Accepted Manuscript Positive predictive value of primary inpatient discharge diagnoses of infection among cancer patients in the Danish National Registry of Patients Louise Holland-Bill , MD Hairong Xu , MD, PhD Henrik Toft Sørensen , MD, PhD, DMSc John Acquavella , PhD Claus Sværke , MSc Henrik Gammelager , MD Vera Ehrenstein , MPH, DSc PII:

S1047-2797(14)00192-6

DOI:

10.1016/j.annepidem.2014.05.011

Reference:

AEP 7661

To appear in:

Annals of Epidemiology

Received Date: 19 December 2013 Revised Date:

9 May 2014

Accepted Date: 20 May 2014

Please cite this article as: Holland-Bill L, Xu H, Toft Sørensen H, Acquavella J, Sværke C, Gammelager H, Ehrenstein V, Positive predictive value of primary inpatient discharge diagnoses of infection among cancer patients in the Danish National Registry of Patients, Annals of Epidemiology (2014), doi: 10.1016/j.annepidem.2014.05.011. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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Positive predictive value of primary inpatient discharge diagnoses of infection among cancer patients in the Danish National Registry of Patients

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Authors and affiliations: Louise Holland-Bill* MD; Hairong Xu§ MD, PhD; Henrik Toft Sørensen* MD, PhD, DMSc; John Acquavella§ PhD; Claus Sværke* MSc; Henrik Gammelager#* MD; Vera Ehrenstein* MPH, DSc

for Observational Research, Amgen International, Amgen Inc. Thousand Oaks, CA, USA.

#Department

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§Center

of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark.

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*Department

of Clinical Epidemiology, Aalborg University Hospital, Aalborg, Denmark.

Corresponding author: Louise Holland-Bill, MD

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Department of Clinical Epidemiology, Aarhus University Hospital Olof Palmes Allé 43-45, 8200 Aarhus N, Denmark

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E-Mail: [email protected], Phone/Fax: +1 (415“ 359 6814 / + 45 871 67215

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Abbreviated running title: Validity of ICD-10 codes for infection Manuscript word count: 2697 Abstract word count: 198

Number of tables and figures: 3 tables and 3 appendix tables containing supplementary material (uploaded separately“

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Abstract Purpose: Purpose: Pharmacovigilance studies of cancer treatment frequently monitor infections. Predictive

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values of algorithms identifying disease depend on prevalence of the disease in the population under study. We therefore estimated the positive predictive value (PPV“ of primary inpatient

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diagnosis of infection among cancer patients in the Danish National Registry of Patients (DNRP“.

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Methods: The algorithm to identify infections in the DNPR was based on International

Classification of Diseases, 10th revision (ICD-10“ codes. A physician blinded to the type of sampled infection, reviewed the medical charts, and assessed presence and type of infection.

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Using the physician global assessment (PGA“ as gold standard, we computed PPVs with and without requiring agreement on infection type.

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Results: We retrieved 266/272 (98%“ medical charts. Presence of infection was confirmed in 261 patients, resulting in an overall PPV of 98% (95% confidence interval [CI]: 96-99%“. When

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requiring agreement on infection type overall PPV was 77%. For skin infections, pneumonia and sepsis PPVs were 79%, 93% and 84, respectively. For these infections, we additionally calculated PPVs using evidence-based criteria as reference. PPV was similar for pneumonia, but lower for skin infections and sepsis.

ACCEPTED MANUSCRIPT 3 Conclusions: The DNRP is suitable for monitoring infections requiring hospitalization among

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cancer patients.

Keywords: Keywords Cancer; Infection; International Classification of Disease Codes; predictive value of

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CI: Confidence interval

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Abbreviations

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tests; Pharmacoepidemiology.

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DNRP: Danish National Registry of Patients ICD-9: International Classification of Diseases, 9th Revision ICD-10: International Classification of Diseases, 10th Revision PGA: Physician Global Assessment PPV: Positive predictive value

ACCEPTED MANUSCRIPT 4 Background Infections frequently complicate cancer and cancer-related therapies, and are therefore often

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examined in pharmacovigilance studies of cancer treatments. Medical databases are commonly used to monitor adverse drug reactions occurring in routine clinical practice (1“. The Danish

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National Registry of Patients (DNRP“ is a potentially valuable data source for monitoring such

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events. It covers all in-hospital stays, outpatient clinic visits, and emergency contacts, in the setting of Denmark s universal health care (2“. However, as the DNRP was not primarily developed to support specific studies or to monitor specific events, the validity of adverse events

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recorded in the DNRP requires assessment (3“.

Previous studies evaluating the positive predictive value (PPV“ of codes for infections in the International Classification of Diseases, 9th revision (ICD-9“ using administrative data have

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found highly variable results, ranging from 1.3% to 100% depending on type of infection and

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population examined (4“. In Denmark, two studies estimated PPVs infections recorded in the DNRP based on the ICD-10 (5,6“. Firstly, a study from 1998 found a low PPV of codes for bacteremia (septicemia“ compared against a database of all positive blood cultures from a clinical microbiology department and medical chart review (5“. In contrast, among patients hospitalized for pneumonia in 1994-2003, a high PPV was found for ICD-10 codes of pneumonia

ACCEPTED MANUSCRIPT 5 (6). Predictive values of algorithms for identifying disease depend on the prevalence of the disease in the population under study, and must therefore be established for each population of

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interest (7“. To date, no study has examined the validity of hospital discharge diagnoses

recorded in administrative registries for identifying infectious conditions among cancer patients.

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We estimated the PPV of the ICD-10 codes used to record primary inpatient discharge

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diagnoses of infection in the DNRP among patients with a history of cancer. We estimated PPVs both regardless of infection type and requiring agreement by type of infection. Furthermore, we estimated the PPV of algorithms to identify three infections of special interest: skin infection,

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pneumonia and sepsis. The study was performed to validate the use of hospital discharge diagnoses in future pharmacoepidemiologic studies with a primary focus on hospitalized

Setting

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Methods

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infections endpoint in patients with solid malignant tumors (4,8“.

The Danish National Health Service provides tax-supported medical care for the entire Danish population, guaranteeing unfettered access to public hospitals free-of-charge (9“. Since 1968, the Danish Civil Registration System has assigned a unique 10-digit identification number ( the CPR

ACCEPTED MANUSCRIPT 6 number “ to each person born in or immigrating to Denmark. This number, which encodes date of birth and sex, is used in all public records and allows unambiguous individual-level linkage

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between all Danish medical databases and virtually complete follow-up of patients receiving care from the Danish universal health service. The Danish Civil Registration System is updated daily

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and tracks residence, migration and vital status of all Danish residents (9“. The Danish National

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Registry of Patients (DNRP“ contains records of all inpatient stays to Danish hospitals since 1977, and all contacts with emergency departments and outpatient clinics since 1995. Each record in the DNRP contains the patient s CPR number, dates of admission and discharge, one

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primary diagnosis, reflecting the main reason for the hospital contact, and up to 19 secondary diagnoses, coded according to the International Classification of Diseases , 10th revision (ICD10“ from 1994 onwards (2,10“. Diagnoses are assigned by the attending physician at time of

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hospital discharge. Data are initially recorded in the hospitals patient administrative system and

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then electronically transferred to the DNPR. Reporting to the DNPR is mandatory, and DNPR data provides the basis for financial reimbursement to hospitals from the government (9“.

