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Factors associated with urinary diversion and fatality of hospitalised acute pyelonephritis patients in France: a national cross-sectional study (FUrTIHF-2)

Published online by Cambridge University Press:  18 September 2023

Leslie Grammatico-Guillon*
Affiliation:
Public Health and Prevention Department, Unit of Regional Clinical Epidemiology, Teaching Hospital of Tours, Medical School, University of Tours, Tours, France
Emeline Laurent*
Affiliation:
Public Health and Prevention Center, Unit of Regional Clinical Epidemiology, Teaching Hospital of Tours, Research Team “Education, Ethics and Health”, University of Tours, Tours, France
Joseph Fuhrman
Affiliation:
Public Health and Prevention Department, Unit of Regional Clinical Epidemiology, Teaching Hospital of Tours, Medical School, University of Tours, Tours, France
Christophe Gaborit
Affiliation:
Public Health and Prevention Department, Unit of Regional Clinical Epidemiology, Teaching Hospital of Tours, Tours, France
Maxime Vallée
Affiliation:
Service of Urology, Teaching Hospital of Poitiers, Medical School, University of Poitiers, Poitiers, France
Aurélien Dinh
Affiliation:
Service of Infectious Diseases, AP-HP, Medical School, University of Paris, Paris, France
Albert Sotto
Affiliation:
Service of Infectious Diseases, Teaching Hospital of Nimes, Medical School, University of Nimes, Nimes, France
Franck Bruyere
Affiliation:
Service of Urology, Teaching Hospital of Tours, Medical School, University of Tours, Tours, France
*
Corresponding authors: Leslie Grammatico-Guillon and Emeline Laurent; Emails: leslie.guillon@univ-tours.Fr; epidclic@chu-tours.Fr
Corresponding authors: Leslie Grammatico-Guillon and Emeline Laurent; Emails: leslie.guillon@univ-tours.Fr; epidclic@chu-tours.Fr
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Abstract

Acute pyelonephritis (AP) epidemiology has been sparsely described. This study aimed to describe the evolution of AP patients hospitalised in France and identify the factors associated with urinary diversion and fatality, in a cross-sectional study over the 2014–2019 period. Adult patients hospitalised for AP were selected by algorithms of ICD-10 codes (PPV 90.1%) and urinary diversion procedure codes (PPV 100%). 527,671 AP patients were included (76.5% female: mean age 66.1, 48.0% Escherichia coli), with 5.9% of hospital deaths. In 2019, the AP incidence was 19.2/10,000, slightly increasing over the period (17.3/10,000 in 2014). 69,313 urinary diversions (13.1%) were performed (fatality rate 6.7%), mainly in males, increasing over the period (11.7% to 14.9%). Urolithiasis (OR [95% CI] =33.1 [32.3–34.0]), sepsis (1.73 [1.69–1.77]) and a Charlson index ≥3 (1.32 [1.29–1.35]) were significantly associated with urinary diversion, whereas E. coli (0.75 [0.74–0.77]) was less likely associated. The same factors were significantly associated with fatality, plus old age and cancer (2.38 [2.32–2.45]). This nationwide study showed an increase in urolithiasis and identified, for the first time, factors associated with urinary diversion in AP along with death risk factors, which may aid urologists in clinical decision-making.

Type
Original Paper
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2023. Published by Cambridge University Press

Introduction

Acute pyelonephritis (AP) is a bacterial infection of the kidney, which is very frequent in the general population worldwide, requiring hospitalisation of patients in 10–30% of cases [Reference Redondo-Sánchez1Reference Czaja5]. Published rates of hospitalisation for urinary tract infections (UTIs), including AP, vary worldwide. In Japan, in 2012, the incidence was 6.8 per 10,000 for men and 12.4 for women but ranged from 2 to 7 per 10,000 according to age and sex in Spain over the 2000–2015 period [Reference Redondo-Sánchez1, Reference Sako6]. Similar variation in the incidence of AP has been recorded in the United States, Canada, and South Korea [Reference Czaja5, Reference Foxman, Klemstine and Brown7, Reference Ki8]. In France, AP generated 88,159 visits to emergency departments in 2019 [Reference Boissier, Savoie and Long9], and nearly one-quarter of in-hospital UTIs were due to AP [Reference de Lafforest10]. Despite the related morbidity, few studies have described a care pathway for AP, and the frequency of hospitalisations is poorly documented, especially where a diversion was necessary.

