The Burden of Streptococcus pneumoniae-Related Admissions and In-Hospital Mortality: A Retrospective Observational Study between the Years 2015 and 2022 from a Southern Italian Province

Streptococcus pneumoniae (SP) has high worldwide incidence and related morbidity and mortality, particularly among children and geriatric patients. SP infection could manifest with pneumonia, bacteremia, sepsis, meningitis, and osteomyelitis. This was a retrospective study aimed at evaluating the incidence, comorbidities, and factors associated with in-hospital mortality of pneumococcal disease-related hospitalization in a province in southern Italy from the years 2015 to 2022. This study was performed in the Local Health Authority (LHA) of Pescara. Data were collected from hospital discharge records (HDRs): this database is composed of 288,110 discharge records from LHA Pescara’s hospitals from 2015 to 2022. Streptococcus Pneumoniae-related hospitalizations were about 5% of the hospitalizations; 67% of these were without comorbidities; 21% were with one comorbidity; and 13% were with two or more comorbidities. Regarding mortality of SP infection, the most affected age group was older people, with the percentage of cases among the over-65s being more than 50% compared to the other age groups. HDRs represent a valid and useful epidemiological tool for evaluating the direct impact of pneumococcal disease on the population and also indirectly for evaluating the effectiveness of vaccination strategies and directing them.


Introduction
Streptococcus pneumoniae is one of the main causes of invasive and non-invasive human infectious diseases, with high worldwide incidence and related morbidity and mortality, particularly among children and geriatric patients [1]. The most common manifestation of pneumococcal disease is pneumonia, which represents one of the most frequent causes of community-acquired pneumonia (CAP). However, a wide range of clinical manifestations can occur due to Streptococcus pneumoniae infection. While some of these infections can be less serious, such as otitis, sinusitis, and bronchitis, others can be very dangerous and lead to illnesses such as bacteremia, sepsis, meningitis, and osteomyelitis. In these cases, we refer to these manifestations as invasive pneumococcal disease (IPD) [2].
For these reasons, according to the World Health Organization (WHO), pneumococcal disease is a major public health problem worldwide. It is estimated that approximately one million children die from pneumococcal disease every year [2].
In Italy, hospital discharge records (HDRs) are a useful tool to evaluate the burden of several diseases related to cost and healthcare utilization [12,13].
It included information on patients' demographic characteristics and the diagnosisrelated group (DRG) used to classify the admission and patients' comorbidities, coded by ICD-9 CM codes. hospital discharge records (HDRs), despite some limitations, can be also considered a proxy for healthcare utilization. In particular, evaluating factors associated with healthcare utilization for patients affected by pneumococcal disease can lead to the improvement of preventive strategies at the regional or country level.
Poor studies were performed in Italy on pneumococcal disease using HDRs. In addition, the major part of them referred only to the pre-pandemic period. For these reasons, we conducted a retrospective study aimed at evaluating the incidence of pneumococcal disease-related hospitalization in a province in southern Italy from the year 2015 to 2022. In addition, we evaluated comorbidities and factors associated with in-hospital mortality.

Materials and Methods
This was a retrospective observational study performed in the Local Health Authority (LHA) of Pescara, a province of the Abruzzo region accounting for about 320,000 inhabitants. It has three hospitals: a tertiary referral hospital and two spokes. Data were collected from the LHA registry of hospital discharge records (HDRs). The HDRs include a large variety of data regarding patients' demographic characteristics and hospitalization such as gender, ages and other information such as admission and discharge date and the discharge type, which also includes death. The HDRs also include information about diagnoses that led to hospitalization or that are concurrent including complications (a maximum of six diagnoses, one principal diagnosis and up to five comorbidities) and a maximum of six procedures or interventions that the patient underwent during hospitalization. Diagnoses and procedures were coded according to the International Classification of Disease, 9th Revision, Clinical Modification (ICD-9-CM), the National Center for Health Statistics (NCHS) and the Centers for Medicare and Medicaid Services External, Atlanta, GA, USA.

Coding of Streptococcus pneumoniae-Hospital Admission
For the selection of admissions with or without directly specified etiology, the following ICD-9-CM codes were used for the relative diagnoses: • Unspecified Pneumonias: 482.9 (Bacterial pneumonia, unspecified); 485 (Bronchopneumonia, organism unspecified); 486 (Pneumonia, organism unspecified).
• Pneumonia All-cause: 480.x, which includes the following diagnoses:  Teneligliptin has 5 times higher activity than sitagliptin because of the presence of a Jshaped anchor-lock domain and stronger covalent bond with DPP-4, also an additional bond with S2 extensive subsite. d  Cyanopyrrolidine scaffold binds to S1.  Hydroxyadamantyl group binds to the S2 subsite.  Saxagliptin has five-times higher activity than vildagliptin.
480.1 (Pneumonia due to adenovirus);  Teneligliptin has 5 times higher activity than sitagliptin because of the presence of a Jshaped anchor-lock domain and stronger covalent bond with DPP-4, also an additional bond with S2 extensive subsite. d  Cyanopyrrolidine scaffold binds to S1.  Hydroxyadamantyl group binds to the S2 subsite.  Saxagliptin has five-times higher activity than vildagliptin.
480.2 (Pneumonia due to respiratory syncytial virus);  Teneligliptin has 5 times higher activity than sitagliptin because of the presence of a Jshaped anchor-lock domain and stronger covalent bond with DPP-4, also an additional bond with S2 extensive subsite. d  Cyanopyrrolidine scaffold binds to S1.  Hydroxyadamantyl group binds to the S2 subsite.  Saxagliptin has five-times higher activity than vildagliptin.
Inhibitors were categorised in several classes based on the binding of inhibitors to the ites present, such as sitagliptin and teneligliptin were categorized in class 1 as it binds with S1, S2, and S2 extensive subsite, those binding to S1′, S2′, S1 and S2 (alogliptin linagliptin) were categorized in third class whereas, inhibitors like vildagliptin and gliptin were ranked in class second as they binds at S1 and S2 subsites only (illusd in Figure 3). Interaction of named drugs such as vildagliptin, sitagliptin, saxagliptin howed in Figure 4. The first class of drugs (e.g., vildagliptin and saxagliptin) founded interacting majorly with S1 and S2 subsites, cyannopyrrolidine moiety interacts with hereas hydroxy adamantyl interacts with the S2 subsite. On the other hand, the second of drugs binds by forming an additional subsite in comparison with the first class. gliptin binds with four subsites, including S1, S2, S1′, and S2, yielding 8-fold higher ity than Alogliptin. Alogliptin finds to be binding with only three subsites, i.e., S1, S2, S1′. Moreover, 3rd class, which holds teneligliptin, is a marketing DPP-4 inhibitor bee of the pentacyclic ring. Teneligliptin has five times higher activity than sitagliptin use of the presence of a J-shaped anchor-lock domain and a stronger covalent bond 480.9 (Pneumonia due to other virus not elsewhere classified).

(Pneumococcal pneumonia);
482.x which includes the following diagnoses: d  Cyanopyrrolidine scaffold binds to S1.  Hydroxyadamantyl group binds to the S2 subsite.  Saxagliptin has five-times higher activity than vildagliptin.