Study population

ACCEPTED MANUSCRIPT 7 We used the DNRP to identify all patients with an inpatient hospital stay at Aalborg University Hospital (AUH“, who had a primary discharge diagnosis of preselected infectious conditions

secondary care

including cancer care

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between 1 January 2006 and 31 December 2010, inclusive. AUH is the main provider of

to residents of the North Denmark Region, with a

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population of 580 000 inhabitants (11“. We restricted the study population to patients with a

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history of a solid malignancy (ICD-10 codes C00-C79, excluding non-melanoma skin cancer C44“ within five years before the admission with an infection. For each patient, we considered only the first inpatient hospital stay with a primary diagnosis of infection during the study period.

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Sampling was restricted to patients older than 18 years at the time of cancer diagnosis. We planned to sample at least 250 patients with a diagnosis of any infection, with additional sampling allowed to ensure at least 40 observations of each of the potential infections of special

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interest: pneumonia, skin infection and sepsis. The ICD-10 codes used for the case-

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ascertainment algorithms for infections are listed in Appendix A.

Medical chart review

We used medical chart review to obtain information on presence and type of infections (3“. We used each patient s CPR number to link between registry data and the medical chart (9“. The

ACCEPTED MANUSCRIPT 8 identified charts were abstracted by one of two study physicians, using a standard Medical Chart Abstraction Form (Appendix B“. The form was used to collect information on evidence-based

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criteria for the infections of special interest, as outlined in the validation study in a US Veterans Affair hospital setting by Schneeweiss and colleagues based on published guidelines (12“. Based

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on the information recorded in the chart, the reviewing physician assessed the presence and type

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of infection and documented it in the abstraction form as an overall Physician Global Assessment (PGA“ (Appendix B“. If charts were unavailable, this was noted and reported. The reviewers were blinded to type of infection and to the evidence-based diagnostic criteria for given infections. The

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evidence-based diagnostic criteria are described in Appendix C. The abstraction form was tested for comprehensibility, validity of questions and reproducibility of information extracted, using a random sample of 8 medical charts. Possible sources of error and discrepancy were identified

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and corrected in the abstraction form before initiation of chart review.

Statistical Analysis

We described patients with available charts in terms of sampled ICD-10 codes, sex, age at diagnosis of infection, length of hospital stay and comorbidity level (using the Charlson

ACCEPTED MANUSCRIPT 9 Comorbidity Index (CCI“ score excluding the patient s cancer diagnosis“ (13“. We extracted data on comorbidities from the DNRP for up to five years prior to the infection-related admission.

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For the primary aim, the PPV was calculated as the proportion of patients for whom a primary discharge diagnosis of infection was confirmed as an infection by medical record review using

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the PGA as the gold standard, with and without requiring agreement by type of infection.

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For the secondary aim, pertaining to infections of special interest, we additionally computed the PPV using as the gold standard information on evidence-based criteria abstracted from the chart. All PPV estimates were reported with 95% confidence intervals (CI“, using Jeffrey s method for

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binomial proportions.

The overall sample size was targeted to include 250 randomly selected patients with a

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primary discharge diagnosis of infection to allow estimating 95% confidence limits within ±6%. It

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was planned to include a minimum of 40 patients for each specific infectious condition of interest (pneumonia, skin infection and sepsis“ to allow estimating 95% confidence limits within ±14%, which is considered ample to assess the PPV for a single infection.

ACCEPTED MANUSCRIPT 10 The study was approved by the Danish Data Protection Agency (record numbers 2010-41-5171,

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2012-41-0045“.

Results

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We sampled 272 potential cases of infection associated with inpatient stays, including at

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least 40 potential cases of the infections of special interest and could retrieve medical charts for 266 (98%“ of the patients. Table 1 shows the distribution of the sampled ICD-10 codes among the 266 patients with available medical charts. Median age of these patients was 67 years

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(quartiles: 59-76 years“, and 118 (44%“ of them were women. Median length of hospital stay was 6 days (quartiles: 3-11 days“, and more than half of the patients had no comorbidity after excluding cancer diagnosis (Table 2“. According to the information recorded in medical charts,

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one-third of the patients had a history of an earlier infection and 18% of the patients had

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undergone a surgery (Table 2“.

The presence of any infection, regardless of type, was confirmed by PGA in 261 of the 266 patients, yielding an overall PPV of 98% (95% CI: 96-99%“ (Table 3“. The remaining five patients had ICD-10 codes for pneumonia (2 patients“, cellulitis (1 patient“, intestinal infection (1 patient“ and urinary tract infection (1 patient“. When requiring agreement on the specific type of

ACCEPTED MANUSCRIPT 11 infection (as defined in Table 1“, the overall PGA-based PPV was 80% (95% CI: 75-85%“. The PGA-based PPVs were 79% (95% CI: 64-90%“ for skin infection, 93% (95% CI: 86-97%“ for

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pneumonia, and 84% (95% CI: 72-93%“ for sepsis (Table 3“. Using broader definitions of

infection types (as listed in Table 1“, resulted in 21 additional confirmations, yielding a PPV for

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the broader categorization of type of infection of 88% (95% CI: 84-92%“. For the infections of

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special interest, the PPVs computed using evidence-based criteria as the gold standard were 89% (95% CI: 82-94%“ for pneumonia, 45% (95% CI: 30-60%“ for skin infection, and 69% (95%

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CI: 55-81%“ for sepsis (Table 3“.

Discussion

Using information from medical charts to confirm primary inpatient discharge diagnoses of

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infection recorded in the DNRP using ICD-10 codes, we found that the overall positive predictive

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value was 98% for presence of any type of infection, and 80% when agreement by infection type was required. Among the infections of special interest, the PPV for pneumonia was close to 90% confirmed by both physician global assessment and evidence-based criteria. The PPV was lower for sepsis (84%“ and for skin infection (79%“ when confirmed by PGA, and decreased when confirmation by evidence-based criteria was required.

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PPV based on agreement on infection type was lower than the overall PPV. One reason

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for this was low confirmation rates for bacteremia (only 1 of 13 potential cases was confirmed“. Patients with potential bacteremia were sampled using ICD-10 code A499, which, in the Danish

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version of the classification, includes both unspecified bacterial infection and unspecified

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bacteremia (codes A499 and A499A“. A large portion of urinary tract infections was not confirmed on the level of specific type of infection (bladder infection, kidney infection and other urinary tract infection“. In addition, infections coded as cellulitis/erysipelas that were not

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confirmed by the PGA on the level of specific type of infection were assessed as other skin infection . Applying a broader categorization increased the PPV for skin infection, consistent with the findings of a study conducted in a primary care setting (14“, and for infections overall. This

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suggests that the algorithm under study may be more suited for identification of broad than

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narrow infection types, for at least some infections. The PPV based on evidence-based confirmation criteria was considerably lower than PPV calculated based on PGA-confirmed infections for skin infection and sepsis. This could be due to a discrepancy between the criteria for duration of treatment with antibiotics (at least 7 days of intravenous antibiotics for sepsis and at least 7 days of antibiotics for skin infection

ACCEPTED MANUSCRIPT 13 [administration route unspecified]“ and daily clinical practice. The primary reason for the observed difference in evidence-criteria based PPV and PGA-based PPV, is however likely to be

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lack of detailed documentation in medical records. Consistent with our results, lack of

documentation would be suspected to have smaller impact in severe infections such as sepsis,

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than for less severe conditions such as skin infections. Another major contributor to the decline in

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PPV for sepsis when using evidence-based confirmation criteria could be that evidence of infection, such as positive culture, positive x-ray finding, or petechiae, contemporaneous to a systemic inflammatory response syndrome, may not be easily obtained. Still, physicians may be

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inclined to give the diagnosis, if the overall clinical picture points toward sepsis, regardless of whether all criteria have been fulfilled.