To date, no comprehensive studies have been performed in France to accurately describe the incidence of hospitalised AP, its care pathway, and outcomes, whereas they already have been intensively studied in other Western countries [Reference Czaja5, Reference Foxman, Klemstine and Brown7]. Cases requiring hospitalisation are the most severe and complicated presentations [Reference Johnson and Russo2], particularly those with hydronephrosis requiring urinary diversion by introducing a retrograde ureteral stent (ureteral or double J stent) or by percutaneous nephrostomy [Reference Drai, Bessede and Patard11, Reference Marien and Miller12]. The frequency of AP requiring ureteral stents remains unknown. Similarly, there are no epidemiological data on the associated factors of diversion and/or poor prognosis (such as death) for patients with AP hospitalised in France.

The French national hospital discharge database (Programme de Médicalisation des Systèmes d’Information (PMSI)) based on the mandatory notification of each hospital stay for all French public or private hospitals represents an extraordinary national data repository. It contains objective information, including socio-demographics, comorbidities, and previous hospital visits or admissions. Although initially designed for billing purposes, with the improvement in data processing, it has proved a powerful tool for epidemiological surveillance [Reference de Lafforest10, Reference Le Meur13Reference Grammatico-Guillon17]. This database gives a hospital stay summary based on diagnostic codes from the 10th revision of the International Classification of Diseases (ICD-10) and procedure codes from the French Current Procedure Terminology (French CPT). As each patient is assigned a unique number, individuals can be followed over time, allowing robust epidemiological studies at the national level [Reference de Lafforest10, Reference Grammatico-Guillon17Reference Laporte20].

The main objective of this study was to estimate the incidence of hospitalised AP in France, both with and without urinary diversions, and to highlight the factors associated firstly with diversion and secondly with survival, using national hospital discharge data.

Methods

Study design and data source

A national cross-sectional study was carried out from 1 January 2014 to 31 December 2019, using national claim data collected from the French diagnosis-related groups (F-DRGs = PMSI); the study ceased the year before the onset of the COVID-19 pandemic.

Study population, case definition, and outcomes

The study population included all adult patients (≥ 18 years old) hospitalised for AP in France over the study period, identified by specific ICD-10 codes (Supplementary material S1). AP in children was excluded due to their different clinical presentation and care pathways and outpatient stays of <24 h.

An algorithm to select patients with UTI was previously validated with a predictive positive value (PPV) of 70.4% [Reference de Lafforest10]. A validation step, focusing on a sample of 150 AP cases, was performed by a clinical reviewer with a second physician check if necessary to define the performance parameters of the specific AP algorithm: PPV 90.6%, with a 95% confidence interval (95% CI) ranging from 84.8% to 94.8%.

Urinary diversions were identified on the same sample, according to specific procedure codes (Supplementary material S1), with excellent performance parameters: PPV of 100% [96.9–100], sensitivity (Se) of 90.9% [75.7–98.0], specificity (Sp) of 100% [96.9–100], and predictive negative value (PNV) of 97.5% [92.9–99.5] (Supplementary material S2). The algorithm also displayed good performance parameters when considering obstructive cases in primary diagnosis as the gold standard (Supplementary material S3).

The AP care episode was defined as all hospitalisations related to the AP or the urinary stent procedure (change in stent) occurring within three months after discharge from the index hospitalisation and up to 28 days after discharge from the last stay within this 3-month period.

Socio-demographic characteristics (age and sex) were recorded along with pre-existing comorbidities (Charlson index and detailed comorbidities [Reference Charlson21]). Obstructive processes such as urinary stone, microbiology result, sepsis, and intensive care unit stay were also documented, as well as the leading cause of hospitalisation defined by the hospital discharge resume. We assumed that the leading cause of hospitalisation, which could be AP but also another condition, was associated with the leading cause of death occurring during the hospital stay.