Inhibitors were categorised in several classes based on the binding of inhibitors to the ites present, such as sitagliptin and teneligliptin were categorized in class 1 as it binds with S1, S2, and S2 extensive subsite, those binding to S1′, S2′, S1 and S2 (alogliptin linagliptin) were categorized in third class whereas, inhibitors like vildagliptin and gliptin were ranked in class second as they binds at S1 and S2 subsites only (illusd in Figure 3). Interaction of named drugs such as vildagliptin, sitagliptin, saxagliptin howed in Figure 4. The first class of drugs (e.g., vildagliptin and saxagliptin) founded interacting majorly with S1 and S2 subsites, cyannopyrrolidine moiety interacts with hereas hydroxy adamantyl interacts with the S2 subsite. On the other hand, the second of drugs binds by forming an additional subsite in comparison with the first class. gliptin binds with four subsites, including S1, S2, S1′, and S2, yielding 8-fold higher ity than Alogliptin. Alogliptin finds to be binding with only three subsites, i.e., S1, S2, S1′. Moreover, 3rd class, which holds teneligliptin, is a marketing DPP-4 inhibitor bee of the pentacyclic ring. Teneligliptin has five times higher activity than sitagliptin use of the presence of a J-shaped anchor-lock domain and a stronger covalent bond 482.0 (Pneumonia due to Klebsiella pneumoniae); d  Cyanopyrrolidine scaffold binds to S1.  Hydroxyadamantyl group binds to the S2 subsite.  Saxagliptin has five-times higher activity than vildagliptin.
Inhibitors were categorised in several classes based on the binding of inhibitors to the ites present, such as sitagliptin and teneligliptin were categorized in class 1 as it binds with S1, S2, and S2 extensive subsite, those binding to S1′, S2′, S1 and S2 (alogliptin linagliptin) were categorized in third class whereas, inhibitors like vildagliptin and gliptin were ranked in class second as they binds at S1 and S2 subsites only (illusd in Figure 3). Interaction of named drugs such as vildagliptin, sitagliptin, saxagliptin howed in Figure 4. The first class of drugs (e.g., vildagliptin and saxagliptin) founded interacting majorly with S1 and S2 subsites, cyannopyrrolidine moiety interacts with hereas hydroxy adamantyl interacts with the S2 subsite. On the other hand, the second of drugs binds by forming an additional subsite in comparison with the first class. gliptin binds with four subsites, including S1, S2, S1′, and S2, yielding 8-fold higher ity than Alogliptin. Alogliptin finds to be binding with only three subsites, i.e., S1, S2, S1′. Moreover, 3rd class, which holds teneligliptin, is a marketing DPP-4 inhibitor bee of the pentacyclic ring. Teneligliptin has five times higher activity than sitagliptin use of the presence of a J-shaped anchor-lock domain and a stronger covalent bond 482.1 (Pneumonia due to Pseudomonas); bond with S2 extensive subsite. d  Cyanopyrrolidine scaffold binds to S1.  Hydroxyadamantyl group binds to the S2 subsite.  Saxagliptin has five-times higher activity than vildagliptin.
Inhibitors were categorised in several classes based on the binding of inhibitors to the ites present, such as sitagliptin and teneligliptin were categorized in class 1 as it binds with S1, S2, and S2 extensive subsite, those binding to S1′, S2′, S1 and S2 (alogliptin linagliptin) were categorized in third class whereas, inhibitors like vildagliptin and gliptin were ranked in class second as they binds at S1 and S2 subsites only (illusd in Figure 3). Interaction of named drugs such as vildagliptin, sitagliptin, saxagliptin howed in Figure 4. The first class of drugs (e.g., vildagliptin and saxagliptin) founded interacting majorly with S1 and S2 subsites, cyannopyrrolidine moiety interacts with hereas hydroxy adamantyl interacts with the S2 subsite. On the other hand, the second of drugs binds by forming an additional subsite in comparison with the first class. gliptin binds with four subsites, including S1, S2, S1′, and S2, yielding 8-fold higher ity than Alogliptin. Alogliptin finds to be binding with only three subsites, i.e., S1, S2, S1′. Moreover, 3rd class, which holds teneligliptin, is a marketing DPP-4 inhibitor bee of the pentacyclic ring. Teneligliptin has five times higher activity than sitagliptin use of the presence of a J-shaped anchor-lock domain and a stronger covalent bond 482.2 (Pneumonia due to Hemophilus influenzae (H. influenzae)); with DPP-4, also an additional bond with S2 extensive subsite. d  Cyanopyrrolidine scaffold binds to S1.  Hydroxyadamantyl group binds to the S2 subsite.  Saxagliptin has five-times higher activity than vildagliptin.
Inhibitors were categorised in several classes based on the binding of inhibitors to the ites present, such as sitagliptin and teneligliptin were categorized in class 1 as it binds with S1, S2, and S2 extensive subsite, those binding to S1′, S2′, S1 and S2 (alogliptin linagliptin) were categorized in third class whereas, inhibitors like vildagliptin and gliptin were ranked in class second as they binds at S1 and S2 subsites only (illusd in Figure 3). Interaction of named drugs such as vildagliptin, sitagliptin, saxagliptin howed in Figure 4. The first class of drugs (e.g., vildagliptin and saxagliptin) founded interacting majorly with S1 and S2 subsites, cyannopyrrolidine moiety interacts with hereas hydroxy adamantyl interacts with the S2 subsite. On the other hand, the second of drugs binds by forming an additional subsite in comparison with the first class. gliptin binds with four subsites, including S1, S2, S1′, and S2, yielding 8-fold higher ity than Alogliptin. Alogliptin finds to be binding with only three subsites, i.e., S1, S2, S1′. Moreover, 3rd class, which holds teneligliptin, is a marketing DPP-4 inhibitor bee of the pentacyclic ring. Teneligliptin has five times higher activity than sitagliptin use of the presence of a J-shaped anchor-lock domain and a stronger covalent bond 482.30 (Pneumonia due to Streptococcus, unspecified); and stronger covalent bond with DPP-4, also an additional bond with S2 extensive subsite. d  Cyanopyrrolidine scaffold binds to S1.  Hydroxyadamantyl group binds to the S2 subsite.  Saxagliptin has five-times higher activity than vildagliptin.
Inhibitors were categorised in several classes based on the binding of inhibitors to the ites present, such as sitagliptin and teneligliptin were categorized in class 1 as it binds with S1, S2, and S2 extensive subsite, those binding to S1′, S2′, S1 and S2 (alogliptin linagliptin) were categorized in third class whereas, inhibitors like vildagliptin and gliptin were ranked in class second as they binds at S1 and S2 subsites only (illusd in Figure 3). Interaction of named drugs such as vildagliptin, sitagliptin, saxagliptin howed in Figure 4. The first class of drugs (e.g., vildagliptin and saxagliptin) founded interacting majorly with S1 and S2 subsites, cyannopyrrolidine moiety interacts with hereas hydroxy adamantyl interacts with the S2 subsite. On the other hand, the second of drugs binds by forming an additional subsite in comparison with the first class. gliptin binds with four subsites, including S1, S2, S1′, and S2, yielding 8-fold higher ity than Alogliptin. Alogliptin finds to be binding with only three subsites, i.e., S1, S2, S1′. Moreover, 3rd class, which holds teneligliptin, is a marketing DPP-4 inhibitor bee of the pentacyclic ring. Teneligliptin has five times higher activity than sitagliptin use of the presence of a J-shaped anchor-lock domain and a stronger covalent bond 482.31 (Pneumonia due to Streptococcus, group A); shaped anchor-lock domain and stronger covalent bond with DPP-4, also an additional bond with S2 extensive subsite. d  Cyanopyrrolidine scaffold binds to S1.  Hydroxyadamantyl group binds to the S2 subsite.  Saxagliptin has five-times higher activity than vildagliptin.