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This study is the first to examine the validity of an ICD-10-based algorithm for a broad

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range of infection diagnoses among cancer patients (4“. In another Danish study, Thomsen et al. estimated PPV of ICD-10 codes for pneumonia in the general adult population (6“. Consistent with our results, they reported a PPV of 90% (95% CI: 82-95%“, based on a slightly different ICD10-based algorithm. For septicemia diagnoses in the DNRP, Madsen et al. estimated a PPV of 22% (95% CI: 13-31%“ when compared against a microbiology database (5“. Because the

ACCEPTED MANUSCRIPT 14 Danish version of ICD-10 applied at the time of their study used the term septicemia , instead of sepsis as is currently used, patients had to have a positive blood culture in order to fulfill the

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criteria for septicemia, which likely explains the low PPV. In our study, the diagnosis of sepsis did not require a positive blood culture. Also consistent with our results are findings of a study by

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Drahos et al. on the PPV of ICD-9 coding of pneumonia and Herpes simplex virus in a multi-

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specialty inpatient and outpatient setting in which the PPV for pneumonia was found to be 88% (15“. In a validation study of ICD-9 codes, Schneeweiss and colleagues found that hospital discharge diagnoses recorded in the US Veterans Affairs administrative database accurately

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identified cases of infections leading to hospitalization (12“, with the overall PPV of 80% for serious bacterial infections, and PPVs ranging from 66% to 100% for selected other infections, and the overall PPV of 76% for opportunistic infections (12“. These estimates are overall

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consistent with our results. However, in contrast to Schneeweiss et al. s PPV of 70% for cellulitis

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confirmed using evidence-based criteria, the corresponding estimate in our study was 45%. We adopted the evidence-based criteria for this study from the study by Schneeweiss et al. The lower PPV for skin infection (including cellulitis“ in our study could be due to differences between the US and Denmark in the type of information routinely recorded in medical charts. Altogether, the evidence suggests high overall validity of primary inpatient diagnoses of infections in routine

ACCEPTED MANUSCRIPT 15 administrative databases, with variation according to the type of infection. The validity of

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pneumonia diagnoses was high across the board.

The strengths of our study include the access to medical records with detailed clinical and

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laboratory data. We retrieved 98% of the randomly sampled medical charts, suggesting negligible

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selection bias. This study was conducted in a well-defined geographic area in Denmark, and all potential cases of infection were identified in a university-hospital setting. Given Denmark s universal health care, we assume minor regional variation in provision of and access to health

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care. Therefore it is reasonable to assume that results from a large university hospital generalize at least to other large hospitals in Denmark (16-18“. Some limitations should be considered when interpreting our results. We selected the first

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recorded hospitalization with a primary diagnosis of infection after the cancer diagnosis, meaning

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that we evaluated only incident cases of serious infections among cancer patients. Patients could, between the cancer diagnosis and the sampled infection, have had infections which either did not require hospitalization or was not the primary reason for hospitalization. Furthermore, we did not distinguish between infections leading to hospitalization or infections developing as a complication to hospitalization. Predictive values of classification algorithms for identifying a

ACCEPTED MANUSCRIPT 16 disease depend on the prevalence of the disease in the population. Because cancer is associated with increased risk of infections (19“, the PPV estimates reported here might not be

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comparable to those reported in non-cancer patient populations (20“. Sensitivity and specificity of algorithms are independent on disease prevalence; however, by design we could not estimate

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these properties in the present study. The PPV indicates a proportion of patients with selected

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ICD-10 codes who have an infection, but carries no information about true infections to which no ICD-10 code was assigned at discharge. Lastly, our PPVs may have been overestimated by requiring only one of the two physicians to confirm presence and type presence and type of

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infection rather than performing dual blinded chart abstraction.

Conclusion

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Primary inpatient discharge diagnoses of an infection in the DNRP correspond to a true infection

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in more than 95% of cases. PPV varies by type of infection and granularity of infection definition. PPV was high for pneumonia, but lower for sepsis and skin infections, likely due to variability in record-keeping or international differences in medical practice.

ACCEPTED MANUSCRIPT 17 Acknowledgements:

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The authors thank Mary Nguyen Nielsen for providing help carrying out medical chart review.

ACCEPTED MANUSCRIPT 18 References (1“ Dreyer NA, Velentgas P. Registries. In: Strom BL, Kimmel SE, Hennessy S, editors.

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Pharmacoepidemiology. 5th ed. Oxford, UK: Wiley-Blackwell; 2012. p. 331-346. (2“ Andersen TF, Madsen M, Jorgensen J, Mellemkjoer L, Olsen JH. The Danish National Hospital Register. A valuable source of data for modern health sciences. Dan Med Bull 1999 Jun;46(3“:263-268.

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(3“ Sorensen HT, Sabroe S, Olsen J. A framework for evaluation of secondary data sources for epidemiological research. Int J Epidemiol 1996 Apr;25(2“:435-442.

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(4“ Barber C, Lacaille D, Fortin PR. Systematic review of validation studies of the use of administrative data to identify serious infections. Arthritis Care Res (Hoboken“ 2013 Aug;65(8“:1343-1357.

(5“ Madsen KM, Schonheyder HC, Kristensen B, Nielsen GL, Sorensen HT. Can hospital discharge diagnosis be used for surveillance of bacteremia? A data quality study of a Danish

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hospital discharge registry. Infect Control Hosp Epidemiol 1998 Mar;19(3“:175-180. (6“ Thomsen RW, Riis A, Norgaard M, Jacobsen J, Christensen S, McDonald CJ, et al. Rising incidence and persistently high mortality of hospitalized pneumonia: a 10-year population-based

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study in Denmark. J Intern Med 2006 Apr;259(4“:410-417. (7“ Altman DG, Bland JM. Diagnostic tests 2: Predictive values. BMJ 1994 Jul 9;309(6947“:102.

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(8“ Carnahan RM, Herman RA, Moores KG. A systematic review of validated methods for identifying transfusion-related sepsis using administrative and claims data. Pharmacoepidemiol Drug Saf 2012 Jan;21 Suppl 1:222-229. (9“ Pedersen CB. The Danish Civil Registration System. Scand J Public Health 2011 Jul;39(7 Suppl“:22-25.

(10“ Lynge E, Sandegaard JL, Rebolj M. The Danish National Patient Register. Scand J Public Health 2011 Jul;39(7 Suppl“:30-33.