Morbidity–mortality

The yearly in-hospital incidence rates of AP, overall and stratified by age and sex, were calculated as the number of hospitalised patients with AP in one year divided by the French adult population during the same year, as reported by the National Institute of Statistics and Economic Studies (INSEE). The overall incidence of AP was estimated by averaging the data for each year. Likewise, the hospital case fatality rate for AP was expressed as the number of deaths that occurred during an AP care episode, divided by the number of hospitalised patients with the condition.

Statistical analyses

The characteristics of the overall study population were stratified according to the presence of a urinary diversion. Continuous variables were described using the mean ± standard deviation (SD) or the median with the minimum, maximum, 1st, and 3rd quartiles. Qualitative variables were expressed as frequency and per cent. Multivariate analyses were performed using logistic regression models. For each outcome, all variables with p < 0.2 in bivariate analysis were included in the initial model. The final model was obtained using a descending stepwise selection. Statistical significance was defined at the threshold of p < 0.05. The same modelling was performed to identify factors associated with hospital AP fatality, including the primary diagnosis as a cofactor. Statistical analyses were performed using the SAS version for Microsoft Windows (SAS Institute, Cary, NC) and Microsoft Excel, version 2010.

Results

From 2014 to 2019, 527,671 AP-related hospitalisations were recorded in France and occurred mainly in females (76.5%) or individuals over 60 years old (66.9%) (Figure 1). The mean annual incidence of cases was 18.3/10,000 inhabitants, increasing from 17.3 to 19.2/10,000 during the study period. Urinary diversion accounted for 69,313 patients (13.1%) and increased over the period (Figure 2). This procedure was mainly performed using a double J stent (85.1%), in patients with a urinary stone (48%), and overall, for 74% of the latter group. In total, 198,011 (37.5%) had at least one comorbidity accounting for a Charlson index of 1 or higher, with the main comorbidities being renal disease (15.3%) or cancer (13%) (Table 1). Among those with a urinary diversion, renal disease and cancer accounted for 18.1% and 19.4% of subjects, respectively. The most common microorganism coded in the hospital resume for AP was Escherichia coli (48.0% of the overall population study) (Table 1); a similar proportion (36.8%) of those with diversion were positive for this species (Figure 3). Apart from the presence of a urinary stone (OR 33.1 [32.3–34.0]), other factors associated with urinary diversion were as follows: age 50 to 69 years, a Charlson score of ≥3, the presence of sepsis, and isolation of bacteria other than E. coli (Figure 4).

Figure 1. Incidences of hospitalised AP by age and sex, France, 2014 vs. 2019.

Figure 2. Kidney diversion rate of patients hospitalised with AP, by sex, France, 2014–2019.

Table 1. Baseline characteristics of the study population, France, 2014–2019

Figure 3. Micro-organisms coded in hospitalised AP, according to the presence of a kidney diversion, France, 2014–2019.

Figure 4. Factors associated with kidney diversion in hospitalised AP, France, 2014–2019.

Among the 527,671 patients, 31,227 deaths occurred (5.9%), and 6.7% for those with a urinary diversion. The hospital-case fatality was associated with increasing age (Figure 5) from OR = 3.6 [3.1–4.2] between 40 and 49 years to OR = 24.8 [21.0–27.0] above 90, and associated with comorbidities, especially cancer (2.4 [2.3–2.5]) and sepsis (3.3 [3.2–3.3]), independently of the hospitalisation main cause.

Figure 5. Factors associated with death of patients with hospitalised AP, France, 2014–2019.

Discussion

This large population-based study allowed studying the burden and predictors of the AP course, including more than 500,000 cases over a long period at a national scale. This study is, to date, one of the only estimations of the incidence of AP-related hospitalisations at this scale. A robust computerised tool using a hospital discharge database algorithm previously validated for UTIs [Reference de Lafforest10] has been applied for AP and urinary diversion, after confirming its performance. In a real-life setting, the incidence estimate of AP-related hospitalisations was 19/10,000 cases, along with diversion recourse and other risk factors resulted in a case fatality of 5.6%.