Inhibitors were categorised in several classes based on the binding of inhibitors to the ites present, such as sitagliptin and teneligliptin were categorized in class 1 as it binds with S1, S2, and S2 extensive subsite, those binding to S1′, S2′, S1 and S2 (alogliptin linagliptin) were categorized in third class whereas, inhibitors like vildagliptin and gliptin were ranked in class second as they binds at S1 and S2 subsites only (illusd in Figure 3). Interaction of named drugs such as vildagliptin, sitagliptin, saxagliptin howed in Figure 4. The first class of drugs (e.g., vildagliptin and saxagliptin) founded interacting majorly with S1 and S2 subsites, cyannopyrrolidine moiety interacts with hereas hydroxy adamantyl interacts with the S2 subsite. On the other hand, the second of drugs binds by forming an additional subsite in comparison with the first class. gliptin binds with four subsites, including S1, S2, S1′, and S2, yielding 8-fold higher ity than Alogliptin. Alogliptin finds to be binding with only three subsites, i.e., S1, S2, S1′. Moreover, 3rd class, which holds teneligliptin, is a marketing DPP-4 inhibitor bee of the pentacyclic ring. Teneligliptin has five times higher activity than sitagliptin use of the presence of a J-shaped anchor-lock domain and a stronger covalent bond 482.32 (Pneumonia due to Streptococcus, group B); because of the presence of a Jshaped anchor-lock domain and stronger covalent bond with DPP-4, also an additional bond with S2 extensive subsite. d  Cyanopyrrolidine scaffold binds to S1.  Hydroxyadamantyl group binds to the S2 subsite.  Saxagliptin has five-times higher activity than vildagliptin.
Inhibitors were categorised in several classes based on the binding of inhibitors to the ites present, such as sitagliptin and teneligliptin were categorized in class 1 as it binds with S1, S2, and S2 extensive subsite, those binding to S1′, S2′, S1 and S2 (alogliptin linagliptin) were categorized in third class whereas, inhibitors like vildagliptin and gliptin were ranked in class second as they binds at S1 and S2 subsites only (illusd in Figure 3). Interaction of named drugs such as vildagliptin, sitagliptin, saxagliptin howed in Figure 4. The first class of drugs (e.g., vildagliptin and saxagliptin) founded interacting majorly with S1 and S2 subsites, cyannopyrrolidine moiety interacts with hereas hydroxy adamantyl interacts with the S2 subsite. On the other hand, the second of drugs binds by forming an additional subsite in comparison with the first class. gliptin binds with four subsites, including S1, S2, S1′, and S2, yielding 8-fold higher ity than Alogliptin. Alogliptin finds to be binding with only three subsites, i.e., S1, S2, S1′. Moreover, 3rd class, which holds teneligliptin, is a marketing DPP-4 inhibitor bee of the pentacyclic ring. Teneligliptin has five times higher activity than sitagliptin use of the presence of a J-shaped anchor-lock domain and a stronger covalent bond 482.39 (Pneumonia due to other Streptococcus); higher activity than sitagliptin because of the presence of a Jshaped anchor-lock domain and stronger covalent bond with DPP-4, also an additional bond with S2 extensive subsite.
d  Cyanopyrrolidine scaffold binds to S1.  Hydroxyadamantyl group binds to the S2 subsite.  Saxagliptin has five-times higher activity than vildagliptin.
Inhibitors were categorised in several classes based on the binding of inhibitors to the ites present, such as sitagliptin and teneligliptin were categorized in class 1 as it binds with S1, S2, and S2 extensive subsite, those binding to S1′, S2′, S1 and S2 (alogliptin linagliptin) were categorized in third class whereas, inhibitors like vildagliptin and gliptin were ranked in class second as they binds at S1 and S2 subsites only (illusd in Figure 3). Interaction of named drugs such as vildagliptin, sitagliptin, saxagliptin howed in Figure 4. The first class of drugs (e.g., vildagliptin and saxagliptin) founded interacting majorly with S1 and S2 subsites, cyannopyrrolidine moiety interacts with hereas hydroxy adamantyl interacts with the S2 subsite. On the other hand, the second of drugs binds by forming an additional subsite in comparison with the first class. gliptin binds with four subsites, including S1, S2, S1′, and S2, yielding 8-fold higher ity than Alogliptin. Alogliptin finds to be binding with only three subsites, i.e., S1, S2, S1′. Moreover, 3rd class, which holds teneligliptin, is a marketing DPP-4 inhibitor bee of the pentacyclic ring. Teneligliptin has five times higher activity than sitagliptin use of the presence of a J-shaped anchor-lock domain and a stronger covalent bond 482.40 (Pneumonia due to Staphylococcus, unspecified);  Teneligliptin has 5 times higher activity than sitagliptin because of the presence of a Jshaped anchor-lock domain and stronger covalent bond with DPP-4, also an additional bond with S2 extensive subsite.
d  Cyanopyrrolidine scaffold binds to S1.  Hydroxyadamantyl group binds to the S2 subsite.  Saxagliptin has five-times higher activity than vildagliptin.
Inhibitors were categorised in several classes based on the binding of inhibitors to the ites present, such as sitagliptin and teneligliptin were categorized in class 1 as it binds with S1, S2, and S2 extensive subsite, those binding to S1′, S2′, S1 and S2 (alogliptin linagliptin) were categorized in third class whereas, inhibitors like vildagliptin and gliptin were ranked in class second as they binds at S1 and S2 subsites only (illusd in Figure 3). Interaction of named drugs such as vildagliptin, sitagliptin, saxagliptin howed in Figure 4. The first class of drugs (e.g., vildagliptin and saxagliptin) founded interacting majorly with S1 and S2 subsites, cyannopyrrolidine moiety interacts with hereas hydroxy adamantyl interacts with the S2 subsite. On the other hand, the second of drugs binds by forming an additional subsite in comparison with the first class. gliptin binds with four subsites, including S1, S2, S1′, and S2, yielding 8-fold higher ity than Alogliptin. Alogliptin finds to be binding with only three subsites, i.e., S1, S2, S1′. Moreover, 3rd class, which holds teneligliptin, is a marketing DPP-4 inhibitor bee of the pentacyclic ring. Teneligliptin has five times higher activity than sitagliptin use of the presence of a J-shaped anchor-lock domain and a stronger covalent bond 482.41 (Methicillin susceptible pneumonia due to Staphylococcus aureus);  Teneligliptin has 5 times higher activity than sitagliptin because of the presence of a Jshaped anchor-lock domain and stronger covalent bond with DPP-4, also an additional bond with S2 extensive subsite.
d  Cyanopyrrolidine scaffold binds to S1.  Hydroxyadamantyl group binds to the S2 subsite.  Saxagliptin has five-times higher activity than vildagliptin.
Inhibitors were categorised in several classes based on the binding of inhibitors to the ites present, such as sitagliptin and teneligliptin were categorized in class 1 as it binds with S1, S2, and S2 extensive subsite, those binding to S1′, S2′, S1 and S2 (alogliptin linagliptin) were categorized in third class whereas, inhibitors like vildagliptin and gliptin were ranked in class second as they binds at S1 and S2 subsites only (illusd in Figure 3). Interaction of named drugs such as vildagliptin, sitagliptin, saxagliptin howed in Figure 4. The first class of drugs (e.g., vildagliptin and saxagliptin) founded interacting majorly with S1 and S2 subsites, cyannopyrrolidine moiety interacts with hereas hydroxy adamantyl interacts with the S2 subsite. On the other hand, the second of drugs binds by forming an additional subsite in comparison with the first class. gliptin binds with four subsites, including S1, S2, S1′, and S2, yielding 8-fold higher ity than Alogliptin. Alogliptin finds to be binding with only three subsites, i.e., S1, S2, S1′. Moreover, 3rd class, which holds teneligliptin, is a marketing DPP-4 inhibitor bee of the pentacyclic ring. Teneligliptin has five times higher activity than sitagliptin use of the presence of a J-shaped anchor-lock domain and a stronger covalent bond 482.42 (Methicillin resistant pneumonia due to Staphylococcus aureus);  Teneligliptin has 5 times higher activity than sitagliptin because of the presence of a Jshaped anchor-lock domain and stronger covalent bond with DPP-4, also an additional bond with S2 extensive subsite.
d  Cyanopyrrolidine scaffold binds to S1.  Hydroxyadamantyl group binds to the S2 subsite.  Saxagliptin has five-times higher activity than vildagliptin.