ACCEPTED MANUSCRIPT 19 (11“ The Danish Regions. Region Statistics. Available at: http://www.regioner.dk/Om+Regionerne/Statistik+ny.aspx. Accessed 4/17/2013, 2013. (12“ Schneeweiss S, Robicsek A, Scranton R, Zuckerman D, Solomon DH. Veteran's affairs

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hospital discharge databases coded serious bacterial infections accurately. J Clin Epidemiol 2007 Apr;60(4“:397-409.

(13“ Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 1987;40(5“:373-

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383.

(14“ Levine PJ, Elman MR, Kullar R, Townes JM, Bearden DT, Vilches-Tran R, et al. Use of

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electronic health record data to identify skin and soft tissue infections in primary care settings: a validation study. BMC Infect Dis 2013 Apr 10;13:171-2334-13-171. (15“ Drahos J, Vanwormer JJ, Greenlee RT, Landgren O, Koshiol J. Accuracy of ICD-9-CM codes in identifying infections of pneumonia and herpes simplex virus in administrative data. Ann Epidemiol 2013 May;23(5“:291-293.

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(16“ Erichsen R, Strate L, Sorensen HT, Baron JA. Positive predictive values of the International Classification of Disease, 10th edition diagnoses codes for diverticular disease in the Danish National Registry of Patients. Clin Exp Gastroenterol 2010;3:139-142.

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(17“ Ministry of Health and Prevention. Health care in Denmark. 2008; Available at: http://www.sum.dk/Aktuelt/Publikationer/~/media/Filer%20-

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%20Publikationer_i_pdf/2008/UK_Healthcare_in_dk/pdf.ashx. Accessed April/15, 2014. (18“ Zalfani J, Olsen M, Frøslev T, Ben Ghezala I, Gammelager H, Arendt J, et al. Positive predictive value of the International Classification of Diseases, 10th edition diagnosis codes for anemia caused by bleeding in the Danish National Registry of Patients Clinical Epidemiology 2012:327.

(19“ Bodey GP. Infection in cancer patients. A continuing association. Am J Med 1986 Jul 28;81(1A“:11-26.

ACCEPTED MANUSCRIPT 20 (20“ Stevenson KB, Khan Y, Dickman J, Gillenwater T, Kulich P, Myers C, et al. Administrative coding data, compared with CDC/NHSN criteria, are poor indicators of health care-associated

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infections. Am J Infect Control 2008 Apr;36(3“:155-164.

ACCEPTED MANUSCRIPT 21 Tables

Specific infection types

Broad infection types

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Table 1. Distribution Distribution of the types of infections and ICDICD-10 codes among the 272 sampled cancer patients. Diagnostic codes according to the

N (%“

Danish version of the ICD-10

Other respiratory tract Infection

Respiratory tract

J139, J151, J152, J157, J159, J180,

infection

J181

Respiratory tract

J189, B599, J019, J039, J209, J320

infection Intestinal infection

Intestinal Infection

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Pneumonia

Other skin infection

Skin infection

Bladder infection

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K811

Skin infection

7 (2.6“

A047, A099, B962, K122, K350, K359, K570, K573, K610, K611, K612, K810,

Cellulitis + erysipelas

95 (34.9“

A469, L030, L031, L038, L089

26 (9.6“ 33 (12.1“ 6 (1.8“

Urinary tract infection

N300, N309

23 (8.5“

Kidney infection

Urinary tract infection

N109, N151

3 (1.1“

Other urinary Tract Infection

Urinary tract infection

N390

7 (2.6“

Endocarditis

Endocarditis

I330

2 (0.7“

Meningitis

Intracranial infection

B003

1 (0.4“

Bacteremia

Bacteremia

A499, A499A

13 (4.8“

Sepsis

Sepsis

A408, A409, A410, A412, A415, A418,

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L021, L022, L029, H620

A419, B377

46 (16.9“

Bone/Joint infection

M860

1 (0.4“

Septic arthritis

Bone/Joint infection

M009

1 (0.4“

Tuberculosis

A169, A180

2 (0.7“

Aspergillosis

B440

1 (0.4“

Other

B370, B378, K122, H031, H702,

5 (1.8“

Tuberculosis Other Total

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Aspergillosis

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Osteomyelitis

ICD-10, International Classification of Diseases, Tenth Revision

272 (100“

ACCEPTED MANUSCRIPT 22 Table 2. Characteristics of cancer patients with a primary discharge diagnosis of infection available for chart review.

Female

118 (44.4“

Male

148 (55.6“

Age at infection diagnosis, years, median (quartiles“

67.1 (58.8 76.2“

Length of hospital stay, days, median (quartiles“

6.0 (3.0 11.0“

Charlson Comorbidity Index*, n (%“ Low (0“

148 (55.6“

Medium (1-2“

88 (33.1“

High (>2“

30 (11.3“

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Selected patient history recorded in medical chart, n (%“

36 (13.5“

Hypertension

102 (38.4“

Cardiovascular disease

73 (27.4“

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Diabetes

End-stage renal disease

7 (2.6“

Liver disease

12 (4.5“

History of infection

88 (33.1“

History of contact to people with infection Recent surgery

4 (1.5“

47 (17.7“ 9 (3.4“

Permanent central venous access lines

12 (4.5“

Bowel incontinence Autoimmune conditions Vaginitis Interstitial cystitis

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Sexually transmitted disease

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Predisposing valvular disease / intravenous drug use Urinary catheter use

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*Calculated after removing diagnoses of cancer

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Gender, n (%“

26 (9.8“ 3 (1.1“ 3 (1.1“ -

ACCEPTED MANUSCRIPT 23

Table 3. PPV of ICDICD-1010-based algorithms to identify primary discharge diagnoses of infections in the DNRP Potential

Confirmed by physician

Confirmed by evidence-based

cases

global assessment

criteria

PPV (95% CI“

266

261

98.1 (95.9 99.3“

266

213

80.1 (75.0-84.5“

Skin infection

38

30

79.0 (64.2 89.5“

17

44.7 (29.8 60.4“

Pneumonia

93

86

92.5 (85.8 96.6“

83

89.3 (81.8 94.3“

Sepsis

45

31

68.9 (54.5 80.9“

Overall without requiring agreement on infection type Overall requiring agreement of specific type of infection* interest requiring agreement on specific type of infection*

* Same definitions as in Table 1.

38

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Restricted to infections of special

N

84.4 (71.9 92.8“

PPV (95% CI“

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N

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Type of infection

CI, confidence interval; DNRP, Danish National Registry of Patients; ICD-10, International Classification of Diseases, Tenth

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Revision; PPV, positive predictive value

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Appendix B: Medical Chart Extraction form.