The incidence of in-hospital AP increased slightly over the 5-year period, which could be related to an ageing population. However, incidence varied substantially by sex and age, likely reflecting specific risk factors for UTIs as suggested by our and other studies [Reference Johnson and Russo2, Reference Czaja5, Reference Foxman, Klemstine and Brown7, Reference de Lafforest10], in that elderly males, sepsis, and comorbid conditions were primarily associated with AP hospitalisation [Reference Johnson and Russo2, Reference Drai, Bessede and Patard11]. Some studies have also reported a proportion of patients hospitalised to be lower than 20% among young people, especially females, and higher in the elderly [Reference Johnson and Russo2, Reference de Lafforest10, Reference Bruyère22]. Differences in incidence rates varied compared with some other Western countries, where in-hospital AP varied widely and was usually less frequent than reported in France [Reference Johnson and Russo2, Reference Czaja5, Reference Foxman, Klemstine and Brown7, Reference de Lafforest10, Reference Nicolle23]. However, an Asian study found markedly higher hospital rates of 30/10,000 inhabitants [Reference Ki8]. Further studies are necessary to address whether the organisation of healthcare systems and reimbursement rates impact hospitalisation care and outcomes, which could be a significant factor in fostering hospital admission in France.

AP may readily progress to severe urosepsis; renal dilatation requires urgent surgical management [Reference Johnson and Russo2, Reference Foxman, Klemstine and Brown7, Reference Boissier, Savoie and Long9, Reference Bruyère24]. The risk factors for renal dilatation are not ascertained and accepted but represent key information for in-hospital AP that can be used to identify patients requiring urinary diversion and/or at risk of severe presentation [Reference Bruyère22, Reference Bruyère24]. Indeed, for economical and organisational reasons, renal imaging, which could quickly detect dilatation, is not mandatory for all patients with AP. In our study, the urinary diversion rate was estimated at 13%. Further definition of risk factors for renal derivation could aid in the identification of patients who require ultrasound or CT scans in an emergency setting. This was the main aim of the study. The presence of a urinary stone (8.6% of AP, OR > 33) was the first predictor, but one-quarter of such patients did not receive a urinary diversion. Checking for the presence of a urinary stone requires an imaging procedure whose result reports, unfortunately, are not available in the medico-administrative database; thus, we were not able to confirm from their coding the presence of dilatation among these patients with urinary stone without diversion. Moreover, we estimated that the diversion frequency increased over the period and was probably linked to the increasing number of AP with lithiasis. Indeed, the incidence of urinary stones increased in the wider population over the period, from 20 to 22/10,000 individuals. Other patient characteristics such as sex, middle age, a Charlson score of 3 or more, and sepsis were also associated with more urinary diversion in our study. A study from 2007 reported that of 2,408 cases of AP, 87% were women and those aged 15–54 years had a higher ratio of outpatient care [Reference Czaja5]. This suggests, similar to our findings, that clinical presentations in younger females result in fewer complications and urinary diversions. The presence of E. coli was significantly associated with less urinary diversion. A French commentary by Bruyere et al. found that the presence of E. coli did not often result in urinary stones [Reference Bruyère24], which could explain the less frequent performance of urinary diversion, as this pathogen is frequent in the general healthy population. Concerning the elderly, where diversion is also less performed, the hypothesis could be that pre-existing medical conditions make this group more challenging for surgery, due to more cancer in advanced stages. Moreover, as older subjects could possibly present more frequently with stones but potentially without an associated obstruction, they would not require urinary diversion. These findings merit further investigation.

This study also documented the AP hospital course and revealed factors associated with a higher fatality, such as older age and cancer. To our knowledge, this is the first study to estimate the morbimortality burden of hospitalised AP, especially in terms of case fatality, and further analyses are clearly warranted. This is evident from our estimates of the impact of the medical conditions responsible for hospital stay and contributing to the mortality rate. Indeed, the risk of death markedly increased (aOR 2.6) when the primary diagnosis for hospital stay was not AP, which was subsequently identified as a contributory diagnosis but was not the leading driver for hospital admission.