Inhibitors were categorised in several classes based on the binding of inhibitors to the ites present, such as sitagliptin and teneligliptin were categorized in class 1 as it binds with S1, S2, and S2 extensive subsite, those binding to S1′, S2′, S1 and S2 (alogliptin linagliptin) were categorized in third class whereas, inhibitors like vildagliptin and gliptin were ranked in class second as they binds at S1 and S2 subsites only (illusd in Figure 3). Interaction of named drugs such as vildagliptin, sitagliptin, saxagliptin howed in Figure 4. The first class of drugs (e.g., vildagliptin and saxagliptin) founded interacting majorly with S1 and S2 subsites, cyannopyrrolidine moiety interacts with hereas hydroxy adamantyl interacts with the S2 subsite. On the other hand, the second of drugs binds by forming an additional subsite in comparison with the first class. gliptin binds with four subsites, including S1, S2, S1′, and S2, yielding 8-fold higher ity than Alogliptin. Alogliptin finds to be binding with only three subsites, i.e., S1, S2, S1′. Moreover, 3rd class, which holds teneligliptin, is a marketing DPP-4 inhibitor bee of the pentacyclic ring. Teneligliptin has five times higher activity than sitagliptin use of the presence of a J-shaped anchor-lock domain and a stronger covalent bond 482.49 (Other Staphylococcus pneumonia);  Alogliptin binds to S1, S2 and S1′ subsites.  Linagliptin binds to S1, S2, S1′, S2′ subsites.  Compared with alogliptin, Linagliptin has 8-fold higher activity.
Inhibitors were categorised in several classes based on the binding of inhibitors to the ites present, such as sitagliptin and teneligliptin were categorized in class 1 as it binds with S1, S2, and S2 extensive subsite, those binding to S1′, S2′, S1 and S2 (alogliptin linagliptin) were categorized in third class whereas, inhibitors like vildagliptin and gliptin were ranked in class second as they binds at S1 and S2 subsites only (illusd in Figure 3). Interaction of named drugs such as vildagliptin, sitagliptin, saxagliptin howed in Figure 4. The first class of drugs (e.g., vildagliptin and saxagliptin) founded interacting majorly with S1 and S2 subsites, cyannopyrrolidine moiety interacts with hereas hydroxy adamantyl interacts with the S2 subsite. On the other hand, the second of drugs binds by forming an additional subsite in comparison with the first class. gliptin binds with four subsites, including S1, S2, S1′, and S2, yielding 8-fold higher ity than Alogliptin. Alogliptin finds to be binding with only three subsites, i.e., S1, S2, S1′. Moreover, 3rd class, which holds teneligliptin, is a marketing DPP-4 inhibitor bee of the pentacyclic ring. Teneligliptin has five times higher activity than sitagliptin use of the presence of a J-shaped anchor-lock domain and a stronger covalent bond 482.81 (Pneumonia due to anaerobes);  Alogliptin binds to S1, S2 and S1′ subsites.  Linagliptin binds to S1, S2, S1′, S2′ subsites.  Compared with alogliptin, Linagliptin has 8-fold higher activity.
Inhibitors were categorised in several classes based on the binding of inhibitors to the ites present, such as sitagliptin and teneligliptin were categorized in class 1 as it binds with S1, S2, and S2 extensive subsite, those binding to S1′, S2′, S1 and S2 (alogliptin linagliptin) were categorized in third class whereas, inhibitors like vildagliptin and gliptin were ranked in class second as they binds at S1 and S2 subsites only (illusd in Figure 3). Interaction of named drugs such as vildagliptin, sitagliptin, saxagliptin howed in Figure 4. The first class of drugs (e.g., vildagliptin and saxagliptin) founded interacting majorly with S1 and S2 subsites, cyannopyrrolidine moiety interacts with hereas hydroxy adamantyl interacts with the S2 subsite. On the other hand, the second of drugs binds by forming an additional subsite in comparison with the first class. gliptin binds with four subsites, including S1, S2, S1′, and S2, yielding 8-fold higher ity than Alogliptin. Alogliptin finds to be binding with only three subsites, i.e., S1, S2, S1′. Moreover, 3rd class, which holds teneligliptin, is a marketing DPP-4 inhibitor bee of the pentacyclic ring. Teneligliptin has five times higher activity than sitagliptin use of the presence of a J-shaped anchor-lock domain and a stronger covalent bond 482.82 (Pneumonia due to escherichia coli (E. coli)); e 1. Illustrating type of class interacting at which subsite of DPP-4 protease.  Alogliptin binds to S1, S2 and S1′ subsites.  Linagliptin binds to S1, S2, S1′, S2′ subsites.  Compared with alogliptin, Linagliptin has 8-fold higher activity.
Inhibitors were categorised in several classes based on the binding of inhibitors to the ites present, such as sitagliptin and teneligliptin were categorized in class 1 as it binds with S1, S2, and S2 extensive subsite, those binding to S1′, S2′, S1 and S2 (alogliptin linagliptin) were categorized in third class whereas, inhibitors like vildagliptin and gliptin were ranked in class second as they binds at S1 and S2 subsites only (illusd in Figure 3). Interaction of named drugs such as vildagliptin, sitagliptin, saxagliptin howed in Figure 4. The first class of drugs (e.g., vildagliptin and saxagliptin) founded interacting majorly with S1 and S2 subsites, cyannopyrrolidine moiety interacts with hereas hydroxy adamantyl interacts with the S2 subsite. On the other hand, the second of drugs binds by forming an additional subsite in comparison with the first class. gliptin binds with four subsites, including S1, S2, S1′, and S2, yielding 8-fold higher ity than Alogliptin. Alogliptin finds to be binding with only three subsites, i.e., S1, S2, S1′. Moreover, 3rd class, which holds teneligliptin, is a marketing DPP-4 inhibitor bee of the pentacyclic ring. Teneligliptin has five times higher activity than sitagliptin use of the presence of a J-shaped anchor-lock domain and a stronger covalent bond 482.83 (Pneumonia due to other Gram-negative bacteria); e 1. Illustrating type of class interacting at which subsite of DPP-4 protease.  Alogliptin binds to S1, S2 and S1′ subsites.  Linagliptin binds to S1, S2, S1′, S2′ subsites.  Compared with alogliptin, Linagliptin has 8-fold higher activity.