Medical Chart Extraction Form

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STUDY ID

1.1 History of infection

Yes

1.1.1 If yes, specify ___________________ 1.2.1 If yes, specify___________________ 1.3 Predisposing valvular diseases or IV drug use

Yes

No/Unknown

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1.2 Exposed to people with known infections

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1. Patient history

No/Unknown

Yes

No/Unknown

Yes

No/Unknown

Yes

No/Unknown

Yes

No/Unknown

Yes

No/Unknown

Yes

No/Unknown

1.9 History or presence of sexually transmitted diseases

Yes

No/Unknown

1.10 History or presence of interstitial cystitis

Yes

No/Unknown

Yes

No/Unknown

Yes

No/Unknown

1.13 History of hypertension

Yes

No/Unknown

1.14 History of presence of end stage of renal disease

Yes

No/Unknown

1.15 History or presence of cardiovascular disease

Yes

No/Unknown

1.16 History of liver disease

Yes

No/Unknown

1.4 Permanent central venous access lines 1.5 History of urinary catheter use 1.6 History of bowel incontinence 1.8 History or presence of vaginitis

TE D

1.7 History or presence of autoimmune conditions

EP

1.10.1 Other, specify ___________________ 1.11 Recent history of surgery

1.11.1 If yes, specify ___________________

AC C

1.12 History of diabetes

. 2. Vital signs during current hospitalisation 2.1 Fever (38 °C, 100 °F)

Yes

No/Unknown

1

ACCEPTED MANUSCRIPT

2.2 Hypothermia (< 36 °C, 97 °F)

Yes

No/Unknown

2.3 Respiratory rate >20 breaths/minute

Yes

No/Unknown

2.4 Heart rate >90 beats/min

Yes

No/Unknown

2.5 Hypotension (systolic blood pressure10% immature (band forms)

No

SC

4.1 Blood test

4.1.3 Abnormal Lymphocyte counts*

Yes

If yes, specify , highest

RI PT

4) _________________________________________

cells/mm3 cells/mm3

No

Unknown

No

Unknown

cells/mm3; lowest

4.1.4 Abnormal Platelet counts*

Unknown

cells/ cells/mm3

Yes

No

Unknown

cells/mm3; lowest

If yes, specify , highest 4.1.5 Abnormal Hematocrit*

cells/ m3

If yes, specify: highest________________; lowest ________________ Yes

No

Unknown

4.1.7 Elevated C - reactive protein level *

Yes

No

Unknown

4.1.8 Elevated Erythrocyte Sedimentation Rate (>75 mm/hr)

Yes

No

Unknown

4.1.9 Elevated LDH (more than 25% above lab’s upper limit)

Yes

No

Unknown

Done

EP

4.2. Cerebrospinal Fluid (CSF)

TE D

4.1.6 Elevated blood protein*

4.2.1 CSF White Blood Cell (WBC)

Not Done ( go to 4.3)

cells /mm3 Done

AC C

4.2.2 WBC correction for traumatic tap?

Not Done

If done, WBC/mm3 after subtracting one WBC for every 1000 RBC cells /mm3

4.2.3 WBC cell differential (%)

Done

Not Done (go to 4.2.4)

Neutrophils (PMNs): _______ ; Lymphocyte: _______ ; Eosinophils : _______ 4.2.4 Elevation of CSF protein level (based on local lab reference range) Yes

No

Unknown

4.2.5 Glucose level (based on local lab reference) If abnormal, specify CSF glucose:

Normal

Abnormal

mg/dL

Unknown

. .

CSF to serum glucose ratio:

.

Unknown

Unknown

5

ACCEPTED MANUSCRIPT

4.3 Synovial fluid analysis

Normal

Abnormal

Not Done ( go to 4.4)

Green

Brown

Red

4.3.1 Color Gray

Other

cells/mm3

4.3.2 WBC: 4.3.3 % Polymorphonucleocytes (PMNs):

%

Unknown

4.3.4 Other abnormal findings, specify : _____________________

RI PT

Yellow

4.4 Pleural fluid effusion

Yes

No/unknown (go to 4.5)

4.4.1 Exudative Effusion

Yes

No

mg/dL

4.4.3 Adenosine deaminase:

U/L

M AN U

4.4.2.1 If yes, specify

Yes

No

SC

4.4.2 Decreased glucose l ( based on local lab reference)

Unknown

Unknown

4.4.4 Other abormal findings, specify _____________________ 4.5 Pericardial fluid effusion

Yes

4.5.1 Exudative effusion

Yes

No/unknown (go to 4.6) No

Unknown

Yes

No

4.5.2 Decreased glucose l ( based on local lab reference) 4.5.2.1 If yes, specify

mg/dL

4.5.3 Adenosine deaminase:

U/L

Unknown

TE D

4.5.4 Other abormal findings, specify _____________________ 4.6 Peritoneal fluid effusion 4.6.1 Exudative effusion

Yes

No/unknown (go to 4.7)

Yes

No

Unknown

Yes

No

4.6.2 Decreased glucose l ( based on local lab reference) mg/dL

EP

4.6.2.1 If yes, specify

4.6.3 Adenosine deaminase:

Unknown

U/L

4.6.4 Other abormal findings, specify _____________________ Done

Not Done (go to section 5)

4.7.1 Abnormal pH

Yes

No /Unknown (to 4.7.2)

4.7.2 Abnormal specific gravity

Yes

No/Unknown

4.7.3 Presence of protein in the urine

Yes

No/Unknown

4.7.4 Elevated glucose

Yes

No/Unknown

4.7.5 Elevated ketones

Yes

No/Unknown

4.7.6 Positive nitrites

Yes

No/Unknown

4.7.7 Positive leukocyte estrace

Yes

No/Unknown

AC C

4.7 Urinalysis

Highest pH: ____________; Lowest : ____________

6

ACCEPTED MANUSCRIPT

4.7.8 Positive urobilinogen

Yes

4.7.9 Abnormal WBC (according to hospital’s reference value)

No/Unknown Yes

No/Unknown

Yes

No/Unknown

4.7.11 Presence of bacteria

Yes

No/Unknown

RI PT

4.7.10 Abnormal RBC

Microbiologic diagnostics

* Fill the results by any smear/stains/ culture /microscopy/serology (antibodies)/molecular methods (e.g. PCR) to confirm the presence of the infectious agents 5.1 If yes, fill in the table below

Not Done (go to section 6.)