Several limitations of our study should be mentioned. First, information bias classifying AP versus cystitis could exist, especially for E. coli, due to the difficulty for some practitioners to distinguish asymptomatic bacteriuria from a UTI [Reference de Lafforest10, Reference Grammatico-Guillon18, Reference Bruyère22, Reference Laurent25]. Nevertheless, the microorganism distribution was similar to the literature with E. coli in first rank, followed by other Gram-negative bacilli [Reference de Lafforest10, Reference Medina and Castillo-Pino26]. However, the species documentation was available for only 60% of the AP cases, which was probably due to a lack of pathogen coding as compared with clinical studies [Reference de Lafforest10, Reference Bruyère24]. Community and hospital-acquired infections cannot be distinguished through medico-administrative databases, which also do not allow to study resistance of isolates. This lack of coding, due to a lack of financial incentive, does not allow their reliable use for epidemiological surveillance, as presented by comparative studies [Reference Grammatico-Guillon17, Reference Leclère27, Reference Grammatico28]. Moreover, hospital stays are sometimes coded by various healthcare practitioners, leading to variation in the coded information [Reference Grammatico-Guillon18, Reference Laporte20]. However, validation of the algorithm showed excellent PPV (91%) for AP, which was higher than our UTI algorithm [Reference de Lafforest10], and excellent PPV and sensitivity for urinary diversion (100% and 91%, respectively). Indeed, these situations rely on each physician’s assessment, leading to wide heterogeneity according to the healthcare practitioner and their specialty: a surgeon will likely not have the same judgement as an infectious disease specialist or an intensivist [Reference Grammatico-Guillon18, Reference Laurent25, Reference Hermetet29]. Eventually, regarding the relatively high fatality rate (6%), the claim data design of the study did not tag the cause of death, although the patient could have had an AP but died primarily from a cancer or diabetes mellitus complication during the stay. We tried to address this limitation by attempting to establish the leading cause of hospitalisation.

This study has several strengths linked to the use of medico-administrative databases, providing a large well-defined real-life population. The reuse of data for epidemiological purposes has been intensively described and demonstrated its reliability, accuracy, and low cost with time-saving, for surveillance when well-designed validated algorithms are utilised [Reference Czaja5, Reference de Lafforest10, Reference Grammatico-Guillon18, Reference Jouan19].

Conclusion

To our knowledge, this is the first population-based study to describe trends in the incidence of AP, its distribution patterns, and factors associated with the derivation of inpatients with acute pyelonephritis, along with the risk factors for death. With the use of a validated algorithm, this national study based on a real-life large database showed an increase from 2014 to 2019 in urinary diversion for AP management, along with an increasing number of patients with urolithiasis. The factors associated with urinary diversion for AP management were identified as sepsis, being elderly, and having comorbidities, which were also associated with fatality. These factors may be of assistance to urologists for rapid decision-making on the presentation of AP.

Supplementary material

The supplementary material for this article can be found at https://doi.org/10.1017/S0950268823001504.

Data availability statement

The data were obtained from the National Research Database of the National Health Insurance Hub, PMSI ATIH. Our study involved the reuse of previously recorded and anonymised data. As a continuation of FUrTIHF-1 [Reference de Lafforest10], this study is part of the protocol that was filed as the FUrTIHF study, which fell within the scope of the French Reference Methodology MR-005 (declarations 2205437v0, 22 August 2018, and 2222651v0, 9 June 2021, endorsed by the Tours Teaching Hospital), which requires neither information nor consent of the included individuals. The FUrTIHF study was registered with the French Data Protection Board (CNIL MR-005 number #2018160620). These data required capacitation from the national level and restrictions concerning the sharing for legal reasons. It may not be shared at the public access. To be able to have access to the data set, you must be authorised and request legal access to the project data set.

Acknowledgements

This study was supported by the French Association of Urology (AFU) and the member of the Infectious Committee of the AFU (CIAFU), Zeina Halbouty.