Inhibitors were categorised in several classes based on the binding of inhibitors to the ites present, such as sitagliptin and teneligliptin were categorized in class 1 as it binds with S1, S2, and S2 extensive subsite, those binding to S1′, S2′, S1 and S2 (alogliptin linagliptin) were categorized in third class whereas, inhibitors like vildagliptin and gliptin were ranked in class second as they binds at S1 and S2 subsites only (illusd in Figure 3). Interaction of named drugs such as vildagliptin, sitagliptin, saxagliptin howed in Figure 4. The first class of drugs (e.g., vildagliptin and saxagliptin) founded interacting majorly with S1 and S2 subsites, cyannopyrrolidine moiety interacts with hereas hydroxy adamantyl interacts with the S2 subsite. On the other hand, the second of drugs binds by forming an additional subsite in comparison with the first class. gliptin binds with four subsites, including S1, S2, S1′, and S2, yielding 8-fold higher ity than Alogliptin. Alogliptin finds to be binding with only three subsites, i.e., S1, S2, S1′. Moreover, 3rd class, which holds teneligliptin, is a marketing DPP-4 inhibitor bee of the pentacyclic ring. Teneligliptin has five times higher activity than sitagliptin use of the presence of a J-shaped anchor-lock domain and a stronger covalent bond 482.84 (Pneumonia due to Legionnaires' disease); ps helping in the formation of Hydrogen-bond [28][29][30].   Alogliptin binds to S1, S2 and S1′ subsites.  Linagliptin binds to S1, S2, S1′, S2′ subsites.  Compared with alogliptin, Linagliptin has 8-fold higher activity.
Inhibitors were categorised in several classes based on the binding of inhibitors to the ites present, such as sitagliptin and teneligliptin were categorized in class 1 as it binds with S1, S2, and S2 extensive subsite, those binding to S1′, S2′, S1 and S2 (alogliptin linagliptin) were categorized in third class whereas, inhibitors like vildagliptin and gliptin were ranked in class second as they binds at S1 and S2 subsites only (illusd in Figure 3). Interaction of named drugs such as vildagliptin, sitagliptin, saxagliptin howed in Figure 4. The first class of drugs (e.g., vildagliptin and saxagliptin) founded interacting majorly with S1 and S2 subsites, cyannopyrrolidine moiety interacts with hereas hydroxy adamantyl interacts with the S2 subsite. On the other hand, the second of drugs binds by forming an additional subsite in comparison with the first class. gliptin binds with four subsites, including S1, S2, S1′, and S2, yielding 8-fold higher ity than Alogliptin. Alogliptin finds to be binding with only three subsites, i.e., S1, S2, S1′. Moreover, 3rd class, which holds teneligliptin, is a marketing DPP-4 inhibitor bee of the pentacyclic ring. Teneligliptin has five times higher activity than sitagliptin use of the presence of a J-shaped anchor-lock domain and a stronger covalent bond 482.89 (Pneumonia due to other specified bacteria); contributes their role in the interaction & potency of composed several halogen ps helping in the formation of Hydrogen-bond [28][29][30].   Alogliptin binds to S1, S2 and S1′ subsites.  Linagliptin binds to S1, S2, S1′, S2′ subsites.  Compared with alogliptin, Linagliptin has 8-fold higher activity.
Inhibitors were categorised in several classes based on the binding of inhibitors to the ites present, such as sitagliptin and teneligliptin were categorized in class 1 as it binds with S1, S2, and S2 extensive subsite, those binding to S1′, S2′, S1 and S2 (alogliptin linagliptin) were categorized in third class whereas, inhibitors like vildagliptin and gliptin were ranked in class second as they binds at S1 and S2 subsites only (illusd in Figure 3). Interaction of named drugs such as vildagliptin, sitagliptin, saxagliptin howed in Figure 4. The first class of drugs (e.g., vildagliptin and saxagliptin) founded interacting majorly with S1 and S2 subsites, cyannopyrrolidine moiety interacts with hereas hydroxy adamantyl interacts with the S2 subsite. On the other hand, the second of drugs binds by forming an additional subsite in comparison with the first class. gliptin binds with four subsites, including S1, S2, S1′, and S2, yielding 8-fold higher ity than Alogliptin. Alogliptin finds to be binding with only three subsites, i.e., S1, S2, S1′. Moreover, 3rd class, which holds teneligliptin, is a marketing DPP-4 inhibitor bee of the pentacyclic ring. Teneligliptin has five times higher activity than sitagliptin use of the presence of a J-shaped anchor-lock domain and a stronger covalent bond 482.9 (Bacterial pneumonia, unspecified).
Inhibitors were categorised in several classes based on the binding of inhibitors to the ites present, such as sitagliptin and teneligliptin were categorized in class 1 as it binds with S1, S2, and S2 extensive subsite, those binding to S1′, S2′, S1 and S2 (alogliptin linagliptin) were categorized in third class whereas, inhibitors like vildagliptin and gliptin were ranked in class second as they binds at S1 and S2 subsites only (illusd in Figure 3). Interaction of named drugs such as vildagliptin, sitagliptin, saxagliptin howed in Figure 4. The first class of drugs (e.g., vildagliptin and saxagliptin) founded interacting majorly with S1 and S2 subsites, cyannopyrrolidine moiety interacts with hereas hydroxy adamantyl interacts with the S2 subsite. On the other hand, the second of drugs binds by forming an additional subsite in comparison with the first class. gliptin binds with four subsites, including S1, S2, S1′, and S2, yielding 8-fold higher ity than Alogliptin. Alogliptin finds to be binding with only three subsites, i.e., S1, S2, S1′. Moreover, 3rd class, which holds teneligliptin, is a marketing DPP-4 inhibitor bee of the pentacyclic ring. Teneligliptin has five times higher activity than sitagliptin use of the presence of a J-shaped anchor-lock domain and a stronger covalent bond 483.0 (Pneumonia due to Mycoplasma pneumoniae); to form a higher number of interactions with DPP-4 protease subsites; different scafcontributes their role in the interaction & potency of composed several halogen ps helping in the formation of Hydrogen-bond [28][29][30].   Alogliptin binds to S1, S2 and S1′ subsites.  Linagliptin binds to S1, S2, S1′, S2′ subsites.  Compared with alogliptin, Linagliptin has 8-fold higher activity.
Inhibitors were categorised in several classes based on the binding of inhibitors to the ites present, such as sitagliptin and teneligliptin were categorized in class 1 as it binds with S1, S2, and S2 extensive subsite, those binding to S1′, S2′, S1 and S2 (alogliptin linagliptin) were categorized in third class whereas, inhibitors like vildagliptin and gliptin were ranked in class second as they binds at S1 and S2 subsites only (illusd in Figure 3). Interaction of named drugs such as vildagliptin, sitagliptin, saxagliptin howed in Figure 4. The first class of drugs (e.g., vildagliptin and saxagliptin) founded interacting majorly with S1 and S2 subsites, cyannopyrrolidine moiety interacts with hereas hydroxy adamantyl interacts with the S2 subsite. On the other hand, the second of drugs binds by forming an additional subsite in comparison with the first class. gliptin binds with four subsites, including S1, S2, S1′, and S2, yielding 8-fold higher ity than Alogliptin. Alogliptin finds to be binding with only three subsites, i.e., S1, S2, S1′. Moreover, 3rd class, which holds teneligliptin, is a marketing DPP-4 inhibitor bee of the pentacyclic ring. Teneligliptin has five times higher activity than sitagliptin use of the presence of a J-shaped anchor-lock domain and a stronger covalent bond 483.1 (Pneumonia due to chlamydia);   Alogliptin binds to S1, S2 and S1′ subsites.  Linagliptin binds to S1, S2, S1′, S2′ subsites.  Compared with alogliptin, Linagliptin has 8-fold higher activity.