AC C

EP

TE D

M AN U

* for each site, if postive, specify time and organism/antigen/antibody

Done

SC

5. Smear/Gram stains/Culture (traditional and advanced methods)

7

ACCEPTED MANUSCRIPT

Sinus secretion / material

Date and Time Postive

mmddyy

: ____/____/____

Negative/Not done Postive

mmddyy

: ____/____/____

Postive

mmddyy

: ____/____/____

secretion/ BAL fluid

M AN U

Negative/Not done Sputum/chest or airway

Postive

mmddyy

Negative/Not done Postive

mmddyy

Negative/Not done

Negative/Not done

specimen

Postive

mmddyy

Negative/Not done Postive

EP

Bronchoscopy/lung biopsy

: ____/____/____

: ____/____/____

TE D

Postive

mmddyy

____ hr ____min

SC

Negative/Not done

____ hr ____min

RI PT

Site

: ____/____/____

: ____/____/____

____ hr ____min

____ hr ____min

____ hr ____min

AC C

Postive

Negative/Not done

2) ____________________ 1) ____________________

2) ____________________ 1) ____________________

2) ____________________ 1) ____________________

1) ____________________

2) ____________________ 1) ____________________

2) ____________________ ____ hr ____min

1) ____________________

2) ____________________ ____ hr ____min

1) ____________________

2) ____________________ mmddyy

: ____/____/____

____ hr ____min

Negative/Not done Stool

1) ____________________

2) ____________________

Negative/Not done Postive

Organism /antigen/antibody

1) ____________________

2) ____________________ mmddyy

: ____/____/____

____ hr ____min

1) ____________________

2) ____________________

8

ACCEPTED MANUSCRIPT

Peripheral blood

Date and Time Postive

mmddyy

: ____/____/____

____ hr ____min

: ____/____/____

RI PT

Site

Negative/Not done Postive

mmddyy

Negative/Not done mmddyy

: ____/____/____

Negative/Not done Postive

mmddyy

Negative/Not done Postive

mmddyy

Negative/Not done Postive

mmddyy

Negative/Not done Postive

mmddyy

Postive

EP

Negative/Not done

: ____/____/____

: ____/____/____

TE D

Urine

: ____/____/____

M AN U

Indwelling line blood

mmddyy

____ hr ____min

SC

Postive

____ hr ____min

: ____/____/____

: ____/____/____

____ hr ____min

AC C

Postive

____ hr ____min

____ hr ____min

Negative/Not done

1) ____________________

2) ____________________ 1) ____________________

2) ____________________ 1) ____________________

1) ____________________

1) ____________________

2) ____________________ ____ hr ____min

1) ____________________

2) ____________________ ____ hr ____min

1) ____________________

2) ____________________ mmddyy

: ____/____/____

____ hr ____min

1) ____________________

2) ____________________ mmddyy

: ____/____/____

____ hr ____min

Negative/Not done Postive

2) ____________________

2) ____________________

Negative/Not done Postive

1) ____________________

2) ____________________

Negative/Not done CSF/spinal fluid

Organism /antigen/antibody

1) ____________________

2) ____________________ mmddyy

: ____/____/____

____ hr ____min

1) ____________________

2) ____________________

9

ACCEPTED MANUSCRIPT

* Fill the results by any tranditinal culture or molecular methods incuding PCR

Brain biospy

Date and Time Postive

mmddyy

: ____/____/____

____ hr ____min

: ____/____/____

RI PT

Site

Negative/Not done Postive

mmddyy

Negative/Not done mmddyy

: ____/____/____

Negative/Not done Postive

mmddyy

Negative/Not done Postive

mmddyy

Negative/Not done Postive

Postive

mmddyy

Postive

EP

Negative/Not done

: ____/____/____

mmddyy

: ____/____/____

: ____/____/____

____ hr ____min

Postive

Negative/Not done

1) ____________________

2) ____________________ 1) ____________________

2) ____________________ 1) ____________________

2) ____________________ 1) ____________________

2) ____________________ ____ hr ____min

1) ____________________

2) ____________________ ____ hr ____min

1) ____________________

2) ____________________ ____ hr ____min

1) ____________________

2) ____________________ ____ hr ____min

Negative/Not done

AC C

Cardiac tissue (biospy)

: ____/____/____

TE D

mmddyy

Negative/Not done

: ____/____/____

M AN U

Cardiac/pericardial fluid

____ hr ____min

SC

Postive

____ hr ____min

Organism /antigen/antibody

1) ____________________

2) ____________________ mmddyy

: ____/____/____

____ hr ____min

1) ____________________

2) ____________________

10

ACCEPTED MANUSCRIPT

* Fill the results by any tranditinal culture or molecular methods incuding PCR

Bone

Date and Time Postive

mmddyy

: ____/____/____

____ hr ____min

: ____/____/____

RI PT

Site

Negative/Not done Postive

mmddyy

Negative/Not done mmddyy

: ____/____/____

Negative/Not done Postive

mmddyy

Negative/Not done Postive

mmddyy

Negative/Not done Postive

Postive

mmddyy

Postive

EP

Negative/Not done

: ____/____/____

mmddyy

: ____/____/____

: ____/____/____

____ hr ____min

Postive

Negative/Not done

1) ____________________

2) ____________________ 1) ____________________

2) ____________________ 1) ____________________

2) ____________________ 1) ____________________

2) ____________________ ____ hr ____min

1) ____________________

2) ____________________ ____ hr ____min

1) ____________________

2) ____________________ ____ hr ____min

1) ____________________

2) ____________________ ____ hr ____min

Negative/Not done

AC C

Abdomimal /peritoneal fluid

: ____/____/____

TE D

mmddyy

Negative/Not done

: ____/____/____

M AN U

Joint/Synovial fluid

____ hr ____min

SC

Postive

____ hr ____min

Organism /antigen/antibody

1) ____________________

2) ____________________ mmddyy

: ____/____/____

____ hr ____min

1) ____________________

2) ____________________

11

ACCEPTED MANUSCRIPT

* Fill the results by any tranditinal culture or molecular methods incuding PCR

Gastrointestinal fluid/tissue

Date and Time Postive

mmddyy

: ____/____/____

____ hr ____min

: ____/____/____

RI PT

Site

Negative/Not done Postive

mmddyy

Negative/Not done mmddyy

: ____/____/____

Negative/Not done Postive

mmddyy

Negative/Not done Postive

mmddyy

Negative/Not done Postive

Other, specify:

Postive

____________________

Negative/Not done

mmddyy

EP

Postive

: ____/____/____

: ____/____/____

TE D

mmddyy

Negative/Not done

: ____/____/____

M AN U

Throat

mmddyy

____ hr ____min

SC

Postive

____ hr ____min

: ____/____/____

: ____/____/____

____ hr ____min

AC C

Negative/Not done

1) ____________________

2) ____________________ 1) ____________________

2) ____________________ 1) ____________________

2) ____________________ 1) ____________________

2) ____________________ ____ hr ____min

1) ____________________

2) ____________________ ____ hr ____min

1) ____________________

2) ____________________ ____ hr ____min

1) ____________________

2) ____________________ ____ hr ____min

Negative/Not done Postive

Organism /antigen/antibody

1) ____________________

2) ____________________ mmddyy

: ____/____/____

____ hr ____min

1) ____________________

2) ____________________

12

ACCEPTED MANUSCRIPT

5.2 Acid-fast bacillus (AFB) smear and culture

Positive

Negative

5.2.1 If positive, presence of mycobacterium avium complex (MAC) Positive

Yes

No

Negative

Not Done (go to 5.5)

RI PT

5.3 Tuberculin skin test (Mantoux test)

Not Done(go to 5.4)

5.3.1 If positive, PPD ___________________mm

Positive

Negative (to 7)

Not Done (to 7)

6.1 If positive, specify the source of specimen

SC

6. Histology /pathology from any site or biopsy or autopsy specimens which confirm infection or inflammation

Cardiac tissues

Brain

GI tract

Bone

Other, specify _______________________

M AN U

Lung /airway

6.2 If postive, specify pathologist’s diagnosis and suggestion (free text)

______________________________________________________________________________________

TE D

_____________________________________________________________________________________

7. Imaging

Done

Not Done (go to 8)

* Fill both non-invasive imagings (X-ray, CT, MRI, EKG, ultrasound, electroencephalography, echocardiogram) and

EP

invasivediagnostics (bronchoscopy, endoscopy, voiding cystourethrogram, intravenous pyelogram, etc.) 7.1 Respiratory tract/ Chest imaging (X-ray, CT, MRI, bronchoscopy, etc.)