Author contribution

Data curation: E.L.; Formal analysis: E.L., J.F., L.G.; Methodology: E.L., F.B., C.G., L.G.; Project administration: E.L., F.B., L.G.; Validation: E.L., L.G.; Writing – original draft: E.L., J.F., L.G.; Writing – review & editing: E.L., A.S., A.D., F.B., M.V., L.G.; Conceptualization: A.S., F.B., M.V., L.G.; Investigation: A.S., A.D., F.B.; Visualization: A.D., F.B., C.G., J.F., M.V., L.G.; Supervision: F.B., L.G.; Funding acquisition: C.G.

Competing interest

The authors declare none.

Ethical standard

Our study involved the reuse of previously recorded and anonymised data. As a continuation of FUrTIHF-1 [Reference Drai, Bessede and Patard11], this study formed part of the protocol of the latter, which fell within the scope of the French Reference Methodology MR-005 (declarations 2205437v0, 22 August 2018, and 2222651v0, 9 June 2021, endorsed by the Tours Teaching Hospital, CNIL MR-005 number #2018160620), which requires neither information nor consent of the included individuals.

Key findings

The first population-based study of hospitalised AP describes trends in incidence and patterns.

Based on real-life data, we showed an increasing number of hospitalised AP and urinary diversions.

Factors associated with urinary diversion and fatality were sepsis, elderly, and comorbidities.

These identified factors could help the urologist for rapid decision-making.