Inhibitors were categorised in several classes based on the binding of inhibitors to the ites present, such as sitagliptin and teneligliptin were categorized in class 1 as it binds with S1, S2, and S2 extensive subsite, those binding to S1′, S2′, S1 and S2 (alogliptin linagliptin) were categorized in third class whereas, inhibitors like vildagliptin and gliptin were ranked in class second as they binds at S1 and S2 subsites only (illusd in Figure 3). Interaction of named drugs such as vildagliptin, sitagliptin, saxagliptin howed in Figure 4. The first class of drugs (e.g., vildagliptin and saxagliptin) founded interacting majorly with S1 and S2 subsites, cyannopyrrolidine moiety interacts with hereas hydroxy adamantyl interacts with the S2 subsite. On the other hand, the second of drugs binds by forming an additional subsite in comparison with the first class. gliptin binds with four subsites, including S1, S2, S1′, and S2, yielding 8-fold higher ity than Alogliptin. Alogliptin finds to be binding with only three subsites, i.e., S1, S2, S1′. Moreover, 3rd class, which holds teneligliptin, is a marketing DPP-4 inhibitor bee of the pentacyclic ring. Teneligliptin has five times higher activity than sitagliptin use of the presence of a J-shaped anchor-lock domain and a stronger covalent bond 483.8 (Pneumonia due to other specified organism).
Inhibitors were categorised in several classes based on the binding of inhibitors to the ites present, such as sitagliptin and teneligliptin were categorized in class 1 as it binds with S1, S2, and S2 extensive subsite, those binding to S1′, S2′, S1 and S2 (alogliptin linagliptin) were categorized in third class whereas, inhibitors like vildagliptin and gliptin were ranked in class second as they binds at S1 and S2 subsites only (illusd in Figure 3). Interaction of named drugs such as vildagliptin, sitagliptin, saxagliptin howed in Figure 4. The first class of drugs (e.g., vildagliptin and saxagliptin) founded interacting majorly with S1 and S2 subsites, cyannopyrrolidine moiety interacts with hereas hydroxy adamantyl interacts with the S2 subsite. On the other hand, the second of drugs binds by forming an additional subsite in comparison with the first class. gliptin binds with four subsites, including S1, S2, S1′, and S2, yielding 8-fold higher ity than Alogliptin. Alogliptin finds to be binding with only three subsites, i.e., S1, S2, S1′. Moreover, 3rd class, which holds teneligliptin, is a marketing DPP-4 inhibitor bee of the pentacyclic ring. Teneligliptin has five times higher activity than sitagliptin use of the presence of a J-shaped anchor-lock domain and a stronger covalent bond d  Cyanopyrrolidine scaffold binds to S1.  Hydroxyadamantyl group binds to the S2 subsite.  Saxagliptin has five-times higher activity than vildagliptin.
Inhibitors were categorised in several classes based on the binding of inhibitors to the ites present, such as sitagliptin and teneligliptin were categorized in class 1 as it binds with S1, S2, and S2 extensive subsite, those binding to S1′, S2′, S1 and S2 (alogliptin linagliptin) were categorized in third class whereas, inhibitors like vildagliptin and gliptin were ranked in class second as they binds at S1 and S2 subsites only (illusd in Figure 3). Interaction of named drugs such as vildagliptin, sitagliptin, saxagliptin howed in Figure 4. The first class of drugs (e.g., vildagliptin and saxagliptin) founded interacting majorly with S1 and S2 subsites, cyannopyrrolidine moiety interacts with hereas hydroxy adamantyl interacts with the S2 subsite. On the other hand, the second of drugs binds by forming an additional subsite in comparison with the first class. gliptin binds with four subsites, including S1, S2, S1′, and S2, yielding 8-fold higher ity than Alogliptin. Alogliptin finds to be binding with only three subsites, i.e., S1, S2, S1′. Moreover, 3rd class, which holds teneligliptin, is a marketing DPP-4 inhibitor bee of the pentacyclic ring. Teneligliptin has five times higher activity than sitagliptin use of the presence of a J-shaped anchor-lock domain and a stronger covalent bond d  Cyanopyrrolidine scaffold binds to S1.  Hydroxyadamantyl group binds to the S2 subsite.  Saxagliptin has five-times higher activity than vildagliptin.
Inhibitors were categorised in several classes based on the binding of inhibitors to the ites present, such as sitagliptin and teneligliptin were categorized in class 1 as it binds with S1, S2, and S2 extensive subsite, those binding to S1′, S2′, S1 and S2 (alogliptin linagliptin) were categorized in third class whereas, inhibitors like vildagliptin and gliptin were ranked in class second as they binds at S1 and S2 subsites only (illusd in Figure 3). Interaction of named drugs such as vildagliptin, sitagliptin, saxagliptin howed in Figure 4. The first class of drugs (e.g., vildagliptin and saxagliptin) founded interacting majorly with S1 and S2 subsites, cyannopyrrolidine moiety interacts with hereas hydroxy adamantyl interacts with the S2 subsite. On the other hand, the second of drugs binds by forming an additional subsite in comparison with the first class. gliptin binds with four subsites, including S1, S2, S1′, and S2, yielding 8-fold higher ity than Alogliptin. Alogliptin finds to be binding with only three subsites, i.e., S1, S2, S1′. Moreover, 3rd class, which holds teneligliptin, is a marketing DPP-4 inhibitor bee of the pentacyclic ring. Teneligliptin has five times higher activity than sitagliptin use of the presence of a J-shaped anchor-lock domain and a stronger covalent bond d  Cyanopyrrolidine scaffold binds to S1.  Hydroxyadamantyl group binds to the S2 subsite.  Saxagliptin has five-times higher activity than vildagliptin.
Inhibitors were categorised in several classes based on the binding of inhibitors to the ites present, such as sitagliptin and teneligliptin were categorized in class 1 as it binds with S1, S2, and S2 extensive subsite, those binding to S1′, S2′, S1 and S2 (alogliptin linagliptin) were categorized in third class whereas, inhibitors like vildagliptin and gliptin were ranked in class second as they binds at S1 and S2 subsites only (illusd in Figure 3). Interaction of named drugs such as vildagliptin, sitagliptin, saxagliptin howed in Figure 4. The first class of drugs (e.g., vildagliptin and saxagliptin) founded interacting majorly with S1 and S2 subsites, cyannopyrrolidine moiety interacts with hereas hydroxy adamantyl interacts with the S2 subsite. On the other hand, the second of drugs binds by forming an additional subsite in comparison with the first class. gliptin binds with four subsites, including S1, S2, S1′, and S2, yielding 8-fold higher ity than Alogliptin. Alogliptin finds to be binding with only three subsites, i.e., S1, S2, S1′. Moreover, 3rd class, which holds teneligliptin, is a marketing DPP-4 inhibitor bee of the pentacyclic ring. Teneligliptin has five times higher activity than sitagliptin use of the presence of a J-shaped anchor-lock domain and a stronger covalent bond 484.6 (Pneumonia in aspergillosis); d  Cyanopyrrolidine scaffold binds to S1.  Hydroxyadamantyl group binds to the S2 subsite.  Saxagliptin has five-times higher activity than vildagliptin.