AC C

Abnormal

Normal (to 7.2)

Not Done/Uninterpretable (go to 7.2)

7.1.1 If Abnormal , specify

Lung Infiltration Lung consolidation of one lung segmental lobe Mediastinal adenopathy Pneumothorax

Cavity with air crescent sign or halo sign or paracavitary Mutiple cavities

13

RI PT

ACCEPTED MANUSCRIPT

Multiple foci of infiltration Multiple nodules Airway ulceration Airway inflammation

SC

Airway plugging by material suggestive to bronchoscopist of fungal infection Parenchymal cavitation or nodular disease or tree-in-bud lesions or known active pulmonary TB

M AN U

Other, specify 1) _______________________ 2) ____________________ 3) _______________________ 4) ____________________ 7.1.2 Radiologist’s diagnosis and suggestion Bronchitis

Pneumonia

Upper respiratory infections

TE D

Other, specify 1) _______________________ 2) ____________________

7.2 Cardiac imaging (including echocardiogram, EKG) Abnormal

Normal (to 7.3)

7.2.1 If abnormal, specify findings

EP

Intracardiac mass

Not Done/Uniterpretable (go to 7.3)

Endocardial abscess

New partial prosthesis dehiscence

AC C

Other, specify: 1) _______________________ 2) ____________________ 3) _______________________ 4) ____________________

7.2.2 Radiologist’s diagnosis and suggestion: Endocarditis

Pericarditis

Other, specify 1) _______________________ 2) ____________________

14

RI PT

ACCEPTED MANUSCRIPT

7. 3 Gastrointestinal tract and abdominal imaging (including endoscopy, X-ray, CT, MRI, urography, pyelography, voiding cystourethrogram, intravenous pyelogram ) Abnormal

Normal (to 7.4)

Not Done/ Uninterpretable (go to 7.4)

SC

7.3.1 if abnormal, specify Upper or lower gastrointestinal ulceration/lesions Upper or lower GI inflammation

M AN U

Visible oral candidiasis or esophageal plaques on esophagogastroduodenoscopy Renal inflammation Kidney stone

Genitourinary tuberculosis (e.g. caliceal destruction, luminal stenosis, simultaneous abnormality of upper and lower urinary tract

TE D

Other, specify: 1) _______________________ 2) ____________________ 7.3..2 Radiologist’s diagnosis and suggestion: Appendicitis Intestinal infections

Gastroenteritis

Nephritis/Kidney infection

Urinary tract infection

Other 1) __________________

EP

Genitourinary TB

Diverticulitis

2) ______________________

AC C

7.4 Neurologic /Brain imaging (including X-ray, CT, MRI, electroencephalography, etc.) Abnormal

Normal (to 7.5)

Not Done/ Uninterpretable (go to 7.5)

7.4.1 If abnormal, specify

Focal edema

Focal periodic discharge Focal inflammation Focal haemorrhage Meningeal inflammation

15

ACCEPTED MANUSCRIPT

Focal brain parenchymal inflammation Other, specify 1) _______________________ 2) ____________________ 7.4.2 Radiologist’s diagnosis and suggestion: Encephalitis

Encephalomyelitis

Other, specify 1) _______________________ 2) ____________________

Abnormal

SC

7.5 Bone/joint imaging (plain X –ray, CT, MRI, White Blood Cell scan or bone scan)

RI PT

Meningitis

Normal (to 7.6)

Not Done/Uninterpretable (go to 7.6)

M AN U

7.5.1 if abnormal, specify 1) _______________________ 2) ____________________

3) _______________________ 4) ____________________ 7.5.2 Radiologist’s diagnosis and suggestion: Osteomyelitis

Necrotizing fasciitis

Joint infection

Other, specify 1) ______________________

TE D

2) ______________________

7.6 Other diagnostic test (fill in additional diagnostic tests useful for infection diagnosis) Done

Not Done (go to section 8) Diagnosis: 1) _______________________

2) _______________________

Diagnosis: 2) _______________________

3) _______________________

Diagnosis: 3) _______________________

AC C

EP

7.6.1 Specify type of test: 1) _______________________

8. Treatment and medication during the given admission * The purpose of this section is to verify whether the patient received the anti-infection treatment and duration of treatments 8.1 Antibiotics

8.1.1 Intravenous

Yes

No (go to 8.2)

Unknown (go to 8.2)

Yes

No (go to 8.1.2)

Unknown (go to 8.1.2)

8.1.1.1 If yes, specify 1) _______________________ 2) ____________________ 3) _______________________ 4) ______________________ 8.1.1.2 Total Duration of treatment

days

16

ACCEPTED MANUSCRIPT

8.1.1.3 Reasons for prescription: 1) _______________________ 2) ____________________

8.1. 2 Oral

Yes

Yes

No/Unknown

No (go to 8.2)

Unknown (go to 8.2)

8.1.2.1 If yes, specify 1) _______________________ 2) ____________________ 3) _______________________ 4) ______________________ days

SC

8.1.2.2 Total Duration of treatment

RI PT

8.1.1.4 Adequate response to drugs

8.1.2.3 Reasons for prescription: 1) _______________________ 2) ____________________ Yes

No/Unknown

M AN U

8.1.2.4 Adequate response to drugs

8.2 Antiviral drugs

Yes

No (go to 8.3)

Unknown (go to 8.3)

8.2.1 Intravenous

Yes

No (go to 8.2.2)

Unknown (go to 8.2.2)

8.2.1.1 If yes, specify 1) _______________________ 2) ____________________ 8.2.1.2 Total Duration of treatment

TE D

3) _______________________ 4) ______________________ days

8.2.1.3 Reasons for prescription: 1) _______________________ 2) ____________________ 8.2.1.4 Adequate response to drugs

Yes

No/Unknown

No (go to 8.3)

EP

8.2. 2 Oral

Yes

Unknown (go to 8.3)

8.2.2.1 If yes, specify 1) _______________________ 2) ____________________

AC C

3) _______________________ 4) ______________________

8.2.2.2 Total Duration of treatment

days

8.2.2.3 Reasons for prescription: 1) _______________________ 2) ____________________ 8.2.2.4 Adequate response to drugs

8.3 Anti-tuberculous therapies

Yes

Yes

No/Unknown

No (go to 8.4)

Unknown (go to 8.4)

17

ACCEPTED MANUSCRIPT

8.3.1 If yes, specify 1) _______________________ 2) ____________________ 3) _______________________ 4) ______________________ 8.3.2 Duration of treatment

days

RI PT

8.3.3 Reason for prescription : 1) _______________________ 2) ____________________ 3) _______________________ 4) ______________________ Yes

No/Unknown

SC

8.3.4 Adequate response to drugs

M AN U

8.4 Other anti-infective treatments Yes

No (go to section 9)

8.4.1 If yes,

Specify 1) ___________________ ; Duration: _____________

Unknown (go to section 9)

Days; Indications : _____________

Specify 2) ___________________; Duration: ______________ Days; Indications : _____________

