;49(11):e1063-e143.\u003c/li\u003e\n\u003cli\u003eSinger M, Deutschman CS, Seymour CW, Shankar-Hari M, Annane D, Bauer M, et al. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA. 2016;315(8):801-10.\u003c/li\u003e\n\u003cli\u003ePeri AM, Stewart A, Hume A, Irwin A, Harris PNA. New Microbiological Techniques for the Diagnosis of Bacterial Infections and Sepsis in ICU Including Point of Care. Curr Infect Dis Rep. 2021;23(8):12.\u003c/li\u003e\n\u003cli\u003eSeymour CW, Gesten F, Prescott HC, Friedrich ME, Iwashyna TJ, Phillips GS, et al. Time to Treatment and Mortality during Mandated Emergency Care for Sepsis. N Engl J Med. 2017;376(23):2235-44.\u003c/li\u003e\n\u003cli\u003eGhazal P, Rodrigues PRS, Chakraborty M, Oruganti S, Woolley TE. Challenging molecular dogmas in human sepsis using mathematical reasoning. EBioMedicine. 2022;80:104031.\u003c/li\u003e\n\u003cli\u003eKadri SS, Lai YL, Warner S, Strich JR, Babiker A, Ricotta EE, et al. Inappropriate empirical antibiotic therapy for bloodstream infections based on discordant in-vitro susceptibilities: a retrospective cohort analysis of prevalence, predictors, and mortality risk in US hospitals. Lancet Infect Dis. 2021;21(2):241-51.\u003c/li\u003e\n\u003cli\u003eMarti C, Garin N, Grosgurin O, Poncet A, Combescure C, Carballo S, Perrier A. Prediction of severe community-acquired pneumonia: a systematic review and meta-analysis. Crit Care. 2012;16(4):R141.\u003c/li\u003e\n\u003cli\u003eChalmers JD, Mandal P, Singanayagam A, Akram AR, Choudhury G, Short PM, Hill AT. Severity assessment tools to guide ICU admission in community-acquired pneumonia: systematic review and meta-analysis. Intensive Care Med. 2011;37(9):1409-20.\u003c/li\u003e\n\u003cli\u003eShady A, Sjoerd HW. van Bree. Community-acquired pneumonia. Anaesth Int Care Med. 2022;23(10):613-19.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-pulmonary-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pulm","sideBox":"Learn more about [BMC Pulmonary Medicine](http://bmcpulmmed.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pulm/default.aspx","title":"BMC Pulmonary Medicine","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Community-acquired pneumonia, severity assessment, antimicrobial stewardship, antimicrobial therapy","lastPublishedDoi":"10.21203/rs.3.rs-4828646/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4828646/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e \u003cp\u003eSeverity assessment of community-acquired pneumonia (CAP) is essential for many purposes. Among these are the microbiological confirmation strategy and choice of empirical antimicrobial therapy. However, many severity assessment systems have been developed to aid clinicians to reach reliable predictions of severe outcomes.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe aimed to apply nine disease severity assessment scoring systems to a large 2016 to 2021 CAP cohort in order to achieve test sensitivity, specificity and predictive values. We used intra-hospital case fatality rate and the need for intensive care therapy as outcomes. The area under the receiver operating characteristic (ROC) curve was used to display test performance.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eA total of 1.112 CAP episodes were included in the analysis, of which 91.4% were radiologically, and 43.7% were microbiologically confirmed. When intra-hospital case fatality was set as outcome, frequently used tests with few data entries typically underperformed as compared to infrequently used tests that require more comprehensive data entries. Comparable results were gained when intensive care admittance was set as outcome. The area under the receiving operating curve was 0.0955, 0.845 and 0.892 for the sequential organ failure assessment (SOFA), pneumonia severity index (PSI), and the Infectious Diseases Society of America/American Thoracic Society definitions, respectively.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion\u003c/b\u003e\u003c/p\u003e \u003cp\u003eCAP severity assessment remains important. Simplified scoring systems underperformed as compared to more comprehensive and sophisticated ones.\u003c/p\u003e","manuscriptTitle":"Assessment of severity in hospitalized community- acquired pneumonia by the use of validated scoring systems","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-09-04 21:39:04","doi":"10.21203/rs.3.rs-4828646/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-08-01T13:02:01+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-07-31T14:01:40+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-07-31T14:01:29+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pulmonary Medicine","date":"2024-07-30T12:05:23+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pulmonary-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pulm","sideBox":"Learn more about [BMC Pulmonary Medicine](http://bmcpulmmed.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pulm/default.aspx","title":"BMC Pulmonary Medicine","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"98ca806d-8962-4cf9-b2d4-317c46eb1a09","owner":[],"postedDate":"September 4th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-03-10T19:46:53+00:00","versionOfRecord":{"articleIdentity":"rs-4828646","link":"https://doi.org/10.1186/s12890-025-03550-y","journal":{"identity":"bmc-pulmonary-medicine","isVorOnly":false,"title":"BMC Pulmonary Medicine"},"publishedOn":"2025-03-03 15:58:38","publishedOnDateReadable":"March 3rd, 2025"},"versionCreatedAt":"2024-09-04 21:39:04","video":"","vorDoi":"10.1186/s12890-025-03550-y","vorDoiUrl":"https://doi.org/10.1186/s12890-025-03550-y","workflowStages":[]},"version":"v1","identity":"rs-4828646","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4828646","identity":"rs-4828646","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}