Inhibitors were categorised in several classes based on the binding of inhibitors to the ites present, such as sitagliptin and teneligliptin were categorized in class 1 as it binds with S1, S2, and S2 extensive subsite, those binding to S1′, S2′, S1 and S2 (alogliptin linagliptin) were categorized in third class whereas, inhibitors like vildagliptin and gliptin were ranked in class second as they binds at S1 and S2 subsites only (illusd in Figure 3). Interaction of named drugs such as vildagliptin, sitagliptin, saxagliptin howed in Figure 4. The first class of drugs (e.g., vildagliptin and saxagliptin) founded interacting majorly with S1 and S2 subsites, cyannopyrrolidine moiety interacts with hereas hydroxy adamantyl interacts with the S2 subsite. On the other hand, the second of drugs binds by forming an additional subsite in comparison with the first class. gliptin binds with four subsites, including S1, S2, S1′, and S2, yielding 8-fold higher ity than Alogliptin. Alogliptin finds to be binding with only three subsites, i.e., S1, S2, S1′. Moreover, 3rd class, which holds teneligliptin, is a marketing DPP-4 inhibitor bee of the pentacyclic ring. Teneligliptin has five times higher activity than sitagliptin use of the presence of a J-shaped anchor-lock domain and a stronger covalent bond d  Cyanopyrrolidine scaffold binds to S1.  Hydroxyadamantyl group binds to the S2 subsite.  Saxagliptin has five-times higher activity than vildagliptin.
Inhibitors were categorised in several classes based on the binding of inhibitors to the ites present, such as sitagliptin and teneligliptin were categorized in class 1 as it binds with S1, S2, and S2 extensive subsite, those binding to S1′, S2′, S1 and S2 (alogliptin linagliptin) were categorized in third class whereas, inhibitors like vildagliptin and gliptin were ranked in class second as they binds at S1 and S2 subsites only (illusd in Figure 3). Interaction of named drugs such as vildagliptin, sitagliptin, saxagliptin howed in Figure 4. The first class of drugs (e.g., vildagliptin and saxagliptin) founded interacting majorly with S1 and S2 subsites, cyannopyrrolidine moiety interacts with hereas hydroxy adamantyl interacts with the S2 subsite. On the other hand, the second of drugs binds by forming an additional subsite in comparison with the first class. gliptin binds with four subsites, including S1, S2, S1′, and S2, yielding 8-fold higher ity than Alogliptin. Alogliptin finds to be binding with only three subsites, i.e., S1, S2, S1′. Moreover, 3rd class, which holds teneligliptin, is a marketing DPP-4 inhibitor bee of the pentacyclic ring. Teneligliptin has five times higher activity than sitagliptin use of the presence of a J-shaped anchor-lock domain and a stronger covalent bond • Unspecified Bacteriemia: 038.0 (Streptococcal septicemia); 038.9 (Unspecified septicemia); 790.7 (Bacteremia).
In the case of unspecified pneumonia, meningitis, and septicemia, a specific percentage could be attributable to pneumococcal infection. According to the recent literature [13], for unspecified pneumonias the attributable percentage to SP could be 36%; for unspecified meningitis an attributable percentage to SP could be 58%; and for unspecified septicemias a percentage due to SP could be 20%.
The proportion of SP-HA was calculated on the assumption that all HDRs mentioning this pathogen were SP-HA, of the cases of pneumonia, meningitis, and septicemia for which no pathogen was specified.

Comorbidity Coding
Comorbidities were calculated according to Charlson through an algorithm proposed by Baldo et al. [14] which follows the ICD-9-CM codes. The comorbidities taken into account are previous myocardial infarction, peripheral vascular disease, cerebrovascular disease, dementia, chronic pulmonary disease, rheumatic disease, peptic ulcer disease, mild liver disease, diabetes without chronic complication, diabetes with chronic complication, hemiplegia or paraplegia, renal disease, any malignancy, moderate or severe liver disease, metastatic solid tumor, and AIDS/HIV.

Statistical Analysis
Qualitative variables were summarized as frequency and percentage. Annual admission rates for each SP-HA were calculated per 100,000 inhabitants using, when appropriate, the related attributable fractions, according to the most recent literature and as described previously [14].
The data related to the demographic structure, sex, and age of the population were collected through free access to the database on the website of the National Institute of Statistics (ISTAT).
Hospitalization rates were standardized for age and gender according to the Abruzzo population in the first year of the study (2015). To evaluate the association between inhospital mortality and predictors, a multivariable logistic model was implemented using the presence or absence of death as the dependent variable (type of hospital discharge: death) and as independent variables, age expressed in categories (0-4, 5-14, 15-65, 65-79, and 80+), gender (M or F), the various invasive bacterial pathologies investigated (All Pneumonia, SP Pneumonia, Unspecified Pneumonia, SP Meningitidis, SP Bacteriemia, and unspecified Bacteriemia), and the presence of individual comorbidities according to Charlson (previous myocardial infarction, peripheral vascular disease, cerebrovascular disease, dementia, chronic pulmonary disease, rheumatic disease, peptic ulcer disease, mild liver disease, diabetes without chronic complication, diabetes with chronic complication, hemiplegia or paraplegia, renal disease, any malignancy, moderate or severe liver disease, metastatic solid tumor, and AIDS/HIV).
For all tests, a p-value less than 0.05 was considered significant. The statistical analysis was performed with STATA v14.2 software (StataCorp LLC, College Station, TX, USA).

Results
Our database comprises 288,110 discharge records from ASL Pescara's hospitals covering the period from 2015 to 2022. Streptococcus pneumoniae-related hospitalizations numbered 14,506 (5.035%), of which 7906 (2.744%) were associated with invasive diseases, including 33 cases of meningitis (0.011%) and 88 cases of bacteremia (0.031%). In contrast, unspecified invasive infections accounted for 1673 pneumonia cases (0.581%) and 5 cases of bacteremia (0.002%). There were no diagnosed cases of meningitis without a defined etiology.
Patients were categorized into different age groups, and it was found that the majority of admissions occurred between the ages of 15 and 64 (42%). Hospitalizations were well distributed across all seven years, with a minimum of 30,166 in 2020 (10%) due to pandemic restrictions and a maximum of 39,225 in 2015 (14%).
Regarding patients' comorbidity, we found that 192,088 had no comorbidity (67%), 59,573 had one comorbidity (21%), and 36,449 had two or more comorbidities (13%) according to the Charlson Index classification. In-hospital deaths totaled 13,434 (5%), with 3060 (1%) associated with Streptococcus pneumoniae. The sample is further detailed in Table 1 About comorbidity distribution, apparently there was a similar pattern among cardiovascular, cerebrovascular, renal, and respiratory diseases and diabetes: the percentage of infants (0-4) with these comorbidities was higher than in children (5)(6)(7)(8)(9)(10)(11)(12)(13)(14), and this fraction progressively increase with age ( Figure 1): for instance, there were 4520 patients between 0 and 4 with at least one cardiovascular disease (9.63%), compared to only 41 patients between 5 and 14 (0.29%). The number of patients with cardiovascular comorbidities peaked in the oldest age class (over 80) with 8457 cases (22.79%). Similarly, cerebrovascular diseases were most common among those over 80 (5928 cases, 15.98%), decreasing to a minimum in children between 5 and 14, with 109 patients (0.78%). Cardiovascular, cerebrovascular, renal, and respiratory diseases and diabetes were more common among the younger age group than in the 15 to 64 age range.
Malignancies showed a slightly different pattern: cancer was most common between 65 and 79, with 9513 patients (13.89%). Malignancies were more frequently found in the central age class , followed by the younger one, with rates of 5.61% and 2.06%, respectively.
In-hospital mortality displayed a similar trend across all comorbidity classes (see Figure 1): it decreased from 0-4 to 5-14 and progressively increased for patients over 80.