TE D

Specify 3) ___________________ ; Duration: ______________ Days; Indications : _____________ Specify 4) ___________________; Duration: ______________ Days; Indications : _____________

8.5 Admission to Intensive Care Unit

Yes

No

9. Discharge

AC C

EP

8.5.1 If yes, diagnosis at admission: ________________________

9. 1 In-hospital patient death during current hospitalization Yes

No

Unknown

9.1.1 If yes, specify primary contributing cause: ________________________ 9.1.2 If yes, autopsy 9.1.2.1 If done, infection confirmed

Done Yes

No

Not Done Unknown

18

ACCEPTED MANUSCRIPT

9.1.2.1.1 If infection confirmed, specify the diagnosis : 1) _______________________ 2) ____________________ 9.2 Summary of doctors’ discharge notes (free text): _______________________________________________________________

AC C

EP

TE D

M AN U

SC

_______________________________________________________________

RI PT

_______________________________________________________________

19

ACCEPTED MANUSCRIPT

Physician’s Global assessment section 1. Patient has infection

Yes

No

1.1 Respiratory tract infections

Yes

No

1.1.1 If yes, pneumonia

Yes

No

Yes

No

RI PT

1.1 If yes, specify the infection type

Other, specify _______________________ 1.2 Intestinal infectious diseases

1.3 Infectious with a predominantly sexual mode of transmission Yes

Other, specify _______________________ 1.4 Urinary tract infections

M AN U

1.3.1 if yes, syphillis

Yes

SC

1.2.1 If yes, specify _______________________

No

Yes

No

Yes

No

Yes

No

Yes

No

Yes

No

Yes

No

Yes

No

Yes

No

Yes

No

Encephalitis

Yes

No

Meningitis

Yes

No

Yes

No

Osteomyelitis

Yes

No

Bacterial /infective arthritis

Yes

No

1.4.1 if yes, kidney infection (pyenephritis) Bladder infection Other, specify _______________________

TE D

1.5 Skin or soft tissue infections 1.5.1 If yes Cellulitis Impetigo

EP

Necrotizing fasciitis

No

Other, specify _______________________ 1.6 Endocarditis 1.7.1 If yes,

AC C

1.7 Brain/central nerve system infection/inflammation

Other, specify _______________________ 1.8 Bone or joint infection 1.8.1 If yes,

20

ACCEPTED MANUSCRIPT

Septic arthritis

Yes

No

1.9 Bacteremia

Yes

No

1.10 Sepsis

Yes

No

1.11 Tuberculosis

Yes

No

1.12 Aspergillosis

Yes

No

1.13 Atypical mycobacterial infections

Yes

No

1.14 Cryptococcosis

Yes

No

1.15 Cytomegalovirus (CMV)

Yes

No

1.16 Histoplasmosis

Yes

1.17Candidiasis

Yes

1.18 Listeriosis

Yes

SC

M AN U

1.19 Other infections, specify:

RI PT

Other, specify _______________________

No

No

No

1) _______________________ 2) ____________________

Study physician: _________________ Signature: _________________

AC C

EP

TE D

Date : _________________

21

ACCEPTED MANUSCRIPT

Appendix A: ICDICD-10 diagnosis codes used in casecase-ascertainment algorithms for infections ICD-10 codes

Pneumonia

J12xx-J18xx

Sepsis

A40xx-A41xx, B377, A327, A548G, A021, A227, A267, A427, A282B

Skin infection

H010x, H03xx, H600x, H601x, H602x, H603x, H62xx, K122x, K130x, K61xx, L01xx, L08xx, M726x, A46xx

Cellulitis

L03xx

Endocarditis

I33xx, I398, B376

Bacteremia

A499

Meningitis

G00xx, G01xx, G02xx, G03xx, A321, A390, A170x, A203, A87x, A548D, A022C, B375, B003, B010, B021, B051,

SC

B261, B384 Encephalitis, myelitis, encephalomyelitis

G04xx, G05xx

N10xx, N11xx, N12xx, N151x, N159x, N30xx, N34xx, N390x

Kidney infection (pyelonephritis)

N10xx, N11xx, N12xx, N151x, N159x

Septic arthritis

M00xx

Infective arthritis

M011x, M013x

Osteomyelitis

M86xx

Tuberculosis

A15xx - A19xx

Atypical mycobacteria

A31xx

Mycoses

B35xx-B49xx

Systemic candidiasis

B37xx

TE D

M AN U

Urinary tract infection

Cryptococcosis

B45xx

Aspergillosis

B44xx B39xx

AC C

EP

Histoplasmosis

RI PT

Discharge diagnosis

ACCEPTED MANUSCRIPT

Appendix C: EvidenceEvidence-based diagnostic criteria for prepre-selected infections

Bacteremia

RI PT

Any one of A‘ Positive peripheral blood culture for any gram-negative organism

B‘ Positive peripheral blood culture for any gram-positive organisms except for coagulase negative

Staphylococcus, Bacillus spp., Corynebacterium spp., Propionibacterium spp., Micrococcus

C‘ Positive peripheral blood culture for coagulase negative Staphylococcus, Bacillus spp., Corynebacterium

SC

spp., Propionibacterium spp., Micrococcus and Patient treated for at least 7 days with intravenous antibiotics for putative bacteremia

M AN U

D‘ Positive blood culture drawn from an indwelling line and patient treated for at least 7 days with intravenous antibiotics for putative bacteremia

Pneumonia

A‘ Any two of: History: New and/or increased cough

•

Shortness of breath

•

Pleuritic chest pain

•

Purulent sputum

Examination:

EP

•

TE D

Infiltrate on chest imaging compatible with pneumonia or lung abscess on formal read and

Temperature alteration < 36 °C (97 °F‘ or > 38 °C (100 °F‘ in first 48 hours of admission

•

Crackles (or physical evidence of consolidation such as egophony, whispered pectoriloquy, etc.‘

•

Shock (volume nonresponsive hypotension‘

Labs:

AC C

•

Peripheral white blood cell (WBC‘ (>11.0x 109/L or 38 °C (100 °F‘ (hypothermia or fever‘.

•

Heart rate > 90 beats per minute.

•

Respiratory rate > 20 breaths per minute or, on blood gas, a PaCO2 less than 32 mm Hg (4.3 kPa‘

AC C

•

(tachypnea or hypocapnia due to hyperventilation‘. •

WBC < 4,000 cells/mm3 or > 12,000 cells/mm3 (< 4 × 109 or > 12 × 109 cells/L‘, or greater than 10% band forms (immature white blood cells‘. (leukopenia, leukocytosis, or bandemia‘

And the presence of signs of infection which include any one of

ACCEPTED MANUSCRIPT

WBCs in normally sterile fluid (such as urine or cerebrospinal fluid (CSF‘

•

Abnormal X-ray /CT scan showing evidence of infection

•

Petechiae, purpura, or purpura fulminans

•

Positive peripheral blood culture

•

Positive blood culture drawn from an indwelling line

•

Positive urine culture

•

Patient treated for at least 7 days with intravenous antibiotics for putative bacteremia

SC

RI PT

•

Cellulitis/erysipelas

M AN U

Soft-tissue erythema of recent onset (