References

Redondo-Sánchez, J, et al. (2021) Trends in urinary tract infection hospitalization in older adults in Spain from 2000-2015. PLOS One 16, e0257546.CrossRefGoogle ScholarPubMed
Johnson, JR and Russo, TA (2018) Acute pyelonephritis in adults. New England Journal of Medicine 378, 4859.CrossRefGoogle ScholarPubMed
Brown, P, Ki, M and Foxman, B (2005) Acute pyelonephritis among adults: Cost of illness and considerations for the economic evaluation of therapy. PharmacoEconomics 23, 11231142.CrossRefGoogle ScholarPubMed
Rowe, TA and Juthani-Mehta, M (2013) Urinary tract infection in older adults. Aging Health 9, 519528.CrossRefGoogle ScholarPubMed
Czaja, CA, et al. (2007) Population-based epidemiologic analysis of acute pyelonephritis. Clinical Infectious Diseases 45, 273280.CrossRefGoogle ScholarPubMed
Sako, A, et al. (2021) Hospitalization for urinary tract infections in Japan, 2010–2015: A retrospective study using a national inpatient database. BMC Infectious Diseases 21, 1048.CrossRefGoogle ScholarPubMed
Foxman, B, Klemstine, KL and Brown, PD (2003) Acute pyelonephritis in US hospitals in 1997: Hospitalization and in-hospital mortality. Annals of Epidemiology 13, 144150.CrossRefGoogle ScholarPubMed
Ki, M, et al. (2004) The epidemiology of acute pyelonephritis in South Korea, 1997–1999. American Journal of Epidemiology 160, 985993.CrossRefGoogle ScholarPubMed
Boissier, R, Savoie, PH and Long, J-A (2021) Épidémiologie des urgences urologiques en France. Progrès en Urologie 31, 945955.CrossRefGoogle Scholar
de Lafforest, S, et al. (2021) FUrTIHF: French urinary tract infections in healthcare facilities – Five-year historic cohort (2014–2018). Journal of Hospital Infection 116, 2936.CrossRefGoogle ScholarPubMed
Drai, J, Bessede, T and Patard, J-J (2012) Prise en charge des pyélonéphrites aiguës. Progrès en Urologie 22, 871875.CrossRefGoogle Scholar
Marien, T and Miller, NL (2015) Treatment of the infected stone. Urologic Clinics of North America 42, 459472.CrossRefGoogle ScholarPubMed
Le Meur, N, et al. (2016) Health insurance database for post-discharge surveillance of surgical site infection following arthroplasty. Journal of Hospital Infection 92, 140146.CrossRefGoogle ScholarPubMed
Moulis, G, et al. (2015) French health insurance databases: What interest for medical research? La Revue De Medecine Interne 36, 411417.CrossRefGoogle ScholarPubMed
Lipsky, BA, et al. (2007) Skin, soft tissue, bone, and joint infections in hospitalized patients: Epidemiology and microbiological, clinical, and economic outcomes. Infection Control and Hospital Epidemiology 28, 12901298.CrossRefGoogle ScholarPubMed
Jouan, Y, et al. (2019) Healthcare trajectories before and after critical illness: Population-based insight on diverse patients clusters. Annals of Intensive Care 9, 126.CrossRefGoogle ScholarPubMed
Grammatico-Guillon, L, et al. (2015) Surgical site infection after primary hip and knee arthroplasty: A cohort study using a hospital database. Infection Control & Hospital Epidemiology 36, 11981207.CrossRefGoogle ScholarPubMed
Grammatico-Guillon, L, et al. (2014) Quality assessment of hospital discharge database for routine surveillance of hip and knee arthroplasty-related infections. Infection Control and Hospital Epidemiology 35, 646651.CrossRefGoogle ScholarPubMed
Jouan, Y, et al. (2015) Long-term outcome of severe herpes simplex encephalitis: A population-based observational study. Critical Care 19, 345.CrossRefGoogle ScholarPubMed
Laporte, L, et al. (2018) Ten-year trends in intensive care admissions for respiratory infections in the elderly. Annals of Intensive Care 8, 84.CrossRefGoogle ScholarPubMed
Charlson, M, et al. (1994) Validation of a combined comorbidity index. Journal of Clinical Epidemiology 47, 12451251.CrossRefGoogle ScholarPubMed
Bruyère, F, et al. (2022) Predictors of ultrasound abnormalities among women treated for community-onset acute pyelonephritis: A prospective study. World Journal of Urology 40, 24992504.CrossRefGoogle ScholarPubMed
Nicolle, LE, et al. (1996) Hospitalization for acute pyelonephritis in Manitoba, Canada, during the period from 1989 to 1992; impact of diabetes, pregnancy, and aboriginal origin. Clinical Infectious Diseases 22, 10511056.CrossRefGoogle ScholarPubMed
Bruyère, F, et al. (2008) Pyélonéphrites aiguës. Progrès en Urologie 18, 1418.CrossRefGoogle Scholar
Laurent, E, et al. (2018) Key features of bone and joint infections following the implementation of reference centers in France. Medecine Et Maladies Infectieuses 48, 256262.CrossRefGoogle ScholarPubMed
Medina, M and Castillo-Pino, E (2019) An introduction to the epidemiology and burden of urinary tract infections. Therapeutic Advances in Urology 11, 1756287219832172.CrossRefGoogle Scholar
Leclère, B, et al. (2014) Matching bacteriological and medico-administrative databases is efficient for a computer-enhanced surveillance of surgical site infections: Retrospective analysis of 4,400 surgical procedures in a French university hospital. Infection Control and Hospital Epidemiology 35, 13301335.CrossRefGoogle Scholar
Grammatico, L, et al. (2008) Epidemiology of vertebral osteomyelitis (VO) in France: Analysis of hospital-discharge data 2002-2003. Epidemiology and Infection 136, 653660.CrossRefGoogle ScholarPubMed
Hermetet, C, et al. (2021) Child maltreatment by non-accidental burns: Interest of an algorithm of detection based on hospital discharge database. International Journal of Legal Medicine 135, 509519. https://doi.org/10.1007/s00414-020-02404-yCrossRefGoogle ScholarPubMed
Figure 0

Figure 1. Incidences of hospitalised AP by age and sex, France, 2014 vs. 2019.

Figure 1

Figure 2. Kidney diversion rate of patients hospitalised with AP, by sex, France, 2014–2019.

Figure 2

Table 1. Baseline characteristics of the study population, France, 2014–2019

Figure 3

Figure 3. Micro-organisms coded in hospitalised AP, according to the presence of a kidney diversion, France, 2014–2019.

Figure 4

Figure 4. Factors associated with kidney diversion in hospitalised AP, France, 2014–2019.

Figure 5

Figure 5. Factors associated with death of patients with hospitalised AP, France, 2014–2019.

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