Logistical analysis for in-hospital mortality ( Table 2) confirmed the previously described trend: being younger than 5 and older than 64 is a risk factor for in-hospital mortality, with odds of 4.786 (p < 0.001) for ages 0 to 4, 2.868 (p < 0.001) for ages 65 to 79, and 6.599 (p < 0.001) for patients older than 80. Sex was not statistically significant as a risk factor (p = 0.480). Malignancies showed a slightly different pattern: cancer was most common between 65 and 79, with 9513 patients (13.89%). Malignancies were more frequently found in the central age class , followed by the younger one, with rates of 5.61% and 2.06%, respectively.
In-hospital mortality displayed a similar trend across all comorbidity classes (see Figure 1): it decreased from 0-4 to 5-14 and progressively increased for patients over 80.
Logistical analysis for in-hospital mortality ( Table 2) confirmed the previously described trend: being younger than 5 and older than 64 is a risk factor for in-hospital mortality, with odds of 4.786 (p < 0.001) for ages 0 to 4, 2.868 (p < 0.001) for ages 65 to 79, and 6.599 (p < 0.001) for patients older than 80. Sex was not statistically significant as a risk factor (p = 0.480).   All S.P.-related invasive infections were correlated with in-hospital mortality, with the highest odds for Streptococcus pneumoniae (4.528 with p < 0.001), followed by S.P. meningitis (3.443 with p = 0.048) and lastly S.P. bacteremia (2.201 with p = 0.050). Among unspecified etiology infections, only pneumonias were significantly related to in-hospital mortality (7.098 with p < 0.001), while there was no association with bacteremia (p = 0.227). It was impossible to evaluate unspecified meningitis as a risk factor due to the lack of cases in the recorded seven years.
The great part of comorbidities included in our evaluation were significantly associated with in-hospital mortality, apart from COPD (p = 0.054), complicated diabetes (p = 0.267), and any -plegia (p = 0.160).
S.P. bacteremia-related deaths began in 2018, with a rate of 0.3 per 100,000 (CI 95% 0-0.8), with no significant differences in the rate trend. In 2022, a not significantly higher in-hospital death rate has been reported with 0.6 per 100,000 (CI 95% 0-1.5), equal to the rate in 2021.

Discussion
With the present study, we analyzed HDRs, from 2015 to 2022, of a local health authority of Pescara, a province in southern Italy with three hospitals, two hubs and one spoke, and approximately 320,000 inhabitants. It was possible to evaluate the burden of hospitalization of all cases of pneumonia, pneumonia caused by streptococcus pneumonia, and pneumonia with non-specific causes. The study of HDRs has already been used as an indirect source of data to measure both the effectiveness of vaccination strategies [9].
Our data appear to be similar with the data of other works carried out in other Italian regions such as in Sicily [9] and the northeast of the country [14], with an admission rate percentage varying between 350 and 450 per 100,000 inhabitants. The epidemiological study of pneumococcal disease is of great importance because it can be effectively prevented through pneumococcal vaccination which has demonstrated its cost-effectiveness in different age groups of population [15,16].
The decrease in admissions observed during the years 2020-22 can be explained by the impact of pandemic on hospital admissions. Healthcare services focused their attention on COVID-19 patients during these years, causing on the other hand a decrease in admissions for other diseases, as reported in previous studies [17,18].
Regarding mortality, pneumonia causes over 27,000 deaths yearly across Europe [19]. We also calculated the odds of death due to invasive streptococcus pneumonia diseases. The most affected age group was older people, as expected, with a percentage of cases in the over-65s of more than 50% compared to the other age groups. The older age group is known to be the most affected group, and it shows the highest mortality risk associated with SP infection. It can be linked to a decrease in immune response and to the high frequency of co-morbidities among the elderly [9]. This point highlights that improving the vaccination among persons ≥65 may be the most cost-effective public health strategy in a community setting. Regarding factors associated with in-hospital mortality, cancers, dementia, heart failure, and kidney diseases are also known risk factors, in line with the previous literature [20]. The positive association of diabetes with mortality is controversial. Some studies reported a negative association [20]; other reported a simply non-significant association [21]. However, a hyperglycemic state caused by infections and relative treatments can worsen patients' conditions, particularly among patients transferred to ICU [21,22]. However, diabetes is well known risk factor in 30-and 90-day mortality after discharge [21], but we are not able to obtain data on out-hospital mortality with this study. The similar age distribution of in-hospital mortality in patients with diabetes, CVDs, or renal diseases can be due to the most frequent distribution of these conditions in older age classes [12,17]. In addition, all these conditions are known risk factors for in-hospital mortality for many other medical conditions such as hip fracture, general surgery, and trauma [23][24][25].
Furthermore, from the analysis of the data from 2020, we reported a significant increase in the number of cases of pneumonia from all causes, compared with a constant or slightly decreased number of pneumonias from Streptococcus pneumoniae. This trend is probably compatible with the pandemic period, in which there was an increase in hospitalizations for COVID-19 pneumonia.
Also, the increased mortality rate reported in the year 2020 can be attributed to COVID-19. On the other hand, across all study periods, the mortality in the younger age class was negligible. This can be due to the extensive mass vaccination campaign performed, accordingly with the Italian National Vaccination Plan, that strongly reduced the mortality for PC diseases [9].
HDRs represent a very important source for invasive Streptococcus pneumoniae disease and for the evaluation of data concerning hospitalizations, comorbidities, and deaths. The study of HDRs has already been used as an indirect source of data to measure both the effectiveness of vaccination strategies [23][24][25] and to guide them [26][27][28].
The main strength of this study is the use of official, routinely collected electronic health databases from the entire population of an Italian province. To our knowledge, this is one of first study conducted in Europe covering a large study period (data from 7 years, from 2015 to 2022) and considering also the pandemic and post-pandemic periods. The evaluation of an entire stable population can be used as a proxy for the evaluation of primary prevention intervention, such as vaccination, or it can be considered as a useful tool to evaluate the impact of infectious diseases on hospital admissions. In addition, this is one of the first studies performed in the Abruzzo region on this topic. Another point of strength is the size of the HDR that we analyzed, which included 288,110 records. The large sample is useful to evaluate factors associated with hospitalization, making results generalizable.
However, this study has several limitations. Firstly, it represents the situation of a single province in southern Italy and the burden of the pneumococcal disease, which is a vaccine-preventable disease, and is therefore affected by the vaccination coverage that the local health authority has managed to achieve.
The second limit is that the HDRs were not completed with epidemiological intent but instead for remunerating purposes of admission. For this reason, comorbidities reported in each record can be overestimated or underestimated.
Thirdly, HDRs do not contain patients' clinical data, such as drug therapies, blood parameters, and the clinical severity of each disease. The lack of this data can limit the power of the analysis. Finally, vaccination status for each included patient was not available, not allowing us to evaluate the effectiveness of vaccination against pneumococcal disease.
Therefore, our analysis can make an important contribution to the study of the characteristics of this disease in our region.

Conclusions
Streptococcus pneumoniae is a pathogen capable of contributing to the hospital burden in terms of both hospitalizations and intra-hospital mortality despite the existence of effective primary prevention tools such as vaccines. HDRs represent a valid and useful epidemiological tool for evaluating the direct impact of pneumococcal disease on the population and indirectly for evaluating the effectiveness of vaccination strategies and directing them.

Institutional Review Board Statement:
The study was conducted in conformity with the regulations on data management of the Regional Health Authority of Abruzzo and with the Italian Law on privacy (Art. 20-21 DL 196/2003), published in the Official Journal, n. 190, on 14 August 2004. The data were encrypted prior to the analysis at the regional statistical office, when each patient was assigned a unique identifier. The identifiers eliminated the possibility of tracing the patients' identities. According to Italian legislation, the use of administrative data does not require any written informed consent from patients.